Soil Organic Nitrogen - Virginia Tech€¦ · Soil Organic Nitrogen ... excellent guidance, endless support, valuable advice and consistent patience during my research. She gave me

Soil Organic Nitrogen

— Investigation of Soil Amino Acids and Proteinaceous Compounds

Li Ma

Dissertation submitted to the faculty of the Virginia Polytechnic Institute and State

University in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

In

Crop and Soil Environmental Sciences

Kang Xia, Chair

Matthew J. Eick

Mark A. Williams

Chao Shang

Jian Wang

April 8, 2015

Blacksburg, VA

Keywords: Free amino acids, hydrolysable amino acids, proteins/peptides,

transects, soil organic carbon, mineral surface, orientation, synchrotron near edge

X-ray fine structure spectroscopy

Copyright © 2015, Li Ma

http://www.cses.vt.edu/people/tenure/eick.html

Soil Organic Nitrogen

— Investigation of Soil Amino Acids and Proteinaceous Compounds

Li Ma

Abstract

Soil carbon (C) and nitrogen (N) are predominantly in organic form. Proteins/ peptides,

as an important organic form of N, constitute a substantial part of soil organic matter. On one

hand, proteins/peptides are an important N source for plants and microorganisms, particularly in

soils where inorganic N is limited. On the other hand, their stabilization in soils by forming

organo-mineral associates or macromolecule complex reduces the C loss as CO2 into the

atmosphere. Therefore, studies on the turnover, abundance, composition, and stability of

proteins/peptides are of crucial importance to agricultural productivity and environmental

sustainability. In the first part of this study, the bioavailability and distribution of amino acids,

(building block of proteins/peptides), were investigated, in soils across the North-South and

West-East transects of continental United States. The second part of this study aimed to

understand the variations of organic C speciation in soils of continental United States. Previous

investigations of the interactions between soil minerals and proteins/peptides were mostly

limited to batch sorption experiments in labs, seldom of which gave the details at the molecular

scales. Therefore, in the third part of this study, the molecular orientation of self-assembled

oligopeptides on mineral surfaces was investigated by employing synchrotron based

polarization-dependent Near Edge X-ray Adsorption Fine Structure Spectroscopy (NEXAFS)

techniques. Specific aims of this study were: 1) to assess potentially bioavailable pool of

iii

proteinaceous compounds and the immediately bioavailable pool of free amino acids in surface

and subsurface soils of various ecosystems; 2) to evaluate the relationship between

environmental factors and levels/composition of the two pools; 3) to investigate the organic C

speciation in soils of various land use; and 4) to understand molecular level surface organization

of small peptides on mineral surfaces.

The levels of free amino acids and hydrolysable amino acids which represent the

potentially bioavailable pool of proteinaceous compounds in A-horizon soils were significantly

high than in C-horizon soils due to the accumulation of organic matter in surface. On average,

free amino acids accounted for less than 4 % of hydrolysable amino acids which represent the

total proteinaceous compounds in soils. The composition of free amino acids was significantly

different between surface soil and subsurface soil and was significantly influenced by mean

annual temperature and precipitation. A relatively uniform composition of hydrolysable amino

acids was observed irrespective of a wide range of land use. Significant variations were observed

for the levels of free and hydrolysable amino acids along mean annual temperature and

precipitation gradients, as well as among vegetation types of continental USA, suggesting levels

of free and hydrolysable amino acids were associated with the above-ground biomass and root

distribution. Organic C speciation investigation revealed the presence of carboxylic-C (38%),

aliphatic-C (~ 22%), aromatic-C (~ 18%), O/N-alkyl-C (~ 16%), and phenolic-C (< 6%). Factors

such as temperature and vegetation cover were revealed in this study to account for the

fluctuations of the proportions of aromatic-C and phenolic-C, in particular. Phenolic-C may

serve as a good indicator for the effect of temperature or vegetation on the composition of SOC.

The average composition of soil organic C, over the continental scale, was relatively uniform

over various soil ecosystems and between two soil horizons irrespective of surface organic C

iv

content. Polarization dependent NEXAFS analysis showed the oligopeptides tend to orient on

mineral surface with an average tilt angle of 40 ° between the molecular chain and the mineral

surface.

v

Acknowledgements

First of all, I would like to sincerely thank my advisor Dr. Kang Xia for her

excellent guidance, endless support, valuable advice and consistent patience during my

research. She gave me the opportunity to be involved in the synchrotron work and access

the wonderful analytical instrument. I gained a lot through the research. I would also like

to express my great gratitude to committee members Dr. Matthew Eick, Dr. Mark

Williams, Dr. Shang Chao and Dr. Jian Wang for their guidance and support during my

PhD studies. Dr. Matthew Eick gave good advice in the methodologies and lots of

guidance in Soil Chemistry class. Dr. Williams taught me how to use the statistical

software to process the data and shared experiences with me in PhD pursuing. Dr. Shang

provided me with lots of information in solving the problems encountered during my

research. Dr. Wang taught me how to operate the synchrotron beamline. I really

appreciate his patience in explaining to me the basic theories and the procedures to deal

with the original data though Skype.

I would also like to thank the technical staff in Canadian Light Source and

Synchrotron Radiation Center in WI for their hard work. I want to thank Dr. David B.

Smith from the United States Geological Services (USGS), who provided the samples,

allowing me to gain meaningful data to fulfill the thesis.

I am grateful to the faculty and staff members in Crop and Soil Environmental

Sciences for their encouraging, concern and support. Dr. Lee Daniels patiently helped me

solve the problems during my academic process. Dr. Xunzhong Zhang shared with me

lots of information in paper writing and career pursuing skills. I would also like to thank

the staff and graduate students, Jude Moon, Rosana Pineda, Richard Rodrigues, Madhavi

http://www.src.wisc.edu/

vi

Kakumanu and Kerri Mills in Rhizosphere-Soil Microbial Ecology and Biogeochemistry

lab of Horticulture Department, for collecting samples and providing the technical

support during my stay in their lab. They shared everything in the lab with me and took

me as one member of the lab, where I finished one third of my experimental work. I

would also like to thank Dr. Alan Esker in Chemistry Department who provided the

equipment. I am also thankful to our lab manager Hubert Walker, my colleagues Chao

Qin, Theresa Sosienski, Julia Cushman, Lucas Waller and Fatmaalzhraa Awad, and my

roommate Shan Sun and Ying Ni for their warm help and encouragement during my PhD

study.

Finally, I would like to extent my deepest gratitude to my family members for

their endless love and unrequited support. I would like to thank my husband Wei Lu’s

meticulous care and long live understanding. I cannot thank enough my parents’

confidence and comfort. Their love and support are spiritual pillars of my life.

Funding by the USDA-AFRI (award #2012-67019-30227) and NSF (award #

EAR 0949653 10010064) is gratefully appreciated. Research based on synchrotron

techniques was performed at the Canadian Light Source, which is supported by Natural

Sciences and Engineering Research Council of Canada (NSERC), National Research

Council (NRC), Canadian Institutes of Health Research (CIHR), and the University of

Saskatchewan.

https://plus.google.com/u/0/114149940861453480252?prsrc=4

vii

Attributions

Chapter 3: Immediately Bioavailable Free Amino Acids in Soils of North-South and

West-East Transects of Continental United States

Kang Xia, PhD (Crop and Soil Environmental Sciences, Virginia Tech): Dr. Xia was the

co-principle investigator for the grant (USDA-AFRI, award #2012-67019-30227)

supporting the research.

Mark A. Williams, PhD (Horticulture Department, Virginia Tech): Dr. Williams was the

principle investigator for the grant (USDA-AFRI, award #2012-67019-30227) supporting

the research.

David. B. Smith, PhD (United State Geological Services): Dr. Smith provided samples

for the research.

Chapter 4: Hydrolysable Amino Acids in Soils of North-South and West-East

Transects of Continental United States






the research.

David. B. Smith, PhD (United State Geological Services): Dr. Smith provided samples

for the research.

Chapter 5: Carbon K-edge Near Edge X-ray Fine Structure Spectroscopic

Investigation of Organic Carbon Speciation in Soils of North-South and West-East





Jinyoung Moon (Horticulture Department, Virginia Tech): Ms. Moon is a PhD candidate

who helped me collect data in synchrotron radiation center, in WI.

viii



the research.

David B. Smith, PhD (United State Geological Services): Dr. Smith provided samples for

the research.

Chapter 6: Polarization dependent X-ray Photoemission Electron Microscopic and

Near Edge X-ray Fine Structure Spectroscopic Investigation of Hexa-glycine

Surface Orientation Sorbed on Montmorillonite


principle investigator for the grant (NSF, award # EAR 0949653 10010064) supporting

the research.

Jian Wang, PhD (Canadian Light Source): Dr. Wang is a research scientist in Canadian

Light Source who helped us collect and analyze the data.


co-principle investigator for the grant (NSF, award # EAR 0949653 10010064)


ix

Table of Contents Abstract ........................................................................................................................................... ii

Acknowledgements ......................................................................................................................... v

Attributions .................................................................................................................................... vii

List of Figures .............................................................................................................................. xiii

List of Tables ............................................................................................................................... xvii

List of Abbreviations .................................................................................................................. xviii

1. Introduction ............................................................................................................................... 1

1.1. Background ................................................................................................................1

1.2. Objectives ...................................................................................................................4

References .........................................................................................................................6

2. Literature Review .................................................................................................................... 10

2.1. Biogeochemistry of amino acids in soils .................................................................... 10

2.1.1 Distribution and occurrence ...................................................................................... 14

2.1.2. Transformation of peptides/proteins into amino acids .......................................... 18

2.1.3. Fate of amino acids .................................................................................................... 21

2.2. Mineral-associated organic N ................................................................................... 22

2.2.1. Mechanisms involved in the mineral organic interactions .................................... 22

2.2.2. Factors influencing mineral-organic N interactions ............................................... 24

2.2.3. Evaluation of molecular orientation on mineral surfaces ...................................... 26

2.2.4. Synchrotron based spectroscopic method to study organic C and N speciation . 28

2.3. Summary .................................................................................................................. 31

References ....................................................................................................................... 33

3. Immediately Bioavailable Free Amino Acids in Soils of North-South and West-East

Transects of Continental United States ..................................................................................... 45

3.1. Abstract .................................................................................................................... 46

3.2. Introduction ............................................................................................................. 48

3.3. Materials and methods ............................................................................................. 50

3.3.1. Study sites and soil sampling .................................................................................... 50

3.3.2. Chemicals ................................................................................................................... 51

3.3.3. Free amino acid extraction from soil ....................................................................... 52

3.3.4. Amino acids derivatization ....................................................................................... 52

3.3.5. HPLC/FLD analysis of derivatized amino acids ..................................................... 54

x

3.3.6. Statistical analysis ...................................................................................................... 55

3.4. Results and discussion .............................................................................................. 56

3.4.1. Composition and concentrations of extractable soil amino acids ......................... 56

3.4.2. Extractable amino acids in A and C horizon soils .................................................. 60

3.4.3. Variations of extractable soil amino acids along MAT and MAP gradients of

continental United States .................................................................................................... 65

3.4.4. Variations of extractable soil amino acids among different vegetation covers .... 72

3.5. Conclusions .............................................................................................................. 75

3.6. Acknowledgements ................................................................................................... 76

References ....................................................................................................................... 77

4. Hydrolysable Amino Acids in Soils of North-South and West-East Transects of

Continental United States ........................................................................................................... 85

4.1. Abstract .................................................................................................................... 86

4.2. Introduction ............................................................................................................. 88

4.3. Materials and methods ............................................................................................. 89

4.3.1. Study sites and sampling ........................................................................................... 89

4.3.2. Chemicals ................................................................................................................... 90

4.3.3. Hydrolysis and purification ...................................................................................... 91

4.3.4. Amino acid derivatization ......................................................................................... 92

4.3.5. Analysis of derivatized amino acids on HPLC/FLD ............................................... 93

4.3.6. Statistical analysis ...................................................................................................... 94

4.4. Results and discussion .............................................................................................. 95

4.4.1. The composition and concentrations of HAAs ........................................................ 95

4.4.2. HAAs in A and C horizons ...................................................................................... 97

4.4.3. Variations of HAAs along MAT and MAP gradients of continental United States

............................................................................................................................................. 101

4.4.4. Variations of HAAs among different vegetation covers ....................................... 104

4.4.5. Comparisons of THAAs with TFAAs and implications ....................................... 109

4.5. Conclusions ............................................................................................................ 114

4.6. Acknowledgements ................................................................................................. 115

References ..................................................................................................................... 116

5. Carbon K-edge Near Edge X-ray Fine Structure Spectroscopic Investigation of Organic

Carbon Speciation in Soils of North-South and West-East Transects of Continental United

States ........................................................................................................................................... 124

xi

5.1. Abstract .................................................................................................................. 125

5.2. Introduction ........................................................................................................... 126

5.3. Materials and Methods ........................................................................................... 128

5.3.1. Study sites and sampling ......................................................................................... 128

5.3.2. Sample preparation ................................................................................................. 129

5.3.3. Date collecting .......................................................................................................... 129

5.3.4. Data processing ........................................................................................................ 130

5.3.5. Statistics .................................................................................................................... 131

5.4. Results and Discussion ............................................................................................ 131

5.4.1. Soil organic C speciation and relative composition characterization ................. 131

5.4.2. Soil organic C speciation and relative composition in A and C horizons ........... 135

5.4.3. Soil organic C speciation and relative composition variations along temperature

and precipitation gradients of continental United States ............................................... 137

5.4.4. Soil organic C speciation and relative composition variations among different

vegetation covers ................................................................................................................ 141

5.5. Conclusions ............................................................................................................ 144


References ..................................................................................................................... 145

6. Polarization Dependent X-ray Photoemission Electron Microscopic and Near Edge X-

ray Fine Structure Spectroscopic Investigation of Hexa-glycine Surface Orientation

Sorbed on Montmorillonite ........................................................................................... 155

6.1. Abstract .................................................................................................................. 156

6.2. Introduction ........................................................................................................... 157

6.3. Materials and methods ........................................................................................... 160

6.3.1 Chemicals and materials .......................................................................................... 160

6.3.2. Preparation of monolayer montmorillonite .......................................................... 161

6.3.3. Polarization-dependent N K-edge NEXAFS ......................................................... 164

6.3.4. Data processing ........................................................................................................ 164

6.4. Results and Discussion ............................................................................................ 165

6.5. Conclusions ............................................................................................................ 173


References ..................................................................................................................... 175

7. Conclusions ............................................................................................................................ 182

xii

Appendix .................................................................................................................................... 186

Appendix A. Geochemical data for samples of surface soils (A horizon) and subsoil (C

horizon) collected in the conterminous United States .................................................... 186

Appendix B. Mineralogical data for samples from the soil C and A horizons in the

conterminous United States ........................................................................................... 192

Appendix C. Concentrations of free amino acids detected in soils (mmol kg-1 dry soil) 203

Appendix D. Concentrations of hydrolysable amino acids detected in soils (µmol kg-1 dry

soil) ............................................................................................................................... 212

xiii

List of Figures

Chapter 1: Introduction Figure 1.1.Simulated terrestrial N cycle modified based on Xu and Prentice (2008); a: sorption; b:

desorption; c: decomposition; d: humification; e: cell uptake (immobilization); f: exudation; g:

autolysis; h: root uptake; i: mineralization; j: tropic interaction; k: degradation & utilization; l:

fixation............................................................................................................................................. 1

Chapter 2: Literature Review Figure 2. 1.The basic structure of amino acid ............................................................................... 10

Figure 2. 2. Combined paradigms of the soil N cycle modified according to (Schimel and Bennett,

2004). Solid line section are common steps for both traditional and new paradims, while dash line

section is exclusive to the new paradim. Red line indicates the rate-limiting step of N cycle in

each paradim. a: depolymerization; b: root uptake; c: mineralization; d: immobilization; e: cell

uptake (immobilization); f: degradation; g: nitrification; h: leaching. .......................................... 22

Figure 2. 3. Geometry of peptide bond (modified based on Liu et al. (2006)). The p-orbital (large

arrow) is oriented perpendicular to the plane of peptide bond. The oligopeptide molecules are

self-assembled on the surface of wafer (lower). ............................................................................ 27

Figure 2. 4. N (1s) K-edge NEXAFS spectra of a 16-unit peptides bound to gold surface recorded

at two incident x-ray angles (Iucci et al., 2008). ........................................................................... 28

Figure 2. 5. Typical C (above) and N (below) K-edge NEXAFS spectrum (TFY) deconvolution

from the mineral-organic fraction of a soil sample. Typical C (above) and N (below) K-edge

NEXAFS spectrum (TFY) deconvolution from the mineral-organic fraction of a soil sample. ... 30


West-East Transects of Continental United States Figure 3. 1. Location of soil sampling sites from west to east and north to south transects on

gradients of (above) MAP, and (below) MAT. Sites were grouped into sub-continental areas as

shown in circles. The legends at the right of each sub-figure apply to the circles. ....................... 50

Figure 3. 2. Chromatograms of derivatized amino acids in (above) 10µM standard and (below) a

A-horizon soil sample from a grassland site in Minnesota. 1=Asp; 2=Glu; 3= 6-aminoquinoline;

4=Ser+Asn; 5=Gly; 6=Gln; 7=His; 8=NH4+; 9=Arg; 10=Tau; 11=Cit; 12=Thr; 13=Ala;

14=GABA; 15=Pro; 16=AABA (internal standard); 17=Tyr; 18=Cys-Cys; 19=Val; 20=Met;

21=Orn; 22=Ile; 23=Lys; 24=Leu; 25=Phe; 26=Trp. .................................................................... 59

Figure 3. 3. NMS ordination of 298 samples from 149 sampling sites. Sites were grouped into A

horizon and C horizon. High correlation of variables (cut off r2 = 0.2) with ordination was

indicated in biplot vector, where length and direction represent the magnitude and direction of the

correlation, respectively. Ordination of sites captured two dimensions with a final stress of 14

where Axis 1 explained 58 % and Axis 2 explained 34 % of total variance respectively. ............ 62

Figure 3. 4. Average composition of individual and sum of eight dominant FAAs in A and C

horizons from different transects. Scale on right side applies to sum of the eight major FAA.

Different lower case letters indicate statistical significance by pairwise comparison (α = 0.05).

Values are expressed as mean ± Standard Error of Mean (SEM). ................................................ 63

xiv

Figure 3. 5. Average concentration of eight major FAAs and TFAAs in two horizon soils from

different transects. Different lower case letters indicate statistical significance by pairwise

comparison (α=0.05). Scale on right side applies to TFAAs. Values are expressed as mean ± SEM.

....................................................................................................................................................... 65

Figure 3. 6. Correlations of NMS axes with MAT and MAP. Black dots represents sampling sites.

The percentages in Y-axis are the variability explained by each NMS ordination axis. ............... 67

Figure 3. 7. NMS ordinations of 298 samples from in four groups. Correlations of variables with

ordination with r2 > 0.2 were indicated in biplot vector, where length and direction represent the

magnitude and direction of the correlation, respectively. Ev, evergreen; Gr, grassland; Sh, shrub;

De, deciduous forest; Cr, cropland; Pa, pasture; Fa, fallow; Re, residential ................................. 68

Figure 3. 8. Average concentrations of eight major FAAs and TFAAs in soils of A and C

horizons along the MAT and MAP gradients of continental US. Scales on right side applies to

TFAAs. MAT and MAP gradients shown in the legends differentiated by color are from the

circled areas specified in Figure 3.1. Values were expressed as mean ± SEM. # mean annual

temperature; * mean annual precipitation; § soils from west coast. .............................................. 71


horizon soils with different vegetation cover. Scales on right side apply to sum of eight major

FAA proportions. Different lower case letters indicate statistical significance among groups.

Values are expressed as mean ± SEM. .......................................................................................... 74

Figure 3. 10. Concentration of TFAAs (A) and total soil organic C content (B) among four

vegetation covers in two horizons. A = A horizon; C = C horizon; A/C Ratio = the ratio of

average TFAA level or soil total organic C content in the A horizon to that in the C horizon.

Values are expressed as mean ± SEM. .......................................................................................... 75


Transects of Continental United States Figure 4. 1. Chromatograms of (A) amino acid derivatives with amino acids standard (10µM) and

(B) the amino acids in a surface soil sampled from a pasture area in Minnesota. Peaks: 1= 6-

aminoquinoline; 2=Asp; 3=Ser; 4=Glu; 5=Gly; 6=His; 7=NH4+; 8=Arg; 9=Thr; 10=Ala; 11=Pro;

12=Tyr; 13=Cys-Cys; 14=Val; 15=Met; 16=L-norvaline; 17=Lys; 18=Ile; 19=Leu; 20=Phe. The

peak between 16 and 17 in (A) is ornithine. .................................................................................. 97

Figure 4. 2. Average composition of individual and sum of eight major HAAs in samples of two

soil horizons from different transects. Scale on right side applies to sum of eight major FAA

proportions. Different lower case letters indicate statistical significance based on pairwise

comparison (α = 0.05). Values are expressed as mean ± Standard Error of Mean (SEM). ........... 98

Figure 4. 3. Average concentration of eight major HAAs and HAAs in two horizon soils from

different transects. Scale on right side applies to THAAs. Different lower case letters indicate

statistical significance among groups (α=0.05). Values are expressed as mean ± SEM. ............ 100

Figure 4. 4. Linear relationship between the concentrations of THAAs and major HAAs with total

soil organic C content (wt%) from two horizons. ....................................................................... 101

Figure 4. 5. Average concentrations of eight major HAAs and THAAs in A- and C-horizon soils

along the MAT and MAP gradients. Scales on right side apply to THAAs. The above two and the

bottom two sub-figures indicate the trend of amino acid level with MAT and MAP, respectively.

Temperature or precipitation gradients shown in the legends differentiated by color are from the

xv

circle areas specified in Figure 3.1. Values were expressed as mean ± SEM. # mean annual

temperature; * mean annual precipitation; § soils from west coast. ............................................ 102

Figure 4. 6. Average composition of individual and sum of eight dominant HAAs in A and C

horizon soils with different vegetation cover. Scales on right side applies to sum of eight major

HAA proportions. Different lower case letters indicate statistical significance among groups

(α=0.05). Values are expressed as mean ± SEM. ........................................................................ 106

Figure 4. 7. Concentration of THAAs (A) and total soil organic C content (B) among four

vegetation covers in two soil horizons. A = A horizon; C = C horizon; A/C Ratio = the ratio of

average THAA level or soil total organic C content in the A horizon to that in the C horizon.

Values are expressed as mean ± SEM. ........................................................................................ 108

Figure 4. 8. The average proportions of each amino acid in the HAA or FAA form. ................. 113

Figure 4. 9. Relationship between TFAAs and THAAs in soils investigated from the 93 sites. Red

and green represent samples from C and A horizon, respectively. ............................................. 114

Chapter 5: Carbon K-edge Near Edge X-ray Fine Structure Spectroscopic

Investigation of Organic Carbon Speciation in Soils of North-South and West-East

Transects of Continental United States Figure 5. 1. C K-edge NEXAFS spectrum deconvolution showing the six main 1s-π* transition

and two σ* transitions and the arctangent step function (290 eV) from a deciduous forest soil

from Missouri. ............................................................................................................................. 133

Figure 5. 2. Carbon K-edge NEXAFS of A-horizon (A) and C-horizon (C) soil samples from a

mixed forest site (California), a shrubland site (New Mexico), and a grassland/herbaceous site

(Oklahoma). ................................................................................................................................. 134

Figure 5. 3. The relative contents (in % of total organic C) of soil organic C species along an A-

horizon soil organic C (wt. %) gradient. ..................................................................................... 137

Figure 5. 4. Relative contents (in % of total organic C) of soil organic C species from A- and C-

horizon soils along the W-E mean annual precipitation transect. The box plots show the median

(the line in the box), 5th/95th percentile (lower and upper bars), and outliers (black dots). ....... 138


horizon soils along the N-S mean annual temperature transect. The box plots show the median

(the line in the box) and 5th/95th percentile (lower and upper bars). .......................................... 138

Figure 5. 6. The relative contents (in % of total organic C) of soil organic C species in A- and C

horizon soils with different vegetation cover. ............................................................................. 142

Figure 5. 7. Weight ratios of (left) (in wt %) of soil organic C species in A- horizon to that in C-

horizon soils with different vegetation cover and (right) ratios of total soil organic C content

(wt %) in A-horizon soil to that in C-horizon soil. ...................................................................... 142

Chapter 6: Polarization dependent X-ray Photoemission Electron Microscopic and

Near Edge X-ray Fine Structure Spectroscopic Investigation of Hexa-glycine

Surface Orientation Sorbed on Montmorillonite Figure 6. 1. Schematic diagram of (a) monolayer montmorillonite preparation using the LB

trough technique and (b) procedure for preparation of monolayer hexa-glycine on

montmorillonite surface............................................................................................................... 163

xvi

Figure 6. 2. AFM image (5µm × 5µm)(left) of montmorillonite-coated Si water. The cross-section

profile (lower right) was determined along the line in the zoomed image (upper right).The height

differences (1.43 nm) indicates the thickness of the montmorilonite sheet. ............................... 163

Figure 6. 3. (a) PEEM image recorded at the Al K-edge at a photon energy of 1579 eV before

(left) and after montmorillonite region (bright area) were selected (middle) and the Al 1s

NEXAFS spectrum of selected area (right); (b) PEEM image recorded at the N K-edge at a

photon energy of 411.2 eV before (left) and after bright area were selected (middle) and the N 1s

NEXAFS spectrum of selected area (right) at grazing incidence; (c) PEEM image recorded at the

N K-edge at the photon energy of 400.1 eV before (left) and after bright area were selected

(middle) and the N 1s NEXAFS spectrum of selected area (right) at normal incidence. ............ 167

Figure 6. 4. N K-edge NEXAFS spectra of peptides adsorped onto monolayer montmorillonite on

Si substrate recorded at normal and grazing incidence. .............................................................. 169

Figure 6. 5. (a)Structural formula, (b) ß-sheet strand and (c) sideview of the sheet of self-

assembled Hexa-glycine; (d) Simplified scheme of assembled peptides on montmorillonite and

definitions of angles used to characterize the molecular orientations. All the angles were

calculated with respect to surface normal. Angle θ1 and θ2 represent the incidence angle at normal

and grazing incidence, and θ1E and θ2E are angles of electric vector with respect to surface normal.

While α is the angle between peptide p-orbital with surface normal, equal to the tilt angle of

peptide backbone with surface. ................................................................................................... 170

Figure 6. 6. Distribution different dissociation states of dissolved Hexa-glycine as a function of

pH, determined based on the published dissociation constants (pKa) of carboxylic acid (3.13) and

the ammonium ion acid (7.69) (Glasstone and Hammel, 1941). ................................................. 172

Figure 6. 7. The proposed schematic diagrams of the orientation of the adsorbed hexa-glycine on

montmorillonite. .......................................................................................................................... 172

xvii

List of Tables Chapter 2: Literature Review

Table 2. 1. Properties of naturally occurred amino acids used in this study ................................. 11

Table 2. 2. C/N 1s NEXAFS approximate fit energy position of primary peaks .......................... 31


West-East Transects of Continental United States Table 3. 1. Detection limits, recovery and the precision of the determination of amino acid

derivatives. .................................................................................................................................... 55

Table 3. 2. Concentrations (mg kg-1

dry soil) of free amino acids ................................................ 63


Transects of Continental United States Table 4. 1. Detection limits, recovery and the precision of the determination of amino acid

derivatives. .................................................................................................................................... 94


dry soil) of major HAAs and THAAs. ................................. 98

xviii

List of Abbreviations

AFM Atomic force microscopy

AQC 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate

FAAs Free amino acids

FLD Fluorescence detector

FTIR Fourier transform infrared spectroscopy

FWHM Full-width at high maximum

HAAs Hydrolysable amino acids

HPLC High performance liquid chromatography

ISON Insoluble organic nitrogen

MAP Mean annual precipitation

MAT Mean annual temperature

MRPP Multiple response permutation procedure

NEXAFS Near edge X-ray fine structure spectroscopy

NMR Nuclear magnetic resonance

NMS Nonmetric multidimensional scaling

N-S North-South

Py-FIMS Pyrolysis-field ionization mass spectrometry

SIMS Secondary ion mass spectrometry

SOC Soil organic carbon

SOM Soil organic matter

SON Soluble organic nitrogen

STXM Scanning transmission X-ray microscope

TEA Triethylamine

TEM Transmission electron microscopy

TEY Total electron yield

TFAAs Total free amino acids

TFY Fluorescence yield

THAAs Total hydrolysable amino acids

W-E West-east

X-PEEM X-ray photoemission electron microscope

XPS X-ray photoelectron spectroscopy

1

1. Introduction

1.1. Background

Soil organic matter (SOM) consists of living soil organisms, plant residues, soil fauna,

and the remains of previous living organisms in their various degrees of decomposition (Paul,

2006). As shown in Figure 1.1, it is estimated that more than 85% of terrestrial N is in organic

form. There is a dynamic flux between the soil soluble organic nitrogen (SON) pool and the soil

insoluble organic nitrogen pool (ISON) (Figure 1.1) The N cycle starts from the degradation of

SOM and proceeds, via the depolymerization of proteins/peptides into free amino acids (FAAs),

which, if not taken up by plant root or microorganisms, are further broken down to ammonium,

followed by the process of nitrification and denitrification.

Figure 1.1.Simulated terrestrial N cycle modified based on Xu and Prentice (2008); a: sorption;

b: desorption; c: decomposition; d: humification; e: cell uptake (immobilization); f: exudation; g:

autolysis; h: root uptake; i: mineralization; j: tropic interaction; k: degradation & utilization; l:

fixation.

Vegetation(5.3 Pg N)

Litter(4.6 Pg N)

Soil(68 Pg N)

Organic N(67 Pg N)

Inorganic N(0.9 Pg N)

SON

Proteins

Peptides

Amino acids

ISON

minerals

organic matter

microorganisms

plant roots

Terrestrial N

ab

cd

ef, g

f, c

h

hi

f j

e

k

c

l

Leaching i

a bd

2

Soil SON is operationally defined as organic form of N dissolved in water or extracted by

0.01M to 2M salt solutions (e.g. CaCl2, KCl, K2SO4)(Chen and Xu, 2006). Unlike inorganic

forms of N which are simple compounds, SON is usually a complex mixture of compounds, such

as phenols, amino acids, amino-sugars, proteins peptides or tannins. Most of tannins and

proteins/peptides are of hydrophobic fraction (Smolander and Kitunen, 2002), while phenols,

amino acids, and amino-sugars are of hydrophilic fraction. The pool size of SON varies with

different soil systems. The SON pool can be as large as the inorganic N pool, both of which can

take up ~ 50% of the soluble N pool (Murphy et al., 2000). The SON consists of two pools: the

SON that is labile and readily available to plants and microorganisms, and the SON that is

recalcitrant and not readily metabolizable (Neff et al., 2003; Ge et al., 2010). It is reported that

nearly 40% of the total soil N is present in form of protein and peptides (Leinweber and Schulten,

1998). Study has shown that approximate 60% of N extracted by 0.01M CaCl2 (i.e SON) from an

agricultural soil was amino acids and peptides (Mengel et al., 1999). These biomolecules, which

are thought to have biologically labile chemical structures, are expected to be quickly

mineralized during early stages of organic matter stabilization (Knicker, 2004).

The classic study on SON assumes microbial mineralization a critical step in terrestrial N

cycling and plants only use inorganic N and are poor competitors for available N relative to

microbes (Fisk and Schmidt, 1995; Schimel and Bennett, 2004). Contrary to the mineralization-

focused paradigm, recent findings suggest that plants can “short circuit” the N cycling via uptake

of soluble organic N such as amino acids (Jones and Darrah, 1994; Kielland, 1994; Neff et al.,

2003), amino sugars (Roberts and Jones, 2012) or peptides and proteins (Abuzinadah and Read,

1989; Paungfoo-Lonhienne et al., 2008). Depolymerization of peptides and proteins was

proposed in the recent paradigm as the rate-limiting step in the transformation from polymetric N

3

to bioavailable N (Schimel and Bennett, 2004; Xu and Prentice, 2008; Rennenberg et al., 2009).

Despite the important roles of peptides and proteins in the terrestrial N cycling, little attention

has been given on their biogeochemistry compared to soil organic C (SOC).

Soluble organic N can be produced from microbial turnover (Seely and Lajtha, 1997) and

through microbial generation of extracellular enzymes (Leirós et al., 2000). In spite of its

importance, there is still uncertainty on its dynamic transformation between the SON and the

ISON pools. It is of great importance to investigate the mechanisms involved in the mobility,

reactivity and stability of soil organic N. There are several mechanisms to explain the stability of

soil organic N in soil systems, for example, encapsulation into hydrophobic macromolecules

(Knicker and Hatcher, 1997), sequestration in nanopores that are too small for organisms or

enzymes to enter, or formation of mineral-organic associates (Baldock and Skjemstad, 2000), the

latter of which was affected by soil mineralogy, mineral surface reactivity, or organic matter

content, etc (Moore et al., 1992; Kaiser and Zech, 2000). The degradability of some organic

compounds will decrease after their sequestration. The interactions between minerals and organic

compounds were widely recognized as of crucial importance in SOM stability (Kleber et al.,

2007). Nevertheless, the early investigations on mineral-organic associates were mostly limited

to observations at the macroscopic scale based on batch equilibrium experiments (Dashman and

Stotzky, 1982, 1984). Little is known about the nature of those interactions at the molecular scale,

especially for proteinaceous compounds regarding the molecular surface organization which, in

turn, will provide information on their bioavailability and stability.

Soluble organic N, accounting for 0.3-1% of the total N in arable soils (Mengel, 1985)

and 0.3-2% in temperate forest soils (Zhong and Makeschin, 2003), serves as both source and

sink for soil inorganic N (Zhong and Makeschin, 2003). It plays an important role on the rapid

4

inorganic N cycling. Despite its importance in the N cycle, there is a gap in our understanding

regarding the composition, sinks, sources, bioavailability, and stability of SON. Better

understanding of N flux between the SON and ISON pools and factors affecting the stabilization

of protein- and peptide-like compounds on mineral surfaces is essential for understanding

terrestrial N dynamics. This knowledge will help maximize the N utilization and minimize SON

loss in agricultural production. Since all forms of organic N are connected to a “C-backbone”,

this implies that SON has not only an indirect but also a direct impact on SOC cycling. The

major forms of SOC in soils are aliphatic-C, carboxylic-C, aromatic-C, phenolic-C and N/O-

alkyl-C as reveled by C K-edge Near Edge X-ray Fine structure Spectroscopic (NEXAFS)

Investigation (Solomon et al., 2005). The information of SOC speciation helps reveal the

changes of SOM composition with cultivation, decipher mechanisms involved in SOC

accumulations from biologically contrasting organic residues, and then provide us insights into

the regulation of SOC stabilization and C sequestration. So far, such investigations are really

lacking. Therefore, the information on stability and the bioavailability of SON as well as the

speciation of SOC not only benefits the agricultural production and the ecosystem management,

but helps better understand soil C sequestration.

1.2. Objectives

The main objective of this research is to investigate the status of the immediately

bioavailable pool of free amino acids and the potentially bioavailable pool of total proteinaceous

compounds across a wide range of soil ecosystems and how the small peptides interact with soil

minerals at molecular scale.

Specific objectives are: 1) to assess the immediately bioavailable pool of free amino acids

s and the potentially bioavailable pool of total proteinaceous compounds in soils of North-South

5

and West-East transects of continental United States and the relationship between their

composition and levels with environmental factors; 2) to evaluate the organic C speciation in

bulk soils of various ecosystems; and 3) to understand molecular level surface organization of

small peptides on mineral surfaces.

To accomplish the above objectives, Objective 1 was covered in Chapter 3 and 4;

Objective 2 was investigated in Chapter 5; Objective 3 was revealed in Chapter 6 respectively.

6

1.3. References

Abuzinadah, R.A., Read, D.J., 1989. The role of proteins in the nitrogen nutrition of

ectomycorrhizal plants .4. The utilization of peptides by birch (betula-pendula l) infected

with different mycorrhizal fungi. New Phytologist 112, 55-60.

Baldock, J.A., Skjemstad, J.O., 2000. Role of the soil matrix and minerals in protecting natural

organic materials against biological attack. Organic Geochemistry 31, 697-710.

Chen, C.R., Xu, Z.H., 2006. On the nature and ecological functions of soil soluble organic

nitrogen (son) in forest ecosystems. Journal of Soils and Sediments 6, 63-66.

Dashman, T., Stotzky, G., 1982. Adsorption and binding of amino-acids on homoionic

montmorillonite and kaolinite. Soil Biology & Biochemistry 14, 447-456.

Dashman, T., Stotzky, G., 1984. Adsorption and binding of peptides on homoionic


Fisk, M.C., Schmidt, S.K., 1995. Nitrogen mineralization and microbial biomass nitrogen

dynamics in 3 alpine tundra communities. Soil Science Society of America journal 59,

1036-1043.

Ge, T.D., Nie, S., Huang, D.F., Xiao, H.A., Jones, D.L., Iwasaki, K., 2010. Assessing soluble

organic nitrogen pools in horticultural soils: A case study in the suburbs of shanghai

(china). Acta Agriculturae Scandinavica Section B-Soil and Plant Science 60, 529-538.

Jones, D.L., Darrah, P.R., 1994. Amino-acid influx at the soil-root interface of zea-mays l and its

implications in the rhizosphere. Plant and Soil 163, 1-12.

Kaiser, K., Zech, W., 2000. Sorption of dissolved organic nitrogen by acid subsoil horizons and

individual mineral phases. European journal of soil science 51, 403-411.

7

Kielland, K., 1994. Amino-acid-absorption by arctic plants - implications for plant nutrition and

nitrogen cycling. Ecology 75, 2373-2383.

Kleber, M., Sollins, P., Sutton, R., 2007. A conceptual model of organo-mineral interactions in

soils: Self-assembly of organic molecular fragments into zonal structures on mineral

surfaces. Biogeochemistry 85, 9-24.

Knicker, H., 2004. Stabilization of n-compounds in soil and organic-matter-rich sediments - what

is the difference? Marine Chemistry 92, 167-195.

Knicker, H., Hatcher, P.G., 1997. Survival of protein in an organic-rich sediment: Possible

protection by encapsulation in organic matter. Naturwissenschaften 84, 231-234.

Leinweber, P., Schulten, H.R., 1998. Nonhydrolyzable organic nitrogen in soil size separates

from long-term agricultural experiments. Soil Science Society of America journal 62,

383-393.

Leirós, M.C., Trasar-Cepeda, C., Seoane, S., Gil-Sotres, F., 2000. Biochemical properties of acid

soils under climax vegetation (atlantic oakwood) in an area of the european temperate–

humid zone (galicia, nw spain): General parameters. Soil Biology and Biochemistry 32,

733-745.

Mengel, K., 1985. Dynamics and availability of major nutrients in soils, In: Stewart, B.A. (Ed.),

Advances in soil science. Springer New York, pp. 65-131.

Mengel, K., Schneider, B., Kosegarten, H., 1999. Nitrogen compounds extracted by

electroultrafiltration (euf) or cacl2 solution and their relationships to nitrogen

mineralization in soils. Journal of Plant Nutrition and Soil Science 162, 139-148.

Moore, T.R., Desouza, W., Koprivnjak, J.F., 1992. Controls on the sorption of dissolved organic-

carbon by soils. Soil Science 154, 120-129.

8

Murphy, D.V., Macdonald, A.J., Stockdale, E.A., Goulding, K.W.T., Fortune, S., Gaunt, J.L.,

Poulton, P.R., Wakefield, J.A., Webster, C.P., Wilmer, W.S., 2000. Soluble organic

nitrogen in agricultural soils. Biology and Fertility of Soils 30, 374-387.

Neff, J.C., Chapin, F.S., Vitousek, P.M., 2003. Breaks in the cycle: Dissolved organic nitrogen in

terrestrial ecosystems. Frontiers in Ecology and the Environment 1, 205-211.

Paul, E.A., 2006. Soil microbiology, ecology and biochemistry. Academic press.

Paungfoo-Lonhienne, C., Lonhienne, T.G.A., Rentsch, D., Robinson, N., Christie, M., Webb,

R.I., Gamage, H.K., Carroll, B.J., Schenk, P.M., Schmidt, S., 2008. Plants can use protein

as a nitrogen source without assistance from other organisms. Proceedings of the

National Academy of Sciences of the United States of America 105, 4524-4529.

Rennenberg, H., Dannenmann, M., Gessler, A., Kreuzwieser, J., Simon, J., Papen, H., 2009.

Nitrogen balance in forest soils: Nutritional limitation of plants under climate change

stresses. Plant Biology 11, 4-23.

Roberts, P., Jones, D.L., 2012. Microbial and plant uptake of free amino sugars in grassland soils.

Soil Biology & Biochemistry 49, 139-149.

Schimel, J.P., Bennett, J., 2004. Nitrogen mineralization: Challenges of a changing paradigm.

Ecology 85, 591-602.

Seely, B., Lajtha, K., 1997. Application of a 15n tracer to simulate and track the fate of

atmospherically deposited n in the coastal forests of the waquoit bay watershed, cape cod,

massachusetts. Oecologia 112, 393-402.

Smolander, A., Kitunen, V., 2002. Soil microbial activities and characteristics of dissolved

organic c and n in relation to tree species. Soil Biology and Biochemistry 34, 651-660.

9

Solomon, D., Lehmann, J., Kinyangi, J., Liang, B.Q., Schafer, T., 2005. Carbon k-edge nexafs

and ftir-atr spectroscopic investigation of organic carbon speciation in soils. Soil Science

Society of America journal 69, 107-119.

Xu, R.I., Prentice, I.C., 2008. Terrestrial nitrogen cycle simulation with a dynamic global

vegetation model. Global Change Biology 14, 1745-1764.

Zhong, Z., Makeschin, F., 2003. Soluble organic nitrogen in temperate forest soils. Soil Biology

and Biochemistry 35, 333-338.

10

2. Literature Review

2.1. Biogeochemistry of amino acids in soils

Amino acids, which are constitutes of proteins or peptides, are usually α-amino acids

with common structure that consists of hydrogen atoms, a R-group, an amino and a carboxyl

functional group attached to the same tetrahedral carbon atom, α-carbon (Figure 2.1). Each

amino acid has its own distinctive R-group (Table 2.1). The presence of amino acids in soils and

organic matter is due to the breakdown of native proteins derived from plants, microbes and

animal tissue (Senwo and Tabatabai, 1998). Amino acids in soils are classified into three pools

(Yu et al., 2002; Jämtgård, 2010): 1) free amino acids (FAAs), which are those dissolved in soil

solution and are directly available to organisms; 2) exchangeable amino acids, which are bound

to charged surfaces on clay particles and soil organic matter (SOM), but potentially

exchangeable into soil solution; and 3) hydrolysable amino acids (HAAs), mostly proteinaceous

compunds (e.g., proteins and peptides), that are tightly bound to mineral surfaces and difficult to

be exchanged into soil solutions.

Figure 2. 1.The basic structure of amino acid

11

Table 2. 1. Properties of naturally occurred amino acids used in this study

Amino acid Abbreviation Structure MW Chemical Families Polarity Side-chain

Chemistry

Glycine Gly

75.1 Aliphatic Nonpolar Neutral

Alanine Ala


Valine Val


Leucine Leu


Isoleucine Ile


Serine Ser

105.1 Non-Aromatic

Hydroxyl Polar Neutral

Threonine Thr

119.1 Non-Aromatic

Hydroxyl Polar Neutral

Methionine Met

149.2 Sulfur-Containing Nonpolar Neutral

12



Chemistry

Cystine Cys-Cys

240.3 Sulfur-Containing Nonpolar Neutral

Aspartic Acid Asp

133.1 Acidic & Amides Polar Acidic

Asparagine Asn

132.1 Acidic & Amides Polar Neutral

Glutamic

Acid Glu

147.1 Acidic & Amides Polar Acidic

Glutamine Gln

146.1 Acidic & Amides Polar Neutral

Arginine Arg

174.2 Basic Polar Basic

Lysine Lys


Histidine His


(Continued)

13



Chemistry

Phenylalanine Phe

165.2 Aromatic Nonpolar Neutral

Tyrosine Tyr

181.2 Aromatic (Hydroxyl ) Nonpolar Neutral

Tryptophan Trp

204.2 Aromatic Nonpolar Neutral

Proline Pro

115.1 Cyclic Nonpolar Neutral

(Continued)

14

2.1.1 Distribution and occurrence

Free amino acids in soils make up only a small fraction of the soil organic N, normally

less than 5% of the total soil organic N (Jones et al., 2004; Ge et al., 2010). In spite of their low

fraction in the soluble organic N (SON) pool, they are widely distributed in different soil systems.

Acidic amino acids including aspartic acid and glutamic acid; neutral amino acids including

glycine, alanine, leucine, isoleucine, valine, serine, and threonine; basic amino acids including

arginine, lysine, and histidine; Imino amino acids including proline and hydroxyproline;

aromatic amino acids including phenylalanine, tyrosine and tryptophane, and non-protein amino

acids such as ornithine and gama-aminobutyric acid have been detected in soils (Gotoh et al.,

1986b; Stevenson, 1994).

Concentration of FAAs can vary many folds among different soil systems (Rothstein,

2009b).The total free amino acids (TFAAs) calculated as the sum of each FAA detected was

reported to be in the range of 20 to 350 nmol per gram dry soil in boreal forest (Werdin-Pfisterer

et al., 2009); 0.1 to 12.7 µM in the agricultural soil solutions (Jämtgård, 2010), from 1.6 to 29.9

µM in forest soil solutions (Yu et al., 2002), and 2 to 10 μM in Arctic and Antarctic soil

solutions (Jones et al., 2005). The concentrations of FAAs in soils or soil solution were found to

exhibit seasonal variations in arctic tundra (Weintraub and Schimel, 2005b) and a young sub-

boreal forest in Wisconsin (Johnson and Pregitzer, 2007) and to be site dependent (Jämtgård,

2010). An increased TFAA concentration in soils across a boreal successional soil sequence was

observed (Werdin-Pfisterer et al., 2009). The major FAAs detected in this study included

glutamic acid, glutamine, aspartic acid, asparagine, alanine, and histidine in all successional

stage (Werdin-Pfisterer et al., 2009). The possible reasons for the increasing FAA concentrations

with soil succession were due to the accumulation of the SOM and subsequent higher biomass

15

across succession, which are sources of amino acids, increased proteolytic activity across

succession, and the greater fine root inputs in later successional stages, which decompose and

turnover faster than the above ground litter inputs (Werdin-Pfisterer et al., 2009). Rothstein

(2009b) found that the pool of FAAs diminished rapidly as site fertility increased along a

temperate forest fertility gradient of northern Lower Michigan, USA, ranging from low mineral

N availability, oak-dominated forests to high mineral N availability, maple-basswood forests.

The concentrations of FAAs in the low fertility site were higher and positively correlated to the

concentration of soluble peptides but universally lower at high fertility sites. These studies

support the hypothesis that peptides or proteins maybe a replenishing source for FAAs. Besides

these, other factors also influence the FAA concentrations in soils, for example plant uptake

(Theodore K. Raab, 1999). The net pool of FAAs is likely a balanced result between productive

processes (i.e. proteolysis, exudation by roots and microbes) and consumptive processes (i.e.

assimilation, mineralization) (Rothstein, 2009b).

In order to quantify peptides/proteins, the largest contributions to the soil organic N pool,

effective methods are needed to cleave all proteins to single amino acids which can be

quantitatively analyzed using modern analytical instrument. The strong hot acid hydrolysis

(normally 6N HCl) has been commonly used to break the peptide bond to liberate FAAs. The

acid released amino acids were called hydrolysable amino acids (HAAs) in this study. This

method accounted for more than half of the total soil N (Olk, 2007). Compared to FAAs in the

soil solution, the total amount of amino acids released by 6 N HCl hydrolysis of SON is usually

dozens of folds higher than TFAAs (Yu et al., 2002; Paul and Williams, 2005; Jämtgård, 2010).

For example, in the soil solutions of agricultural soils, the TFAA concentrations ranged from 0.1

to 12.7 µM while the concentrations of total amount of amino acids released by hydrolysis of

16

SON were 50 times higher than the TFAA concentrations (Jämtgård, 2010). The content of

amino acids released by hydrolyzing the whole soil changed from site to site and was influenced

by crop types or cultivation methods. The concentrations of total hydrolysable amino acids

(THAAs) in 8 soils under arable, grassland and forest use ranged from 34 to 855µmol N g-1

soil

(Friedel and Scheller, 2002). Legumes were suggested to enrich soil HAAs but pearl millet

depleted them in soil, while the application of residues of manure reversed this effect of pearl

millet (Praveen et al., 2002b). This study suggests that soil amendment of organic materials will

increase soil organic N that can be hydrolyzed to amino acids (Jansson et al., 1982; Campbell,

1991; Senwo and Tabatabai, 1998). Research has also suggested that the concentrations of

soluble or total soil HAAs were different based on its origin. The total HAAs ranged from 566 to

1509 mg amino acids kg -1

soil (equivalent to about several to a dozen µmol per gram soil)

(Senwo and Tabatabai, 1998) in the organic matter of surface soils in Iowa with two cropping

systems, around dozens of µM (Jämtgård, 2010) in soil solution, and from 0.70 to 6.1µmol

amino acid-N g -1

dry soil in micro-organisms, from 656 to 855µmol amino acid-N g -1

in litter

layer soils (Friedel and Scheller, 2002).

Despite of substantial concentration differences in soils with different cultivation and

rotation, the composition of the HAAs shows minor differences (Stevenson, 1956; Campbell,

1991; Senwo and Tabatabai, 1998). The composition of individual amino acid expressed as

molar percentage of total amino acids was rather uniform among agricultural soils (Gotoh et al.,

1986b) and soils of different climatic conditions (Sowden et al., 1977). Studies conducted by

Gotoh et al. (1986b) on the rice field soil showed uniform amino acid composition for both

FAAs and HAAs in whole soils regardless of organic amendment. This result suggests that the

distribution pattern of amino acids is not greatly influenced by the organic matter forms. And

17

among the individual amino acid, aspartic acid, glutamic acid, glycine, and alanine were also

found to be dominant amino acids in various soils (Gotoh et al., 1986b; Campbell, 1991; Friedel

and Scheller, 2002). This indicates the relative abundance of dominant amino acids may also be

uniform. The relative molar distribution of HAAs in the whole soil investigated by Friedel and

Scheller (2002) was rather uniform despite a wide range of site properties and different land use.

It was also observed that the pattern of HAAs of the bulk soil was inconsistent to that derived

from microorganisms of the same soil. This study suggested that microbial cell walls were not

the major direct contributor to the bulk of the amino acids in the soil. This observation was

partially inconsistent with the statement by Sowden et al. (1977) and Leinweber and Schulten

(1998) that microorganisms play a major role in the formation of major soil amino acids. Plant

residues, however, were suggested to be the largest contributor to soil amino acids (Friedel and

Scheller, 2002).

Acid hydrolysis of a soil is a commonly used method to extract the soil bound amino

acids, allowing us to determine the fraction of amino acids bound in biomass and those

associated with non-living SOM (i.e. peptides/proteins). The hydrolysis with 6 N HCl normally

releases only 64 - 80% of Kjeldahl-N and bout 20% to 35% of Kjeldahl-N cannot be hydrolyzed

by 6N HCl (Schnitzer and Ivarson, 1982). Mechanism involved in the protection of proteins from

strong acid hydrolysis is by interaction with mineral phase, sorption to clay particles, forming

protein-tannin complexes encapsulation into hydrophobic structures (Knicker, 2011) and other

physical protection such as forming soil aggregation (Rillig et al., 2007). This non-hydrolysable

part of N needs to be qualified and quantified by some other methods such as Pyrolysis-Field

Ionization Mass Spectrometry (Py-FIMS) or X-ray photoelectron spectroscopy (XPS), or

18

synchrotron-based spectroscopy to reveal its relationship with the soil properties and

environmental factors.

2.1.2. Transformation of peptides/proteins into amino acids

It is generally recognized that depolymerization or proteolysis of protein and peptides by

extracellular enzymes is the most important process by which FAAs are produced in soils

(Lipson and Nasholm, 2001; Jones and Kielland, 2002; Schimel and Bennett, 2004). The

proteinaceous or peptidic compounds, once broken down into amino acids, are subject to plant

uptake, leaching, or immobilized and mineralized by soil organisms and microbes. Therefore, to

study the transformation of peptides/proteins is of great significance to better understand the N

flux between SON and ISON pools.

Since extracellular enzymes play a crucial role in peptides/proteins transformation

process, the activity of the enzymes may be used as a measurement of FAA replenishment

capacity (Lipson and Monson, 1998; Weintraub and Schimel, 2005b). The soil N-enzyme

activities can even be used as potential indicators of soil SON pools in the temperate forest

ecosystem because concentrations of soil SON were positively correlated with the soil N-

degrading enzymes independent of sampling time (Yang et al., 2012). Such correlation has also

been observed in the plantation forests in subtropical China (Xing et al., 2010).These results

indicated the production of soil SON was strongly influenced by N-degrading enzymes. The

contribution of microbial turnover to the SON pool, the presence of microbial origin extracellular

enzymes as well as the high microbial biomass in SON (Leirós et al., 2000; Neff et al., 2003;

Xing et al., 2010; Vranova et al., 2013) suggested the major role of microbes involved in the

transformation process. The factors affecting the enzyme activity, such as temperature, substrate,

and pH, will influence the transformation of peptides/proteins into FAAs in soils. Related studies

19

have been reported over various soil systems. Research performed by Berthrong and Finzi (2006)

showed that proteolysis was substrate limited in cold-temperate forests. The protease activity

exponentially increased in response to soil temperature range of -2 to 21 (Fraser et al., 2013).

Both soil protease activities and amino acid flux were inversely correlated with soil pH in Taiga

forest (r2>0.90) (Kielland et al., 2007). Contrary to results by Fraser et al. (2013), the amino acid

transformation was not responsive to 10 temperature differences among the successional

coniferous ecosystems (Kielland et al., 2007). This discrepancy suggested that the soil pH may

exert more influence than the temperature. Other factors such as certain polyphenolic compounds,

aromatic moieties and tannins in particular may retard the transformation process by

sequestrating the substrate or deactivating enzymes (Ladd and Brisbane, 1967; Fierer et al., 2001;

Kraus et al., 2004).

The results by Weintraub and Schimel (2005b) on Alaskan arctic tundra soils were

inconsistent with the findings of Kielland et al. (2007) and Rothstein (2009b). Firstly, Weintraub

and Schimel (2005b) observed that the protein degradation was generally limited by enzyme

activity and only became substrate limited at the times when activity was the highest. This

indicates the protein degradation wasn’t substrate limited when soils were amended with protein

at the time enzyme activities were not the highest. Secondly, Weintraub and Schimel (2005b)

suggested that the recalcitrant SON pool fueled the increase in protease activity, rather than the

labile SON pool in the tundra soils. But in the study of Kielland et al. (2007), it was suggested

that the labile SON from decomposition of fine roots facilitates the protease activity in the

Alaska black spruce stands. Lastly, Weintraub and Schimel (2005b) also observed that

concentrations of TFAAs did not track soil soluble protein levels, and the two often had

opposing patterns, with increasing soluble proteins and decreasing in TFAA levels. Based on the

20

fact that concentrations of TFAAs were low when protease activity was high, the author

suggested that the decline in TFAAs was caused by increased plant and microbial uptake of

amino acids rather than a decline in their supplies. The conclusion was that N limitation induced

protease synthesis was the most likely explanation for increases in protease potential observed in

these tundra soils because an increase in protease was driven by increased N demand but not the

protein availability. While in the study performed by Kielland et al. (2007), the soil protease

activity was closely related to the TFAAs (r2=0.97) and exhibited a curvilinear relationship to

soil soluble protein (extracted with 0.1 M NaHCO3) levels, indicating that the increased

proteolysis maybe protein supply driven based on the natural substrate pool.

It is assumed the microbial biomass usually undergoes large seasonal fluctuations and

contributes to labile soil organic N (Lipson and Nasholm, 2001). Lipson et al. (1999b) observed

that microorganisms declined immediately after snowmelt, releasing proteins to the soil along

with the saturated proteases but later became substrate limited. Lipson and Monson (1998)’s

study, however, showed that the microorganisms in alpine soils were resistant to freezing and

drying stress, and insignificant amount of biomass was reduced during the adverse environment;

the water-extractable amino acids decreased by freezing, but increased by drying. These results

contrast to the claims by others that large microbial population was killed during the dry-

rewetting or freeze-thaw situation (Kieft et al., 1987; Skogland et al., 1988). Thus, the variation

of microbial biomass at challenging environment and their contribution to the amino acid

turnover need to be re-evaluated. In summary, as discussed by Weintraub and Schimel (2005b),

two processes are limiting the proteolysis, one by substrate availability controlled by fine roots

or microbial turnover, and the other by increased N demand controlled by solubilization of

recalcitrant protein complexes. It seems microorganisms play an important role in the process by

21

excreting extracellular enzymes and contributing to increased substrate availability or by

absorbing the amino acids resulting in decreased substrate availability.

2.1.3. Fate of amino acids

Amino acids are subject to plant uptake, microorganism immobilization, leaching loss,

humification into organic matter, and decomposition into inorganic N (Figure 1.1 and 2.1). The

fact that plant can uptake amino acids has been demostrated in different ecosystems, such as

agricultural fields (Lipson and Nasholm, 2001), arctic coastal salt marsh (Henry and Jefferies,

2003), and tundra (Schimel and Chapin, 1996), and by different plant species (Persson and

Näsholm, 2001). Amino acid transporters are suggested to be facilitators for amino acid

assimilation by roots (Rentsch et al., 2007). Plants assimilate amino acids in direct competition

with soil microbes which immolilize amino acid for biomass acquisition (Berthrong and Finzi,

2006). Figure 2.2 showed a comparison of the traditional and new pagradigms which recognized

different steps that regulate overal N cycling. Micorbial mineralization of amino acids is an

essential step for transformation of organic N to inorganic N, which is emphasized in the

traditional N cyclying theory (Figure 2.2). Amino acids may regulate the rate of ammonification

and nitrification in soil by providing the substrate for these conversion. At the same time, the

inorganic forms of N (e.g. NH4+) can be immobilized by microbes to synthesize amino acids,

which will be liberated after microbial death and lysis of micorbial cells. Therefore, the amino

acids may serve as both sink and source for inorganic N (Chen and Xu, 2006). The amino acid

loss by leaching was evidenced in many soil systems (Perakis and Hedin, 2002; Neff et al., 2003).

Amino acid leaching limits the accumulation and stock of organic N in terrestrial ecosystems but

enhance N availability in aquatic ecosystems.

22

Figure 2. 2. Combined paradigms of the soil N cycle modified according to (Schimel and

Bennett, 2004). Solid line section are common steps for both traditional and new paradims, while

dash line section is exclusive to the new paradim. Red line indicates the rate-limiting step of N

cycle in each paradim. a: depolymerization; b: root uptake; c: mineralization; d: immobilization;

e: cell uptake (immobilization); f: degradation; g: nitrification; h: leaching.

2.2. Mineral-associated organic N

2.2.1. Mechanisms involved in the mineral organic interactions

In contrast to FAAs which have short turnover time in the range of hours (Jones and

Kielland, 2002; Kielland et al., 2007), peptides and proteins tend to be adsorbed to clay or

immobilized by minerals and thus have longer residence time up to centuries (Amelung et al.,

2006). Chirality measurement of some amino acids showed that certain proteins may persist

hundreds of years (Amelung et al., 2006). The different residence time of FAAs and peptides

suggest that they have different turnover kinetics depending on their molecular structure and

chemical environment (Miltner et al., 2009). The adsorption of proteins or peptides to mineral

surfaces protects them from extracellular enzyme attack because of their multifunctional

structure. The hydrophilic and hydrophobic functional groups of proteins or peptides made them

easily sorbed to any surface area over a wide range of pH and the electrostatic attraction can be

reinforced by conformational changes to gain entropy (Kleber et al., 2007).

23

There are several models explaining the mineral associated organic N. The “onion-

layering model” specified by Sollins et al. (2006) stated that the peptidic compounds form a

stable inner organic layer onto which hydrophobic and less polar organics could sorb more

readily than onto the highly charged mineral surface. The “bilayer model” of organo-mineral

interactions showed that the hydrophilic functional groups were firstly bonded to the minerals

surface, while the hydrophobic groups of the bonded molecule were shielded away from polar

water phase by a second layer of amphiphiles, forming a bilayer (Wershaw et al., 1996). The

most recently developed “zone model” (Kleber et al., 2007) suggested three zones of mineral-

associated molecules: contact zone, hydrophobic zone, and kinetic zone. In the contact zone, the

amphiphilic portion of the compounds was attached to the mineral surface by electrostatic

interactions, with the hydrophobic portions pointing to the polar aqueous solution. In the

hydrophobic zone, the hydrophobic portion of the adsorbed molecules was shielded from polar

aqueous phase through association with hydrophobic moieties of other amphiphilic molecules to

form a bilayer. In the kinetic zone, proteins were adsorbed to the hydrophilic exterior of the

hemimicellar coatings loosely via cation bridging, by hydrogen bonding and other interactions,

allowing frequent exchange with surrounding soil solution. In the three models, it is the

amphiphiles that show the key roles. The proteins and peptides are amphiphiles, therefore, it may

be the reason that proteins and peptides form strong interactions with minerals. This can be at

least partially corroborated by the decreased C/N ratio after sorption of peptidic compounds to

minerals (Sollins et al., 2006; Kleber et al., 2007). Evidences that proteins are preferentially

adsorbed to mineral surfaces were given by other studies (Omoike and Chorover, 2006). The

adsorption phenomena can be observed by using isotope amino acid tracking technique and

confirmed by solid state 14

C, 13

C or 15

N NMR spectroscopy. For instance, by using solid state 13

C

24

NMR, Wershaw et al. (1996) found the compost leachate dissolved organic C adsorbed on

alumina by forming a bilayer. Similarly, Solomon et al. (2012b) by using Scanning Transmission

X-ray Microscope coupled with Near Edge X-ray Absorption Fine Structure Spectroscopy

(STXM–NEXAFS), suggested the protonated and deprotonated termini of the proteinaceous

compounds could serve as a binding link bridging mineral and hydrophobic matter (black-C

substances) in a “three way” association.

2.2.2. Factors influencing mineral-organic N interactions

Factors such as mineral types, pH, and temperature have been reported to influence the

adsorption of peptides/proteins on mineral surface. Early studies by Greenland et al. (1962)

showed increased adsorption of glycine peptides with concentration and molecular weight, while

Dashman and Stotzky (1984) contended the molecular weight and basicity of amino acids were

not as important in their adsorption and binding as its amino or carboxyl functional groups.

Studies conducted by Jones and Hodge (1999) indicated the amount of amino acids sorbed to the

clay loam soil was concentration dependent and followed the series lysine > glycine > glutamate

for all concentrations. Research conducted by Kalra et al. (2003) showed that the maximum

adsorption of simple peptides of glycine and peptides of glycine-alanine on montmorillonite with

or without metal ion substitution at neutral pH (7.02) and a temperature of 23 . Adding cations

increased sorption of peptides on clay surfaces. For example, Ca2+

-montmorillonite exhibited

better adsorption of small peptides of glycine and peptides of glycine-alanine as compared to

montmorillonite without Ca2+

or Mg2+

(Kalra et al., 2003).The charge property of the amino

acids backbone of a peptide/protein seemed to affect the adsorption behavior of the minerals.

Basic amino acids tended to bind strongly to negatively charged aluminosilicate minerals

(Aufdenkampe et al., 2001) while the acid amino acids inclined to attach to metal oxides such as

25

ferrihydrite with positive charges (Matrajt and Blanot, 2004). Most of these studies are limited to

observations at the macroscopic scale based on macroscopic batch equilibrium experiments

(Greenland et al., 1962; Dashman and Stotzky, 1982, 1984; Murphy et al., 1990).

Leinweber and Schulten (2000) found the non-hydrolysable organic N in soils resulted

from its binding to reactive surfaces (i.e. silicates, pedogenic oxides) and the proportions of

amino-N were underestimated by approximately 25% of the non-hydrolysable N if the mineral-

bound peptides were not solubilized. This result is consistent with their previous study

(Leinweber and Schulten, 1998). Mikutta et al. (2006) confirmed that stabilization of organic

matter by interaction with poorly crystalline minerals and polymeric metal species was the most

important mechanisms for organic matter preservation in the acidic subsoil horizons. Mikutta et

al. (2010) studied the mineralogical impact on organic N across a long-term soil chronosequence

(0.3 - 4100 kyr). Mineral associated organic N was characterized by XPS and synchrotron-based

NEXAFS spectroscopy. The results showed the youngest site contained the largest proportion of

hydrolysable amino sugars and amino acids, the intermediate weathering stage contained more

minerals associated organic N but a smaller proportion of hydrolysable amino sugars and amino

acids, while in the final weathering stage, less mineral associated organic N was held. Poorly

crystalline minerals in intermediate sites retained more organic N than the youngest and oldest

sites with primary minerals (olivine, pyroxene, feldspar) and secondary Fe/Al oxides and kaolin

minerals respectively. This study provided strong evidence that the soil mineral composition

affects the N cycling by controlling the amount and chemical composition of soil organic N. This

implied that soil mineralogy played an important role in the stabilization of proteinaceous

compounds. While whether this phenomenon is universal in a wider range of soils systems needs

to be evaluated.

26

2.2.3. Evaluation of molecular orientation on mineral surfaces

Molecular surface organization of compounds sorbed on mineral surfaces may strongly

influence their reactivity, stability, and bioavailability, as well as modify the surface property of

organo-minerals. Little is known about the nature of interactions between peptides/proteins and

minerals at molecular scale, especially their surface organization such as molecular orientation,

spatial distribution, packing density, etc. Recent molecular level investigation by spectroscopy

showed that amino acid molecules tend to self-organize themselves on the mineral surface in

response to different environment. According to Sverjensky et al. (2008), at pH of 3, glutamine

sorbed on titanium dioxide surface “lying down” at low concentration, and “standing up” at high

concentration. It was assumed that the surface coverage accounted for the change since at higher

concentration, the standing up organization maximized the coverage of the molecules sorbed.

Polarization-dependent NEXAFS has been used to reveal the molecular orientation of the

sorbed molecules on surfaces (Peters et al., 2002; Liu et al., 2006; Samuel et al., 2006; Cao et al.,

2011). The angular dependence of the π*-transition intensities of the NEXAFS spectra can be

used to determine the average molecule tilt angle of the attached molecules with respect to the

surface (Seifert et al., 2007). Typical elements in biomolecules, such as C and N, exhibit simple

s-to-p transitions, which are dipole-allowed if the electric field vector E of the incident X-rays is

parallel to the transition dipole moment. The intensity of the s-to-p transition peaks in a

NEXAFS spectrum follows a cos2θE pattern around that axis. Rotating the sample changes the

polar angle of incidence and therefore the angle θE of the electric field vector E with respect to

the surface normal (for p-polarized light). For a peptide, amino acids are linked by peptides bond.

As summarized by Liu et al. (2006), the peptide bond electrons are delocalized across the entire

peptide bond, so the double-bound character are extended to both the carbon-oxygen and the

27

carbon-nitrogen bonds. The shared π* orbital limits the free rotation of peptide C-N, so the six

atoms surrounding a peptide group lie in a single plane. The π* orbital (p orbital) is oriented

perpendicular to the peptide plane (Figure 2.3).

Figure 2. 3. Geometry of peptide bond (modified based on Liu et al. (2006)). The p-orbital (large

arrow) is oriented perpendicular to the plane of peptide bond. The oligopeptide molecules are

self-assembled on the surface of wafer (lower).

The N K-edge NEXAFS spectra in Figure 2.4 exhibit a strong θ dependence for the peak

of π* peptide bond (normally around 402.2eV). By collecting two NEXAFS spectra, for example

one at 90° incident X-ray angle and the other at 16°, the tilt angle of a molecule bound to the

surface can be calculated using equation (Stöhr, 1992):

𝐈(𝛉𝟐)

𝐈(𝛉𝟏) = 1 + p[

𝟐

𝐬𝐢𝐧𝟐 𝛂− 𝟑] [𝐬𝐢𝐧𝟐𝛉𝟐 − 𝐬𝐢𝐧𝟐𝛉𝟏]

where θ is the angle of incident X-ray from sample surface (θ=90°-𝜃𝐸), α is the tilt angle of p-

orbital of peptide bond from surface normal, and P is the degree of polarization of the X-rays.

Polarization dependent NEXAFS can be used to investigate the surface orientation of

peptides/proteins sorbed on mineral surface. It is of great importance to shed light on the

28

molecular level surface organization which appears to strongly affect the reactivity, stability and

bioavailability of the sorbed molecules, as well as modify the surface property of organo-

minerals.

Figure 2. 4. N (1s) K-edge NEXAFS spectra of a 16-unit peptides bound to gold surface

recorded at two incident x-ray angles (Iucci et al., 2008).

2.2.4. Synchrotron based spectroscopic method to study organic C and N speciation

The synchrotron based NEXAFS is a powerful technique to analyze organic C and N

speciation in soils (Vairavamurthy and Wang, 2002; Leinweber et al., 2007). Compared to other

spectroscopic techniques such as NMR, synchrotron based NEXAFS requires minimum sample

manipulation, is elemental specific, and has higher spatial resolution, lower detection limit (Dhez

et al., 2003). An NEXAFS spectrum is usually characterized by intense resonance features,

arising from 1s to π* transitions and from multiple scattering of the emitted photoelectrons, then

total fluorescence yield (TFY) and total electron yield (TEY) are collected (Leinweber et al.,

29

2007). Different N or C species have different binding energy, and generate unique spectral

features for ammonia N, nitro N, amino acids, peptides or aromatic-heterogeneities and aromatic

C, phenolic-C, aliphatic-C, carboxylic-C, and O-alkyl-C (Solomon et al., 2005; Gillespie et al.,

2009). By deconvoluting a C or N K-edge NEXAFS spectrum using a series of Gaussian curves

(G) at energy positions of known transitions, along with a step function at the edge, qualification

and semi-quantification of different organic N and C speciation in a sample can be achieved. An

example of typical C/N K-edge NEXAFS spectra showing the main 1s-π* transitions and two σ*

transitions for bulk soils are shown in Figure 2.5 (TFY mode). The spectra showed multiple

peaks of K-edge NEXAFS region for C (284 – 290 eV) and N (400 – 410 eV). By referring to

standard substances or published data, the peak resonances were correlated to different

functional groups. Table 2.2 shows the general approximate transition energy ranges and peak

assignments for primary adsorption peaks (Vairavamurthy and Wang, 2002; Jokic et al., 2004;

Lehmann et al., 2005; Kinyangi et al., 2006b; Leinweber et al., 2007; Wan et al., 2007; Gillespie

et al., 2009; Gillespie et al., 2011; Heymann et al., 2011; Kleber et al., 2011; Kiersch et al., 2012).

So far, NEXAFS technique has been increasingly used in soil samples, such as extracted humic

substances (Scheinost et al., 2001; Solomon et al., 2005), black C (Liang et al., 2006; Liang et al.,

2008; Heymann et al., 2011), soil colloids (Rothe et al., 2000; Schumacher et al., 2005), soil

organo-mineral microaggregates (Kinyangi et al., 2006a; Wan et al., 2007), microbial residues

(Liang et al., 2006; Keiluweit et al., 2012), and other environmental samples (Brandes et al.,

2004; Braun, 2005; Schumacher et al., 2006), to investigate the elemental distribution, speciation

or spatial heterogeneities.

30

Figure 2. 5. Typical C (above) and N (below) K-edge NEXAFS spectrum (TFY) deconvolution

from the mineral-organic fraction of a soil sample. Typical C (above) and N (below) K-edge

NEXAFS spectrum (TFY) deconvolution from the mineral-organic fraction of a soil sample.

31

Table 2. 2. C/N 1s NEXAFS approximate fit energy position of primary peaks

Functional groups Transition Fit position Deconvolution curve

C Form

Quinone type-C 1s-π* 283-284.5 G1

Aromatic-C 1s-π* 284.9-285.5 G2

Phenolic-C 1s-π* 286.0-287.2 G3

Aliphatic-C 1s-3p/σ* 287.3-287.6 G4

Carboxylic-C

1s-π* 288.5-288.8 G5

O-alkyl-C 1s-π* 289.2-290.0 G6

N Form

Pyridines/pyrazines/imines

1s- π* 398.7 G1

Pyrazoles/nitriles 1s- π* 399.9 G2

Amide (protein)

1s- π* 401.3 G3

Pyrrollic

1s- π* 402.5 G4

Nitroaromatic

1s- π* 403.7 G5

Nitrate 1s- π* 405.8 G6

Alkyl N 1s-σ* 406.2 G7

Unsaturated/heterocycles 1s-σ* 407.4 G8

2.3. Summary

As reviewed, although there have been attempts of characterizing soil amino acids and

proteins and peptides, those studies have focused on a limited number of ecosystems.

Information on the dynamics of amino acids and proteins/peptides, an important form of soluble

organic N, across a wider range of ecosystems is still lacking. In addition, little is known about

the factors affecting the transformation of proteins/peptides into FAAs and the molecular level

interactions between organic N and mineral surfaces. In our research, FAAs and HAAs in soils

of North-South and West-East transects of continental United States and the relationship between

their composition with environmental factors were investigated (Objective 1). For Objective 2,

i.e. to evaluate the organic C speciation in bulk soils of various ecosystems, different soil organic

C moieties were studied by NEXAFS spectroscopy to test the hypothesis that organic forms of C

have an overall uniform composition among the wide range of ecosystems investigated. To

understand molecular level surface organization of small peptides on mineral surfaces (Objective

32

3), hexa-glycine was organized on montmorillonite to test the hypothesis that oligopeptides

sorbed to mineral surfaces tend to form a well-extended structure with an angle with respect to

the mineral surfaces.

Synchrotron-based techniques, characterized by their high sensitivity, in situ

investigation at the molecular level, and spatial resolution, have revolutionized our way we

approach the investigation of soil organic matter (Lombi and Susini, 2009). Besides to record the

element speciation, the techniques will be employed to reveal nano-scale complexity and

conduct multi-elemental mapping of soil organic matter.

33

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45

3. Immediately Bioavailable Free Amino Acids in Soils of North-

South and West-East Transects of Continental United States

L. Maa, K. Xia

a*, M. A. Williams

b, and D. B. Smith

c

aDepartment of Crop and Soil Environmental Sciences, Virginia Polytechnic Institute and State

University, Blacksburg, VA 24061, USA

bRhizosphere and Soil Microbial Ecology Laboratory, Department of Horticulture & Molecular

Plant Sciences, Virginia Tech, VA 24061, USA

cUS Geological Survey, MS 973, Denver, CO 80225, USA

*Corresponding author. Tel.: 540-231-9323; Email address: [email protected]

mailto:[email protected]

46

3.1. Abstract

Free amino acids are those dissolved in soil solution or weakly bound to charged soil

surfaces and are extractable using 0.01M KCl which mimic the ionic strength of a typical soil

solution. The extractable free amino acids are considered to be immediately bioavailable to plant

and organisms. In spite of their low fraction (less than 5%) in the soil soluble organic nitrogen

pool, free amino acids play a vital role in plant nutrition and nitrogen fluxes in terrestrial

ecosystems. Research has been conducted to characterize free amino acids in a limited number of

surface soils, it is unknown if those findings apply to a wide range of ecosystems. In addition,

little is understood about the status of subsurface amino acids. The primary objective of this

study was to assess the levels and composition of free amino acids in A and C horizons of a large

number of soils from 149 sites along north-south temperature and west-east precipitation

transects of continental United States. The soil samples were a subset of the samples collected

from 2007 to 2010 for the USGS Geochemical Landscapes Project which assessed the

abundance and spatial distribution of chemical elements and minerals in soils of 4,857 sites (1

site/1,600 km2) of the conterminous United State. Free amino acids in soil samples were

extracted using 0.01M KCl, derivatized, and analyzed on a high performance liquid

chromatography equipped with a fluorescence detector. A total of 24 amino acids were extracted

and quantified. The results showed significant variations for the levels of total free amino acids

among soils from different sites. The concentrations of total free amino acids in the A-horizon

were several to dozens times higher than in the C-horizon soils, ranging from 0.74 to 273 mg kg-

1 soil (dry weight basis) in the A horizon and from 0.12 to 22 mg kg

-1 soil (dry weight basis) in

the C horizon. The concentrations of individual free amino acid were also significantly higher in

the A-horizon than in the C-horizon soils (p<0.0001). Although the major free amino acids in

47

both soil horizons were glutamic acid, glutamine, aspartic acid, leucine, alanine, threonine,

glycine and valine, the mole percent composition of free amino acids was significantly different

between the two horizons, suggesting different physicochemical processes affecting the

dynamics of amino acids along soil depth. For both soil horizons, significant variations were

observed for the levels or composition of soil free amino acids along the mean annual

temperature, mean annual precipitation, and vegetation gradients of continental United States,

suggesting that environmental factors might play an important role in affecting organic nitrogen

dynamics.

48

3.2. Introduction

Amino acids (in the form of peptide/protein) play a critical role in the terrestrial nitrogen

(N) cycling due to their considerable proportion amongst the organic nitrogen pool to serve as

potential N source to organisms and plants. Free amino acids (FAAs) are those dissolved in soil

solution or weakly bound to charged soil surfaces, which are easily consumed by plants and

organisms. In soluble organic N (SON) pool, FAAs take the smallest fraction, normally less than

5% (Jones et al., 2005), but they are immediately bioavailable to plants particularly when the soil

inorganic N is insufficient for plant uptake (Jones et al., 2005). Numerous studies confirmed the

fact that plants can consume amino acids through roots via transporters or even without any

assistance from other organisms such as mycorrhizas (Kielland, 1994; Lipson and Nasholm,

2001; Rentsch et al., 2007; Jämtgård et al., 2008; Paungfoo-Lonhienne et al., 2008). The

dynamics and cycling of FAAs have been extensively studied in a limited number of agricultural

soils (Brzostek et al., 2012), tundra soils (Weintraub and Schimel, 2005a), forest soils

(McFarland et al., 2002; Berthrong and Finzi, 2006), and grassland soils (Warren and Taranto,

2010). The levels of FAAs were different in different soil systems (Rothstein, 2009a). They are

subjective to seasonal changes (Weintraub and Schimel, 2005a; Johnson and Pregitzer, 2007;

Warren and Taranto, 2010), successional sequence (Werdin-Pfisterer et al., 2009) and fertility

gradient (Rothstein, 2009a), and variations of soil properties (Rothstein, 2010). The

depolymerization of proteinaceous compounds by extracellular enzymes is the key process that

affecting levels of FAAs in soils (Jones and Kielland, 2002; Schimel and Bennett, 2004). The

levels of soil protein/peptides thus influence the concentrations and composition of soil FAAs.

Fine root turnover (Kielland et al., 2007), root secretion (Dakora and Phillips, 2002), and

bacterial cell lysis under adverse environment (Lipson and Monson, 1998) can enhance the

49

concentrations of soluble proteins, which can be used as substrates for microbial utilization and

in turn influence the production rate of FAAs in soils, resulting in their significant variation

during seasonal change, cultivation or sequence succession (Lipson et al., 1999b; Hertenberger et

al., 2002; Weintraub and Schimel, 2005a; Werdin-Pfisterer et al., 2009). Amino acid uptake by

plants and sorption to soil minerals could decrease their concentrations in soil solution (Lipson

and Nasholm, 2001; Weintraub and Schimel, 2005a; Rothstein, 2010). Therefore, soil properties

and vegetation may regulate the amino acid availability to plants and microorganisms to some

extent. Free amino acids can be produced by the proteolytic enzymes via peptide bond cleavage

of proteins and peptides, while microbial consumption/mineralization or plant uptake can deplete

them from the bioavailable pool. The levels and relative composition of soil FAAs are therefore

a constant balance between the productive and consumptive processes in soils (Rothstein, 2009a).

Information of soil FAAs is able to provide a snapshot of this balance.

Compared to studies on levels of FAAs (Yu et al., 2002; Weintraub and Schimel, 2005a;

Amelung et al., 2006; Berthrong and Finzi, 2006; Formanek et al., 2008), there have been fewer

investigations on the composition of FAAs. In spite of the large variations in levels of FAAs, a

relatively constant composition of FAAs was reported across a boreal forest successional

sequence(Werdin-Pfisterer et al., 2009). It is unknown, however, whether this situation is

applicable to the FAAs across various ecosystems. It is also unclear whether there is any trend of

FAA abundance and composition with soil depth and along a temperature and a precipitation

gradient. So far, no such information of FAAs has been reported in soils of a wide land use.

In this part of research, the levels and composition of FAAs in the soils of A horizon and

C horizons along the north-south (N-S) and west-east (W-E) transects of continental United

States were investigated. The following hypotheses were tested: 1) the A-horizon soil FAA

50

levels and profiles are significantly different from those of C horizon; 2) soil FAAs vary

significantly among different vegetation systems; 3) soil FAAs are affected by the mean annual

temperature (MAT) and precipitation (MAP) gradients at the continental scale. To the best of our

knowledge, this work reveals, for the first time, the status of FAAs in soils of a wide range of

ecosystems in the United States.

3.3. Materials and methods

3.3.1. Study sites and soil sampling

Soil samples of A and C horizons from 149 sites along N-S and W-E transects of

continental United States (Figure 3.1) were a subset of samples collected from a total of 4871

sites (1 site/1600 km2) by the USGS from 2007 to 2010 for the USGS Geochemical Landscapes

Project. Detailed sampling protocols were described elsewhere (Smith et al., 2013). Briefly,

visible plant materials were removed from each collected soil, sieved through 2-mm sieve, air

dried, and stored in glass jars at 4 oC until further analysis. Mineralogical and chemical data on

all the soils were published by the USGS (Smith et al., 2013).

Figure 3. 1. Location of soil sampling sites from west to east and north to south transects on

gradients of (above) MAP, and (below) MAT. Sites were grouped into sub-continental areas as

shown in circles. The legends at the right of each sub-figure apply to the circles.

40-60 in20-40 in4-20 in40-60 in

East-West Transect

Precipitation:

35-50oF50-55oF55-60oF

North-South Transect

Temperature:

51

3.3.2. Chemicals

Waters AccQ·FluorTM

Reagent Kit was purchased from Waters (Milford, MA, USA).

The Kit included Waters AccQ·Fluor derivative powder, 6-aminoquinolyl-N-

hydroxysuccinimidyl carbamate (AQC), Waters AccQ·Fluor dilution solution, and 0.2 M borate

buffer (pH 8.8). The AccQ·Fluor (powder) was sealed with paraffin wax film (Pechiney,

Menasha, WI, USA) and kept in a desiccator. Unopened AccQ·Fluor Reagent kit may be stored

at room temperature for one year. Once opened, the kit is better to be used within six months.

Ultrapure water (18MΩ) was produced with Millipore Q water systems from Millipore Corp

(Bedford, MA, U.S.A.). The ACS reagent grade sodium acetate (CH3COONa), sodium EDTA

(EDTANa2·2H2O), sodium azide (NaN3), hydrochloric acid (HCl, 37%), phosphoric acid (H3PO4,

85%) were purchased from Sigma (St. Louis, MO, U.S.A). The HPLC grade acetonitrile (ACN),

triethylamine (TEA) were purchased from Fisher Scientific (New Jersey, USA). Individual

amino acid standard including alanine (Ala), arginine (Arg), aspartic acid (Asp), glutamic acid

(Glu), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine

(Met), phenylalanine (Phe), proline (Pro), serine (Ser), threonine (Thr), tyrosine (Tyr), and valine

(Val), cystine (Cys–Cys), asparagine (Asn), glutamine (Gln), tryptophan (Trp), ϒ-aminobytyric

acid (GABA), taurine (Tau), citrulline (Cit), ornithine HCl (Orn) with purity >97% were

purchased from Sigma. Alpha-amino butyric acid (AABA) purchased from Sigma was used as

internal standard for the amino acids analysis.

Each amino acid stock solution and internal standard was prepared at 25mM or 2.5mM

by dissolving the target amino acid in 0.1M HCl. The 2.5mM and 25mM stock solutions were

stored at -20 and can be used for up to 3 and 6 months, respectively. An intermediate

composite standard was prepared by combining appropriate amount of individual amino acid

52

stock solution to achieve a final concentration of 0.25mM for each amino acid. The 0.25mM

intermediate composite standard was then mixed with appropriate amount of AABA in various

amounts of ultrapure water to yield mixed amino acid calibration standards ranging from 0.005

to 0.1mM for each of the 24 amino acids and 0.1mM for AABA. The calibration standards can

be stored at -20 and reused within one month.

3.3.3. Free amino acid extraction from soil

The extractant of FAAs should be mild enough without lysing the soil microbial cells and

should prevent protein hydrolysis or enrichment of any other form of amino acid during the soil

extraction (Lojkova et al., 2006). High-concentration salt solution, such as 1M KCl or 0.5M

ammonia acetate, can extract too much ammonia, resulting in chromatographic interferences

with FAAs. Therefore, 0.01M KCl was used in this study as extractant to mimic the soil solution.

Two grams of air dried soil was weighed into 50 mL sterile polypropylene centrifuge tube

(Fisher Scientific, Mexico). Ten mL 0.01M KCl containing 10mM NaN3 was added into the

centrifuge tube. An aliquot of 8 µL 2.5 mM internal standard was spiked to the mixture to

achieve a final concentration the same as that in the calibration solution, assuming 100%

recovery during the extraction. The mixture was shaken gently on a reciprocal shaker at room

temperature for 15min, followed by centrifugation at 3500 rpm for 15min at room temperature.

After centrifugation, the supernatant was collected and filtered through a 0.22µm polyvinylidene

fluoride (PVDF) membrane syringe filter into a new polypropylene centrifuge tube. An aliquot

of exactly 500 µL of the filtrate was pipetted into a glass vial for freeze drying. The dried residue

shall be immediately stored at -20 oC if not immediately derivatized.

3.3.4. Amino acids derivatization

53

The amino acids in the free dried soil extracts were derivatized using the Waters

AccQ·Fluor TM

Reagent Kit (AccQ, 1993). To prepare the AccQ·Fluor reagent for amino acids

derivatization, 1 mL Waters AccQ·Fluor dilution solution was transferred into the AccQ·Fluor

reagent vial containing Waters AccQ·Fluor reagent powder, tightly capped, mixed on a vortex

for 15 s, and then incubated at 55 in an oven (Model 40GC Lab Oven; Quincy Lab Inc.,

Chicago, IL, USA) for 10 min until the powder was completely dissolved. The final reconstituted

AccQ·Fluor solution was colorless and transparent and contained AccQ·Fluor reagent at about

3mg/mL (ca.10 mM). Appearance of color or precipitation indicates deactivation of the reagent

or contamination and needs to be discarded. The tightly sealed reconstituted AccQ·Fluor solution

can be stored in a desiccator at room temperature or at 4 and reused within one or two weeks,

respectively.

The freeze-dried soil extract residue was reconstituted in 10 µL 0.05M HCl, followed by

addition of 70 µL borate buffer to adjust the pH to 8 - 10 for subsequent optimum derivatization

using the AccQ·Fluor reagent. The mixture was then briefly vortexed for several seconds,

followed by addition of 20 µL reconstituted AccQ·Fluor solution. The mixture was immediately

capped with a silicon-lined septum, mixed on a vortex for 15 s to prevent 6-aminoquinolyl-N-

hydroxysuccinimidyl carbamate hydrolysis to 6-aminoquinoline, and incubated for 1 min at

room temperature. The mixture was then incubated at 55 in an oven for 10 min to complete

the amino acids derivatization before analysis on a high performance liquid chromatography

equipped with a fluorescence detector (HPLC/FLD). Ten µL of amino acids mixture standard at

each concentration was derivatized following the same procedure as that for soil extracts

described above. The derivatized samples are stable at room temperature for one week before the

HPLC analysis.

54

3.3.5. HPLC/FLD analysis of derivatized amino acids

Derivatized amino acids were analyzed using an HPLC 1260 Infinity system (Agilent

Technologies, USA) coupled with a fluorescence detector (FLD). Separation of derivatized

amino acids was carried out on a Waters X-Terra MS C18 column (2.1 mm × 150 mm, 3.5 µm

particle size, Waters Corporation, USA). The mobile phase consisted of A: a solution containing

140 mM sodium acetate, 17 mM TEA with 0.1% (g/L, w/v) EDTA-2Na (titrated to pH 5.8 with

phosphoric acid) and B: ACN/water (60:40, v/v). The mobile phase flow rate was 0.35ml/min

with gradient conditions at: 0 - 17 min, 100 - 93 % A, 17 - 21 min 93 - 90 % A, 21 - 30 min 90 -

70 % A, 30 -35 min 70% A, 35 - 36 min 70 - 0 % A, and 36-40 min 0 % A. The column was then

further re-equilibrated for 9 min at the initial gradient of 100 % A. Before beginning the gradient,

the column was equilibrated in 100% A for 30 min. After every sequence was done, the column

was washed with Eluent B at 0.2 mL/min for 1 hour. The column temperature was maintained at

45 . The injection volume was 5 µL. The fluorescence excitation and emission wavelengths

were set at 250 nm and 395 nm respectively.

Each derivatized amino acid in a sample was identified by comparing its retention time

with that of derivatized individual amino acid standard and quantified using the internal standard

method (Hou et al., 2009; Fiechter and Mayer, 2011). The detection limits, precision (relative

standard deviation %), and recoveries of this method were summarized in Table 3.1.

55

Table 3. 1. Detection limits, recovery and the precision of the determination of amino acid

derivatives.

Amino acid Detection limit

(nmol kg-1

dry soil) a

Recovery (%) b

Precision (RSD %) c

Asp 22 86.7 1.4

Glu 15 98.6 2.8

Ser+Asn 6 78.2 6.2

Gly 11 88.1 2.2

Gln 10 79.7 2.7

His 39 15.1 1.6

Arg 24 23 1.5

Tau 6 88.8 0.5

Cit 7 88.8 0.5

Thr 8 87.9 5.3

Ala 6 89.7 5.5

GABA 5 74.2 3.6

Pro 9 94.8 2.4

Tyr 9 80.9 6.6

Cys-Cys 22 70.8 9.7

Val 3 90.4 3.4

Met 6 85.1 5.8

Orn 21 20.8 2.9

Ile 3 93 6.6

Lys 36 17.7 1.9

Leu 4 89.9 6.3

Phe 4 85.6 5.9

Trp 269 62 13 a The detection limits in soil samples were estimated from the detection limit of a 0.5 µM amino

acid standard on column based on a S/N ratio of 3:1 and the recovery of amino acids in spiked

samples. b

the recovery was evaluated by spiking amino acid standard at concentration of 0.5µmol kg-1

dry

soil and then the amino acids in the spiked sample and the same soil samples without spiking

were also determined at the same time. The recover was calculated as the percentage of the

concentration differences relative to the spiked concentration. c n = 3

3.3.6. Statistical analysis

The composition was calculated as the molar percentages of each amino acid out of total.

The concentrations were measured at dry soil basis. The composition and concentration

variations of the FAAs between A and C horizons were evaluated by matched pair’s t test

56

analysis. The composition and concentration variations of FAAs along MAT and MAP gradients,

and among different vegetation covers were analyzed using multiple comparisons based on

Turkey’s honest significant difference (HSD) test, provided by the statistical software JMP 9.0

(SAS Software, Cary, NC), and nonmetric multidimensional scaling (NMS), provided in

statistical software PC-ORD ver.6 (MjM Software, OR). The Sorenson (Bray-Curtis) distance

was used to represent compositional dissimilarity. For the NMS analysis, a maximum of 250

iterations were used for 50 runs with real data, with a stability criterion of 0.00001. The

recommended dimensions with proper stress in each case were used. Amino acid concentration

(µmol kg-1

soil air dry soil basis) at 149 sites were saved as the main matrix which, after

relativization become a matrix of amino acid percent composition. The amino acids as response

variable were always quantitative in the main matrix. Amino acids Cit, Tau, Cys-Cys, Met and

Trp were eliminated from the tested samples before transformation to reduce noise due to the

fact that their levels in most of the samples were below their detection limits. Explanatory

variables, depth, vegetation, MAT and MAP, were imported into PC-ORD as the second matrix.

Pearson correlation coefficients between MAT, MAP and the ordination axes were calculated

and the significance of the correlation was tested using JMP 9. In the multidimensional cases,

only two axes that accounted for largest variance were displayed. The relationship of amino acid

composition and explanatory variables was explored using biplot, which indicated the direction

and the strength of the highly correlated explanatory variables. Multiple Response Permutation

Procedure (MRPP) were performed to examine the differences in amino acid composition

between A and C horizons.

3.4. Results and discussion

3.4.1. Composition and concentrations of extractable soil amino acids

57

Twenty-two derivatized amino acids in a sample were separated on a chromatogram

except for Ser and Asn which were co-eluted (Figure 3.2). The molar percentages of each FAA

varied site from site. Despite the site variations, the FAA pool was dominated by the following

amino acids: Asp, Glu, Gly, Gln, Thr, Ala, Val and Leu. These eight major FAAs accounted for

44 - 85% of the TFAA pool. The average molar percentages of the eight major FAAs were 5 %,

20 %, 8 %, 8 %, 16 %, 6 %, 5 % and 4 % for Asp, Glu, Gly, Thr, Ala, Leu, Val, and Gln,

respectively. Similar trend has also been observed in most of other studies (Kielland, 1995;

Nordin et al., 2001; Yu et al., 2002). These major amino acids are mostly the major constitutes of

soil proteinaceous compounds (Senwo and Tabatabai, 1998; Moura et al., 2013). In addition, the

prevalent abundance of polar amino acids compared to nonpolar ones among the eight major

amino acids coincides with the fact that polar amino acids are generally located on the surfaces

of protein structure (Nelson et al., 2008), allowing a preferential initial decomposition. Amino

acids, His and Arg were observed as minor FAA components in this study, however, they have

been reported as major FAAs in the boreal forest soils of Alaska (Werdin-Pfisterer et al., 2009,

2012), boreal forest soils of Sweden (Nordin et al., 2001), and heathland soils (Abuarghub and

Read, 1988). The vegetation such as alder transports more precursor of Arg, thus possibly

facilitates the synthesis and storage of Arg in such soils (Werdin-Pfisterer et al., 2009). The

slower diffusion of basic amino acids through soil might constrain the uptake rates by plants or

organisms relative to other amino acids (Nasholm and Persson, 2001), extractant with high ionic

strength, therefore, can extract more basic amino acids from the adsorption sites. The highly

abundant His, in the heathland soil for instance, could be released by 0.5 M NH4OAC from soil

exchangeable sites where amino acids from microbial or plant tissues not yet readily utilized

were sorbed (Abuarghub and Read, 1988). In our study, Lys, Met and traces of Trp and Cys-Cys

58

were also detected as minor FAAs, which are similar to other studies (Werdin-Pfisterer et al.,

2009). The trace levels of non-protein amino acids including GABA, Tau, Cit and Orn, which

may be from bacterial osmolytes (Lipson and Nasholm, 2001) were detected at < 3% of TFAA in

the soils investigated. The small contribution of non-protein amino acids to the TFAA pool could

corroborate the assumption that soil protenaceous substances may mainly originate from plant

materials.

Among the naturally occurring amino acids detected in the studied soils, the average

relative molar percentages followed the order of neutral > acidic > basic > aromatic amino acids,

which averaged 60 %, 24 %, 6 % and 5 % of the TFAA pool, respectively. The amino acids

interact with soil components via ligand exchange, bridges of polyvalent cations, Van Der Waals

forces or hydrophobic interactions, and ligand exchange occurs as the strongest interaction

(Sollins et al., 1996). Considering the large number of neutral amino acids and the high

proportions of acidic amino acids in this study, our results more or less supported the statement

presented by Jones and Hodge (1999) that the sorption to colloidal fraction of the soil was

greatest for positively charged amino acids, intermediate for neutral amino acids and least for

negatively charged amino acids. The low recovery of spiked basic amino acids extracted with

water and salt solution demonstrated the strong sorption of these positively charged amino acids

(Paul and Schmidt, 1960; Gilbert and Altman, 1966). Strong base such as Ba(OH)2 was shown to

be a good basic solution to increase the recovery of those basic amino acids due to its ability to

replace sorbed basic amino acids and flocculate the soils (Paul and Schmidt, 1960). Rothstein

(2010), however, found that the negatively-charged Glu was sorbed as strongly as the positively-

charged Arg. This discrepancy with abovementioned statement could be explained by the

59

considerate anion exchange capacity or the irreversible chemical adsorption of anion amino acids

to humic acids in those soils (Rosenfeld, 1979).

Figure 3. 2. Chromatograms of derivatized amino acids in (above) 10µM standard and (below) a

A-horizon soil sample from a grassland site in Minnesota. 1=Asp; 2=Glu; 3= 6-aminoquinoline;

4=Ser+Asn; 5=Gly; 6=Gln; 7=His; 8=NH4+; 9=Arg; 10=Tau; 11=Cit; 12=Thr; 13=Ala;

14=GABA; 15=Pro; 16=AABA (internal standard); 17=Tyr; 18=Cys-Cys; 19=Val; 20=Met;

21=Orn; 22=Ile; 23=Lys; 24=Leu; 25=Phe; 26=Trp.

m in15 20 25 30 35

LU

0

10

20

30

40

50

60

70

80

12

3

4

5 6

7

8

910

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

m in15 20 25 30 35

LU

0

10

20

30

40

50

1

2

3

4 5

6

89

11

12

13

14

15

16

17

19

20

21

22

23

24

25

60

The concentrations of TFAAs ranged from 0.12 to 273 mg kg-1

in soils of the 149 sites,

respectively. The wide concentration range of TFAA could be due to variations in soil type,

vegetation change, management practices and environmental conditions among sites. If an

average ratio of 1.4 mole N per mole of amino acids was used to convert concentrations of FAAs

to that of amino acid-N (Rothstein, 2009a), concentrations of total free amino acid N ranged

from 0.017 to 36.48 mg N kg-1

in all the soil investigated, a range that is comparable to the

reported concentrations from 0.438 to 4.867 mg N kg-1

dry soil for total amino acid-N extracted

using water from the top 20 cm soils across a boreal forest successional sequence (Werdin-

Pfisterer et al., 2009). The average concentrations of the eight major amino acids were 0.5 mg

kg-1

for Asp, 2 mg kg-1

for Glu, 0.3 mg kg-1

for Gly, 0.8 mg kg-1

for Gln, 0.6 mg kg-1

for Thr, 0.9

mg kg-1

for Ala, 0.4 mg kg-1

for Val and 0.5 mg kg-1

for Leu. These FAAs are mostly common

among the major amino acids mentioned (Lipson and Nasholm, 2001). The concentration of the

major amino acids in this study fall into the range reported by others (Werdin-Pfisterer et al.,

2009, 2012).

3.4.2. Extractable amino acids in A and C horizon soils

The MRPP analysis illustrated in Figure 3.3 suggested significant differences in amino

acid composition between A and C horizons (agreement statistic [A] = 0.052; P<0.0001). The

amino acids shown in the biplot vector have a high correlation (r2 > 0.2) with the ordinate axes,

indicating the depth distribution of them was more pronounced than others. Glu and Ala have the

strongest preferential distribution in A and C horizon, respectively. In addition, Gln is more

abundant in A horizon, Thr, Gly, and Ser/Asn in C horizon, while Val, Leu, Phe, and Ile in both

horizons. Figure 3.4 shows that ~ 75% of the FAAs in soils of both A and C horizons consist of

eight amino acids, out of a total of 24 amino acids measured. Although the types of major amino

61

acids as well as their total mole percent relative to the FAAs in both A and C horizon soils are

near the same, their relative distribution is different between the two soil horizons (Figure 3.4).

The Glu, Asp and Gln were relatively more abundant in A-horizon than in C horizon, while the

opposite was observed for Gly, Thr and Ala (Figure 3.4) similar to the observations of NMS. The

molar percentages relative to total FAA for Val and Leu in the A horizon soils are similar to that

in the C horizon soils. These shifts of amino acid composition with soil depth are primarily

related to the changes in the molar abundance of the acidic amino acids Asp, Glu and neutral

amino acids Gly, Gln and Ala (Figure 3.3 and 3.4). The preferential decomposition of acidic

amino acids by enzymatic decarboxylation at α-C to form nonprotein amino acids ß-alanine and

γ-aminobutyric acid in deep soil possibly results in the decreasing molar abundance of Asp and

Glu with soil depth (Rosenfeld, 1979; Andersson et al., 2000). The amide Gln, which is the most

abundant FAA in boreal forest soil and tree leaves (Edfast et al., 1990; Werdin-Pfisterer et al.,

2012), originates most likely from aboveground xylem and phloem. Amino acid Gly and Ala,

which are more refractory from the bacterial utilization than others, are more abundant in

refractory proteinaceous compounds and tend to accumulate in deep soil profile as the degree of

degradation progressed (Yamashita and Tanoue, 2003). More extensive investigations at

different depth intervals are needed to test whether this pattern of amino acid distribution is a

common phenomenon. The results from this study support the findings of Abuarghub and Read

(1988) that the molar percentages of Asp and Glu in heathland soils decreased with soil depth

while the neutral components were generally higher in deep soil horizons. Similar trend of FAAs

were also reported in sediments (Rosenfeld, 1979).

62

Figure 3. 3. NMS ordination of 298 samples from 149 sampling sites. Sites were grouped into A

horizon and C horizon. High correlation of variables (cut off r2 = 0.2) with ordination was

indicated in biplot vector, where length and direction represent the magnitude and direction of

the correlation, respectively. Ordination of sites captured two dimensions with a final stress of 14

where Axis 1 explained 58 % and Axis 2 explained 34 % of total variance respectively.

Glu

Ser+Asn

Gly Gln

Arg

ThrAla

ValIle

LeuPhe

-3 -1 1 3

-3

-1

1

3

Axis 1 (58 %)

Axis

2 (

34 %

)

Depth

C horizonA horizon

63


horizons from different transects. Scale on right side applies to sum of the eight major FAA.

Different lower case letters indicate statistical significance by pairwise comparison (α = 0.05).

Values are expressed as mean ± Standard Error of Mean (SEM).


dry soil) of free amino acids

A horizon C horizon

Range Average Range Average

Asp 0.03 – 9.8 0.95 < 1.2 0.09

Glu 0.2 – 29.4 3.9 < 4.9 0.41

Gly 0.024 – 3.6 0.44 0.005 - 1 0.1

Gln 0.005 – 1.3 1.6 < 0.5 0.07

Thr 0.05 – 9.3 0.96 0.006 - 2.3 0.17

Ala 0.069 – 15.3 1.5 0.013 – 2.8 0.25

Val 0.023 - 5 0.59 < 1.5 0.12

Leu 0.031 – 5.9 0.82 < 1.9 0.13

TFAAs 0.74 - 273 15.8 0.12 - 22 2.1

Asp Glu Gly Gln Thr Ala Val Leu N.a.N. SUMAm

ino

ac

id c

om

po

sit

ion

re

lati

ve

to

to

tal (m

ol %

)

0

5

10

15

20

25

30

0

20

40

60

80

A horizon

C horizon

a

b

a

b

a

b

a

b

ab

a

b

ab

64

Concentrations of TFAAs ranged from 0.12 to 22 and 0.74 to 273 mg kg-1

in soils of C

and A horizon, respectively, corresponding to total extracted amino acid-N ranging from 0.017 to

3.36 mg kg-1

and from 0.11 to 36.48 mg kg-1

in C and A horizons (Table 3.2), similar to the

summarized range: 0.1-8 µg N g-1

soil in the surface organic horizon and 0.5-21 µg N g-1

soil in

the surface mineral soil horizon (Berthrong and Finzi, 2006). As shown in Figure 3.5, there is

significantly higher amount of FAAs in the A-horizon soils comparing to C-horizon soils due to

the accumulation of soil organic matter and soil microorganisms in surface soils (Goh, 1972).

Similar results were also observed in soils of the temperate forest (Berthrong and Finzi, 2006;

Song et al., 2008) and boreal forest (Werdin-Pfisterer et al., 2012). Although the proteolytic

activities in each horizon were not tested, the enzyme activities of organic matter rich surface

soils were assumed to be higher than in subsoil (Berthrong and Finzi, 2006). Larger proteolytic

activities in substrate rich surface soils thereby replenish more FAAs. The opposite trend was

also noticed in several sites which showed greater amount of TFAAs in the C-horizon than in the

A-horizon soils, possibly because of the patchy distribution of buried organic horizons or to the

hotspots of amino acids like dead animals and visible fine roots in subsoil, as well as to manual

turbulence such as deep tillage (Brzostek et al., 2012). The detected range and average

concentrations of amino acid in A and C horizon were summarized in Table 3.2. The

concentrations of each major amino acid are variable and are in the same order of magnitude

with the reported results of major FAAs from soil surface to 35 cm depth profile in a

stagnohumic gley soil (Abuarghub and Read, 1988).

65

Figure 3. 5. Average concentration of eight major FAAs and TFAAs in two horizon soils from

different transects. Different lower case letters indicate statistical significance by pairwise

comparison (α=0.05). Scale on right side applies to TFAAs. Values are expressed as mean ±

SEM.

3.4.3. Variations of extractable soil amino acids along MAT and MAP gradients of

continental United States

Soil samples were classified into four groups based on transects and horizons: north-

south transect A horizon, north-south transect C horizon, west-east transect A horizon, and west-

east transect C horizon. The N-S transect crosses significant gradients in MAT from extreme

cold in the north to extreme heat in the south. The W-E transect has significant differences in

precipitation, along humid west coast, to arid and semiarid interior western half of the USA, and

all the way to the humid eastern half of the country (Woodruff et al., 2009). The N-S transect has

less dramatic precipitation changes and the W-E transect has minor temperature differences.

Results of the four groups were projected by NMS onto a two dimensional ordination based on

amino acid molar percentages. Scores of ordination axes were correlated with values of MAT

and MAP (Figure 3.6). Mean annual precipitation significantly correlated with the composition

Asp Glu Gly Gln Thr Ala Val Leu N.a.N.TFAAs

Co

ncen

trati

on

s (

mg

kg

-1 d

ry s

oil

)

0

1

2

3

4

5

0

2

4

6

8

10

12

14

16

18

20

A horizon

C horizon

a

b

a

a

a

a

a

aa

b

a

bbbb

bb

b

66

of the extracted FAAs in soils of both A and C horizons of W-E transects and significant

correlations between MAT and composition of extracted FAAs were observed for A- and C-

horizon soils from the N-S transect. Figure 3.7 shows how the environmental factors affect the

composition. Along the N-S temperature gradient, the composition of FAA in A horizon tends to

be different among vegetation. Along the W-E precipitation gradient, the vegetation tends to be

distributed in a more scattered manner. It is postulated the temperature and precipitation

influenced the composition of FAA by their effect on vegetation cover, microbial activity and

mineralogy. Great precipitation increases soil moisture, and then enhances plant coverage, which

causes changes in microbial biomass by way of changing organic C inputs (Zak et al., 2003;

Zhao et al., 2011). High temperature, however, reduces soil moisture, plant coverage and soil

organic C content (Jobbagy and Jackson, 2000; Zhang et al., 2013). Precipitation and

temperature enhance weathering of parent minerals and mineral loss through leaching. The

combination of mineral inheritance from parent materials and development of secondary

minerals through weathering and leaching determined the mineralogy of a specific site

(Woodruff et al., 2009). Typical mineralogical characteristics in response to climatic changes

usually regulate the stabilization of amino acids (Vieublé Gonod et al., 2006; Mikutta et al.,

2010).

67

Figure 3. 6. Correlations of NMS axes with MAT and MAP. Black dots represents sampling

sites. The percentages in Y-axis are the variability explained by each NMS ordination axis.

MAT (oC)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Ax

is 2

(2

9.3

)

2

4

6

8

10

12

14

16

18

20

MAT (oC)

2 4 6 8 10 12 14 16 18 20

Ax

is 1

(4

7.9

%)

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

MAP (cm)

0 20 40 60 80 100 120 140

Ax

is 2

(1

7.9

%)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

MAP (cm)

0 20 40 60 80 100 120 140

Ax

is 1

(4

7.4

%)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

y=-0.0764x + 0.7114

r2=0.2331

P<0.001

y=-0.0879x + 0.8133

r2=0.2044

p<0.01

y=-0.0062x + 0.4502

r2=0.2399

P<0.001

y=-0.0089x + 0.6473

r2=0.2582

P<0.001

N-S A horizon N-S C horizon

W-E A horizon W-E C horizon

68

Figure 3. 7. NMS ordinations of 298 samples from in four groups. Correlations of variables with

ordination with r2 > 0.2 were indicated in biplot vector, where length and direction represent the

magnitude and direction of the correlation, respectively. Ev, evergreen; Gr, grassland; Sh, shrub;

De, deciduous forest; Cr, cropland; Pa, pasture; Fa, fallow; Re, residential

As an aid to illustrate large-scale patterns of FAAs along MAT and MAP gradients,

sample sites were grouped based on MAT and MAP range (Figure 3.1). As shown in Figure 3.8,

the concentrations of each of eight major FAAs and TFAAs in soils of A horizon decreased with

increasing MAT, while an opposite trend was observed for soils of C horizon. No consistent

patterns of amino acid concentrations with the MAP gradient in the A-horizon soils were found,

but there was an initial increasing followed by a decreasing trend along the gradient. In C

horizon, however, an overall decreasing trend of average concentrations of each major FAAs and

TFAAs with increasing MAP was observed. Though the effects of climate on soil organic matter

MAPAsp

GluSer+Asn

Gly

Gln

Thr

Ala

Pro

Val

Ile

Lys

Leu

Phe

-2.0 -1.0 0.0 1.0 2.0

-2.0

-1.0

0.0

1.0

2.0

C-EW

Axis 1 (47.4%)

Axi

s 2

(3

4.5

%)

Vegetation

EvGrShDeCrPaFaRe

MAT

MAP

Asp

Glu

Gly

Gln

Arg

Thr

Ala

GABA

Tyr

Val

Met

Orn

Ile

Lys

LeuPhe

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

A-NS

Axis 1 (62.2%)

Axi

s 2

(2

9.3

%)

Vegetation

GrShDeCrPaFa MAT

MAP

Asp

Glu

Ser+Asn

Gly

Gln

His

Arg

Thr

Ala

GABA

Val

Orn

Ile

Lys

Leu

Phe

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

C-NS

Axis 1 (47.9%)

Axi

s 2

(4

5.3

%)

Vegetation

GrShDeCrPaFa

MAP

Glu

Gln

Arg

Thr

Ala

GABA

Tyr

Val

Met

Orn

Ile

Lys

Leu

Phe

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

A-EW

Axis 1 (76.3%)

Axis

2 (

17

.9%

)

Vegetation

EvGrShDeCrPaFaRe

MAPAsp

GluSer+Asn

Gly

Gln

Thr

Ala

Pro

Val

Ile

Lys

Leu

Phe

-2.0 -1.0 0.0 1.0 2.0

-2.0

-1.0

0.0

1.0

2.0

C-EW

Axis 1 (47.4%)

Axis

2 (

34.5

%)

Vegetation

EvGrShDeCrPaFaRe

N-S A horizon N-S C horizon

W-E A horizon W-E C horizon

69

formation were complicated, the most important drivers are temperature and precipitation (Jenny,

1941). Higher precipitation enhances plant productivity resulting in above-ground C additions,

while higher temperature increase organic C decomposition rates, leading to less above-ground C

accumulations (Dixon and Weed, 1989; Smith et al., 2013). Higher concentration of organic C

provides larger amount of proteinaceous substrates for FAA enrichment. The pattern of FAA

level in A horizon along N-S transect matches the organic matter pattern of decreasing organic C

concentration with increasing MAT from north to south. The pattern of FAA level in A horizon

along W-E transect didn’t track exactly the reported pattern of high organic C in west coast, low

organic C in neighboring interior region and increasingly higher organic C from west to east

(Woodruff et al., 2009). It is possible that some combinations of local temperature or topography

explain this inconsistence.

The vertical distribution of soil organic C had a stronger relationship with vegetation than

with climate (Jobbagy and Jackson, 2000). The vegetation across N-S transect is covered by

shallow-rooted cultivated crops in the north, and deeply rooted shrubs in the south. So

underground soil organic inputs should increase from the north to the south. The pattern of

increasing FAA levels in the C horizon from north to south generally matches the pattern of

underground organic inputs which provide substrates for extracellular enzymes. The W-E

transect crosses notable vegetation transition from mainly evergreen forest in the west coast, to

shrubs in the arid and semiarid regions, and to grassland/pasture and cultivated crops in the

central and eastern region of the United States. Generally, forests have a deepest root system and

the highest root biomass, followed by shrubs, grasslands or pastures, and cultivated crops

(Canadell et al., 1996; Jackson et al., 1996). From the low precipitation west to the high

precipitation east, the FAA levels generally follow the pattern of underground organic input

70

contributed by root biomass. However, along the west coast covered majorly by deep-rooted

forests, levels of FAAs were the lowest among the sub-continental areas. This suggested the

substrate abundance may be not the only factors affecting FAA enrichment in the C horizon,

other component such as protease activities could influence the depolymerization rates. The high

lignin or tannin content of the hard-woody forest in the west coast could slow the rates of

proteolysis (Northup et al., 1995; Yu et al., 2003; Berthrong and Finzi, 2006). The amino acid

pattern in C horizon generally tracks vegetation root distributions. Root exudates and root

residues could also be contributing to the deep soil SOM deposition (Dick et al., 2005). Root

turnover rates increased with MAP for fine roots of grassland, forests and shrubland (Gill and

Jackson, 2000).

71

Figure 3. 8. Average concentrations of eight major FAAs and TFAAs in soils of A and C

horizons along the MAT and MAP gradients of continental US. Scales on right side applies to

TFAAs. MAT and MAP gradients shown in the legends differentiated by color are from the

circled areas specified in Figure 3.1. Values were expressed as mean ± SEM. # mean annual

temperature; * mean annual precipitation; § soils from west coast.

Asp Glu Gly Gln Thr Ala Val Leu N.a.N. TFAAs

0

1

2

3

4

5

6

7

0

5

10

15

20

25

30


0

2

4

6

8

10

0

10

20

30

40

50Asp Glu Gly Gln Thr Ala Val Leu N.a.N. TFAAs

Co

ncen

trati

on

s (

mo

l kg

-1 d

ry s

oil

)

0

10

20

30

40

50

0

20

40

60

80

100

120

140

160

35-50

50-55

55-60

A horizon

C horizon


0

10

20

30

40

50

60

0

50

100

150

200

250

300

4-20

20-40

40-60

40-60

A horizon

C horizon

#MAT (

oF)

*MAP (in)

§

72

3.4.4. Variations of extractable soil amino acids among different vegetation covers

The relative abundance of all eight FAAs in both A and C horizons was relatively

uniform among the four vegetation covers, although significant differences were observed for

certain major amino acids (Figure 3.9). Glu had the largest variation among the eight dominant

amino acids. Gly and Ala were more abundant in C-horizon while Glu was much richer in A

horizon. The results were consistent with what was revealed by NMS (Figure 3.3). The relative

molar percent composition of FAAs observed in this study was similar to the observations by

Werdin-Pfisterer et al. (2009) in soils of five successional stages (willow, alder, balsam poplar,

white spruce and black spruce), possibly because, on a global scale, the overstory and understory

plant litter, the major sources of FAAs, contain similar chemical structure and share the similar

biochemistry in the production and re-synthesis of amino acids during SOM formation, and in

the ecosystem processes linking them, regardless of vegetation type, soil environment, or climate.

The concentrations of TFAAs in soils of the four vegetation sites of either horizon didn’t

track the content of total soil organic C (Figure 3.10). The organic C content in A-horizon soils

follows the order as evergreen > pasture > grassland > shrub, consistent with the sequence of

above-ground biomass of the vegetation types (Mendoza-Ponce and Galicia, 2010). The levels of

TFAAs in A horizon followed in the order: evergreen ≈ pasture ≈ grassland > shrub (Figure

3.10). The divergence was probably due to the low C quality (highest C-to-N and lignin-to-N

ratios) in the hard woody forests and shrubs, resulting in low rates of decomposition in forest

sites (Aitkenhead and McDowell, 2000; Lovett et al., 2004; Grunzweig et al., 2007). In addition,

the pH of high precipitation forest soils is usually lower than soils in arid or semi-arid region, not

favoring microbial mediated proteolytic enzymatic activities. The contribution of the higher

above-ground biomass to proteinaceous substrate was eclipsed by the higher C to N ratio in

73

woody forest sites compared to grassland and pasture sites. Therefore, the similar levels of FAAs

in evergreen forest, grassland and pasture sites could be a compromise of organic inputs, organic

matter qualities and microbial activities. The total organic C content in C horizon follows the

order as: evergreen > shrub > pasture ≈ grassland, but evergreen sites have the lowest

concentration of TFAAs. The lowest TFAA level in evergreen site is consistent with the lowest

FAA concentrations in the west coast as illustrated in Figure 3.8. One explanation for this was

the semi-arid grass/pasture and shrubland have higher protease activity than the high

precipitation forest sites because, on average, semi-arid grassland and shrub sites have the

highest pH, favoring both bacterial biomass and proteolytic enzyme activity (Hofmockel et al.,

2010). In grassland and pasture sites, the higher ratios of TFAA concentration than that of the

total organic C in the A-horizon soil to that in C-horizon soil indicated the amino acids or

organic matter tend to be depleted during the vertical transport from surface soil to subsoil.

74


horizon soils with different vegetation cover. Scales on right side apply to sum of eight major

FAA proportions. Different lower case letters indicate statistical significance among groups.

Values are expressed as mean ± SEM.

Asp Glu Gly Gln Thr Ala Val Leu N.a.N. SUM

Am

ino

acid

co

mp

osit

ion

rela

tive t

o t

ota

l (m

ol %

)

0

5

10

15

20

25

0

20

40

60

80

Asp Glu Gly Gln Thr Ala Val Leu N.a.N. SUM

0

5

10

15

20

25

30

0

20

40

60

80

Evergreen

Grassland

Pasture

Shrub

abab

a

b

abab

a

b

abab

a

b

a

aba

b

ab

a a

b

a

ab ab

b

abb

b

a

ababa

b

C horizon

A horizon

75

Figure 3. 10. Concentration of TFAAs (A) and total soil organic C content (B) among four

vegetation covers in two horizons. A = A horizon; C = C horizon; A/C Ratio = the ratio of

average TFAA level or soil total organic C content in the A horizon to that in the C horizon.


3.5. Conclusions

Evergreen Grassland Pasture ShrubConcentr

ation o

f T

FA

As (

mol kg-1

soil)

0

50

100

150

200

250

Concentr

ation r

atio (

A/C

)

0

2

4

6

8

10

12

14

A

C

A/C Ratio

Land cover

Evergreen Grassland Pasture Shrub

Concentr

ation o

f soil

org

anic

C c

onte

nt (w

t)

0

2

4

6

8

10

12

Conte

nt

ratio (

A/C

)

0

2

4

6

8

10

12

A

C

A/C Ratio

B.

A.

76

This research is the first attempt to assess the levels and composition of FAAs from soils

of such variable ecosystems at continental scale. Findings in this research generally support the

original hypotheses. The concentrations of FAAs of the A-horizon soils were significantly higher

than that of the C-horizon soils and the compositional pattern was separated by depth. The major

FAAs were Asp, Glu, Gly, Gln, Thr, Ala, Val and Leu. The concentrations of TFAAs varied

significantly among the four major vegetation covers, but the composition of individual FAAs

relative to total was relatively uniform though some noticeable variations of certain amino acids

were observed. Concentrations of FAAs decreased with increasing temperature in A horizon and

an opposite trend was observed in C horizon. Though no consistent trend of FAA concentrations

with MAP was found in A horizon, a decreasing trend of FAA concentrations with increasing

precipitation was found in C horizon. The climatic factors control A-horizon FAA levels

generally by their effect on the proteinaceous substrate inputs while the root distributions of a

specific vegetation cover regulate the subsoil FAA levels along the MAT and MAP gradients.

Significant associations between amino acid distribution and the climatic factors were found.

Temperature and precipitation could influence the amino acid composition indirectly via their

effect on organic matter decomposition rates, vegetation cover, microbial activities and soil

mineralogy.

3.6. Acknowledgements

We would like to thank USGS for proving the soil samples. We thank the financial

support of USDA-AFRI (award #2012-67019-30227).

77

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85

4. Hydrolysable Amino Acids in Soils of North-South and West-East


L. Maa, K. Xia

a*, M. A. Williams

b, and D. B. Smith

c



bRhizosphere and Soil Microbial Ecology Laboratory, Department of Horticulture & Molecular

Plant Sciences, Virginia Tech, VA 24061, USA


*Corresponding author. Tel.: 540-231-9323; Email address: [email protected]

86

4.1. Abstract

Proteins or peptides are significant contributors to soil organic matter pool. Their

stabilization and bioavailability are considered to be critical points in terrestrial nitrogen cycle.

However, in depth studies on their abundance, composition, and turnover are lacking especially

in soils across a wide range of ecosystems. Our aims were to quantify contents of hydrolysable

amino acid in A-and C-horizon soils from north-south temperature and west-east precipitation

transects of continental United States and to investigate changes of hydrolysable amino acids

along vegetation, temperature and precipitation gradients. Hydrolysable amino acid is a measure

of acid cleaved amino acids. It indicates levels of soil proteins and peptides either in free form or

associated with minerals. Soil samples were hydrolyzed using 6 N HCl at 115 for 24 h. Amino

acids in the hydrolysates were derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl

carbamate, followed by analysis on a High Performance Liquid Chromatography equipped with

a fluorescence detector. Seventeen amino acids were characterized. The concentrations of total

and individual hydrolysable amino acids were significantly higher in A- than in C-horizon soils,

ranging from 211 mg kg-1

dry soil to 15 g kg-1

dry soil in A horizon and from 18 mg kg-1

dry soil

to 6.4 g kg-1

dry soil in C horizon soils, respectively. The levels of hydrolysable amino acids

were highly correlated with soil organic carbon content and levels of total free amino acids were

highly correlated with that of total hydrolysable amino acids. The concentration ratios of total

hydrolysable amino acid level in the A-horizon soils to that in the C-horizon soils were higher

for the grassland and pasture sites, than the evergreen forests and shrubs sites. Levels of major

and total hydrolysable amino acids decreased in A horizon and increased in C horizon with

increasing mean annual temperature, while increased in A horizon and decreased in C horizon

with increasing mean annual precipitation. These results suggested levels of hydrolysable amino

87

acids were associated with the above-ground biomass and root vertical distribution. The most

abundant hydrolysable amino acids were neutral, followed by acidic, basic and aromatic amino

acids in all soils. The composition of hydrolysable amino acids in the whole soils was rather

uniform regardless of variable concentrations. Major amino acids aspartic acid, serine, glutamic

acid, glycine, threonine, alanine, proline and valine took up 58 to 88% of the total hydrolysable

amino acids while the major free amino acids were glutamic acid, glutamine, aspartic acid,

leucine, alanine, threonine, glycine and valine. The overall composition of hydrolysable amino

acids differs from that of the free amino acids in A and C horizons possibly because microbial

turnover, root exudate and fine root turnover contribute to the free amino acid pool in addition to

the microbial mediated depolymerization of proteinaceous compounds.

88

4.2. Introduction

Soil is the biggest reservoir of terrestrial nitrogen (N) and ~90% of total soil N is in the

organic form (Senwo and Tabatabai, 1998; Butterbach-Bahl et al., 2011). Proteins and peptides,

in particular, play a crucial role in terrestrial N cycling, constituting ~ 40% of total soil N and as

a regulator of overall N availability (Schulten and Schnitzer, 1997; Chen and Xu, 2006;

Paungfoo-Lonhienne et al., 2008). Proteins and peptides mainly originate from plant, animal or

microbial residues at different stages of decomposition (Miltner et al., 2009). Proteins and

peptides are thus an important form of both labile and stabilized organic N. Studies on the levels

and composition of the proteinaceous compounds, therefore, are crucial to understand their

stabilization and bioavailability.

Proteins and peptides were combined amino acids with peptide linkages. Their levels

were usually measured indirectly by quantifying the acid cleaved amino acids. A small amount

of proteinaceous compounds may escape from the chemical hydrolysis because of the strong

adsorption to soil minerals, entrapment in mesopores or microaggregates, or complexing with

some organic macromolecules for their amphipathic nature (Sollins et al., 1996; Kleber et al.,

2007; Rillig et al., 2007; Knicker, 2011). By hydrolyzing proteins/peptides into free amino acids

(FAAs), we were able to quantify most of the proteinaceous substances associated to minerals,

immobilized by microorganism, as well as those in the free form. The previous studies on

hydrolysable amino acids (HAAs) were mostly limited to isolated sites. So far, no information

about the levels and composition of HAAs in soils of a wide ecosystems and different depth was

available. The concentrations of HAAs were very variable site to site and subject to the influence

of soil management, cultivation method or environmental changes (Senwo and Tabatabai, 1998;

Praveen et al., 2002a; Brodowski et al., 2005). Despite of the substantial differences in

89

concentrations, the molar percent composition of the HAAs was shown by most of previous

investigations to exhibit minor variations with various land use, climatic conditions and of soil

depth (Gotoh et al., 1986a; Campbell, 1991; Senwo and Tabatabai, 1998). Research conducted

by Sowden et al. (1977) suggested the composition of HAAs in agriculture soils was rather

uniform regardless of organic amendment. The relative distribution of HAAs in the whole soil

investigated by Friedel and Scheller (2002) was also relatively constant irrespective of a wide

land use and site conditions. In addition, Asp, Glu, Gly and Ala were found by most of others to

be the dominant amino acids in a variety of soils (Sowden et al., 1977; Gotoh et al., 1986a;

Friedel and Scheller, 2002). However, noticeable changes in HAA distribution were reported in

the composting cotton wastes (Baca et al., 1994), humic substances (Ding et al., 2001), and

decomposing plant materials (Rovira et al., 2005). The main objective of the current is therefore

to investigate the levels and overall composition of HAAs in soils across wide ecosystems. The

data collected from this investigation might help us interpret the disparities of results by others.

In this research, HAAs in A- and C-horizon soils of north-south (N-S) temperature and

west-east (W-E) precipitation transects of continental United States were investigated with the

aim to examine levels and composition of HAAs in A-and C- horizon soils of various

ecosystems and the effect of climatic factors on the concentrations and distribution of HAAs at

the continental scale. To the best of our knowledge, this was the first attempt to assess the status

of HAAs in soils over a wide range of ecosystems in United States.


4.3.1. Study sites and sampling

A subset of soil samples of A and C horizons from 93 sites along N-S and W-E transects

of continental United States (Figure 3.1) were selected from a total of 4871 sites (1site/1600km2)

90

by the USGS from 2007 to 2010 for the USGS Geochemical Landscapes Project (Smith et al.,

2013). Details on sampling protocols and sample treatment were provided elsewhere (Smith et

al., 2013). Briefly, visible plant materials were removed from each collected soil, air dried,

sieved through 2-mm sieve, and stored in glass jars at 4 oC until analysis. Mineralogical and

chemical analysis on all the soils was carried out by the USGS (Smith et al., 2013).

4.3.2. Chemicals

Waters AccQ·FluorTM

Reagent Kit was purchased from Waters (Milford, MA, USA).

The kit included Waters AccQ·Fluor derivative powder, Waters AccQ·Fluor dilution solution

and 0.2 M borate buffer (pH 8.8)(Liu et al., 1998). The ultra-pure water was produced by a Milli-

Q water purification system (Millipore, Milford, MA, USA). The ACS grade sodium acetate

(CH3COONa), anhydrous oxalic acid (H2C2O4, 98%), sodium EDTA (EDTA-Na2·2H2O),

sodium azide (NaN3), hydrochloric acid (HCl, 37%), phosphoric acid (H3PO4, 85%) were

purchased from Sigma (St. Louis, MO, U.S.A). Ammonium solution (NH4OH, 5M) was

obtained from Ricca Chemicals (Arlington, Texas, USA). The HPLC grade acetonitrile (ACN),

triethylamine (TEA) and sodium hydroxide (NaOH) pellets were purchased from Fisher

Scientific (New Jersey, USA). Individual amino acid standards including alanine (Ala), arginine

(Arg), aspartic acid (Asp), glutamic acid (Glu), glycine (Gly), histidine (His), isoleucine (Ile),

leucine (Leu), lysine (Lys), methionine (Met), phenylalanine (Phe), proline (Pro), serine (Ser),

threonine (Thr), tyrosine (Tyr), valine (Val), and cystine (Cys–Cys), as well as the internal

standard L-norvaline were purchased from Sigma. Dowex 50WX8 50-100 (H) cation exchange

resin was purchased from Fisher.

Each amino acid stock solution was prepared at the concentration of 25 mM by

dissolving precalculated amino acids standard in 0.1 M HCl solution. The stock solutions were

91

stored at -20 and can be used for 6 months. An intermediate composite standard was prepared

by combining appropriate amounts of the 17 amino acid stock solution to achieve a final

concentration of 0.25 mM for each amino acid. The intermediate composite standard was then

mixed with 2.5 mM L-norvaline in appropriate amounts of ultrapure water to yield mixed amino

acid calibration standards ranging from 0.005 to 0.2 mM for 17 amino acid and 0.1 mM for

internal standard. The calibration standards can be stored at -20 and reused within one month.

4.3.3. Hydrolysis and purification

The proteins/peptides in soils were acid liberated by 6N HCl. The hydrolytes were

purified according to the modified procedure of Amelung and Zhang (2001). One gram of air

dried soil was weighed into the 12 mL glass vials. Ten mL of 6N HCl was added into the vials.

An aliquot of 50 µl internal standard solution containing 1.25 µmol L-norvaline was spiked to

the mixture to achieve a final concentration the same as that in the calibration solution. The vials

were then incubated in the ~115 bead bath for ~ 24h. After the hydrolysis, the vials were

allowed to stand still at room temperature for cooling. About 1.5 mL of the supernatant from

each vial was transferred to the 2mL polypropylene centrifuge tubes and centrifuged at 10,000×g

for 10min. After the centrifugation, an aliquot of 400 µl of hydrolyte was pipetted into a 50 mL

centrifuge tube, which was brought to 50 mL graduation with ultra-pure water. The diluent was

loaded to a polypropylene sample preparation cartridge, pre-filled with 3 g Dowex 50 W X8

cation exchange resin which was prepared and conditioned as described by Boas (1953)and Küry

and Keller (1991). Briefly, the resin was conditioned with 25 mL of 2M NaOH, neutralized by

25 mL 2 M HCl and then rinsed with 40 ml ultrapure water to get an approximate neutral pH

(checked with pH test strip). After all the hydrolytes were transferred onto the cartridge, the resin

was rinsed with 25 mL 0.1 M oxalic acid (pH 1.7 ± 0.1, adjusted with NH4OH), 5mL 0.01 M

92

HCl and 8 mL ultrapure water in turn. Finally, the retained amino acids were eluted with 5 × 5

ml of 3 M NH4OH. After filtering through 0.22 µm PVDF syringe filters, 500 µL of the

ammonium filtrate was dried in SpeedVac at 60 for 2 h. The dried residue was reconstituted

with 10 µL 0.05 mM HCl, waiting for derivatization.

4.3.4. Amino acid derivatization

The detailed procedure for amino acid derivatization procedure using the Waters

AccQ·FluorTM

Reagent Kit can be found elsewhere (AccQ, 1993). To reconstitute the

AccQ·Fluor Reagent, 1mL of AccQ·Fluor Reagent diluent was transferred to the vial containing

the AccQ·Fluor Reagent power. The vial was tightly capped, mixed on a vortex for 10 seconds,

and then incubated at 55 in an oven for 10 min until the powder was completely dissolved.

The final reconstituted AccQ·Fluor solution was colorless and transparent and contained

AccQ·Fluor reagent at about 3mg/mL (ca.10 mM). The tightly sealed reconstituted AccQ·Fluor

solution can be stored in a desiccator at room temperature or at 4 and reused within two to

four weeks.

The dried residue was reconstituted in 10 µL of 0.05 M HCl and buffered by 70 µL

borate buffer. The mixture was vortexed for 10 seconds, followed by addition of 20 µL

reconstituted AccQ·Fluor solution. The mixture was mixed immediately on a vertex for 10

seconds and incubated for 1 min at room temperature. The mixture was then transferred to the

bottom of an autosampler vial limited volume insert, capped with a silicone-lined septum and

incubated at 55 in an oven for 10 min to complete the derivatization of amino acids in the

sample before being analyzed on the High Performance Liquid Chromatography equipped with a

fluorescence detector (HPLC/FLD). An aliquot of 10 µL of each calibration standard was

93

pipetted into the HPLC sample vial with 200 µL insert followed the described steps to initiate the

derivatization.

4.3.5. Analysis of derivatized amino acids on HPLC/FLD

Derivatized amino acids were analyzed using a HPLC 1260 Infinity system (Agilent

Technologies, USA) coupled with a fluorescence detector. Separation of the 17 amino acids was

carried out on a Waters X-Terra MS C18 column (2.1 mm × 150 mm, 3.5 µm particle size,

Waters Corporation, USA). The mobile phase consisted of A: a solution containing 140 mM

sodium acetate, 17 mM TEA, and 0.1% (g/L, w/v) EDTA-2Na (pH 5.05, adjusted with

phosphoric acid solution) and B: ACN/water (60:40, v/v). The gradient conditions were 0 - 17

min 100 - 93% A, 17 - 21 min 93 - 90% A, 21 - 30 min 90 - 70% A, 30 - 35 min 70% A, 35 - 36

min 70 - 0% A, and 0 % A for 4 min. The column was thermostated at 50 and operated at a

flow rate of 0.35 ml/min. The injection volume was set at 5 µL. The detection was accomplished

by fluorescence with excitation and emission wavelengths set at 250 nm and 395 nm separately.

Each derivatized amino acid in a sample was identified by comparing its retention time with that

of a derivatized individual amino acid standard and quantified using the internal standard method.

The detection limits, precision (relative standard deviation %), and recoveries of this method

were shown in Table 4.1.

94

Table 4. 1. Detection limits, recovery and the precision of the determination of amino acid

derivatives.

Amino acid

Detection limit

(µmol kg-1

dry

soil) a

Recovery (%) b Precision (RSD %)

c

Asp 8.9 100.4 0.5

Ser 9.6 108.9 2.9

Glu 18.5 101.5 0.1

Gly 9.9 111.5 4.3

His 8.2 99.6 1.7

Arg 8.4 82.9 3.6

Thr 6.6 98.3 2.2

Ala 5.5 103.9 3.2

Pro 7.4 105.2 3.3

Tyr 3.7 96.5 2.8

Cys-Cys 9.3 83.8 2.0

Val 1.9 102.5 0.2

Met 3.4 76.0 1.1

Lys 4.0 94.7 1.0

Ile 1.8 103.0 2.0

Leu 2.0 103.3 2.0

Phe 2.0 95.2 2.8 a The detection limits in soil samples were estimated from the detection limit of a 0.5 µM amino

acid standard on column based on a S/N ratio of 3:1 and the recovery of amino acids in spiked

samples. b

the recovery was evaluated by spiking amino acid standard at concentration of 125 µmol kg-

1dry soil and then the amino acids in the spiked sample and the same soil samples without

spiking were also determined at the same time. The recover was calculated as the percentage of

the concentration differences relative to the spiked concentration. c n = 3

4.3.6. Statistical analysis

The composition was calculated as the molar percentages of each amino acid out of total.

The concentrations were measured at dry soil basis. Concentration of total hydrolysable amino

acids (THAAs) was calculated as the sum of each HAA. The composition and concentration

variations of the FAAs between A and C horizons was evaluated by matched pair’s t test analysis.

The composition and concentration of HAAs between A and C horizons, along mean annual

temperature (MAT) and precipitation (MAP) gradients, and among different vegetation covers

were analyzed with multiple comparisons of means using a Tukey’s HSD (honest significant

95

difference), provided by JMP Pro 11 (SAS Software, Cary, NC), and nonmetric

multidimensional scaling (NMS), provided by PC-ORD ver.6 (MjM Software, OR). Linear

regression was performed by JMP. Amino acid Cys-Cys and Met was discarded while

performing NMS to reduce noise due to the fact that their levels in most of the samples were

below their detection limit. The significance level α was set at 0.05.

4.4. Results and discussion

4.4.1. The composition and concentrations of HAAs

Totally 20 peaks at the chromatogram were baseline separated (Figure 4.1), including the

derivatives of 17 amino acids, ammonium, L-norvaline (internal standard) and 6-aminoquinoline

(by product of derivatization). The chromatogram was clean and with no noticeable interferences,

allowing a good quantification of amino acid derivatives. Among the 17 HAAs identified, Asn

and Gln were transformed to Asp and Glu respectively during the hydrolysis. The concentrations

of Asp thus were reported as the sum of Asp and Asn, and Glu as the sum of Glu and Gln. A

trace levels of Met and Cys-Cys were recovered in our results due to oxidation loss during

hydrolysis (Davidson, 1997), similar to the reports by Rovira et al. (2008).

The THAA pool was dominated by eight amino acids: Asp, Ser, Glu, Gly, Thr, Ala, Pro

and Val, which were summed to 58 to 88 % of the THAA pool. The average mole percent

relative to total were 15 % for Asp, 7 % for Ser, 11 % for Glu, 16 % for Gly, 7 % for Thr, 6 %

for Pro, 12 % for Ala, and 5 % for Val in all the soil samples. Amino acids Arg, Lys, Ile, Leu,

and Phe each composts of < 5% of the THAAs. Neutral amino acids took the largest part of

THAA pool, followed by acidic, basic and aromatic amino acids, which were, on average, 61 %,

26 %, 9 %, and 4 % in molar percentages relative to THAAs, respectively. These results are

congruent with most of the previous studies (Gotoh et al., 1986a; Friedel and Scheller, 2002).

96

The average molar composition of the 17 HAAs in our research are generally consistent with the

relative abundance of amino acids (mostly hydrolysable) from more than 100 different

environmental conditions (eg., Aquatic, terrestrial and host-associated) (Moura et al., 2013). It is

suggested the HAAs were majorly of plant origin rather than microbial origin (Friedel and

Scheller, 2002).

The overall concentration of THAAs ranged from 18 mg kg-1

to 15 g kg-1

(corresponding

to ~ 3 mg to 2.5 g hydrolysable amino acid-N per kilogram of dry soil). The average

concentrations of the eight dominant amino acids were for 330 mg kg-1

for Asp (35 mg amino

acid-N kg-1

), 145 mg kg-1

for Ser (20 mg amino acid-N kg-1

), 274 mg kg-1

for Glu (27 mg amino

acid-N kg-1

), 209 mg kg-1

for Gly (39 mg amino acid-N kg-1

), 152 mg kg-1

for Thr (18 mg amino

acid-N kg-1

), and 194 mg kg-1

for Ala (31 mg amino acid-N kg-1

). These concentrations are

consistent with the previous reported results (Senwo and Tabatabai, 1998; Hou et al., 2009;

Creamer et al., 2013).

97

Figure 4. 1. Chromatograms of (A) amino acid derivatives with amino acids standard (10µM)

and (B) the amino acids in a surface soil sampled from a pasture area in Minnesota. Peaks: 1= 6-

aminoquinoline; 2=Asp; 3=Ser; 4=Glu; 5=Gly; 6=His; 7=NH4+; 8=Arg; 9=Thr; 10=Ala; 11=Pro;

12=Tyr; 13=Cys-Cys; 14=Val; 15=Met; 16=L-norvaline; 17=Lys; 18=Ile; 19=Leu; 20=Phe. The

peak between 16 and 17 in (A) is ornithine.

4.4.2. HAAs in A and C horizons

The composition of the HAAs was fairly uniform between A and C horizons, though

fluctuations of the proportions of certain major amino acids were noted (Figure 4.2). The overall

m in10 15 20 25 30 35

LU

0

10

20

30

40

50

60

1

23

4

5

6

7

8

9

10

11

12

14

15

16 17

18

19

20

m in10 15 20 25 30 35

LU

0

5

10

15

20

25

30

35

40

45

1

2

3

45

6

7

8 9 1011

12

13

14

15

16

17

18

1920A.

B.

98

variations of the major amino acids in A and C horizon were less pronounced than that of FAAs.

The variation of Asp was more pronounced than that of other HAAs.

Figure 4. 2. Average composition of individual and sum of eight major HAAs in samples of two

soil horizons from different transects. Scale on right side applies to sum of eight major FAA

proportions. Different lower case letters indicate statistical significance based on pairwise

comparison (α = 0.05). Values are expressed as mean ± Standard Error of Mean (SEM).


dry soil) of major HAAs and THAAs.

A horizon C horizon

Range Average Range Average

Asp 33 - 1899 549 3 - 966 111

Ser 12 - 1012 250 2 - 581 39

Glu 31 - 1869 466 1 - 802 83

Gly 24 - 1315 360 2 - 615 58

Thr 10 - 1034 259 1 - 464 44

Ala 22 - 1378 332 1 - 568 55

Pro 8 - 924 219 < 361 33

Val 4 - 991 197 0.1 - 301 31

THAAs 211 - 15110 3646 18 - 6442 618

Asp Ser Glu Gly Thr Ala Pro Val N.a.N. SUMAm

ino

ac

id c

om

pso

itio

n r

ela

tive

to

to

tal (m

ol %

)

0

2

4

6

8

10

12

14

16

18

0

20

40

60

80

100

A horizon

C-horizon a

b

ab

ab

ab

ab

99

The concentration ranges of each major HAAs and THAAs were summarized in Table

4.2 and plotted in Figure 4.3.The sum of the 17 amino acids, defined as THAAs, ranged from

211 mg kg-1

to 15 g kg-1

in A horizon soils and 18 mg kg-1

to 6.4 g kg-1

in C horizon soils. The

average concentration of the major HAAs and THAAs in this study are congruent with the

previously reported value in the Hawaiian soils (about dozens g kg-1

soil in total)(Mikutta et al.,

2010), the corn tillage field soils (about several g kg-1

soil in total)(Martens and Loeffelmann,

2003), four kinds of surface soils from China (about several g kg-1

soil in total, Ultisol, Alfisol,

Inceptisol and Mollisol), and the organic matter from the cropping surface soils (about 566 to

1509 mg kg-1

soil in total)(Senwo and Tabatabai, 1998). If an average ratio of 1.4 mole N per

mole of amino acids was used to convert concentrations of THAAs to that of total hydrolysable

amino acid-N (Rothstein, 2009a), the total amino acid-N was ranged from 35 to 2488 mg kg-1

dry soil and from 2 to 1065 mg kg-1

dry soil in A and C horizon, respectively. The reported

concentrations of total hydrolysable amino acid-N in New Zealand soil profiles fell well in this

range (from 566 to 2084 mg kg-1

soil in A horizon and 28 to 156 mg kg-1

soil in C horizon) (Goh,

1972). The concentrations of HAAs were significantly higher in A horizon than that in C horizon

(Figure 4.3). The similar trend was also found for other HAAs. The higher amount of HAAs in

the A- than in the C-horizon soils was mostly ascribed to the high organic matter content in the

surface soil (Gotoh et al., 1986a; Praveen et al., 2002a; Frunze, 2011). The concentrations of

THAAs and each major HAA were positively correlated with soil organic C content (P<0.001)

(Figure 4.4), because the organic N is always connected to a C backbone. The THAAs were also

found by Senwo and Tabatabai (1998) to be highly correlated with the soil organic C from the

ten surface soils of two cropping systems. The high positive correlations also suggest the

proteinaceous compounds are associated with soil organic matter by forming complexes with

100

recalcitrant substances such as lignins, tannins and polyphenols (Warman and Isnor, 1991; Rillig

et al., 2007). At sites with low C content (low C:N ratio, high organic C quality), soil amino acid

concentrations were less scattered than that in sites with high C content (high C:N ratio, low

organic C quality) (Figure 4.4), possibly driven by the quality of soil organic C.

Figure 4. 3. Average concentration of eight major HAAs and HAAs in two horizon soils from

different transects. Scale on right side applies to THAAs. Different lower case letters indicate

statistical significance among groups (α=0.05). Values are expressed as mean ± SEM.

Asp Ser Glu Gly Thr Ala Pro Val N.a.N.THAAsAm

ino

ac

id c

on

ce

ntr

ati

on

s (

mg

kg

-1 d

ry s

oil)

0

100

200

300

400

500

600

700

0

1000

2000

3000

4000

5000

A horizon

C horizon a

b

a

a

a

a

a

aa

a

b

bb

b bb b

b

101

Figure 4. 4. Linear relationship between the concentrations of THAAs and major HAAs with

total soil organic C content (wt%) from two horizons.

4.4.3. Variations of HAAs along MAT and MAP gradients of continental United States

In order to illustrate large-scale patterns of amino acid distribution with the climatic

gradients, the sampling sites were grouped into coherent, sub-continental areas (Figure 3.1).

Consistent trends of HAA variations with environmental controls were found (Figure 4.5).

Concentrations of eight major HAAs and THAAs decreased with increasing MAT in the A-

horizon soils, but an opposite trend was found in the C-horizon soils. Similarly, the levels of

eight major HAAs and THAAs exhibited an overall increasing trend with increasing MAP in the

A-horizon soils. In C horizon, however, as the precipitation went up from the west to the east,

0 2 4 6 8 10

0

20

40

60

80

100

Y=2.089+13.029X

R2=0.667P<0.001

THAAs

0 2 4 6 8 10

0

2

4

6

8

10

12

14

Y=0.694+1.336X

R2=0.553P<0.0001

Asp

0 2 4 6 8 10

0

2

4

6

8

10

Y=0.212+0.889X

R2=0.605P<0.0001

Ser

0 2 4 6 8 10

Am

ino

ac

id c

on

ce

ntr

ati

on

s (

mm

ol kg

-1 d

ry s

oil)

0

2

4

6

8

10

12

Y=0.450+1.007X

R2=0.576P<0.0001

Glu

0 2 4 6 8 10

0

2

4

6

8

10

12

14

16

Y=0.602+1.634X

R2=0.616P<0.0001

Gly

0 2 4 6 8 10

0

2

4

6

8

Y=0.280+0.759X

R2=0.562P<0.0001

Thr

0 2 4 6 8 10

0

2

4

6

8

10

12

14

Y=0.449+1.314X

R2=612P<0.0001

Ala

0 2 4 6 8 10

0

1

2

3

4

5

6

7

Y=0.220+0.667X

R2=0.556P<0.0001

Pro

Total soil organic C content (wt. %)

0 1 2 3 4 5 6

0

2

4

6

8

C horizon

A horizon

Y=-0.044+0.929X

R2=845P<0.0001

Val

102

the concentrations decreased. But at the west coast, the concentrations rose and become the

highest among the four sub-continental areas.

Figure 4. 5. Average concentrations of eight major HAAs and THAAs in A- and C-horizon soils

along the MAT and MAP gradients. Scales on right side apply to THAAs. The above two and

the bottom two sub-figures indicate the trend of amino acid level with MAT and MAP,

respectively. Temperature or precipitation gradients shown in the legends differentiated by color

are from the circle areas specified in Figure 3.1. Values were expressed as mean ± SEM. # mean

annual temperature; * mean annual precipitation; § soils from west coast.

C horizon

Asp Ser Glu Gly Thr Ala Pro Val N.a.N. THAAs

0.0

0.5

1.0

1.5

2.0

2.5

0

2

4

6

8

10

12


Am

ino

acid

co

nc

en

trati

on

s (

mm

ol

kg

-1 d

ry s

oil

)

0

1

2

3

4

5

6

7

0

10

20

30

40

50

35-50

50-55

55-60

A horizon


0

2

4

6

8

10

0

10

20

30

40

50

60

70


0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0

5

10

15

20

25

4-20

20-40

40-60

40-60

¡

§

A horizon

C horizon

#MAT (

oF)

*MAP (in)

103

The N-S temperature gradient has less dramatic precipitation changes but has significant

differences in MAT, and the W-E precipitation gradient has less distinct temperature variations

but has important differences in MAP. Temperature and precipitation, therefore, are the major

controlling factors along the N-S transect and W-E transect, respectively. Cold whether inhibits

the decomposition rates of organic matter, thus, resulting in the large accumulations of organic C

at the surface soil. The organic C content in the A horizon soils, therefore, decreased with

increasing MAT from the north to the south along the N-S MAT transects. High precipitation

increases the organic C accumulations by increasing above-ground vegetation productivity. The

organic C content of the A-horizon soils thus should be high at the west coast, low in the

intermediate area, and gradually increase to the east along the W-E precipitation gradient. The

pattern of organic C distribution along the two transects were illustrated further by Woodruff et

al. (2009). Since the levels of HAAs were positively correlated with soil organic C content, the

trends of decreasing levels of HAA with increasing MAT and decreasing MAP match the

patterns of soil organic C distribution in the A-horizon soils of the two transects. It is concluded

that the climatic factors affect the HAA abundance in the same way as they influence levels of

soil organic C. The importance of these environmental controls, however, switched with depth,

with root distributions the dominant affecting factor in subsoil (Jobbagy and Jackson, 2000). The

major vegetation along the N-S transect changed from crops in the north to shrubs in the south.

The vegetation along the west coast was dominated with evergreen forests. From the sub-

continental area next to the west coast to the east areas, the major vegetation changed from

shrubs/evergreen forests to pastures/grasslands/crops. Among these vegetation covers, forests

have the deepest root system and highest root biomass, followed by shrubs, grasslands/pastures,

and crops/grains (Canadell et al., 1996; Jackson et al., 1996). The subsoil organic C content

104

should be the highest for the forest sites, intermediate for pasture/grassland sites, and least for

cultivation sites. The trends of subsoil HAAs thus generally track the underground root profiles

and biomass.

4.4.4. Variations of HAAs among different vegetation covers

In general, the composition of HAAs was fairly uniform among vegetation covers (Figure

4.6). In addition, the mole abundance of each major amino acid tended to be relatively constant

with either MAT or MAP along the two transects (data not shown), although a consistent change

of the concentrations with MAT and MAP was observed. These results are in line with the

previous findings of a uniform HAA distribution in soils of various cropping and cultivating

systems or from different climate zones (Sowden et al., 1977; Gotoh et al., 1986a; Senwo and

Tabatabai, 1998; Friedel and Scheller, 2002). Soil protein and peptides originate from plant

residues and microbial biomass. The amino acid composition from fresh plants or living

microorganisms, however, was supposed to differ from that in the bulk soils (Stouthamer, 1973;

Scheller et al., 2000; Friedel and Scheller, 2002; Creamer et al., 2013).The reasons why the bulk

HAA composition remains no substantial change despite of the dissimilar composition in

original plant residues and litter are unclear. Possibly, there is an N transformation process after

the plant residues and microbial biomass are stabilized to the SOM, which, once aged, doesn’t

show significant chemical alternation. Study by Miltner et al. (2009) suggested the microbial

amino acids were quickly turned over in the microbial food web or were stabilized into non-

living SOM. And the redistribution of microbial biomass into non-living SOM doesn’t alter the

chemical composition of SOM significantly and the composition of amino acids gradually tended

to approach a stable level similar to that of bulk SOM. Likewise, as suggested by Friedel and

Scheller (2002), the amino acid transformation already takes place at the first stage of

105

degradation of plant residues. In view of this, it is postulated although the amino acid

composition from plant residue or living microorganism was distinguished from that of the bulk

soil, in the processes of forming SOM, there is a conversion process to allow the amino acid

composition to reach a steady state. After the bulk SOM formation, there is a tendency for the

chemical composition of the organic N pool to be maintained in soils (Gotoh et al., 1986a). And

the minor fluctuations may be caused by the limited amount of amino acids in living

microorganisms or particulate organic matter.

By summarizing results of the previous work on the relative distribution of HAAs, we

found that the statements on uniformness of HAA composition were subjective to the statistic

methodologies. For example, only small differences were found in the patterns of HAA

distribution related to treatments when the data were plotted as curves, but measurable

distinction in the patterns of HAA distribution was seen between soils with and without manure

application by employing the multivariate analysis (Beavis and Mott, 1996, 1999; Rovira et al.,

2008; Moura et al., 2013). This suggested the multivariate methods may be a good statistical tool

to fingerprint the amino acids. Multivariate analysis by NMS showed the composition of HAA in

this research were relatively uniform along the two transects and in two soil horizons, suggesting

the minimum climatic effects on composition alteration of HAAs.

106

Figure 4. 6. Average composition of individual and sum of eight dominant HAAs in A and C

horizon soils with different vegetation cover. Scales on right side applies to sum of eight major

HAA proportions. Different lower case letters indicate statistical significance among groups

(α=0.05). Values are expressed as mean ± SEM.

In A horizon, the pattern of the total organic C content among the four vegetation covers

generally matches that of above-ground biomass inputs (Mendoza-Ponce and Galicia, 2010)

(Figure 4.7). The levels of THAAs among the four vegetation covers, however, didn’t follow that

of total organic C content, with higher THAA concentrations in grassland and pasture soils than

Asp Ser Glu Gly Thr Ala Pro Val N.a.N. SUM

Co

mp

osit

ion

of

am

ino

acid

s r

ela

tive t

o t

ota

l (m

ol

%)

0

2

4

6

8

10

12

14

16

18

20

0

20

40

60

80

100

Evergreen

Grassland

Pasture

Shrub

Asp Ser Glu Gly Thr Ala Pro Val N.a.N. SUM

0

2

4

6

8

10

12

14

16

18

20

0

20

40

60

80

100

A horizon

C horizon

a a

bab

ab

aab

b

ab aba

b

a

babab

a

a

b

ab

ab abab

aba

bab

107

expected (Figure 4.7). This is likely because the low quality organic inputs (high C-to-N ratio

and lignin to N ratio) in the woody forest and shrub sites inhibited the initial microbial

breakdown of plant residues than grassland and pasture sites, thereby decreasing the protein-

substrate availability (Aitkenhead and McDowell, 2000; Lovett et al., 2004; Grunzweig et al.,

2007). The lowest THAA content in shrub sites was ascribed not only to the woody structure but

also the lowest aboveground biomass. The lower THAA content in C horizon and higher THAA

ratios in A-horizon to that in C-horizon soils of grassland and pasture sites suggested the organic

matter inputs were depleted in the subsoil compared to that in the surface soil (Figure 4.7). The

lower THAA levels in grassland and pasture soils compared to shrub and evergreen forest soils

were in contrast to that for the total free amino acids (TFAAs) which were found to be contained

in higher concentrations in grassland and pasture soils than other sites (Figure 3.10). This

indicates the FAA production is not only affected by protein-substrates availability but also other

factors which influence the proteolysis rates. Though hydrolysis can liberate most of the

proteinaceous substances from the mineral associates or protein-polyphenol complexes, the

proteolysis rates were reduced by those complexes (Berthrong and Finzi, 2006).

108

Figure 4. 7. Concentration of THAAs (A) and total soil organic C content (B) among four

vegetation covers in two soil horizons. A = A horizon; C = C horizon; A/C Ratio = the ratio of

average THAA level or soil total organic C content in the A horizon to that in the C horizon.


Evergreen Grassland Pasture Shrub

Co

nc

en

tra

tio

ns

of

TH

AA

s (

mm

ol k

g-1

dry

so

il)

0

10

20

30

40

50

Co

nc

en

tra

tio

n r

ati

o (

A/C

)

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14A

C

A/C Ratio

Vegetation

Everygreen Grassland Pasture Shrub

To

tal o

rga

nic

C c

on

ten

t (w

t.%

)

0

1

2

3

4

Co

nte

nt

rati

o (

A/C

)

-4

-2

0

2

4

6A

C

A/C Ratio

109

4.4.5. Comparisons of THAAs with TFAAs and implications

In order to compare the composition of HAAs with that of FAAs, non-protein amino

acids and Trp in the FAA pool were discarded because these amino acids were either destroyed

by deamination during hydrolysis or below detection limit. Amino acid Gln in the TFAA pool

was included in the calculation of Glu because Gln was transformed to its acid form as Glu

during hydrolysis. Asn cannot be separated from Ser, so Ser of FAAs was a sum of Ser and Asn.

The composition of THAAs was mostly different from that of TFAAs, especially for Asp, Glu,

Gly and Ala (Figure 4.8).

There are several possibilities responsible for the differences of FAAs and HAAs in

composition. As we discussed before, the FAAs were produced majorly by enzymatic hydrolysis

of soil proteinaceous compounds (Schimel and Bennett, 2004), the preferential hydrolysis could

influence the composition of FAA released. Polar amino acids, which are generally located on

the surface of protein structures (Nelson et al., 2008), may be more vulnerable to enzymes while

Gly, which are more refractory from the bacterial attack than other amino acids, tend to be less

abundant as hydrolysis proceeded (Yamashita and Tanoue, 2003). A relatively high Glu and low

Gly percentages in FAAs than in HAA thus seem feasible (Figure 4.8). In addition, plant roots

FAAs and microbial cell walls contain higher Glu and Ala than Asp and Gly than in bulk soils

(Chiang and Nip, 1973; Friedel and Scheller, 2002) suggested plant root exudate, along with fine

root and microbial turnover are an important sources of soil extracted FAA.

The concentrations and composition of FAAs tend to be more diverse among sites than

that of HAAs. The concentrations of both FAAs and HAAs share generally similar trend with

environmental factors both in A and C horizons, but the composition of FAAs was more

subjective to climatic changes while a rather uniform composition of HAAs was found. In

addition, the variability of FAA composition was more pronounced between the two soil

110

horizons while a relatively uniform composition was observed for HAAs. These results

suggested FAA production is more subjective to environmental or seasonal changes while HAAs

are more stabilized in soils. Large variations of composition and concentrations of FAAs were

also observed in temperature-forest soils across the landscape fertility gradient (Rothstein, 2009b)

and in Alaskan Arctic tundra soils and a temperate grassland soil to exhibit seasonal dynamics

due to plant-driven or microbial fueled process (Weintraub and Schimel, 2005a; Warren and

Taranto, 2010). The review on literature data also shows a variable composition of FAA in

different ecosystems (Werdin-Pfisterer et al., 2009).

Hydrolysable amino acids represent soil total amino acids with and without peptide

linkages, scarcely in free form and largely in insoluble form sequestrated by organo-mineral

associates or microorganisms, entrapped in micropores or stabilized by macromolecules

(Knicker, 2011). There is a flux between of N between the soluble and insoluble N pools

(Schimel and Bennett, 2004; Chen and Xu, 2006). Regardless of whether HAAs are in soluble or

insoluble form, the majority of them is not directly bioavailable. Depolymerization is thus

needed to transform the polymeric N to bioavailable dissolved organic N such as FAAs, in

particular. The high correlations of the concentration of TFAAs with that of THAAs further

confirmed the fact that soil FAAs are majorly produced via depolymerization of HAAs (Figure

4.10). Any factors such as pH, temperature and substrate availability and quality that influence

enzymatic activities could influence the production of FAAs (Fierer et al., 2001; Weintraub and

Schimel, 2005b; Kielland et al., 2007). On average, less than 4 % of THAAs was in the form of

TFAAs (Figure 4.10). Such small fraction of organic N, however, serves as an alternative N

source for plants because plants can compete with microbes to “short circuit” amino acids (Neff

et al., 2003).

111

The capacity of plant uptake FAAs seems to be ubiquitous and has been recorded from

various plant species (Persson and Näsholm, 2001; Weigelt et al., 2005; Kielland et al., 2006;

Jämtgård et al., 2008).The uptake of amino acid by microbes was majorly used for microbial

biomass production and partially for respiration (Vinolas et al., 2001). Uptake of FAAs by plant

or microorganisms is due to active transport, mediated by specific membrane transporters

(Jämtgård, 2010). Generally, the uptake rates are concentration dependent, increasing with

increased concentrations of amino acids (Jämtgård et al., 2008). The concentration dependencies

were described by Michaelis-Menten kinetics (Vinolas et al., 2001; Jämtgård et al., 2008).

Experiment on isotopically labeled amino acids, on the other hand, showed preferential uptake of

certain FAAs in a solution with some amino acids at the same initial concentration. Weigelt et al.

(2005) found a grass species was more effective in using Gly than complex amino acid Phe while

another species preferred Ser. Such species-specific preferential uptake of amino acids by plants

has also been demonstrated by others (Miller and Bowman, 2003). Complementary preferences

for amino acids between plants and microbes were also found by Lipson et al. (1999a) and

Endres and Mercier (2003). In their studies, bromeliad and alpine sedge preferentially adsorb

Gly over other amino acid such as Gln and Glu due to decreased microbial demand for this

compound. On the contrary Jämtgård et al. (2008) found differences in amino acid (incubation

solution of Ser, Glu, Gly, Arg and Ala at four concentration levels, 2, 5, 10 and 25 µM) uptake

by barley root were small, suggesting no preferential uptake of amino acids in barley. We thus

suggested, in soils with certain vegetation cover, the preferences for FAA types are a function of

the substrate concentration, i.e. differences in uptake of different FAAs in soil solution reflect the

edaphic variations in availability of the FAAs rather than any preferential uptake of amino acids.

Among soils with different vegetation cover, on the other hand, preferential uptake of amino

112

acids could happen based on specific requirement of different vegetation for C or N. Actually,

the rapid uptake of added, isotopically labeled amino acids suggested the released FAAs in soils

were very short-lived and will be used up by microbes and plants once they are available even in

low concentrations (Jones and Kielland, 2002; Hobbie and Hobbie, 2012). It is thus suggested

these amounts of detected FAAs in soils are those protected via trapping in microaggregates,

pores or chemically sorbed, or released from fine root turnover and microbial lysis during

extraction (Hobbie and Hobbie, 2012).

113

Figure 4. 8. The average proportions of each amino acid in the HAA or FAA form.

Asp SerG

lu Gly

His

Arg ThrAla

Pro Tyr

Cys

-Cys Val

Met

Lys Ile Leu phe

Co

mp

os

itio

n o

f a

min

o a

cid

re

lati

ve t

o t

ota

l (m

ol %

)

0

5

10

15

20

25

30

35

HAAs

FAAs

A horizon

Asp SerG

lu Gly

His

Arg ThrAla

Pro Tyr

Cys

-Cys Val

Met

Lys Ile Leu phe0

5

10

15

20

25C horizon

114

Figure 4. 9. Relationship between TFAAs and THAAs in soils investigated from the 93 sites.

Red and green represent samples from C and A horizon, respectively.

4.5. Conclusions

Our result confirmed that the overall composition of HAAs was uniform irrespective of

site properties and land use. Up to eighty percent of the soil THAAs was composed of Asp, Ser,

Glu, Gly, Thr, Ala, Pro, and Val. The THAA levels were found to be related to soil organic C

content. They were significantly higher in the surface soil than in the subsoil due to more organic

substance in the surface soil. Concentrations of major HAAs and THAAs were found to decrease

with increasing MAT and decreasing MAP in the A-horizon soils along the N-S and W-E

transect, respectively. The trends were opposite in the C-horizon soils. The climatic factors

mainly affected the variation of surface HAAs via their influences on soil organic C inputs. The

levels of subsoil HAAs were majorly related to the vegetation types. Soils in the evergreen and

shrub sites contained less THAAs than grassland and pasture sites in the A horizon. This

suggested the quality of above-ground biomass plays an important role in HAA production. Soils

of evergreen forest followed by shrub sites with deep root system and large root biomass had

Concentration of THAAs (mmol kg-1 dry soil)

0 20 40 60 80 100

Co

nc

en

tra

tio

n o

f T

FA

As

(

mo

l k

g-1

so

il)

0

100

200

300

400

500

600

Y= -1.141+3.376x

r2=0.570

P<0.0001

115

more THAA content in the subsoil due to larger underground organic C biomass than soils of the

shallow-rooted grassland, pasture and cropland sites. The composition of FAAs varied more

among sites and between depth than that of HAAs, suggesting that FAAs are more voluntary to

environmental factors and epidemic changes. On average, less than 4 % of HAAs was in the

form of FAAs. HAAs served as substrate for FAA enrichment. The differences of relative molar

percentages of major amino acids between FAAs and HAAs were possibly due to preferential

hydrolysis of proteinaceous compounds, FAAs enrichment by microbial or fine root turnover and

root exudate, as well as the sorption of FAAs to soil.


We thank USGS for proving the soil samples. We thank the financial support of USDA-

AFRI (award #2012-67019-30227).

116

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124

5. Carbon K-edge Near Edge X-ray Fine Structure Spectroscopic

Investigation of Organic Carbon Speciation in Soils of North-South

and West-East Transects of Continental United States

L. Maa, Jinyoung Moon, K. Xia

a*, M. A. Williams

b, and D. B. Smith

c



b Rhizosphere and Soil Microbial Ecology Laboratory, Department of Horticulture, Virginia

Polytechnic Institute and State University, Blacksburg, VA 24061, USA


*Corresponding author. Email address: [email protected]

125

5.1. Abstract

Soil is the largest reservoir of terrestrial C. The studies of the distribution of organic C

speciation are of significance to better understanding of soil C sequestration. In this study, the

organic C speciation in surface and subsurface soils from north-south and west-east transects of

continental United States was investigated using C K-edge Near Edge X-ray Fine Structure

Spectroscopy. The aim is to explore the effect of climatic factors on soil organic C speciation at

different soil depth. Carbon K-edge spectra showed the presence of carboxylic-C (38%),

aliphatic-C (~ 22%), aromatic-C (~ 18%) and O/N-alkyl-C (~ 16%) and phenolic-C (< 6%)

moieties. Although certain fluctuations of the proportions of aromatic-C and phenolic-C species

were observed, the overall composition of soil organic C was relatively uniform among sites and

between two horizons irrespective of the variations in organic C content. Factors such as

temperature and vegetation cover were revealed in this study to account for the changes of pool

size of aromatic-C and phenolic-C species. Phenolic-C may be a good indicator for the effect of

temperature or vegetation on the composition of soil organic C. The study showed synchrotron

based Near Edge X-ray Fine Structure Spectroscopy was a powerful technique to reveal

chemical structure of soil organic matter.

126

5.2. Introduction

On average, 70% of the terrestrial C is in soils (Eswaran et al., 1993). The enrichment of

soil organic C (SOC) enhances the nutrient supply to crops, thus improves soil quality and crop

productivity (Cooper et al., 2004). Degradation of SOC, ultimately released as CO2 to

atmosphere, contributes to the greenhouse effect (Hansen et al., 1981). The decomposition,

stability and sequestration of SOC play a paramount role in climate change and agricultural

management (Dai et al., 2011).

The major forms of SOC in soils are aliphatic-C, carboxylic-C, aromatic-C, phenolic-C

and polysaccharides (Kunlanit et al., 2014). The general composition of SOC, revealed by 13

C

nuclear magnetic resonance (NMR), was reported to be relatively uniform despite a wide range

of land use and climatic conditions (Mahieu et al., 1999) and great chemical heterogeneity of

SOC was also observed at nano-scale soil aggregates as revealed by STXM (Schumacher et al.,

2005; Kinyangi et al., 2006b). Some studies indicated the chemical composition of SOC can be

altered by organic residues with contrasting C quality (Kunlanit et al., 2014), vegetation types

(Quideau et al., 2001; Hannam et al., 2004), pedogenic environment (Rumpel et al., 2002) and

anthropogenic perturbations (Solomon et al., 2002; Solomon et al., 2007). The major mechanism

of the effect of these factors on chemical alteration of SOC was possibly associated with

different rates of decomposition (Rovira and Vallejo, 2002). Cellulose, hemicelluloses, and

lignin, the major components of plant materials, degrade into phenols and aromatics, etc (Kögel-

Knabner, 2002; Jokic et al., 2003). The decomposition or anthropogenic perturbations foster the

repletion of labile proteinaceous and carbohydrate fractions and the accumulation of refractory

compounds (Solomon et al., 2002; Keiluweit et al., 2010). A clear knowledge of SOC

composition helps decipher mechanisms involved in SOC accumulations from biologically

127

contrasting organic residues and betters our understanding of vegetation and climate driven

alteration of SOC composition in soils, which provide us insights into the regulation of SOC

stabilization and C sequestration (Alvarez-Arteaga et al., 2012; Kunlanit et al., 2014). So far,

most of the previous investigations of the composition of SOC were limited to ecosystems in a

small scale. Collecting such soils information over a wide range of land use remains largely

unknown.

Many techniques such as NMR, 13

C CPMAS NMR in particular (Mahieu et al., 1999),

pyrolysis field-ionization mass-spectrometry (Py-FIMS), secondary ion mass spectrometry

(SIMS), X-ray photoelectron spectroscopy (XPS), stable isotopic composition and radiocarbon

dating, and transmission electron microscopy (TEM)(Beyer et al., 1992; Victoria et al., 1995;

Bird and Pousai, 1997; Martin et al., 2002; Gerin et al., 2003; Gonzalez Perez et al., 2004; Jones

and Singh, 2014; Poch and Virto, 2014) have been used for soil organic matter characterization.

NMR spectroscopy can provide most of the information about the functional groups of SOC, but

suffers from interferences by paramagnetic minerals (Li et al., 2013). Py-FIMS yields

information of the decomposition products of the volatile macromolecules but cannot resolve

elemental functionality (Gillespie et al., 2009). Although laboratory spectroscopy and

microscopy techniques such as TEM, SIMS and XPS can provide atomic information or

information on the organic C species, they lack the sensitivity to differentiate different forms of

C (Myneni, 2002).

Synchrotron-based Near Edge X-ray Fine Structure (NEXAFS) spectroscopy provides

detailed information on SOC speciation and enable semi-quantitative estimation of relative

composition of each SOC species (Lehmann et al., 2009). The technique uses intense, highly

polarized X-ray provided by a synchrotron radiation light source to probe element speciation in

128

samples. When the energy of incident electrons from synchrotron radiation matches the binding

energy of the electron at C atom orbitals, the electron is suddenly removed from the atom in an

ionization event (Lehmann et al., 2009). If the energy is just below the absorption edge, the

energy can lift an electron to unoccupied, not fully occupied, or higher orbitals; these pre-edge

resonances between 284 to 290eV are typical C K-edge NEXAFS features. The vacancy of

removed inner electron can be filled by electrons from higher orbitals, and the energy differences

is emitted in the form of fluorescent photon or Auger electron emission (Stöhr, 1992). The

NEXAFS spectra can be collected both in total fluorescent yield (TFY) and total electron yield

(TEY) mode, providing information of soil characteristics at a depth of ~ 100nm and at surface

(~ 10nm), respectively. The lower pre-edge resonances of C K-edge NEXAFS is usually

associated with the excitation to lowest π* anti-bonding orbitals and mixed Rydberg/valence

states for molecules with double or triple covalent bonds, and the higher energy features (near

290eV) are typically σ* transitions from saturated covalent bonds (Kinyangi et al., 2006a).

Compared to NMR, NEXAFS spectroscopy is nondestructive, sensitive and element selective

(Creamer et al., 2013). The approach has been extensively applied to environmental samples

(Vairavamurthy and Wang, 2002; Lehmann et al., 2009). The objective of the current study was

to employ NEXAFS spectroscopy to identify and quantify the speciation of SOC associated with

different functional groups in surface and subsurface soils from north-south (N-S) and west-east

(W-E) transects of continental United States.

5.3. Materials and Methods

5.3.1. Study sites and sampling

Surface (A horizon) and subsurface (C horizon) soil samples collected from 93 sites

across United States were investigated. This set of soil samples is a subset of samples collected

129

from a total of 4871 sites (nominal density of 1 site per 1600 km2 in conterminous USA) by the

USGS from 2007 to 2010 for the USGS Geochemical Landscapes Project (Smith et al., 2013).

After collection, visible plant materials and stones were picked out from soils, which were air

dried, sieved through 2-mm sieve, and then stored in glass jars at 4 oC temperature in a

warehouse at the USGS Denver Federal Center. The 93 sites selected for the current study

represent locations along N-S temperature gradient and W-E precipitation gradient transects of

continental United States. The samples were stored in plastic vials at 4oC until analysis.

Mineralogical and chemical analysis on all the soils was conducted by the USGS (Smith et al.,

2013). Mean annual precipitation (MAP) and temperature (MAT) of the sampling sites were

obtained from a database at USA.COM.

5.3.2. Sample preparation

The air dried bulk soil samples were grinded and pulverized to fine powder. About 100

mg of the powder was pressed by a small metal cylinder onto a pre-prepared 0.5 × 1 cm soft

indium foil taped on a steel sample holder to form a flat thin layer. Loosely attached soil particles

were removed by slightly tapping the side of the sample holder on a hard surface. The indium

foils were taped to a steel sample holder using double-sided conductive carbon tape without

exposing the C tape. The sample holders were screwed onto a mechanical arm to be transferred

into the chamber. Each arm held 6 samples each time, including one empty indium foil as blank

and one with crystallized glycine deposited for energy calibration.

5.3.3. Date collecting

Carbon K-edge NEXAFS spectra were acquired on the high energy resolution

monochromator (HERMON) beamline at the Synchrotron Radiation Center (SRC), University of

Wisconsin-Madison. This is a bending magnet beamline covering the energy range from 62-1400

130

eV to achieve a resolving power in excess of 10,000 in the soft X-ray range. The sample was

introduced into the measurement chamber by a load lock, and the pressure of the chamber was

maintained at less than 10-10

Torr (Luk et al., 2004). Medium energy grating (MEG) was chosen

to cover the energy range for C detecting. At the beginning, the entrance and the exit slits were

set at 250 and 500µm separately to focus the visible beam spot on the sample. Then decrease

them to 20 and 40 µm to ensure the resolution. The spectra were recorded in TEY mode with a

fine step of 0.1 eV at the energy range from 255 to 310 eV where the major resonance peaks

appear (270 - 296 eV), and at larger steps elsewhere (0.5 eV). At the same time, spectra of the in-

line gold mesh were collected to compensate for the “optics” effect due to the non-uniform

absorption by the beamline optics. After each collection, the in-line gold mesh was refreshed by

shifting to a new target position. Each samples were scanned for once, otherwise three times by

moving the sample if the intensity was low.

The monochromator energy scale was calibrated by setting the C (1s) to π* transition in

Glycine to 288.5 eV. Thin film of calibration substance was prepared by drying 100 µL of

glycine standard dissolved in ultra-pure water (1mg/mL) onto a clean indium foil under a fume

hood. Spectra of the glycine reference and indium foil blank were acquired after every 12

samples.

5.3.4. Data processing

All the data were saved as TXT files which can be read by Excel. Regions with signal

glitches in the spectra were manually removed and substituted with a straight line. Each

spectrum was normalized to that of the in-line gold mesh collected simultaneously during sample

data collection. The normalized spectra were subject to linear background subtraction at the pre-

edge region which was then normalized to a unity absorption jump height of C1s absorption edge

131

from 280 to 300eV. All the above mentioned steps were conducted suing IDL6.1 Virtual

Machine Version of aXis2000 (Hitchcock Group, Canada). The spectrum was deconvoluted

using eight Gaussians at energy position of known transitions with an arctangent function (AT)

for the ionization step at 290 eV. A full-width at high maximum (FWHM) was restricted to

around 0.4 eV for the first six deconvoluted peaks, which fingerprint the 1s- π* resonances

around 284.3, 285.0, 286.5, 287.3, 288.4, and 289.3 eV Kinyangi et al. (2006a). The two broad

resonances (around 290 and 291eV) were simulated with FWHM of 0.8 ~ 1.2 and 1 ~ 2eV

respectively. Each spectrum was curve fitted using the Microsoft Excel Solver platform. The

deconvolution procedure was applied to the extracted spectra through the energy range from 280

to 294eV.

5.3.5. Statistics

The area of six fitted peaks representing different functional groups was summarized.

The relative composition of each SOC species was calculated using the ratio of the peak area of

each species to sum of the six peak areas. Since no replicas were taken in each sampling site, we

combined all the results of organic-C composition and divided them into different groups

according to transects, vegetation, or horizon for comparison. One-way ANOVA followed by a

multiple comparisons of means using a Tukey’s HSD was implemented to compare the content

and proportion of functional groups in each group.

5.4. Results and Discussion

5.4.1. Soil organic C speciation and relative composition characterization

The deconvoluted C K-edge NEXAFS spectra indicating the six main 1s-π* and two σ*

transitions were shown in Figure 5.1. The peak at 284.3eV represents quinone-C and protonated

and alkylated aromatic-C (Brandes et al., 2004; Braun et al., 2007; Solomon et al., 2012a). The

132

resonance near 285.2 eV is associated with aromatic-C including the ring structures of polycylic

hydrocarbons, unsaturated hydrocarbons and olefins (Solomon et al., 2005; Gillespie et al., 2011;

Solomon et al., 2012a). The sum of the two resonances was regarded as aromatic-C in the

present study. Peak near 286.5eV corresponds to phenolic-C including a variety of compounds

ranging from simple phenol derivatives such as hydroquinone to substances with complex

structures such as tannins, lignins, and flavonoids (Kögel-Knabner, 2002; Brandes et al., 2004;

Braun et al., 2007; Lehmann et al., 2009). Phenols can be oxidized to quinones. Phenolic-C and

quinone-C groups in soils mostly originate from plant derived lignin degradation (Kinyangi et al.,

2006a; Solomon et al., 2012a) and represent the recalcitrant part of SOC. The feature near 287.3

eV is related to aliphatic-C, caused by C1s-3p/σ* Rydberg-like excitations from CH, CH2, and

CH3 groups of functionalities of amino acids and phospholipid fatty acid, etc (Kaznacheyev et al.,

2002; Zubavichus et al., 2005). The absorption band near 288.4 eV is ascribed to carboxylic-C,

while the fingerprint near 289.3eV features the characteristics of O/N-alkyl-C (Myneni, 2002;

Kinyangi et al., 2006a; Zhou et al., 2008). Carboxylic-C can serve as both labile and recalcitrant

form of C in soils due to its zwitterion nature. The labile portion of carboxylic-C such as water

soluble proteins, peptides and FAAs are rapidly cycled with a short turnover time; the

amphoteric part, however, tend to form highly recalcitrant complex such as polyphenol-protein,

lignin-protein complex, allowing a long residence time in soils. O/N-alkyl-C was a labile form of

soil organic C, represented by polysaccharides which constitute the cell walls of microbes and

higher plants and serves as energy substances (Lehmann et al., 2009). Since the peaks of two σ*

transitions are very broad and overlap, only the six 1s-π* resonances were involved in

subsequent data analysis.

133

Figure 5. 1. C K-edge NEXAFS spectrum deconvolution showing the six main 1s-π* transition

and two σ* transitions and the arctangent step function (290 eV) from a deciduous forest soil

from Missouri.

A series of normalized C K-edge NEXAFS spectra, exampled by three sites, revealed

changes of contents of typical organic C species with horizon and land cover (Figure 5.2). In the

grassland/herbaceous site, larger carboxylic (at 288.4 eV) content was found in C horizon than in

A horizon, possibly due to an strong oxidation of plant materials (lignin,, tannins or flavoids) in

C horizon (Jokic et al., 2003). The other functionalities bear similar content in both horizons. In

the shrub site, aromatic-C and O/N-alkyl-C functionalities (at 284.4, 285.2 and 289.3 eV) were

more pronounced in subsoil than in surface soil. No substantial differences in the content of each

functional species were observed in the mixed forest site. The surface soil spectra for the mixed

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

280 282 284 286 288 290 292 294

No

rmalz

ied Inte

nsity

Photon Energy (eV)

284.4

285.2

286.6

287.6

288.5

289.3

290.4291.6

134

forest site indicated an increase in the aromatic-C moiety compared with other two sites, and the

spectra for shrub site featured the most prominent carboxylic-C form than others. In subsoil, on

the other hand, shrub site contained the largest amount of aromatic-C group, followed by mixed

forest site and then grassland/herbaceous site. The content of carboxylic-C functionality was

largest in shrub soil, moderate in grassland/herbaceous site, and least in mixed forest site. The

O/N-alkyl-C group was prominent in the shrub subsoil and remained no substantial change in

other soils. The phenolic-C resonance was less developed in all the spectra. The aliphatic-C

feature appeared majorly as shoulder in most of the spectra and was more or less similar in

abundance except in shrub subsoil which showed the highest amount among the three sites.

Figure 5. 2. Carbon K-edge NEXAFS of A-horizon (A) and C-horizon (C) soil samples from a

mixed forest site (California), a shrubland site (New Mexico), and a grassland/herbaceous site

(Oklahoma).

Photon Energy (eV)

280 285 290 295 300 305 310

Norm

aliz

ed inte

nsity

0

1

2

3

4

5

6

7

Grassland/herbaceous C

Grassland/herbaceous A

Shrubland C

Shrubland A

Mixed forest C

Mixed forest A

135

The normalized spectra indicated the subsoil SOC storage is not ignorable. The deep

SOC majorly originates from root litter (Rumpel et al., 2002). Root litter inputs and quality could

impact the content and composition of subsoil organic C (Rumpel et al., 2002). Deep SOC was

dominated with low quality C (e.g., high lignin concentration, high C-to-N ratio) (Bosatta and

Agren, 1999) and are majorly mineral associated (Diochon and Kellman, 2008). The clay content,

shoot/root allocations and root biomass could possibly influence the subsoil organic C storage

(Burke et al., 1989; Bird et al., 2003; Rasse et al., 2005). So far, studies documenting on deep

soil organic C dynamics were scant. Studies on soil SOC dynamics at low soil profile therefore

need more attention.

5.4.2. Soil organic C speciation and relative composition in A and C horizons

The curve fitting results revealed the SOC was dominated by carboxylic-C, representing

on average 38% of the total SOC identified by C K-edge NEXAFS spectroscopy. Moderate

proportions of aliphatic-C (~ 22%), aromatic-C (~ 18%) and O/N-alkyl-C (~ 16%) and least

proportion of phenolic-C (< 6%) moieties were characterized. These results were partially in line

with the C K-edge NEXAFS results presented by Solomon et al. (2005), where on average

values of 36.5%, 23.8%,14.6%, 14.1%, and 11% were reported for carboxylic-C, O-alkyl-C,

phenolic-C, aromatic-C, and aliphatic-C groups, respectively, in humic substances from the clay

fractions of natural forest, tea plantation and cultivation soils.

As an aid to illustrate the variations of SOC species in both horizons revealed by surface

SOC condition, samples were divided into four groups according to the A-horizon soil total SOC

content (wt. %) (Figure 5.3). In both A and C horizons, no consistent changes of proportions of

each functional group were observed with total SOC gradient. It is found that the proportions of

aliphatic-C, carboxylic-C and O/N-alkyl-C groups were similar in A- and C-horizon soils. The

136

overall uniform composition of SOC in surface soil and subsoil irrespective of surface soil

surface organic C input was in accordance with the results presented by Mahieu et al. (1999),

who, by summarizing the 13

C NMR data from the published literature and their own results on

311 soil samples, found a remarkable similarity in the structure make-up of SOC despite a wide

range of land use, climate or cropping practices. The composition of SOC didn’t change

markedly with depth, in agreement with the previous findings (Dick et al., 2005; Fontaine et al.,

2007). The composition of SOC was determined by the composition of the plant remains and the

decomposition rate of these resources (Swift et al., 1979). The relative uniform composition of

SOC could be due to the fact that the composition of plant residues is approximately similar in

all systems worldwide (Mahieu et al., 1999) and the decomposition pattern could be similar with

rates being altered by temperature and moisture (Jenkinson and Ayanaba, 1977). Soil mineralogy,

physical or chemical properties could have small modifications on the chemical structure of SOC.

It is possibly that SOM maintains the abundance of the major chemical elements at homeostatic

values. Compared to the fairly uniform composition of bulk SOC, a large variability in the

composition of SOC were evidenced between soil size fractions (Mahieu et al., 1999; Solomon et

al., 2005). In addition, anthropogenic perturbations (Solomon et al., 2002; Solomon et al., 2007),

local environmental conditions (Hannam et al., 2004), and temperature (Fissore et al., 2008)

could more or less alter the chemical composition of SOC. The results investigated in this study

showed, on average, an overall uniform chemical composition. Some fluctuations of certain

functional groups, however, were noticed with SOC content.

In A horizon, the proportions of phenolic-C was low (~ 3 %) in response to moderate

amount of surface SOC and high (~ 7.5 %) corresponding to the lowest and highest SOC content.

In C horizon, a different trend was observed with the highest proportion (~7.5 %) appearing in

137

the presence of moderate surface organic C content (1-2 %) and constant proportions (~ 5 %)

elsewhere. Similarly, the aromatic-C moiety tended to accumulate in A horizon but decreased in

C horizon with increasing surface SOC content (from 1% to > 3). The phenolic-C content may

have positive relationship with the surface SOC content (Martens et al., 2004). An increasing

proportion of phenolic-C and aromatic-C with soil depth had been observed (Dick et al., 2005) in

Ferralsols soils with changing mineralogical characteristics along depth. These results suggested

surface SOC has no major effect on the overall chemical structure of SOC while local pedogenic

environment or climatic conditions, to name a few, could make some patchy modifications.

Figure 5. 3. The relative contents (in % of total organic C) of soil organic C species along an A-

horizon soil organic C (wt. %) gradient.

5.4.3. Soil organic C speciation and relative composition variations along temperature and

precipitation gradients of continental United States

Organic C species

Rela

tive t

o t

ota

l o

rgan

ic C

(%

)

0

10

20

30

40

50

60

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

<1% OC1-2% OC2-3% OC>3% OC

A-horizon C-horizon

<1% OC1-2% OC2-3% OC>3% OC

138


horizon soils along the W-E mean annual precipitation transect. The box plots show the median

(the line in the box), 5th/95th percentile (lower and upper bars), and outliers (black dots).


horizon soils along the N-S mean annual temperature transect. The box plots show the median

(the line in the box) and 5th/95th percentile (lower and upper bars).

R

ela

tive t

o t

ota

l o

rgan

ic C

(%

)

0

10

20

30

40

50

60

70

40-60

20-40

4 - 20

40-60

* MAP (in)

§

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Organic C species

A-horizon C-horizon

Rela

tive t

o t

ota

l o

rgan

ic C

(%

)

0

10

20

30

40

50

60

70A-horizon

35-50

50-55

55-60

C-horizon* MAT (o

F)

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Organic C species

139

The effects of environmental factors on soil organic C speciation were illustrated in

Figure 5.4 and 5.5. In both the A- and C-horizon soils along the W-E precipitation transect, there

was no consistent change of the relative percentages of each organic C species with precipitation,

suggesting the minimum effect of precipitation on chemical alteration of SOC. Precipitation

induced vegetation change could affect the composition (Quideau et al., 2001). The high rainfall

(40 - 60 in) west coast, on average, contained the highest phenolic-C, and the sites with moderate

precipitation (20 - 40 in) the least of all in both A and C horizons. The high phenolic-C in west

coast was possibly associated with the high lignin content in woody forest which was the major

vegetation cover in the moist west coast.

In A-horizon soils along the N-S temperature transect, there was a generally decreasing

relative proportion of aromatic-C with increasing MAT and an opposite trend for phenolic-C

moiety. The aliphatic-C, carboxylic-C and O/N-alkyl-C moieties exhibited no obvious changes

with temperature change. In C horizon, however, no consistent trend was observed. The

composition of each functional group was relatively uniform in the C-horizon soil. These results

suggested temperature has more impact than precipitation on dynamics of surface soil organic C

speciation. It was also noted the variability of the composition of SOC along the precipitation

gradient was more pronounced than that along the temperature gradient possibly because of the

larger sample size along the precipitation transect.

It is assumed that MAT influences SOC dynamics via its controls on the litter

decomposition rate, litter production, and stabilization of the decomposed products (Dalias et al.,

2001; Thornley and Cannell, 2001; Raich et al., 2006; Conant et al., 2011). The faster rates of

litter decomposition than production result in a reduced C accumulation at soil surface (Raich et

al., 2006). During this process, increasing temperature stimulates microbial activity, resulting in

140

the rapid utilization of liable SOC and ensuing higher accumulation of stable compounds such as

the macromolecules formed by polymerization and condensation (Fissore et al., 2008). The

increasing recalcitrant phenolic-C form with MAT in our study partially agrees with the results

by Fissore et al. (2008) who found a decreased SOC quality (high decay-resistant compounds)

with MAT by conducting a laboratory incubation study on forest soils from a temperature

gradient. The relatively constant composition of the labile fractions along the temperature

gradient in the current study, on the other hand, was different from results by Dalias et al. (2001)

who found a rapid exhaustion of the liable fractions of the decomposition materials at higher

incubation temperatures. This can be explained by the fact that these dissolved organic matter

was sorbed directly to mineral surfaces during their translocation (Kaiser and Guggenberger,

2000; Kaiser and Zech, 2000) or they could be resynthesized into more recalcitrant polymers by

polymerization reactions (Bremner, 1967). The discrepancy suggested the need of long term and

in situ experiments to further illustrate the environmental effect on SOC quality. Another

explanation for the temperature effect could be associated with the enhanced transfers of organic

C from unprotected to stabilized pools at warmer sites (Dalias et al., 2001; Thornley and Cannell,

2001). Lignin-derived compounds can incorporate N to form condensation products. Physical

protection of such molecules from enzymes was also important for stabilization. In this study, it

is assumed the physical-chemical reactions which facilitate phenolic-C stabilization may be

enhanced by warming. A relatively inert response of chemical composition of SOC to

temperature in C horizon than A horizon suggested that temperature facilitated decomposition

rate of SOC could diminish with soil depth (VanDam et al., 1997; Jobbagy and Jackson, 2000)

possibly because the stabilized SOC in subsoil was unable to provide enough energy to sustain

microbial activity (Fontaine et al., 2007).

141

5.4.4. Soil organic C speciation and relative composition variations among different

vegetation covers

Figure 5.6 revealed the relatively larger variability of aromatic-C and phenolic-C, similar

to what was observed in Figure 5.3.The proportions of aromatic-C in A-horizon and C-horizon

soil were lower in shrub and evergreen forest soils than that in grass and pasture soils. The

proportion of phenolic-C moiety generally followed opposite order with that of aromatic-C group.

The ratios of the content of phenolic-C in A horizon over C horizon were greater for grass and

pasture sites than for shrub and evergreen sites which were consistent with horizontal ratios of

total SOC content among these sites. The aromatic-C ratio of A-horizon over C-horizon soils

also varied among the four vegetation sites.

The depth distribution of other three species was rather similar among four vegetation

sites (Figure 5.7). The results suggested a potential effect of vegetation types in the larger

variability of aromatic-C and phenolic-C depth distribution. Grass and pasture sites had higher

ratios of total SOC in A- to that in C-horizon soils compared with shrub and evergreen site

(Figure 5.7), in accordance with the low root biomass and shallow root depth of grass and

pasture as compared with forest and shrub (Jackson et al., 1996). These results suggested that

vegetation types serve as potential modifiers in the chemical alteration of SOC, along with litter

quality, shoot/root ratio and root distribution (Jackson et al., 1996; Jobbagy and Jackson, 2000).

Vegetation was reported as a major factor controlling SOM composition in California mountain

soils (Quideau et al., 2001).

142

Figure 5. 6. The relative contents (in % of total organic C) of soil organic C species in A- and C

horizon soils with different vegetation cover.

Figure 5. 7. Weight ratios of (left) (in wt %) of soil organic C species in A- horizon to that in C-

horizon soils with different vegetation cover and (right) ratios of total soil organic C content

(wt %) in A-horizon soil to that in C-horizon soil.

Organic C species

Rela

tive t

o t

ota

l o

rgan

ic C

(%

)

0

10

20

30

40

50

60A

rom

atic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

Aro

matic-C

Phenolic-C

Aliphatic-C

Carb

oxyl

ic-C

O/N

-alk

yl-C

ShurbEvergreenGrassPasture

A-horizon C-horizon

Organic C species

A-h

ori

zo

n/C

-ho

rizo

n

0

5

10

15

Aro

mat

ic-C

Phen

olic-C

Alip

hatic

-C

Car

boxylic

-C

O/N

-alk

yl-C

Land cover

Shru

b

Eve

rgre

en

Gra

ss

Pas

ture

CA

-ho

rizo

n/C

C-h

ori

zo

n

0

2

4

6

8ShurbEvergreenGrassPasture

143

Plants residues are the primary source of SOC (Kögel-Knabner, 2002).The surface SOM

in these sites was thus mainly from the responding plant residues related to the chemical

structure of plant cell walls (Martens et al., 2004). Lignin and tannins are abundant constitutes of

plant and are important source of refractory materials in soils (Kögel-Knabner, 2002). Soil

phenolic-C and quinone-C could be mostly of lignin derived (Lorenz and Lal, 2005; Solomon et

al., 2005). The source of SOM at different decomposition status could influence the phenolic-C

and aromatic-C content. The relatively higher proportions of phenolic-C in both A and C

horizons in shrub and evergreen sites could be associated with the high lignin content in woody

plant remains. The higher composition of aromatic-C in grass and pasture sites suggested a

higher degree of decomposition (Kögel-Knabner et al., 1988; Kleber and Johnson, 2010) or the

contribution of black C (Rodionov et al., 2010) or due to the lower proportions of phenolic-C. In

general, forest litter contains higher lignin due to woody tissues than herbaceous materials, and

roots higher than leaves (Wang et al., 2004). High refractory contents such as lignin and tannins

of plant roots compared to shoots, woody structure to herbaceous materials, probably lead to the

lower decomposition rate of woody materials and roots. Plant root/shoot allocations are probably

the major determinants of the relative distribution of SOC with depth (Jobbagy and Jackson,

2000). Vegetation types differing in their vertical root distribution therefore would imprint the

depth distribution of SOC. The average rooting depth follows the order as shrub > forest > grass

(Canadell et al., 1996).The depth to which 95% root biomass occurs is the lowest for grasses,

highest for shrubs, and intermediate for forest (Jackson et al., 1996; Jackson et al., 1997). Root

litter and rhizodeposition account for a substantial deep SOC input (Fernandes et al., 1997). The

large SOC storage can transfer C into subsoil horizons of on average several meters (Canadell et

al., 1996). Shrublands and forests, for example, have more SOC storage in the second to third

144

meters than grassland until 1-m depth (Lorenz and Lal, 2005).The higher ratios of SOC in A

horizon than that in C horizon for grass and pasture sites as compared with shrub and forest sites

were expected in this results (Figure 5.7). The data suggested the relative abundance of phenolic-

C may be the best indicator of the effect of vegetation on the composition of SOC.

5.5. Conclusions

The C K-edge NEXAFS results indicated carboxylic-C (38 %) moiety was the dominant

form of SOC followed by moderate proportions of aliphatic-C (~ 22 %), aromatic-C (~ 18 %)

and O/N-alkyl-C (~ 16 %) and minor proportion of phenolic-C (< 6 %) moieties. Of all the C

species, aromatic-C and phenolic-C were greatly affected by climatic factors. Temperature was

shown to have more effect than precipitation in chemical alteration of surface SOC, possibly by

way of affecting decomposition rates and adsorption of organic C species. Vegetation can be

another factor controlling SOM composition due to their differences in litter quality, shoot/root

allocations and root depth distribution. Phenolic-C may be a good indicator of the effect of

temperature or vegetation on the composition of SOC.


We would like to thank the technical staff at the UW-Madison Synchrotron Radiation

Center for their technical support. We thank the financial support of USDA-AFRI (award #2012-

67019-30227).

145

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6. Polarization Dependent X-ray Photoemission Electron

Microscopic and Near Edge X-ray Fine Structure

Spectroscopic Investigation of Hexa-glycine Surface

Orientation Sorbed on Montmorillonite

K. Xiaa*, L. Ma

a, J. Wang

b, and M. A. Williams

c



bCanadian Light Source Inc., Saskatoon, Canada SK S7N 2V3

cDepartment of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, VA

24061, USA

*Corresponding author. Email address: [email protected]

156

6.1. Abstract

Proteins and peptides constitute a substantial part of soil organic N pools. The

interactions of proteins and peptides with minerals have strong effect on their reactivity,

availability and stability. Previous investigations on protein/peptide-mineral interactions,

however, have been largely limited to macroscopic scale batch equilibrium experiments. There is

limited understanding of their interactions on mineral surfaces at molecular levels. The

molecular level surface orientation of hexa-glycine, selected as a model peptide compound,

sorbed on montmorillonite was investigated using X-ray Photo Emission Electron Microscopy

and polarization dependent Near Edge X-ray Fine Structure Spectroscopy. The results suggested

that hexa-glycine sorbed on montmorillonite surfaces at an average angle of about 40° relative to

surface. The techniques enable us gain further insights into the interpretation of adsorption

behaviors of peptides/proteins.

157

6.2. Introduction

Proteins and peptides, constituting up to half of the soil organic N pool, play a vital role

in the terrestrial N cycling (Sowden et al., 1977; Senwo and Tabatabai, 1998; Friedel and

Scheller, 2002). Their stabilization and turnover have become an important topic of research. It

has been reported that sorption of proteins and peptides on mineral surface affect its stabilization

against biodegradation (Sollins et al., 1996; Mikutta et al., 2006). Studies on the interactions

between proteinaceous compounds and minerals thus benefit our understanding of N cycle in

soils.

Amino acids, especially the basic amino acids, were reported to be adsorbed strongly to

clay minerals due to their positive charge (Lipson and Nasholm, 2001; Vieublé Gonod et al.,

2006; Kitadai et al., 2009). The amphipathic proteins and peptides tend to bind to mineral

surfaces by conformation change to maximize entropy due to the polar and apolar side chains

and their ability to develop positive and negative charge (Kleber et al., 2007; Rillig et al., 2007).

The mechanisms of the protein/peptides and mineral interactions were illustrated by the “onion”

zonal model and “bilayer” layering model, which both emphasize that the amphiphiles serve as a

reactive chemical coatings on mineral surface for coupling and cross linking of other C-rich

organic matter (Wershaw et al., 1996; Kleber et al., 2007). However, there have been limited

molecular level spectroscopic observations of behaviors of these proteinaceous substances

sorbed on soil mineral surface.

Although plenty of studies have been conducted on the sorption characteristics of

proteins or peptides on minerals, most of them were limited to observations at the macroscopic

scale based on batch equilibrium experiments (Greenland et al., 1962; Dashman and Stotzky,

1982, 1984; Kalra et al., 2003). There is paucity of information on molecular-level adsorption

http://dict.youdao.com/w/amphipathic/

158

behaviors, especially regarding the surface organization (molecular orientation, spatial

distribution, packing density, etc.) which may affect the reactivity, stability, and bioavailability

of the adsorbed molecules. Recent spectroscopic investigation of amino acids surface speciation

suggested that amino acids of different speciation states attach to the material surface with a

variety of spatial arrangements. For example, a study by Sverjensky et al. (2008) suggested at pH

3-5 and low (1× 10-5

M ) and intermediate (1× 10-4

M) concentrations, glutamate adsorbed “lying

down” on oxide surface as a divalent anion. While at high concentrations, glutamate adsorbed

“standing up” by the γ-carboxylate end only with the α-carboxylate and amine groups pointing

away from the surface. Similarly, Kitadai et al. (2009) suggested that lysine sorbed vertically on

the montmorillonite surface through the protonated side-chain amino group. The adsorbed lysine

was present mainly as cationic state over the whole pH range 4.9 - 9.7. However, it is not known

whether this surface organization applied to proteins or peptides sorbed on soil minerals.

So far, investigations of the interactions between proteins/peptides and the minerals

suggested that factors such as pH, composition of inorganic cations and anions, mineral surface

properties, and chemical structure and molecular weight of the adsorbate which affect

protein/peptide adsorption capacity may influence their surface organization (Greenland et al.,

1962; Dashman and Stotzky, 1984; Jones and Hodge, 1999; Kalra et al., 2003; Pradier et al.,

2007; Rocha et al., 2007). The recently developed powerful synchrotron based techniques enable

us to investigate the sorption behavior at molecular scale. Synchrotron based polarization

dependent near edge X-ray adsorption fine structure (NEXAFS) spectroscopy has been used to

assess the orientation of amino acids, peptides, proteins or other organic substance sorbed on

gold, silver, TiO2, silicon substrate (Peters et al., 2002; Petoral and Uvdal, 2003; Liu et al., 2006;

159

Iucci et al., 2008; Battocchio et al., 2010). Little NEXAFS work has been performed on surface

orientation investigation of peptides/proteins assembled on soil clay minerals.

Numerous studies on interactions between peptides and surfaces of biomedical materials

have shown that peptides can be self-assembled on the surfaces of metal oxides and semi-

conduct substrates (Au, Si, TiO2, etc.) to form ordered extended monolayers with the peptide

chains in ß-sheet conformation (Polzonetti et al., 2006). Non-covalent interactions such as

hydrogen bonding, hydrophilic/hydrophobic forces or electrostatic forces are the driving forces

for peptides self-assemblance on the surfaces of biomedical related materials (Filiberto et al.,

2011). The tilt angle between the peptide backbone and the surface normal can be investigated

by polarization dependent NEXAFS, which has been successfully used to investigate the

molecular orientation of 16-unit peptides EAK16 on TiO2 (Polzonetti et al., 2006; Iucci et al.,

2007).

Synchrotron based X-ray is highly polarized. Rotating the sample changes the incidence

angle of synchrotron X-ray and the ensuing angle (θE) of the electric field vector E with respect

to the surface normal (Figure 6.5). The C and N atoms in peptides exhibit simple s-to-p

transitions, which are dipole-allowed if the electric field vector E of the incident X-rays and the

transition dipole moment are parallel with each other. The transition intensity maximizes when

the electric field vector E lies along the direction of the final state molecular orbital and vanishes

when E is normal to it (Hahner, 2006). Therefore, the intensities of the transition depend on the

orientation of the electric field vector E relative to the orientation of the molecule (Hahner, 2006).

By changing the angle of the incidence light, the tilt angle of the molecules can be determined.

For a peptide, amino acids are linked by peptides bond. The peptide bond electrons are

delocalized across the entire peptide bond, so the double-bound character is extended to both the

160

carbon-oxygen and the carbon-nitrogen bonds (Liu et al., 2006). As described in Figure 2.3 the

shared π* orbital limits the free rotation of peptide C-N, so the six atoms surrounding a peptide

group are coplanar. The π* orbital (p orbital) is oriented perpendicular to the peptide plane.

The N (1s) NEXAFS spectra exhibit a strong θ dependence for the peak of π* peptide

bond (401.5 eV). By collecting two NEXAFS spectra, one at normal incident X-ray angle and

the other at a different incident X-ray angle, the tilt angle of a molecule bound to the surface can

be calculated by using equation 2.1 below (Stöhr, 1992; Liu et al., 2007),

𝐈(𝛉𝟐)

𝐈(𝛉𝟏) = 1 + p[

𝟐

𝐬𝐢𝐧𝟐 𝛂− 𝟑] [𝐬𝐢𝐧𝟐𝛉𝟐 − 𝐬𝐢𝐧𝟐𝛉𝟏]

where θ2 and θ1 are the angles of incidence from the surface normal taken at grazing and normal

incidence respectively, α is the tilt angle of p-orbital of peptide bond from surface normal, and P

is the degree of polarization of the X-rays. A value 0.95 was assigned to P for threefold or higher

symmetry substrates. The tilt angle between the π* vector orbital of the C=O bond and the

normal to the surface which equal the angle between the molecular main chain with mineral

surface can be calculated from the intensity (area) ratio of Iθ2/Iθ1, determined for the selected

resonance by peak fitting. In the present study, peptide, hexa-glycine, was selected as a model

peptide compound to assess the feasibility of using polarized NEXAFS to investigate surface

orientation of peptides sorbed on montmorillonite, a common 2:1 clay minerals in soils.


6.3.1 Chemicals and materials

Hexa-glycine (Gly-Gly-Gly-Gly-Gly-Gly) (MW: 360.3232 g/mol) was supplied by

Sigma. The 2-D structure of Hexa-glycine was shown in Figure 6.5 a. Methanol (HPLC grade)

and chloroform (>99.9%) was purchased from Fisher and Fluka (New Jersey, USA) respectively.

Na-montmorillonite (SWy-2, Crook County, Wyoming) was obtained from the Source Clays

161

Repository of the Clay Minerals Society (Purdue University, West Lafayette, IN). The cation

exchange capacity and theoretical external surface area of SWy-2 provided by the Clay Minerals

Society were 76.4 cmolc/kg and 31.82 ± 0.22 m2/g, respectively. The octadecylammonium

chloride (ODAH+Cl

-) was purchased from Alfa Aesar (Ward Hill, MA, USA). Silicon (100)

wafer was purchased from SPI Supplies (West Chester, PA).

6.3.2. Preparation of monolayer montmorillonite

Monolayer montmorillonite was prepared on pretreated 2 cm × 2 cm Si wafers using the

Langmuir-Blodgett (LB) trough technique (Takahashi et al., 2003). The Si wafers were

pretreated by immersion in a mixed solution of 30% hydrogen peroxide and 25% ammonium

hydroxide (1:1 v/v) at 80 °C for 2 h. After the pretreatment, the Si wafers were thoroughly rinsed

with ultra-pure water according to Takahashi et al. (2003). The hydrophilicity is associated with

the formation of OH groups on the surface(Grundner and Jacob, 1986). To prepare the

monolayer montmorillonite sorbed on the Si wafer, 3 to 4 mg montmorillonite was dispersed in 2

L ultrapure water and then poured into a LB trough reservoir (KSV Instrument; Connecticut,

USA). Surfactant (ODAH+Cl

-) dissolved in chloroform and methanol mixture (10:1, v/v) at a

concentration of 1.68 ×10-4

mol L-1

, used as spreading solution, was slowly drop-spread onto the

surface of the aqueous phase containing dispersed montmorillonite until a monolayer film was

formed on the surface when the surface tension reached to ~7mN/m. The system was left

undisturbed for about 90 minutes to allow chloroform to evaporate. After chloroform

evaporation, Si wafers vertically clamped side by side on a plate were mechanically dipped

slowly into the aqueous solution in the LB trough reservoir. The monolayer film on the surface

of the aqueous phase was then compressed from both ends of the aqueous surface at a rate of

10cm2/min until the surface tension reached to 15mN/m. The Si wafers were mechanically lifted

162

out of the aqueous phase in the LB trough reservoir at a rate of 1mm/min. At this point,

monolayer montmorillonite was sandwiched between the Si wafer and the monolayer surfactant

(Fig 6.1). The monolayer surfactant was then removed by soaking the montmorillonite coated Si

wafers in MeOH for 20 h followed by washing with ultrapure water, and then air drying. Figure

6.2 showed the surface topography and height of monolayer montmorillonite determined by a

Nanoscope III Atomic Force Microscopy (AFM) apparatus by using tapping mode in the

scanning range of 5 × 5µm.

Appropriate amount of hexa-glycine to achieve monolayer surface coverage on

montmorillonite surface was dissolved in aqueous solution at pH 6, incubated for 12 h with the

prepared monolayer montmorillonite sorbed on the Si wafer, then rinsed with ultra-pure water to

remove excess hexa-glycine (Figure 6.1). The freshly prepared hexa-glycine-montmorillonite

was air dried and immediately analyzed using the polarization-dependent NEXAFS spectroscopy.

163

Figure 6. 1. Schematic diagram of (a) monolayer montmorillonite preparation using the LB

trough technique and (b) procedure for preparation of monolayer hexa-glycine on

montmorillonite surface.

Figure 6. 2. AFM image (5µm × 5µm)(left) of montmorillonite-coated Si water. The cross-

section profile (lower right) was determined along the line in the zoomed image (upper

right).The height differences (1.43 nm) indicates the thickness of the montmorilonite sheet.

aqueous

phase

air

Si wafer

surfactant

aqueous

phase

air

montmorillonite

sheet

monolayer

surfactant

aqueous

phase

air

montmorillonite

sheet

Cl-surfactant: octadecylammonium chloride

LB-trough preparation of monolayer montmorillonite on Si wafer

Immerse in MeOH (20h)

React with hexa-glycine at pH=6 (12h)

mono-layer hexa-glycine

Sorption of monolyer hexa-glycine on montmorillonite surface

a

b

1.43nm

164

6.3.3. Polarization-dependent N K-edge NEXAFS

All samples were previewed under the optical microscope in order to choose

representative areas before loading in the X-ray Photo Emission Electron Microscope (X-PEEM)

microscope. The Polarization-dependent NEXAFS spectra were collected in total electron yield

mode at the beamline 10ID-1 (SM) with the X-PEEM endstation and an elliptically polarized

undulator (EPU) at the Canadian Light Source (CLS) located at the University of Saskatchewan,

Saskatoon, Canada. X-ray photon energy at N K-edges was calibrated using the gas phase

NEXAFS of N2 (1s→ π* at 400.87eV). The N K-edge stacks and Al K-edge stacks were scanned

from 395 to 420eV and 1570 to1610 eV, respectively, with an energy step of 0.1 to 0.2 eV

around the NEXAFS peaks and of 0.4 to 1.0 eV in the pre-edge and continuum. The Al K-edge

was scanned first to locate its position and make a stack in order to locate the position of

montmorillonite sorbed on the Si Wafer. The stack scan size was defined to include region of

interest (I) and blank region (I0) where there was no sorbed montmorillonite. The silicon wafer

pretreated with HF under vacuum was prepared as blank. The N (1s) spectrum were collected at

normal (0° of X-rays with surface normal, E-vector in surface plane) and grazing (74° of X-rays

with surface normal, E-vector near surface normal) incidence angles of the polarized photon

beam. All the samples were cooled with liquid nitrogen during spectra collection in order to

alleviate radiation damage to the N-containing hexa-glycine.

6.3.4. Data processing

All the NEXAFS data and images are manipulated with IDL6.1 Virtual Version of

aXis2000 (Hitchcock Group, Canada). Aluminum is firstly located in the image and make a stack,

based on which, the spectra of N was retrieved. The spectra of N was firstly normalized though

division by the intensity of background (I0). Before curve fitting, the pre-edge was linear

165

background subtracted from the spectrum which was then normalized to a unity absorption jump

height of the N 1s absorption edge (from the pre-edge at 395eV to the post-edge at 420eV). The

normalized N 1s spectra at grazing and normal incidence were plotted in overlay format. The

angle of hexa-glycine relative to the surface normal of montmorillonite was calculated using

Equation 2.1.

6.4. Results and Discussion

The Al K-edge NEXAFS spectrum was recorded in order to locate the montmorillonite

sheet adsorbed on the Si wafer. Montmorillonite is a naturally occurring cation exchangeable

material that consists of two Si tetrahedral sheets sandwiching a Al octahedral sheet with the

total thickness of ca. 0.95 nm (Brown and Brindley, 1980). The negative charge occurs as a

result of isomorphous substitution of Al(Ⅲ) with Mg(Ⅱ) in the octahedral sheet or Si (Ⅳ)with

Al(Ⅲ) in the tetrahedral sheet. ODAH+ was immobilized on montmorillonite surface by

electrostatic forces (Moraru et al., 1981). Dispersed montmorillonite was strongly fixed on a

hydrophilic Si substrate possibly due to electrostatic forces between the negatively charged clay

layer and the protonated OH termini on Si substrate surface (Grundner and Jacob, 1986;

Takahashi et al., 2003). The AFM image showed a relatively uniform structure and parallel

orientation of the monolayer montmorillonite deposited on the Si substrate as demonstrated by

in-plane X-ray diffraction measurements of similar studies (Takahashi et al., 2002)(Figure 6.2).

The calculated thickness of monolayer montmorillonite was about 1.43 nm by AFM, larger than

the reported 0.95 nm, probably due to the solvated Na+ ions between clay layer and a Si wafer

(Takahashi et al., 2003). The PEEM image acquired at Al K-edge was shown in Fig 6.3(a). The

bright region in the image which indicated the presence of Al formed a contrast with Al free dark

area. The sharply bright dots could be the area with uneven surface. The Al covered region as

166

shown in the middle image of Figure 6.3(a) was selected. The Al spectral signatures were

resolved and revealed a distinctive adsorption band near 1575-1590 eV. Ildefonse et al. (1994)

ascribed these resonances to the results of the transitions of core electrons to the first empty

electronic bond state orbitals (1s-3p) and multiple scattering effect. The spectrum revealed two

main sharp resonances at 1579.4 and 1581.8 eV and a minor feature near 1586.8 eV. These

spectral features and energy positions were similar to the spectra collected from six-fold

coordinated Al in montmorillonite (Doyle et al., 1999).

The PEEM image recorded at N K-edge at grazing and normal incidence was shown the

same way as that of the Al K-edge (Figure 6.3.b and 6.3.c). The average N K-edge NEXAFS

spectra of montmorillonite region, defined by the Al K-edge image, was processed because the

focus of this study was those hexa-glycine self-assembled on the montmorillonite not on the Si

wafer. The N spectra after normalization, recorded at normal and grazing incidence, were

reported in Figure 6.4 to evidence the angular dependence behavior. The sharp peak around

401.6 eV was ascribed to transition of N 1s to π* of peptide C=O bond, and the broad bands near

~ 407 and ~ 412eV could be assigned to N 1s to σ* resonances. These peaks were in good

agreement with the reported glycine-based oligopeptides (Gordon et al., 2003; Cooper et al.,

2004; Zubavichus et al., 2004).

167

Figure 6. 3. (a) PEEM image recorded at the Al K-edge at a photon energy of 1579 eV before

(left) and after montmorillonite region (bright area) were selected (middle) and the Al 1s

NEXAFS spectrum of selected area (right); (b) PEEM image recorded at the N K-edge at a

photon energy of 411.2 eV before (left) and after bright area were selected (middle) and the N 1s

NEXAFS spectrum of selected area (right) at grazing incidence; (c) PEEM image recorded at the

N K-edge at the photon energy of 400.1 eV before (left) and after bright area were selected

(middle) and the N 1s NEXAFS spectrum of selected area (right) at normal incidence.

168

A strong polarization dependence effect was detectable, as evidenced by the differences

of the peptide peak height near 401.6 eV (Figure 6.4). The ratio of the peak intensities near 401.6

eV at normal and grazing incidence, acquired by peak curve fitting, was employed to calculate

the tilt angle between the p orbital of C=O bond and the surface normal according to formula 2.1.

Hexa-glycine was assumed to exhibit ß-sheet conformation after self-assembling from

aqueous solution according to the Fourier transform infrared spectroscopy (FTIR) investigation

on the backbone conformation of peptides EAK 16 assembled on TiO2 (Iucci et al., 2008). The

six atoms connect peptide bond are coplanar as shown in the shadow plane (Figure 6.5b). Two

adjacent planes are connected by α-C atoms. The peptide bonds of adjacent residues point in

opposite directions. The delocalization of the peptide bond electrons restricts the free movement

of the peptide bond. Two planes can be rotated freely around α-atoms. It was assumed the

assembled molecules form a well extended conformation with “head” attached to the mineral

surface and the “tail” extended to outmost surface, forming a zig-zag sideview (Figure 6.5.c).

Molecules interact with each other by H-bonding to form ß-sheet. The intensity of the NEXAFS

spectra is a combination of each individual peptide bond. Since p-orbital of the peptide bond is

normal to the shaded plane, the average vector of p-orbital should be perpendicular to the peptide

axis. The average peptide bond direction defines a molecular axis along the chain and the

effective peptide p-orbital was, on average, perpendicular to the backbone. So based on this

assumption, a simplified scheme of assembled peptides on montmorillonite and definitions of

angles used to characterize the molecular orientations were illustrated in Figure 6.5.d.

169

Figure 6. 4. N K-edge NEXAFS spectra of peptides adsorped onto monolayer montmorillonite

on Si substrate recorded at normal and grazing incidence.

The intensity difference of the peptide feature at grazing and normal incidence implied

the peptide molecules were averagely well-organized in the montmorillonite surface. The

intensity maximized when the electric vector is lined with the direction of the final orbital but

vanishes when the electric vector is orthogonal to the direction of the final orbital (Petoral and

Uvdal, 2003, 2005). The intensity of the peptide feature in our experiment was higher at grazing

than normal incidence (Figure 6.4). The average tilt angle (α) of the π* vector orbital with

respect to the surface normal was about 40° acquired by using Equation 2.1. That is the

molecules have a tilt angle of about 40° with mineral surface, similar to some of the reported

angles on biomedical materials (Battocchio et al., 2010).

N K-edge

Photon Energy (eV)

400 405 410 415

No

rma

lize

d In

ten

sit

y

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Grazing incidence

Normal incidence

170

Figure 6. 5. (a)Structural formula, (b) ß-sheet strand and (c) sideview of the sheet of self-

assembled Hexa-glycine; (d) Simplified scheme of assembled peptides on montmorillonite and

definitions of angles used to characterize the molecular orientations. All the angles were

calculated with respect to surface normal. Angle θ1 and θ2 represent the incidence angle at

normal and grazing incidence, and θ1E and θ2E are angles of electric vector with respect to

surface normal. While α is the angle between peptide p-orbital with surface normal, equal to the

tilt angle of peptide backbone with surface.

π*

α

αθ2

θ1

θ2E

θ1E

Surface normal

171

At the studied pH values (pH = 6), the most abundant species of hexa-glycine is the

zwitterionic form (Figure 6.6) and the surface of montmorillonite is negatively charged because

the point of zero charge of the montmorillonite ranged from 1 to 2.5 (Juang et al., 2002).

Previous studies on the adsorption of self-assembling peptides on biocompatible materials or

minerals suggested an electrostatic interaction between the carboxylic oxygen atoms of the

peptides and the positive charge site of the oxide substrate (Tzvetkov et al., 2004; Polzonetti et

al., 2008). Studies on the adsorption of glycine or lysine on montmorillonite indicated the

hydrogen bonding between the NH3+ group and the basal oxygen of the montmorillonite

interlayer surface (Kitadai et al., 2009; Ramos and Huertas, 2013). Hexa-glycine in this study

was most likely to interact via protonated amino-terminal end (NH3+) with monolayer

montmorillonite surface driven by electrostatic forces or hydrogen boding. In addition, at the

studied pH, the edge sites of montmorillonite should have a positive charge by protonation of Al

sites below pH ~7 (Rozalen et al., 2009). Hexa-glycine is thus in contact with the positively

charged edges through the –COO- group of the zwitterion form and the >AlOH2

1/2+ group of

montmorillonite. Taking account of all the above analysis, an adsorption model of the hexa-

glycine species was shown in Figure 6.7.

172

Figure 6. 6. Distribution different dissociation states of dissolved Hexa-glycine as a function of

pH, determined based on the published dissociation constants (pKa) of carboxylic acid (3.13)

and the ammonium ion acid (7.69) (Glasstone and Hammel, 1941).

Figure 6. 7. The proposed schematic diagrams of the orientation of the adsorbed hexa-glycine on

montmorillonite.

pH

2 4 6 8 10

Mole

Fra

ction

0.0

0.2

0.4

0.6

0.8

1.0Cationic

Zwitterionic Anionic

-Si – OHAl – OH2

1/2+

Si – OH

173

The polarization dependent NEXAFS results in this study indicate the monolayer

peptides adsorbed to montmorillonite are oriented in order on the surface. The investigation of

the tilting angle of self-assembled peptides with respect to different mineral surface, with

differences in pH, ionic strength, molecular weight, and side chain chemistry, would help fill the

gaps and resolve inconsistencies from the previous batch equilibrium experimental results. For

example, Greenland et al. (1962) found an increasing sorption of small peptides on layer silicates

with increasing molecular weight of the peptides; Dashman and Stotzky (1982, 1984), however,

found the chain length may not necessarily enhance the adsorption. Later studies on the

oligopeptides of glycine by Kalra et al. (2003) found similar results as Greenland et al. (1962).

Polarization dependent NEXAFS results suggest it was likely that smaller molecules tend to

form a “lying down” orientation with title angle close to zero, while large molecules or those

with longer chains or more side chains take a “standing up” orientation, with higher degree of

title angles, in order to maximize the surface coverage. The long chain molecules, with alternate

hydrophobic and hydrophilic groups and different kinds of side chains in particular, are more

likely to adopt a more upright orientation via forming well extended conformation. Molecules

with more ordered organization tend to be adsorbed more than those with disordered

arrangement. A better interpretation on the results of previous batch equilibrium experiments

will be drawn after our further investigation on these factors in the near future.

6.5. Conclusions

In summary, AFM, PEEM and NEXAFS were used in our study to investigate the

molecular orientations of Hexa-glycine self-assembled on monolayer montmorillonite sheets.

The AFM image proved that the LB trough technique is capable of preparing a single layer

hybrid film. Hexa-glycine interacts with montmorillonite surface via NH3+ group to form an

174

extended structure. Minor amount of hexa-glycine was adsorbed to the Al edge site at the

carboxylic end. Previous studies suggested the interaction was driven by electrostatic forces

between the positively charged NH3+ group and the negatively charged montmorillonite surface

or by hydrogen bonding between NH3+ group and the basal oxygen of montmorillonite.

Polarization dependent NEXAFS analysis revealed hexa-peptides tend to form an average tilt

angle of 40° between the molecular axis and the montmorillonite surface. The results

demonstrated polarized NEXAFS can be used to evaluate the surface orientation of oligopeptides

adsorbed on montmorillonite. However, more factors such as pH, mineral type, peptide chain

length need to be tested at the molecular scale to investigate their effect on the adsorption

behavior.


We would like to thank Dr. Alan Esker and his graduate students in Chemistry

Department of Virginia Tech for the technical assistance. We thank the financial support from

NSF (award # EAR 0949653 10010064).

175

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182

7. Conclusions

Proteins and peptides, as a regulator of overall N availability, play a central role in

terrestrial N cycling. Proteins and peptides, by interacting actively with minerals and

macromolecules in soil solution due to their amphoteric nature, are thus a critical pool for soil

organic matter (SOM) and an important form of stabilized organic C and N. Proteins and

peptides, in the soluble organic N (SON) pool, can be stabilized on mineral surface, immobilized

by microorganisms or consumed by plants, making contributions to the insoluble organic N

(ISON) pool and vice versa. There is a rapid flux of organic N between the two pools and its

availability to both plants and microorganisms. The conversion of organic N from stabilized

form to soluble form was regarded as the rate limiting step in terrestrial N cycling. This

dissertation, therefore, focused on the dynamics of organic N in soils especially extractable free

amino acids (FAAs) and hydrolysable amino acids (HAAs). To accomplish this, a series of

experiments were designed and various techniques were applied. High Performance Liquid

Chromatography (HPLC) was used to quantify both FAAs and HAAs. C and N K-edge near

edge X-ray absorption fine structure (NEXAFS) spectroscopy was employed to investigate the

oligopeptides orientation on mineral surface and SOC speciation.

In order to evaluate the amino acid level and composition variability, we investigated

hundreds of soil samples from North-South (N-S) and West-East (W-E) transects of continental

United States. These soils were a subset of samples collected from a total of 4871 sites (1

site/1600 km2) by the USGS from 2007 to 2010 for the USGS Geochemical Landscapes Project.

The soils feature different vegetation cover, C content, depth (surface and subsurface) and most

noticeably mean annual temperature (MAT) or mean annual precipitation (MAP) gradients.

183

We firstly assessed the FAA level in 298 soil samples (half from surface, half from

subsurface counterpart). The levels of FAAs in surface soil were turn out to be extremely higher

than in subsurface soils. Major FAAs identified were Glu, Gln, Asp, Leu, Ala, Thr, Gly and Val.

Though no overall big differences in composition of FAAs among vegetation cover as observed

by multiple comparisons, the composition in surface soil was distinguished from subsurface as

witnessed by NMS. The depth effect in FAA composition could be due to the fine root exudate

and turnover and the selective sorption between. It was also revealed the FAA composition was

highly correlated with MAT and MAP. Significant variations were observed for the levels of soil

FAAs along the MAT and MAP gradient, and among vegetation types, suggesting that

environmental factors might play an important role in affecting organic N dynamic and, therefore,

extractable amino acids.

FAAs, immediately bioavailable to plants and microorganisms, constitute a very small

fraction of soluble organic N pool. The HAAs, calculated as sum of acid cleaved amino acid

from proteins/peptides, are potentially bioavailable. The concentrations of HAAs are about 50

times higher than FAAs. When whole soil was hydrolyzed in hot acid, both water soluble

proteins/peptides and those bound to organo-mineral interface were released. Similar to FAAs,

HAAs existed in extreme high concentration in surface than in subsurface soils due to higher

organic matter accumulations on soil surface. The composition of HAAs was relatively more

uniform than FAAs and no high correlation were found between the HAA amino acid pattern

with environmental factors (MAT and MAP). Major HAAs were Asp, Ser, Glu, Gly, Thr, Ala,

Pro, Val, most of which are also abundant in FAA pool. The uniform composition of HAAs was

similar with the claimed Redfield ratios (references), i.e. the ratios of certain elements were

constant and similar in the organisms and their living environment. It was suggested the uniform

184

composition of amino acids may probably be due to the homeostatic effect of SOM which

maintain the environmental abundance of major elements during the transformation of plant and

microbial residue to degradation products to form SOM. The high correlations of MAT and

MAP with composition of FAAs instead of hydrolysable suggested amino acid FAA were more

subjective to environmental changes. The differences of composition between FAAs and HAAs

are possibly due to the contribution of microbial turnover, fine root exudate and turnover to the

FAA pool.

Although proteins and peptides constitute a substantial part of SOM, other forms of

organic N/C such as aromatics, phenols, polysaccharides, aliphatic and carboxylic compounds

have also been identified in large quantity dependent on soil types. Our C K-edge NEXAFS

spectra revealed the presence of largest proportion of carboxylic-C (38 %), moderate proportions

of aliphatic-C (~ 22 %), aromatic-C (~ 18 %) and O/N-alkyl-C (~ 16 %) and least proportion of

phenolic-C (< 6 %) moieties. The composition of SOC was relatively uniform among sites and

between two horizons irrespective of surface organic C content. Factors such as temperature and

vegetation cover were revealed in this study to account for the fluctuations of the proportions of

aromatic-C and phenolic-C species, in particular. This is somehow in accordance with the

relative even distribution of amino acids. The C K-edge NEXAFS spectra were acquired with

total electron yield (TEY) mode which only probes the surface soil up to 10nm, total

fluorescence yield (TFY) spectra which reflect deep soil (~100nm) features as well as N K-edge

NEXAFS spectra should be collected in future once we got more access to the more powerful

synchrotron tools.

As is stated in the introduction part, there is a flux of proteinaceous compounds between

SON and ISON pool by way of sorption and desorption. Previous studies on adsorption were

185

mostly based on batch equilibrium experiment in labs, seldom of them used spectroscopic

methods to investigate the adsorption behavior in molecular scales. The polarization dependent

NEXAFS combined with photoemission electron microscopy (PEEM) enabled us to explore the

interactions of small peptides with mineral surfaces at microscopic level, especially regarding the

molecular surface organization (molecular orientation, spatial distribution, packing density, etc).

Surface organization regulated the availability, stability and reactivity of the adsorbed molecules.

Using hexa glycine as model peptide compound, our research demonstrated that it tends to form

a “lying down” orientation with an average tilt angle of 40 ° with mineral surface. The “lying

down” organization enhances the interaction between the molecules and the mineral surface,

fosters the entropy gain, thus facilitates the molecular stability. The “lying down” orientation

may be attributed to the lower concentration of the peptides. As the increase of the concentration,

molecules could be “standing up” to maximize the coverage of the molecules sorbed, contrary to

“lying down” configuration. As observed by the batch equilibrium experiment, others factors all

could influence the adsorption behavior, such as the peptide side chain length, mineral types,

temperature, or peptide chain chemistry, which need to be interpreted at molecular scales. Since

the depolymeriztion of proteinaceous substances by extracellular enzymes into FAAs are the rate

limiting step in new N cycling paradigm, environmental factors which influence FAA

enrichment need to be evaluated in our future study.

186

Appendix

Appendix A. Geochemical data for samples of surface soils (A horizon) and subsoil (C horizon) collected in the conterminous United

States

Sampling

date Land Cover1 Land Cover2

Surface ("A") Subsurface ("C")

ID Stat

e

Transec

t

MAT

(°C)

MAP

(cm) Latitude Longitude Depth

(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)

15-Jul-10 Forested Upland Mixed Forest 0-26 2.6 70-80 0.5 9823 CA WE 13 119 39.073 -123.471


13-Jul-10 Planted/Cultivated Fallow 0-10 0.9 81-87 0.2 10591 CA WE 17 61 38.35028 -121.231

10-Jul-10 Herbaceous Upland Grassland/Herbaceous 0-20 3.3 80-100 0.4 5007 CA WE 8 125 38.182 -120.385

09-Jul-10 Forested Upland Evergreen Forest 0-26 5.7 80-103 1.1 1935 CA WE 15 107 38.278 -120.311





01-Jul-10 Shrubland Shrubland 0-21 0.9 38-43 0.7 207 CA WE 9 35 38.006 -119.154

27-Jul-08 Shrubland Shrubland 0-3 0.4 70-80 0.1 8079 NV WE 11 15 38.20693 -118.391




01-Aug-08 Shrubland Shrubland 0-5 1.3 60-65 0.4 10351 NV WE 10 18 38.4116 -116.44

03-Aug-08 Shrubland Shrubland 0-5 0.5 80-90 0.3 3183 NV WE 13 19 38.09385 -116.136



17-Jul-08 Shrubland Shrubland 0-5 0 80-90 0 11231 NV WE 9 29 38.18024 -114.949



24-Jun-08 Shrubland Shrubland 0-5 0.5 70-80 0.4 10975 UT WE 9 30 37.91777 -113.781

24-Jun-08 Shrubland Shrubland 0-5 0.7 100-116 0 303 UT WE 10 27 38.15714 -113.244

26-Jun-08 Shrubland Shrubland 0-10 5 60-70 0.7 10287 UT WE 9 29 37.84254 -112.539

187


States

Sampling



ID Stat

e

Transec

t

MAT

(°C)

MAP


(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)

26-Jun-08 Shrubland Shrubland 0-5 3 45-55 0.6 2095 UT WE 9 27 38.1999 -112.346



28-Jun-08 Forested Upland Evergreen Forest 0-5 0.2 100-120 0.4 8347 UT WE 9 22 37.92292 -111.234



02-Jul-08 Forested Upland Evergreen Forest 0-5 0.4 100-115 0.5 4507 UT WE 13 21 38.03381 -110.185

02-Jul-08 Forested Upland Mixed forest 0-16 4.8 110-130 0.4 3227 UT WE 10 30 37.76386 -109.771


01-Jul-08 Shrubland Shrubland 0-8 1.4 100-115 0.2 411 UT WE 12 24 37.78493 -109.308

01-Oct-08 Forested Upland Evergreen Forest 0-6 2.2 20-30 1.4 5675 CO WE 9 35 37.82026 -108.726

01-Oct-08 Shrubland Shrubland 0-5 1.4 5-13 1.5 9883 CO WE 7 48 37.65978 -108.4

01-Oct-08 Forested Upland Deciduous forest 0-10 8.8 28-36 4.5 10907 CO WE 7 48 37.74476 -108.148

10-Jun-08 Forested Upland Evergreen Forest 0-8 1.9 70-80 0.1 3291 CO WE 3 58 37.84253 -107.24

02-Oct-08 Forested Upland Mixed Forest 0-5 0.9 10-18 0.6 4571 CO WE 5 29 38.2135 -106.572

05-Jun-08 Shrubland Shrubland 0-12 0.4 45-65 0.2 475 CO WE 6 31 38.11813 -105.995

09-Jun-08 Forested Upland Evergreen Forest 0-6 3 30-35 0.7 5355 CO WE 6 33 38.05137 -105.537

09-Jun-08 Forested Upland Evergreen Forest 0-5 6 50-65 0.5 9451 CO WE 9 40 38.06527 -105.125

09-Jun-08 Herbaceous Upland Grassland/Herbaceous 0-7 0.9 100-115 0.5 6379 CO WE 10 36 38.10829 -104.665




21-Jun-08 Herbaceous Upland Grassland/Herbaceous 0-3 3 100-115 0.5 4779 CO WE 12 39 37.95591 -102.467


28-Apr-08 Planted/Cultivated Small Grains 0-12 1.2 90-100 0.3 5803 KS WE 12 43 38.00617 -101.754

28-Apr-08 Herbaceous Upland Grassland/Herbaceous 0-10 1.7 40-50 0.7 4523 KS WE 12 47 37.92534 -101.158

27-Apr-08 Planted/Cultivated Small Grains 0-10 1.9 90-100 0.6 10859 KS WE 12 51 37.93475 -100.573

(Continued)

188


States

Sampling



ID Stat

e

Transec

t

MAT

(°C)

MAP


(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)



27-Apr-08 Planted/Cultivated Pasture/Hay 0-11 1 70-80 0.6 12584 KS WE 12 53 37.88446 -100.044

26-Apr-08 Planted/Cultivated Row Crops 0-10 3.2 80-90 0.8 6872 KS WE 12 57 38.20009 -99.5269

26-Apr-08 Planted/Cultivated Small Grains 0-8 1 80-90 0.5 5848 KS WE 13 66 38.16625 -98.8945

26-Apr-08 Planted/Cultivated Row Crops 0-12 1 90-100 0.6 10280 KS WE 13 69 37.91554 -98.6917

25-Apr-08 Developed Low Intensity Residential 0-10 2.2 45-55 0.7 7384 KS WE 13 85 37.99772 -97.3322

24-Apr-08 Planted/Cultivated Pasture/Hay not recorded 2.9 90-100 1.7 12952 KS WE 13 85 38.04795 -96.8593

24-Apr-08 Planted/Cultivated Pasture/Hay 0-8 2.4 40-50 1.2 4760 KS WE 13 94 37.98804 -96.1589

22-Apr-08 Planted/Cultivated Pasture/Hay 0-6 3.5 55-65 0.6 664 KS WE 13 101 37.95192 -95.7368

22-Apr-08 Herbaceous Upland Grassland/Herbaceous 0-12 3.2 50-60 1 3736 KS WE 13 101 37.93123 -95.189

19-Jun-08 Herbaceous Upland Grassland/Herbaceous 0-30 1.1 60-70 0.8 1944 MO WE 13 106 38.11101 -94.5866

19-Jun-08 Planted/Cultivated Pasture/Hay 0-20 1.9 75-90 0.5 11656 MO WE 13 112 37.8354 -94.0932


20-Jun-08 Forested Upland Deciduous forest 0-5 3.3 30-40 0.7 648 MO WE 13 113 38.11709 -92.9008


20-Jun-08 Developed Low Intensity Residential 0-5 3.1 20-35 2.1 5256 MO WE 13 111 37.9503 -92.2735




11-Aug-10 Planted/Cultivated Row Crops 0-20 1.6 120-160 0.1 8200 IL WE 13.4 108 38.062 -90.0358

11-Aug-10 Planted/Cultivated Urban/Recreational Grasses 0-19 1.3 124-151 0.1 2804 IL WE 13.3 108 37.90189 -89.8154

12-Aug-10 Herbaceous Upland Grassland/Herbaceous 0-25 1.3 116-155 0.3 3828 IL WE 13 108 38.15436 -89.0082

13-Aug-10 Planted/Cultivated Pasture/Hay 0-18 2.4 122-158 0.2 7924 IL WE 13 111 38.11849 -88.4933

13-Aug-10 Planted/Cultivated Row Crops 0-20 1.9 119-150 0 12020 IL WE 13 113 38.18385 -88.3259

13-Aug-10 Planted/Cultivated Row Crops 0-18 1.4 117-150 0.2 5356 IL WE 13 115 38.21364 -88.1738

14-Jul-10 Planted/Cultivated Row Crops 0-17 1.2 85-109 0.1 9452 IN WE 13 118 38.06446 -87.8145

(Continued)

189


States

Sampling



ID Stat

e

Transec

t

MAT

(°C)

MAP


(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)

14-Jul-10 Herbaceous Upland Grassland/Herbaceous 0-19 1.3 19-29 1 12524 IN WE 13 120 38.06611 -87.4459

15-Jun-10 Planted/Cultivated Row Crops 0-5 2.4 105-120 0.3 4332 KY WE 13 122 37.88713 -86.8794

15-Jun-10 Planted/Cultivated Row Crops 0-25 1 100-120 0.1 6060 KY WE 13 120 37.98769 -86.3855

16-Jun-10 Forested Upland Deciduous forest 0-1 16.8 95-120 0.4 11180 KY WE 13 115 37.85822 -85.7503

16-Jun-10 Herbaceous Upland Grassland/Herbaceous 0-5 5.2 58-65 0.4 2988 KY WE 13 116 37.95921 -85.4513

15-Jun-10 Planted/Cultivated Pasture/Hay 0-9 3.1 85-95 0.3 5292 KY WE 13 116 38.02005 -85.1837



05-Jun-10 Forested Upland Mixed forest 0-12 1.1 50-60 0.3 1708 KY WE 12 119 37.87397 -83.6725

05-Jun-10 Forested Upland Deciduous forest 0-8 4.1 60-75 0.3 5804 KY WE 12 117 38.17695 -83.6147

06-Jun-10 Forested Upland Deciduous forest 0-13 4 110-130 4.5 4780 KY WE 12 113 37.93259 -82.6477

11-Sep-08 Forested Upland Deciduous forest 0-20 1.5 36-56 0.4 12972 WV WE 12 115 37.89719 -82.4245

11-Sep-08 Forested Upland Mixed forest 0-15 3.7 15-28 3.6 5596 WV WE 13 117 37.80871 -81.9172

12-Sep-08 Forested Upland Deciduous forest 5-36 1 99-119 0.2 12764 WV WE 13 115 38.08966 -81.6225

16-Sep-08 Forested Upland Deciduous forest 0-30 3.2 81-102 4.3 5852 WV WE 11 128 38.06657 -80.6321

27-May-10 Forested Upland Mixed forest 2-3 38.6 85-100 0.1 6876 VA WE 9 110 38.06033 -79.5412

27-May-10 Herbaceous Upland Grassland/Herbaceous 0-12 1.6 90-110 0.5 2780 VA WE 10 109 37.97994 -79.4946

28-May-10 Forested Upland Mixed forest 1-2 16.7 80-95 0.2 7324 VA WE 11 109 37.86616 -79.1468

31-May-10 Planted/Cultivated Pasture/Hay 0-18 1.6 80-100 0.1 3228 VA WE 10 104 38.18265 -79.0993

15-Nov-10 Forested Upland Deciduous forest 0-10 2.3 114-142 0.2 9372 VA WE 13 112 37.97075 -77.9308

05-Nov-10 Forested Upland Mixed forest 0-15 24.4 127-157 0.1 9916 VA WE 13 106 38.09006 -77.4293

04-Nov-10 Herbaceous Upland Grassland/Herbaceous 0-25 0.6 114-132 0 2748 VA WE 14 106 38.0045 -76.9432

04-Nov-10 Forested Upland Deciduous forest 0-5 1.7 132-152 0.1 1724 VA WE 15 112 37.79612 -76.4342

10-Jul-08 Planted/Cultivated Pasture/Hay 0-25 1.8 100-115 0 4852 MD WE 14 113 38.13279 -75.7937

04-Nov-10 Forested Upland Evergreen Forest 0-15 1.6 91-102 0.1 8948 VA WE 14 113 37.92581 -75.6325

19-Jun-10 Planted/Cultivated Row Crops 0-20 1.4 87-109 0.6 9556 TX NS 18 25 31.59578 -106.239

17-Apr-09 Herbaceous Upland Grassland/Herbaceous 0-40 0.9 40-70 0.4 11327 NM NS 12 46 33.51821 -105.512

(Continued)

190


States

Sampling



ID Stat

e

Transec

t

MAT

(°C)

MAP


(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)

17-Apr-09 Shrubland Shrubland 0-30 0.9 0-30 0.8 8687 NM NS 13 47.1 32.06299 -105.447

16-Apr-09 Shrubland Shrubland 0-10 2.9 0-10 2.9 4591 NM NS 10 57 32.88267 -105.152






13-Apr-09 Herbaceous Upland Grassland/Herbaceous 0-60 0.4 60-100 0.2 9535 NM NS 14 38 34.39302 -104.495


04-Apr-09 Shrubland Shrubland 0-10 1 10-50 0.6 3135 NM NS 14 40 35.1692 -104.244

04-Apr-09 Shrubland Shrubland 0-30 0.4 90-120 0 9195 NM NS 12 42 35.61959 -103.679


01-Apr-09 Herbaceous Upland Grassland/Herbaceous 0-20 0.6 40-100 0.6 1643 OK NS 12 43 36.56712 -102.715

20-Jun-08 Shrubland Shrubland 0-4 1.2 100-115 0.3 12075 CO NS 13 45 37.35293 -102.162

28-Apr-08 Planted/Cultivated Small Grains 0-18 0.4 90-100 0.2 9323 KS NS 13 45 37.73737 -101.769

28-Apr-08 Planted/Cultivated Small Grains 0-12 1.2 90-100 0.3 5803 KS NS 12 43 38.00617 -101.754

29-Apr-08 Planted/Cultivated Row Crops 0-10 1.2 90-100 0.8 11435 KS NS 11 49 38.74379 -101.104

15-Apr-08 Planted/Cultivated Row Crops 0-10 1.4 60-70 0.5 3947 KS NS 11 55 39.63387 -100.425

15-Apr-08 Herbaceous Upland Grassland/Herbaceous 0-15 1.1 80-90 0.5 8088 KS NS 11 58 39.78564 -99.9978

16-Aug-07 Planted/Cultivated Row Crops 0-15 2 58-100 0.5 12888 NE NS 10 60 40.61944 -99.4847

25-Jul-07 Planted/Cultivated Row Crops 0-18 1.5 81-100 0.3 600 NE NS 9 66 41.09167 -98.8833

27-Jul-07 Herbaceous Upland Grassland/Herbaceous 0-23 1.7 64-100 0.4 4952 NE NS 9 67 41.44944 -98.5008

27-Jul-07 Planted/Cultivated Pasture/Hay 0-13 0.8 30-100 0.5 4248 NE NS 9 68 41.625 -98.4456

26-Aug-09 Planted/Cultivated Pasture/Hay 0-18 4.5 89-114 1.3 153 ND NS 4 50 48.21375 -98.1167

24-Jun-09 Planted/Cultivated Pasture/Hay 0-13 3.1 38-43 0.5 5977 ND NS 4 49 48.87624 -97.9825

26-Aug-09 Planted/Cultivated Row Crops 0-36 1.9 86-109 0.4 4249 ND NS 4 50 48.37001 -97.7849

04-Aug-07 Planted/Cultivated Small Grains 0-15 0.8 46-97 0.5 2248 NE NS 9 68 42.68194 -97.7761

(Continued)

191


States

Sampling



ID Stat

e

Transec

t

MAT

(°C)

MAP


(cm)

C

(wt. %)

Depth

(cm)

C

(wt. %)

12-Aug-09 Planted/Cultivated Small Grains 0-23 1.2 75-90 0.5 12488 SD NS 9 64 42.96555 -97.7024

02-Aug-07 Planted/Cultivated Row Crops 0-20 0.6 74-102 0.2 4440 NE NS 9 69 42.29806 -97.6411

24-Jun-09 Planted/Cultivated Row Crops 0-20 2.4 86-114 0.1 1881 ND NS 4 49 48.72058 -97.5585

23-Nov-09 Planted/Cultivated Fallow 0-23 1.5 74-89 0.6 10440 SD NS 9 65 42.992 -97.5547

14-Nov-08 Herbaceous Upland Grassland/Herbaceous 0-20 3.8 100-115 0.8 7368 SD NS 8 66 43.60178 -97.095

30-Sep-09 Planted/Cultivated Row Crops 0-22 3.4 100-120 0.7 9049 MN NS 4 50 48.79665 -96.9522

30-Sep-09 Planted/Cultivated Fallow 0-23 1.7 100-120 0.9 4953 MN NS 4 50

-96.9098

18-Aug-09 Planted/Cultivated Row Crops 0-35 3.1 90-140 0.1 11208 MN NS 7 69 44.15255 -95.8536

29-Sep-09 Forested Upland Deciduous forest 0-9 4.4 80-100 0 6617 MN NS 4 59 47.62273 -95.5756

19-Sep-09 Planted/Cultivated Row Crops 0-30 3.7 100-140 0.2 12232 MN NS 7 70 44.7382 -95.3656

29-Aug-09 Forested Upland Deciduous forest 0-15 4.2 40-50 0.4 9433 MN NS 5 67 46.22335 -95.3268

19-Sep-09 Planted/Cultivated Row Crops 0-30 3.2 95-125 0.2 6041 MN NS 6.5 70 45.0163 -95.0542

28-Aug-09 Forested Upland Deciduous forest 0-5 2.7 80-110 0.1 12505 MN NS 5 67 46.84748 -95.0427

28-Sep-09 Planted/Cultivated Pasture/Hay 0-5 1 115-130 0.1 2521 MN NS 4 65 47.47011 -95.0292

29-Aug-09 Planted/Cultivated Pasture/Hay 0-25 0.6 95-125 0.1 2713 MN NS 5 67 46.50399 -94.8848

29-Aug-09 Herbaceous Upland Grassland/Herbaceous 0-25 1.9 95-105 0 7065 MN NS 6 69 45.91189 -94.87

04-Sep-09 Herbaceous Upland Grassland/Herbaceous 0-25 1.9 60-100 0.2 10137 MN NS 6 71 45.39033 -94.8242

Sampling date, date sample was collected in MM/DD/YY; Land Cover 1, primary classification from National Land Cover Database 1992 Classification System; Land Cover 2,

secondary classification from National Land Cover Database 1992 Classification System; “A” and “C” in the column heading indicate A and C horizon; C (wt. %), organic carbon

content; “ID” in the column heading signifies unique identifier assigned by generalized random tessellation stratified design software. State, abbreviation for state name as follows:

CA, California; NV, Nevada; UT, Utah; CO, Colorado; KS, Kansas; MO, Missouri; IL, Illinois; KY, Kentucky; IN, Indiana; WV, West Virginia; VA, Virginia; MD, Maryland;

TX, Texas; NM, New Mexico; OK, Oklahoma; NE, Nebraska; ND, North Dakota; SD, South Dakota; MN, Minnesota; “WE” and “NS” in the transect column mean West-East

and North-South transect, respectively; “MAT” and “MAP” signify mean annual temperature and mean annual precipitation, respectively.

(Continued)

192

Appendix B. Mineralogical data for samples from the soil C and A horizons in the conterminous United States

ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z

eol Gyp Talc Hor Ser Her Goe Pyr Pt

Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

982

3 C 48.2 7 13.5 20.4 3.2 6.5 3.6 13.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.1

675

1 C 33 4.2 15.9 20.1 4.2 17 N.D. 21.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.7

105

91 C 26.9 2.1 10.8 12.9 11.5 7.6 N.D. 19.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. N.D. N.D. 40.7

500

7 C 9.7 N.D. N.D. N.D. N.D. 4.3 79.9 84.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. 5.6

193

5 C 4.2 N.D. N.D. N.D. N.D. 13.3 56.8 70.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.5 2.3 N.D. N.D. N.D. N.D. 19.9

603

1 C 35.8 11.7 12.8 24.5 3.5 9 N.D. 12.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 6.1 N.D. N.D. N.D. N.D. N.D. N.D. 21.2

295

9 C 34 3.2 30.9 34.1 1.1 20.4 N.D. 21.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 9.4 N.D. N.D. N.D. N.D. N.D. N.D. 1

910

3 C 37.7 21.2 34.9 56.2 N.D. 2.8 N.D. 2.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.4

942

3 C 25.6 4.2 6.7 11 3.2 4.7 N.D. 7.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 55.6

207 C

27.3 13.3 19.3 32.7 1 6.5 N.D. 7.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.7 N.D. N.D. N.D. N.D. N.D. N.D. 30.9

807

9 C 39.7 22.7 35.9 58.7 N.D. 1.7 N.D. 1.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

124

95 C 10 20.2 43.1 63.3 N.D. 5.3 N.D. 5.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.2 N.D. 0.6 N.D. N.D. N.D. N.D. 20.6

106

07 C 11.9 12.2 34.4 46.6 N.D. 1.4 3.1 4.6 N.D. 2.7 N.D. N.D. 2.7 N.D. 4.9 4.9 0.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 29

753

5 C 26.5 16.5 25.5 42 N.D. 7.6 N.D. 7.6 N.D. 1.9 N.D. N.D. 1.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 22

103

51 C 30.4 15.8 25.4 41.1 N.D. 7.7 N.D. 7.7 N.D. 0.3 N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 20.5

131

83 C 50.4 3.2 3.8 7 N.D. 14.4 3.3 17.7 N.D. 0.8 N.D. N.D. 0.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 24.1

108

63 C 18.7 23 37.4 60.3 N.D. 2.1 N.D. 2.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.9

369

5 C 11.1 11.2 32 43.2 4.3 1.8 N.D. 6.1 N.D. 7.4 N.D. N.D. 7.4 N.D. N.D. N.D. N.D. N.D. 0.9 N.D. N.D. N.D. N.D. N.D. N.D. 31.3

175

9 C 13.7 8.3 17 25.3 N.D. 5.1 0.8 5.9 N.D. 32 9 N.D. 41 N.D. N.D. N.D. N.D. N.D. 0.7 N.D. N.D. N.D. N.D. N.D. N.D. 13.4

112

31 C 7.4 3.3 3.4 6.7 N.D. 2.4 N.D. 2.4 N.D. 25.9 49.9 N.D. 75.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.7

109

75 C 20.6 7.3 17.5 24.8 3.7 4.8 N.D. 8.5 N.D. 20.7 N.D. N.D. 20.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.4

303 C

19.4 2.4 2.7 5.2 N.D. 8.4 5.7 14.1 N.D. 19.9 10 N.D. 29.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 31.5

102

87 C 6.1 4.6 20.5 25.1 1.4 14 N.D. 15.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 53.4

120


619

1 C 19.7 N.D. 19.9 19.9 N.D. 4 N.D. 4 N.D. 25 N.D. N.D. 25 0.3 N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. 7.2 N.D. N.D. 23.7

393

1 C 33 6.6 10.9 17.5 6.1 9.9 N.D. 16 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.4 N.D. 10.6 N.D. N.D. 21.5

834

7 C 21.8 5.9 N.D. 5.9 N.D. 32.2 4.2 36.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 8.3 27.6

117

9 C 69.5 5.4 3.9 9.3 3.1 5.8 N.D. 8.9 N.D. 5.2 N.D. N.D. 5.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.1

193


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

937

1 C 63.9 4.4 3.7 8.1 N.D. 10.1 4 14.1 N.D. 1 N.D. N.D. 1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 13

450

7 C 59.1 4.6 3.5 8.1 N.D. 5.9 1.3 7.2 N.D. 3.9 11.7 N.D. 15.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 10.1

322

7 C 56.4 2.3 2.5 4.8 2.6 10.5 3.4 16.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. N.D. 22

220

3 C 79.9 7.1 N.D. 7.1 N.D. 6.9 N.D. 6.9 N.D. 1.8 N.D. N.D. 1.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 4.3

411 C

59.9 3 4.5 7.6 N.D. 14.2 2.4 16.5 N.D. 0.6 N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15.5

567

5 C 58.4 5.7 6.1 11.8 2 7.2 2.5 11.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.1

988

3 C 53.2 4.8 5.5 10.3 N.D. 9.4 3.1 12.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.9

109

07 C 56.1 2.1 2.9 5 N.D. 10.9 2.5 13.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.6

329


457


475 C

22 9.3 45 54.2 N.D. 16.9 N.D. 16.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.6 N.D. 0.9 N.D. N.D. N.D. N.D. 2.4

535

5 C 33.8 10.8 23.9 34.7 0.7 7.6 0.7 9.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.4 N.D. N.D. N.D. N.D. 21.1

945

1 C 25.1 15.6 40 55.5 1.3 2.9 N.D. 4.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 2.3 N.D. 1.2 N.D. N.D. N.D. N.D. 11.8

637

9 C 24.2 5.5 17.6 23.1 4.4 8.6 N.D. 13 N.D. 17.3 N.D. N.D. 17.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 22.4

415

5 C 29.9 12 11.1 23 5.9 7.7 N.D. 13.7 N.D. 9.5 N.D. N.D. 9.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 24

253

9 C 24.1 4.3 6.6 10.9 3.7 5.5 1.6 10.8 N.D. 28.8 N.D. N.D. 28.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.5

683 C

54.6 15 6.2 21.2 N.D. 3.9 N.D. 3.9 N.D. 12.9 N.D. N.D. 12.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.5

477

9 C 35 7.1 7.4 14.5 3.9 6.7 1.2 11.8 N.D. 8.5 N.D. N.D. 8.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 30.3

129

71 C 46 8 11.3 19.3 3.8 6.7 N.D. 10.5 N.D. 6.9 N.D. N.D. 6.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 17.3

580

3 C 39.4 6.4 14.2 20.6 3 9.4 N.D. 12.4 N.D. 4.6 N.D. N.D. 4.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.1

452


108

59 C 29.9 3.1 10.4 13.4 2.3 11.1 N.D. 13.4 N.D. 8 N.D. N.D. 8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 35.3

861


127


125

84 C 27.7 4.6 3.3 7.8 N.D. 6.8 N.D. 6.8 N.D. 39.6 N.D. N.D. 39.6 N.D. N.D. N.D. 0.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 17.7

584

8 C 55.7 5.6 13.6 19.2 1.3 8.7 N.D. 10 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15.2

687


102

80 C 61.4 5.3 9.8 15.1 1.5 7.8 N.D. 9.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 14.3

(Continued)

194


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

738


129

52 C 45.3 3 6.7 9.6 2.3 11.3 N.D. 13.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 31.5

476


664 C

63.9 N.D. 5.9 5.9 N.D. 7.8 4.7 12.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.3 N.D. N.D. N.D. 16.4

373

6 C 47.6 1.8 5.2 7 7.1 13.4 N.D. 20.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 24.8

194

4 C 63.6 1.1 3.6 4.7 N.D. 20.7 N.D. 20.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. 10.6

116

56 C 70.7 0.4 1 1.3 N.D. 11.1 11.5 22.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 5.4

129

36 C 46.4 N.D. 2.3 2.3 14.5 30.7 N.D. 45.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. 5.8

648 C

75.2 1.6 3.3 4.9 N.D. 10.1 4 14.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 5.8

116

0 C 52.8 2.1 2.8 4.9 N.D. 21.1 N.D. 21.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. 20.7

525


103

76 C 69.9 2.3 4.8 7 N.D. 23.1 N.D. 23.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

218


103

2 C 68.8 3 6 9 N.D. 11.8 N.D. 11.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 10.4

820

0 C 48.8 5.5 11.1 16.6 4 5.6 N.D. 9.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.1

280

4 C 52.6 7.3 15 22.3 4.7 5.9 N.D. 10.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 14.6

382

8 C 59.8 4 8.8 12.7 N.D. 9.1 3.4 12.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15

792

4 C 58.9 4.4 10.7 15.1 1.8 10.1 2.2 14 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12

120

20 C 40.6 4.7 8.7 13.5 2.5 10.4 N.D. 12.9 N.D. 3.6 15.5 N.D. 19.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 13.9

535

6 C 66.9 8.1 5.8 13.8 1.7 9 N.D. 10.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 8.6

945

2 C 74.2 1.6 3.2 4.7 2.5 4.4 2.8 9.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 11.4

125

24 C 34.8 N.D. 6.2 6.2 6.3 20.8 6.7 33.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 24.8

433

2 C 78 3.1 6.4 9.5 N.D. 6.6 1.3 7.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 4.6

606


111

80 C 29 0.7 1.9 2.6 5.8 17.3 5 28.1 N.D. 6.3 10.1 N.D. 16.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.9

298

8 C 21.5 4 2.7 6.7 2.3 16.9 2 21.2 N.D. 19.6 N.D. N.D. 19.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 31

529

2 C 20.3 5.4 2.6 7.9 5 16 2.3 23.2 N.D. 20.5 N.D. N.D. 20.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28.1

964

4 C 86.2 0.9 N.D. 0.9 N.D. 7.2 4.3 11.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.4

(Continued)

195


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

124

60 C 56.6 N.D. N.D. N.D. N.D. 26 N.D. 26 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 9.3 N.D. N.D. N.D. 8.1

170

8 C 88.3 1 1.5 2.5 N.D. 2.9 1.4 4.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 4.8

580


478


129


559

6 C 50.3 1.6 N.D. 1.6 4.7 18.6 8.6 31.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 16.2

127

64 C 82.5 N.D. N.D. N.D. N.D. 8.2 9.1 17.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.3

585

2 C 48.7 1.1 N.D. 1.1 N.D. 25.2 12.4 37.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12.6

687

6 C 88.6 N.D. N.D. N.D. N.D. 7.2 N.D. 7.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 4.2

278

0 C 71.9 N.D. 1.4 1.5 1.8 12.3 1.5 15.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 11.1

732

4 C 30.7 19.7 N.D. 19.7 3.7 11 23.1 37.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 11.9

322

8 C 47.9 3.2 N.D. 3.2 N.D. 13.8 11.7 25.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. 22.8

937

2 C 11.1 N.D. N.D. N.D. N.D. N.D. 57.7 57.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 10.5 N.D. N.D. N.D. 20.8

991

6 C 91.2 2 N.D. 2 N.D. 6.7 N.D. 6.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

274

8 C 83.1 10.7 3.6 14.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 2.6

172

4 C 84.4 1 N.D. 1 N.D. 8.9 2 10.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.7

485


894

8 C 88.2 4.8 6.3 11.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.6

955

6 C 21.5 2.8 8.1 10.8 6.4 7.1 3.4 16.9 N.D. 7.6 N.D. N.D. 7.6 N.D. N.D. N.D. 1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 42.2

113

27 C 67.4 3.6 1.2 4.8 N.D. 6.6 3.7 10.3 N.D. 8.5 N.D. N.D. 8.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 8.9

868

7 C 44.8 10.5 10.5 21 N.D. 7.2 N.D. 7.2 N.D. 9.8 N.D. N.D. 9.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. N.D. 16.8

459

1 C 36.4 7.4 4.1 11.5 N.D. 10.8 N.D. 10.8 N.D. 8.7 3.7 N.D. 12.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28.9

543

9 C 35.9 7.8 11.3 19.1 N.D. 6.3 N.D. 6.3 N.D. 16.4 N.D. N.D. 16.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.4 N.D. 1.9 N.D. N.D. 20.1

561

5 C 8.7 3.1 2.7 5.8 N.D. 7.1 N.D. 7.1 N.D. 20.2 3.4 N.D. 23.6 N.D. N.D. N.D. 33.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.7

127

83 C 52 10.6 8.8 19.4 N.D. 5.2 N.D. 5.2 N.D. 4.4 4.6 N.D. 8.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 14.5

723

1 C 30.8 5.4 5.6 11 3 6.8 N.D. 9.8 N.D. 24.9 N.D. N.D. 24.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.3 N.D. N.D. N.D. N.D. 23.2

791


953


(Continued)

196


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

211


313


919

5 C 82.7 5.6 4.5 10.1 N.D. N.D. 0.5 0.5 N.D. 0.8 N.D. N.D. 0.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 6

689

1 C 42.6 2.7 2.9 5.6 N.D. 5.4 N.D. 5.4 N.D. 34.4 N.D. N.D. 34.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12

164


120

75 C 57.9 13.8 8.6 22.4 N.D. 7 N.D. 7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12.8

932


114


394

7 C 34.1 3.3 11 14.3 1.8 15.5 N.D. 17.3 N.D. 6.4 N.D. N.D. 6.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28

808

8 C 42.8 4 18.6 22.6 1.4 9.2 N.D. 10.6 N.D. 0.6 N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.4

128


600 C

35.4 4 13.4 17.4 3.5 12.6 N.D. 16.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 31.1

495


424

8 C 40.7 7.5 10.6 18.1 0.7 15.2 1.4 17.3 N.D. 3.1 1.9 N.D. 4.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.9

153 C

31.1 3.5 8.7 12.2 6.6 3.5 N.D. 10.1 N.D. 6.9 10.3 N.D. 17.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 29.5

597

7 C 39.6 N.D. 11.9 11.9 N.D. 6.5 0.9 7.3 N.D. 0.6 6.7 N.D. 7.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 33.2

424

9 C 57.3 5.8 19.5 25.2 0.5 3.6 N.D. 4.1 N.D. 5.7 3.9 N.D. 9.6 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 3.5

224


124

88 C 45.1 4.7 14.1 18.8 3 4 N.D. 7 N.D. 3.9 7.2 N.D. 11.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18

444


188

1 C 33.2 4.8 7.3 12.1 5.7 6.6 N.D. 12.3 N.D. 3.6 16.3 N.D. 19.9 N.D. N.D. N.D. 1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.6

104

40 C 32.8 5.1 9.2 14.3 5.3 5.1 N.D. 10.5 N.D. 11 9.8 N.D. 20.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.6

736

8 C 35.4 5.4 8.7 14.1 8.1 6.1 N.D. 14.2 N.D. 4 5.1 N.D. 9.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 27.2

904

9 C 20.8 4 5.5 9.5 11.5 7 N.D. 18.5 N.D. 5.6 9.7 N.D. 15.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 36

495

3 C 18.8 4 5.9 9.9 12.4 7.2 1.6 21.2 N.D. 1.2 7.2 N.D. 8.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 41.7

112

08 C 37.7 3.7 10.5 14.2 3.1 5.2 N.D. 8.3 N.D. 12.2 8.6 N.D. 20.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 19

661

7 C 32.2 5.4 14.7 20.1 0.8 3.2 N.D. 4 N.D. 9.6 20.6 N.D. 30.2 N.D. N.D. N.D. N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. 13.2

122

32 C 50.7 5 16.9 21.9 0.7 3 N.D. 3.7 N.D. 3 8.2 N.D. 11.2 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 12.3

(Continued)

197


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

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ay Gs Cc Dm An

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Oth

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wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

943

3 C 47.3 8.3 27.9 36.2 1.7 4.7 N.D. 6.4 N.D. 0.2 N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. 1.3 N.D. N.D. N.D. N.D. N.D. N.D. 8.6

604

1 C 38.3 4.7 14.8 19.5 0.8 6 N.D. 6.8 N.D. 4.3 12.3 N.D. 16.6 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 18.6

125

05 C 61.5 8.9 26.3 35.1 N.D. 2.2 N.D. 2.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D.

252

1 C 61.9 9.1 21.7 30.9 N.D. 2.6 N.D. 2.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1 N.D. N.D. N.D. N.D. N.D. N.D. 3.8

271

3 C 65.2 7.2 22.6 29.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.8 N.D. N.D. N.D. N.D. N.D. N.D. 4.2

706

5 C 60.3 8.1 26.6 34.7 N.D. 2.8 1 3.9 N.D. N.D. 0.4 N.D. 0.4 N.D. N.D. N.D. N.D. N.D. 0.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D.

101

37 C 54.8 7.4 24 31.4 N.D. 1.6 N.D. 1.6 N.D. 5.2 6.1 N.D. 11.3 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 0.7

9823 A 48.3 6 15.3 21.3 N.D. 8.7 4.8 13.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 17

6751 A 30.9 4.9 17.2 22.1 2.3 17.8 5.5 25.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.4

10591 A 53.5 3.2 12.8 15.9 N.D. 7.4 N.D. 7.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.9 N.D. 0.3 N.D. N.D. N.D. N.D. 22

5007 A 44.9 N.D. N.D. N.D. N.D. 16.2 23.4 39.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15.5

1935 A 3.8 N.D. 1.3 1.3 N.D. 25.2 43.7 68.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.6 1.5 N.D. N.D. N.D. N.D. 23.9

6031 A 33.2 11.4 12.9 24.3 4.2 11.3 N.D. 15.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.6 N.D. N.D. N.D. N.D. N.D. N.D. 23.4

2959 A 30.8 5.9 26.7 32.6 N.D. 10.2 N.D. 10.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 4.7 N.D. N.D. N.D. N.D. N.D. N.D. 21.7

9103 A 37.3 22.2 38.2 60.4 N.D. 2.3 N.D. 2.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

9423 A 16.5 10 8.7 18.6 1.8 3.2 1.9 6.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 58

207 A 26.4 11.6 19.5 31.1 N.D. 5 N.D. 5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 N.D. N.D. N.D. N.D. N.D. N.D. 36.8

8079 A 32 13.6 50.5 64.1 0.9 2.3 N.D. 3.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D.

12495 A 12.9 16.4 36.6 53 N.D. 4.3 N.D. 4.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. 29.2

10607 A 11.9 11.7 32 43.7 N.D. 2.5 1.7 4.1 N.D. N.D. N.D. N.D. N.D. N.D. 4 4 N.D. N.D. 0.4 N.D. N.D. N.D. N.D. N.D. N.D. 35.8

7535 A 25.3 17 29.6 46.6 N.D. 4.8 N.D. 4.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 N.D. N.D. N.D. N.D. N.D. N.D. 22.6

10351 A 37 7.6 15.3 22.9 N.D. 14.2 N.D. 14.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.6 N.D. N.D. N.D. 25.4

13183 A 54.4 4.4 5.4 9.8 N.D. 13.9 N.D. 13.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.9

10863 A 14.9 19.4 35.2 54.6 N.D. 2 N.D. 2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28.4

3695 A 11.2 17.4 45 62.4 N.D. 1.6 N.D. 1.6 N.D. 1.1 N.D. N.D. 1.1 N.D. N.D. N.D. N.D. N.D. 1.7 N.D. N.D. N.D. N.D. N.D. N.D. 22.1

1759 A 19.3 9.2 21.1 30.3 0.3 4.7 N.D. 5 N.D. 20.8 8.7 N.D. 29.5 N.D. N.D. N.D. N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. 15.4

11231 A 11.9 4.9 8.5 13.4 N.D. 4.3 N.D. 4.3 N.D. 15.2 43.4 N.D. 58.6 N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. N.D. N.D. 11.4


(Continued)

198


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% wt. % wt. % wt. % wt. % wt. %

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% wt. %

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% wt. %

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%

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% wt. %

wt.

%

wt.

%

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%

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%

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%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

303 A 66.9 6 12.3 18.3 N.D. N.D. N.D. N.D. N.D. 5.1 2.1 N.D. 7.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.6


12095 A 26.9 2.6 1.9 4.5 3.1 7.2 N.D. 10.3 N.D. 31.5 N.D. N.D. 31.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 26.9

6191 A 29.3 N.D. 23.2 23.2 2.4 7.4 N.D. 9.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.1 N.D. N.D. 30.7

3931 A 37.7 6.8 10 16.8 N.D. 10.7 N.D. 10.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.1 N.D. 7.5 N.D. N.D. 26.1

8347 A 36.1 4.3 N.D. 4.3 N.D. 14.6 4.4 19 N.D. 3.5 9.2 N.D. 12.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 27.9


9371 A 67.2 9.3 6.7 16 N.D. 6.1 2.3 8.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 8.4

4507 A 76.8 5.6 N.D. 5.6 4 N.D. 0.4 4.4 N.D. 0.5 N.D. N.D. 0.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.6 N.D. N.D. 11.1


2203 A 84.4 8.9 N.D. 8.9 N.D. 3.7 N.D. 3.7 N.D. 0.9 N.D. N.D. 0.9 2.1 N.D. 2.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

411 A 69.4 5.1 6.2 11.3 N.D. 6.4 0.9 7.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12.1


9883 A 57.9 N.D. 6.1 6.1 N.D. 9.2 6.2 15.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 20.6

10907 A 46.6 1 2 3 N.D. 9.2 N.D. 9.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 41.2

3291 A 22.5 17.9 27 44.9 N.D. 2.2 10.5 12.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 20


475 A 31.6 17.8 46.1 63.9 N.D. 4.5 N.D. 4.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.

5355 A 34.5 11.1 21.2 32.2 N.D. 7.5 N.D. 7.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.2 N.D. N.D. N.D. N.D. 24.6

9451 A 25.5 13.2 29.7 43 N.D. 3.2 N.D. 3.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28.4

6379 A 26.2 7.8 21.3 29.1 N.D. 9.5 1.4 10.8 N.D. 10.6 N.D. N.D. 10.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.4

4155 A 55.4 16.6 14.9 31.5 1.7 4.3 N.D. 6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 7.1

2539 A 34.7 11.3 13 24.3 N.D. 9.2 1.8 11 N.D. 5.2 N.D. N.D. 5.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 24.9


4779 A 38.2 8.8 9.3 18.2 1 10 N.D. 10.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 32.7


5803 A 40.2 7.4 11.3 18.7 2.6 9 N.D. 11.5 N.D. 4.2 N.D. N.D. 4.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.4

4523 A 35 5.4 8.3 13.7 N.D. 14.7 1.2 15.9 N.D. 0.3 N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 35.1

(Continued)

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%

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%

wt.

%

wt.

%

wt.

%

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10859 A 43.3 7 14.1 21.1 N.D. 11.3 2.7 14 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 21.6

8619 A 37.3 4.2 12 16.2 1 7 N.D. 8 N.D. 4.4 N.D. N.D. 4.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 34.2



5848 A 65 5.5 14.1 19.6 N.D. 7.1 N.D. 7.1 N.D. 0.4 N.D. N.D. 0.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 8

6872 A 39.7 5.5 10.1 15.5 N.D. 10.9 2.1 13 N.D. 1.9 N.D. N.D. 1.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 29.9

10280 A 64.2 6.8 8.7 15.5 N.D. 7.8 N.D. 7.8 N.D. 0.2 N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 12.3

7384 A 46.4 4.1 6.9 11 N.D. 12 N.D. 12 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 30.7


4760 A 44.6 3 7.7 10.7 1.8 15.7 3.5 20.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.8

664 A 55.4 2.1 3.4 5.5 N.D. 9.5 N.D. 9.5 N.D. 2.7 N.D. N.D. 2.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 27

3736 A 56.1 2 6.4 8.4 N.D. 13.1 N.D. 13.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 22.5


11656 A 78.1 1.7 1.9 3.7 N.D. 4.2 2.6 6.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 11.4

12936 A 72.6 3.4 5.8 9.2 2.7 3.6 N.D. 6.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 11.9


1160 A 67.7 2.8 3 5.8 N.D. 12.7 N.D. 12.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 13.8

5256 A 64 4 3.2 7.2 N.D. 10.7 N.D. 10.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.1

10376 A 68.1 6.3 6.5 12.8 N.D. 9 N.D. 9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 10


1032 A 53.4 3.3 5.5 8.7 5.1 5.5 N.D. 10.6 N.D. N.D. 11.5 N.D. 11.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15.8

8200 A 58.3 8.5 10.2 18.7 N.D. 4.5 N.D. 4.5 N.D. 0.5 N.D. N.D. 0.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18




12020 A 62.6 7.1 8 15 N.D. 4.6 N.D. 4.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 17.7


9452 A 61.2 9.3 12.9 22.2 N.D. 6.8 N.D. 6.8 N.D. 1.5 0.5 N.D. 2 N.D. N.D. N.D. N.D. N.D. 0.4 N.D. N.D. N.D. N.D. N.D. N.D. 7.4

(Continued)

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wt.

%

wt.

%

wt.

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4332 A 59.5 3 8.8 11.7 2.4 5.2 N.D. 7.6 N.D. 2 N.D. N.D. 2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 19.3


11180 A 36.5 6.4 N.D. 6.4 1.7 13.9 N.D. 15.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 41.5

2988 A 46.4 2.7 2.1 4.8 N.D. 17.2 N.D. 17.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1 N.D. N.D. N.D. 30.7



12460 A 63 1.2 3.7 4.9 N.D. 8.9 N.D. 8.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 23.2

1708 A 84.6 1.2 2.3 3.5 2.4 3.7 N.D. 6.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.3 N.D. N.D. N.D. 5.5

5804 A 45.7 1.7 2.6 4.3 3 18.5 9.5 31 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 19.1



5596 A 49.8 0.4 2.6 3 5.1 16.7 7.1 28.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.3

12764 A 89.9 1.9 N.D. 1.9 N.D. N.D. 6.3 6.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 2

5852 A 63.4 N.D. N.D. N.D. N.D. 13.2 11.5 24.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 9.2 N.D. N.D. 2.8

6876 A 37 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 63

2780 A 79.9 0.9 2.1 3 3.1 10.3 N.D. 13.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.6

7324 A 27.7 10.7 N.D. 10.7 N.D. 8.8 14 22.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 38.9

3228 A 71.1 1.1 N.D. 1.1 N.D. 6.4 3.9 10.4 N.D. N.D. N.D. 1.1 1.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 16.3

9372 A 65.3 1.9 1.9 3.8 1.3 0.4 15.4 17.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3.2 N.D. N.D. N.D. N.D. 10.7

9916 A 54.8 3 N.D. 3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 42.2

2748 A 86.3 5 3 7.9 N.D. 3 0.9 3.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.8

1724 A 90.9 0.4 2.4 2.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 6.3

4852 A 73.7 2 4 6 N.D. N.D. N.D. N.D. N.D. 4.5 N.D. N.D. 4.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 15.8

8948 A 84 1.7 4.1 5.8 N.D. 5.3 1.8 7.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 3

9556 A 28.3 3.7 8.4 12.1 0.7 13.1 3 16.8 N.D. 5.6 N.D. N.D. 5.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 37.2

11327 A 64.7 1.7 4.3 6 N.D. 9.8 2.9 12.6 N.D. 2.8 N.D. N.D. 2.8 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 13.9

8687 A 48.6 11.8 8.7 20.5 N.D. 6.4 N.D. 6.4 N.D. 7.3 N.D. N.D. 7.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 N.D. N.D. N.D. N.D. 16.6

(Continued)

201


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

4591 A 39 7.7 6.4 14.1 N.D. 9 N.D. 9 N.D. 7 3.6 N.D. 10.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. 26.9

5439 A 40.6 10.2 16.3 26.5 N.D. 8.8 N.D. 8.8 N.D. 1.9 N.D. N.D. 1.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 N.D. N.D. N.D. N.D. 21.5

5615 A 27.4 4.2 12.3 16.6 N.D. 11.1 N.D. 11.1 N.D. 15.8 4.1 N.D. 20 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25

12783 A 49.6 8.4 12.4 20.7 N.D. 2.8 N.D. 2.8 N.D. 5.8 7.2 N.D. 13 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 14

7231 A 26.6 3.4 6.2 9.5 N.D. 6.9 N.D. 6.9 N.D. 29.3 1.1 N.D. 30.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 26.6

7919 A 84.2 6.1 5.3 11.4 N.D. 4.1 N.D. 4.1 N.D. 0.3 N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.





6891 A 46.8 5.4 4.6 10 N.D. 6.7 N.D. 6.7 N.D. 17.3 N.D. N.D. 17.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 19.2

1643 A 69.3 6.7 9.3 16.1 N.D. 5 N.D. 5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. 9.5



11435 A 40.2 5.7 13 18.7 N.D. 11.5 N.D. 11.5 N.D. 0.6 N.D. N.D. 0.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 29.1






4248 A 36.3 5 11.6 16.6 3.5 8 N.D. 11.4 N.D. 2.8 1.9 N.D. 4.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 31

153 A 39.2 3.3 12.9 16.2 N.D. 6.8 N.D. 6.8 N.D. 0.4 0.7 N.D. 1.1 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 36.6


4249 A 52.1 4.9 16.1 21.1 N.D. 4.6 N.D. 4.6 N.D. 3.6 N.D. N.D. 3.6 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 18.5

2248 A 36.8 3.5 6.7 10.3 2 12.3 N.D. 14.3 N.D. 3.1 3.1 N.D. 6.2 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 32.5

12488 A 50.9 5.1 14.6 19.7 4 6.6 N.D. 10.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 18.8



(Continued)

202


ID H Qz

Tot_K

_fs

Tot_Pl

ag

Tot_Fl

ds

Tot_1

4A

Tot_1

0A Kao

Tot_Cl

ay Gs Cc Dm An

Tot_C

arb Ac Hd

Tot_Z


Oth

er Aph

wt.

% wt. % wt. % wt. % wt. % wt. %

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

% wt. %

wt.

%

wt.

% wt. %

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

wt.

%

10440 A 48.1 5.6 13 18.6 0.5 9.9 N.D. 10.4 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 22.9


9049 A 23.7 15.3 5.5 20.8 7 10.1 N.D. 17.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 38.5

4953 A 17.1 3.2 4.9 8.1 15.4 6.7 N.D. 22.2 N.D. 0.2 7.3 N.D. 7.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 45.2

11208 A 41.2 5.8 11.7 17.4 N.D. 10 4.3 14.3 N.D. N.D. N.D. N.D. N.D. 0.3 N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 26.8

6617 A 51.9 8.8 19.4 28.2 N.D. 4.6 N.D. 4.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.8 N.D. N.D. N.D. N.D. N.D. N.D. 14.6

12232 A 35.7 5.1 12 17.1 6.1 6.8 N.D. 13 N.D. 4.8 0.9 N.D. 5.7 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 28.6

9433 A 45.5 8.3 23.3 31.6 0.8 0.8 N.D. 1.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1 N.D. N.D. N.D. N.D. N.D. N.D. 20.2

6041 A 35.8 12.3 12.1 24.4 6.3 6.3 N.D. 12.6 N.D. 0.9 0.7 N.D. 1.6 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 25.6

12505 A 63.1 9.1 24.8 33.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. 2.7

2521 A 52.8 9.3 24 33.3 N.D. 2.1 N.D. 2.1 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.2 N.D. N.D. N.D. N.D. N.D. N.D. 10.6

2713 A 67.9 9.5 20.1 29.6 N.D. 1.8 N.D. 1.8 N.D. 0.2 N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. 0.5 N.D. N.D. N.D. N.D. N.D. N.D. N.D.

7065 A 54.4 9.6 18.1 27.7 1.8 0.3 N.D. 2 N.D. N.D. N.D. 0.5 0.5 N.D. N.D. N.D. N.D. N.D. 0.2 N.D. N.D. N.D. N.D. N.D. N.D. 15.2

10137 A 51.1 7.1 22.5 29.6 0.6 3.3 N.D. 3.9 N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.3 N.D. N.D. N.D. N.D. N.D. N.D. 15.1

“ID” in the column heading signifies unique identifier assigned by generalized random tessellation stratified design software. H, horizon; Qz, quartz; Tot, total; Tot_K_fs, total

potassium feldspar; Tot_Plag, total plagioclase feldspar; Tot_Flds, total feldspar; Tot_14A, total 14-angstrom clay minerals; Tot_10A, total 10-angstrom clay minerals; Kao,

kaolinite; Gs, gibbsite; Cc, calcite; Dm, Dolomite; An, aragonite; Tot_Carb, total carbonate minerals; Ac: analcime; Hd, heulandite; Tot_Zeol, total zeolite minerals; Gyp, Gypsum;

Hor, hornblende; Ser, serpentine; Her, heratite; Geo, goethite; Pyr, pyroxene; Pt, pyrite Aph, amorphous; N.D. , note detected.

(Continued)

203

Appendix C. Concentrations of free amino acids detected in soils (mmol kg-1 dry soil)

ID Horizon Asp Glu Ser+Asn Gly Gln His Arg Tau Cit Thr Ala GABA Pro Tyr Cys-Cys Val Met Orn Ile Lys Leu Phe Trp

9823 C 0.04 0.92 0.38 0.16 0.16 0.04 0.21 0 0.047 0.31 0.9 0.23 0.12 0.17 0.1 0.2 0.11 0.017 0.065 0.098 0.4 0.1 0

6751 C 0.43 1.74 0.74 0.98 0.013 0.04 1.66 0 0.092 0.77 2.07 0.51 0.28 0.1 0.4 0.33 0.16 0.12 0.04 0.17 0.42 0.14 0.17

10591 C 0.16 1.57 0.22 0.36 0 0 0.058 0 0.16 0.47 0.77 0.38 0.11 0.058 0.18 0.26 0.062 0.02 0.098 0.031 0.28 0.12 0

5007 C 0.1 0.2 0.68 0.97 0.063 0.03 0.47 0 0.16 1.01 2.32 1.03 0.64 0.15 0.11 0.57 0.078 0.11 0.24 0.11 0.66 0.42 0.13

1935 C 0 0.21 0.42 0.52 0 0.005 0.67 0 0.012 0.41 1.34 0.27 0.57 0.03 0 0.15 0.07 0.12 0.04 0.03 0.19 0.047 0

6031 C 0.46 2.61 1.52 1.25 0.4 0.17 5.12 0 0.21 1.01 3.1 1.25 1.29 0.26 0.21 0.48 0.29 0.27 0.12 0.6 0.67 0.25 0

2959 C 0.09 0.54 0.42 0.53 0.049 0.047 1.53 0 0.06 0.36 1.2 0.36 0.32 0.074 0 0.17 0.098 0.13 0.057 0.22 0.22 0.22 0

9103 C 0.28 2.53 0.54 0.66 0.31 0.082 0.65 0 0.12 0.28 0.73 0.18 0.28 0.09 0 0.086 0.082 0.077 0.012 0.17 0.14 0.062 0

9423 C 2.09 7.46 6.74 4.71 2.15 0.48 10.1 0 0.81 2.94 9.85 10.18 3.14 0.95 0 1.27 0.93 0.89 0.23 2.66 1.74 0.65 0.74

207 C 0.9 3.49 1.38 0.94 0.64 0.06 1.28 0.1 0.39 1.25 2.61 0.77 0.78 0.46 0 0.74 0.35 0.15 0.31 0.57 1.3 0.57 0.13

8079 C 0.1 0.4 0.2 0.22 0.06 0.018 0.1 0 0.08 0.14 0.32 0.066 0.077 0.039 0 0.06 0.037 0.057 0.001 0.077 0.12 0.04 0

12495 C 0.52 3.86 1.04 0.96 0.41 0.05 0.14 0 0.14 1 1.98 0.44 0.83 0.17 0 0.71 0.19 0 0.25 0.03 0.79 0.34 0

10607 C 0.31 0.87 0.42 0.6 0.068 0.035 0.036 0.04 0.06 0.32 0.84 0.2 0.14 0.06 0.027 0.23 0.05 0.098 0.087 0.063 0.21 0.079 0

7535 C 0.5 2.73 0.72 0.88 0.42 0.094 0.16 0 0.49 1.02 1.93 0.094 0.26 0.26 0 0.77 0.22 0.056 0.34 0.12 0.96 0.41 0.1

10351 C 0.42 1.16 0.72 0.75 0.31 0.1 0.18 0 0.037 1.02 2.02 0.07 0.24 0.28 0.32 0.78 0.21 0.05 0.42 0.08 1.04 0.41 0

3183 C 0.6 2.87 0.94 1.17 0.67 0.16 0.44 0 0.15 1.39 2.73 0.14 0.19 0.28 0 1 0.28 0.06 0.46 0.13 1.21 0.51 0

10863 C 0.09 0.37 0.192 0.2 0.04 0.01 0.026 0 0.076 0.16 0.33 0.055 0 0.038 0 0.076 0.033 0.043 0 0.037 0.093 0.029 0

3695 C 0.56 1.59 1.62 1.29 0.37 0.22 0.16 0 0.08 1.54 2.75 0 0.26 0.37 0.08 1.08 0.27 0.31 0.48 0.17 1.22 0.53 0

11231 C 0.75 3.62 1.38 1.44 0.79 0.2 0.52 0 0.16 1.6 3.2 0.11 0.28 0.36 0 1.15 0.31 0.067 0.47 0.16 1.32 0.59 0

1759 C 0.56 3.22 1.04 1.05 0.64 0.13 0.37 0 0.29 1.16 2.15 0.16 0.3 0.29 0 0.81 0.23 0.082 0.4 0.18 1.06 0.43 0.12

9951 C 0.91 1.27 0.6 1.84 0.01 0.07 0.23 0 0.039 1.25 3.1 1.08 0 0.04 0.06 1.04 0.045 0.09 0.28 0.068 0.41 0.28 0

10975 C 0.13 0.77 0.44 0.33 0.16 0.04 0.026 0 0.16 0.25 0.48 0.13 0.088 0.07 0 0.12 0.04 0.17 0.024 0.065 0.14 0.043 0

303 C 0.036 0.84 0.172 0.07 0.14 0.02 0.0006 0 0.03 0.07 0.15 0.09 0 0 0.05 0 0.006 0 0 0 0 0 0

10287 C 0.25 1.51 0.62 0.4 0.19 0.08 0.17 0 0.28 0.55 1.08 0.078 0.13 0.27 0.018 0.45 0.17 0.058 0.12 0.089 0.66 0.29 0

2095 C 1.74 1.53 0.98 1.64 0 0.2 0.53 0 0.16 1.61 1.68 1.24 0.36 0.21 0 0.46 0.17 0.48 0.13 0.62 0.63 0.21 0.1

6191 C 1.5 4.05 2.88 3.13 0.63 0.44 0.33 0 0.45 4.12 6.71 0.29 1.15 0.95 0.026 3.08 0.58 0.16 1.4 0.27 3.08 1.33 0.14

3931 C 0.16 0.69 0.42 0.32 0.12 0.07 0.1 0 0.17 0.43 1.03 0.12 0.16 0.18 0 0.46 0.12 0.067 0.13 0.059 0.64 0.26 0

8347 C 0.13 0.46 0.28 0.27 0.13 0.02 0.034 0 0.03 0.3 0.64 0.12 0.07 0.08 0 0.2 0.07 0.03 0.065 0.045 0.29 0.093 0

9371 C 0.39 1.54 0.38 1.01 0.2 0.02 0.079 0 0.11 0.74 1.41 0.14 0.15 0.1 0 0.6 0.08 0.04 0.29 0.06 0.46 0.2 0

1179 C 0.27 0.65 0.62 0.48 0.2 0.13 0.22 0 0.086 0.47 1.04 0.069 0.13 0.17 0 0.37 0.13 0.064 0.067 0.11 0.5 0.22 0

4507 C 0.23 0.73 1.1 0.69 0.015 0.14 0.015 0 0.05 0.46 0.76 0.11 0.08 0.08 0.04 0.22 0.028 0.36 0.037 0.08 0.19 0.08 0

3227 C 0.23 0.77 0.62 0.55 0.085 0.11 0.12 0 0.12 0.72 1.93 0.049 0.23 0.22 0.13 0.67 0.13 0.022 0.34 0.031 0.91 0.32 0.13

2203 C 0.55 2.25 0.88 0.97 0.41 0.21 0.44 0 0.32 1.09 1.96 0.11 0.24 0.26 0 0.79 0.25 0.11 0.24 0.24 0.92 0.47 0

411 C 0.47 0.65 0.24 0.16 0.026 0.023 0.025 0 0.14 0.21 0.6 0.08 0 0.04 0 0.23 0.05 0 0.04 0 0.26 0.07 0

5675 C 0.25 1.11 0.54 0.44 0.23 0.035 0.21 0.13 0.043 0.78 1.84 0.29 0.12 0.45 0 0.57 0.49 0 0.35 0.28 1.38 0.45 0.1

9883 C 2.08 18.13 3.28 2.84 2.62 0.13 1.91 0 0.74 3.64 6.73 1.08 0.64 1.19 0.16 2.43 1.11 0.12 1.19 0.34 3.9 1.6 0

204



10907 C 9.44 17.94 11.7 9.84 1.71 0.17 0.64 0.5 0.6 19.64 25.79 0.42 1.16 3.97 0 11.12 1.59 0.77 6.18 0.89 12.66 5.67 0.23

3291 C 0.23 0.53 0.82 0.79 0 0.017 0.14 0 0.024 0.88 1.63 0.3 0.25 0.015 0 0.39 0.04 0 0.09 0.096 0.21 0.16 0

4571 C 1.87 6.02 2.34 1.87 0.58 0.11 1.58 0 0.12 2.07 5.26 3.63 0.41 0.36 0 1.12 0.28 0.67 0.48 0.67 1.33 0.51 0.12

475 C 0.31 2.05 0.6 0.61 0.34 0.06 0.2 0 0.18 0.57 1.15 0.08 0.24 0.16 0.2 0.38 0.13 0.09 0.21 0.11 0.53 0.2 0

5355 C 0.44 1.95 0.4 0.34 0.6 0.03 0.08 0.04 0.13 0.49 0.87 0.12 0 0.18 0.1 0.29 0.13 0 0.07 0.17 0.44 0.16 0

9451 C 0.46 0.4 1.32 0.83 0.06 0.05 0.13 0.16 0 2.23 2.94 0.21 0 1.05 0.37 1.15 0.72 0.036 0.53 0.28 1.33 0.4 0

6379 C 0.41 2.79 0.8 1.13 0.5 0.05 0.27 0 0.41 1.07 2.15 0.28 0.24 0.18 0 0.72 0.16 0.03 0.27 0.03 0.74 0.36 0

4155 C 0.29 0.94 0.62 0.57 0.25 0.05 0.11 0.15 0.054 0.65 1.29 0.19 0.21 0.18 0 0.45 0.12 0.038 0.17 0.058 0.57 0.22 0.12

2539 C 0.56 1.26 1.34 0.99 0.38 0.18 0.29 0 0.23 1.21 2.29 0.18 0.32 0.39 0.022 0.88 0.23 0.13 0.32 0.13 1.14 0.5 0

683 C 0.46 1.13 0.52 0.99 0.097 0.1 0.27 0.02 0.011 0.69 1.42 0.13 0.16 0.15 0 0.51 0.11 0.043 0.16 0.082 0.6 0.24 0

4779 C 0.88 2.17 0.8 1.87 0.29 0.14 0.19 0.03 0.15 1.44 3.11 0.46 0.4 0.28 0 1.08 0.16 0.032 0.38 0.024 0.94 0.44 0.11

12971 C 0.44 1.61 0.62 0.94 0.28 0.035 0.13 0.03 0.09 0.74 1.51 0.18 0.21 0.15 0 0.5 0.11 0.05 0.23 0.07 0.53 0.22 0

5803 C 0.29 2.16 0.46 0.77 0.35 0.039 0.14 0 0.3 0.71 1.34 0.16 0.21 0.16 0 0.46 0.12 0.048 0.19 0.077 0.54 0.24 0.11

4523 C 1.85 6.77 3.66 3.63 1.57 0.3 1.74 0 0.89 4.07 6.72 0.51 1.18 1.05 0 3.43 0.84 0.28 1.66 0.39 3.75 1.67 0

10859 C 0.23 1.75 0.5 0.41 0.23 0.046 0.046 0 0.12 0.57 1.12 0.26 0.19 0.17 0 0.45 0.09 0.026 0.14 0.055 0.52 0.18 0

8619 C 0.47 2.25 0.82 1.15 0.32 0 0.079 0 0.24 1.36 2.11 0.2 0.13 0.11 0 0.77 0.07 0.036 0.37 0.044 0.46 0.24 0

12715 C 0.61 4.09 0.86 1.15 0.64 0 0.28 0 0.3 0.97 2 0.41 0.27 0.2 0 0.76 0.15 0.06 0.34 0.1 0.7 0.32 0

12584 C 0.57 3.2 1.2 1.32 0.3 0.056 0.3 0 0.45 1.13 2.08 0.24 0.24 0.18 0 0.74 0.12 0.1 0.34 0.096 0.61 0.3 0

6872 C 0.62 3.27 0.9 1.69 0.43 0 0.47 0 0.29 1.74 3.47 0.4 0.33 0.19 0 1.51 0.15 0.069 0.64 0.064 1.07 0.53 0

5848 C 0.79 3.19 1.94 2.31 0.11 0.03 0.35 0.05 0.13 2.5 3.9 0.68 0.34 0.19 0 1.29 0.1 0.21 0.59 0.14 0.94 0.65 0

10280 C 1.01 6.11 1.78 2 0.48 0.1 0.59 0 0.33 2.23 4.07 0.5 0.56 0.4 0 1.39 0.3 0.14 0.56 0.17 1.35 0.67 0

7384 C 0.56 5.03 1.26 1.31 0.66 0.03 0.75 0 0.35 1.13 2.72 0.43 0.44 0.26 0 0.88 0.19 0.074 0.42 0.074 0.97 0.42 0.13

12952 C 1.74 12.01 2.3 3.58 0.82 0.055 0.35 0.13 0.36 3.67 8.31 0.86 0.53 0.6 0.04 3.52 0.47 0.2 1.68 0.21 3.3 1.33 0.16

4760 C 1.4 7.26 2.22 2.95 0.76 0.07 1.5 0 1.04 3.03 7.12 1.07 0.45 0.4 0 2.74 0.41 0.08 1.3 0 2.42 1.11 0

664 C 0.22 0.74 0.24 0.26 0 0.05 0.033 0.05 0 0.34 1.04 0.19 0.14 0.2 0.015 0.35 0.16 0.053 0.14 0.075 0.7 0.21 0

3736 C 0.52 3.6 2.12 2.83 0.18 0.012 1 0.11 0.36 2.9 5.31 0.84 0.77 0.32 0.22 1.64 0.21 0.23 0.74 0.19 1.34 0.9 0.1

1944 C 0.3 0.99 2.9 2.56 0.25 0 2.56 0 0.44 2.01 4.71 0.61 0.36 0.32 0 1.07 0.27 0.15 0.4 0.17 1.27 0.69 0

11656 C 0 0.81 1.4 2.09 0.63 0 0.94 0 0.12 0.72 2.61 0.32 0.42 0.19 0.18 0.19 0.14 0.12 0.1 0.12 0.35 0.17 0

12936 C 0.96 1.83 9.98 8.57 0.08 0.1 1.06 0 0.66 13.67 19.46 0.65 4.47 1.38 0 5.63 0.24 0.03 2.48 0.18 4.27 4.29 0

648 C 0.53 3.28 2.52 3.11 1.3 0 1.96 0.18 0.25 1.61 3.61 0.62 0.79 0.39 0.85 0.41 0.36 0.24 0.094 0.24 0.83 0.34 0.22

1160 C 0.77 3.96 3.18 2.87 0.26 0.04 2.65 0 0.33 3.03 7.9 1.27 0.45 0.49 0 2.61 0.35 0.21 1.22 0.2 2.21 1.22 0

5256 C 5.17 18.14 5.14 4.48 2.3 0.16 5.7 0 1.29 4.89 13.43 3.73 3.07 1.44 0.42 3.3 1.7 0.88 1.55 1.26 4.65 1.88 0.49

10376 C 0.45 1.23 4.3 4.05 0.68 0.098 0.8 0 0.66 4.88 8.08 1.07 1.54 0.67 0.14 2.23 0.21 0.26 1.04 0.2 2.1 1.59 0

2184 C 0 0.18 0.24 0.24 0.09 0 0.048 0 0.03 0.15 0.4 0.12 0 0.05 0 0.023 0.034 0.03 0 0.04 0.05 0.02 0

1032 C 0.09 0.17 0.26 0.28 0 0.005 0.07 0.73 0.005 0.2 0.41 0.065 0.11 0 0.24 0.045 0.003 0.016 0.006 0.038 0.04 0 0

8200 C 0 0.29 0.09 0.31 0 0.08 0.078 0 0.076 0.11 0.28 0.05 0.1 0.032 0 0.012 0.013 0 0 0.019 0.031 0.023 0

(Continued)

205



2804 C 0.15 0.93 0.44 0.39 0.16 0 0.11 0 0.17 0.17 0.44 0.1 0.087 0.063 0 0.1 0.048 0.075 0 0.059 0.1 0.067 0

3828 C 0.055 0.45 0.48 1.01 0.047 0 0.23 0.03 0.11 0.54 1.2 0.14 0.15 0.06 0 0.26 0.054 0.011 0.083 0.059 0.28 0.2 0

7924 C 2.17 9.65 3.9 4.2 0.88 0.18 1.73 0 1.51 4.29 12.86 0.82 1.05 0.98 0 3.67 0.69 0.13 1.83 0.17 3.74 1.69 0.12

12020 C 0.2 1.43 0.3 0.58 0.056 0.098 0.14 0 0.27 0.51 1.11 0.036 0.13 0.097 0 0.39 0.06 0 0.15 0.014 0.41 0.21 0

5356 C 0.017 0.12 0.28 0.38 0 0.031 0.14 0 0.026 0.23 0.52 0.15 0.1 0.019 0.22 0.08 0.039 0.031 0 0.051 0.13 0.065 0

9452 C 0.05 0.35 0.12 0.2 0.05 0.0035 0.018 0 0.09 0.12 0.24 0.07 0 0.045 0 0.024 0.023 0.035 0 0.029 0.046 0.012 0

12524 C 0.43 8.85 1.64 0.58 1.96 0 0.99 0 0.81 0.92 2.03 0.2 0.38 0.24 0 0.59 0.17 0.023 0.31 0.15 0.73 0.3 0

4332 C 0.14 0.45 0.52 0.82 0 0.02 0.14 0 0.077 0.56 1.09 0.087 0.07 0.03 0.11 0.25 0.03 0.034 0.04 0.04 0.19 0.15 0

6060 C 0.03 0.15 0.58 0.54 0.016 0.004 0.034 0 0.05 0.61 0.89 0.14 0.24 0.08 0 0.28 0.07 0.087 0.12 0.048 0.297 0.17 0

11180 C 0.29 3.37 0.8 0.93 0.57 0.037 0.39 0 0.35 0.97 2.23 9.96 0.16 0.18 0 0.76 0.14 0.044 0.34 0.06 0.89 0.42 0.11

2988 C 0.96 8.94 3.62 2.25 1.75 0.16 0.94 0 0.48 2.6 7 0.36 0.36 0.54 0 2.03 0.46 0.07 0.97 0 2.16 1.08 0

5292 C 0.14 1.33 0.4 0.51 0.16 0.018 0.075 0 0.19 0.44 0.91 0.069 0.062 0.019 0 0.26 0.034 0.016 0.1 0 0.28 0.12 0

9644 C 0 0.19 0.22 0.45 0.14 0.006 0.03 0 0.037 0.13 0.33 0.11 0 0.05 0 0 0.04 0.035 0 0.05 0.05 0 0

12460 C 0 0.14 0.18 0.23 0 0 0.035 0 0.03 0.11 0.33 0.09 0.09 0 0 0 0.025 0.012 0 0 0 0 0

1708 C 0.51 2.04 0.52 0.69 0.34 0.03 1.4 0.02 0.15 0.57 1.6 0.27 0.1 0.15 0 0.3 0.24 0.03 0.12 0.24 0.58 0.2 0

5804 C 0 0.43 0.58 1.44 0.13 0.02 0.37 0.02 0.085 0.48 1.66 0.3 0.3 0.03 0 0.14 0.09 0.11 0.007 0.14 0.13 0.05 0

4780 C 0.3 1.48 0.64 1.12 0.44 0 0.56 0 0.21 0.62 1.74 0.23 0.34 0.15 0 0.26 0.15 0.11 0.077 0.19 0.35 0.13 0

12972 C 3.63 6.08 3.3 7.21 0.84 0.23 1.47 0.44 0.27 2.86 6.91 4.88 1.02 0.24 0.21 1.29 0.12 9.02 0.27 7.58 0.6 0.4 0.1

5596 C 1.85 3.6 3.42 2.25 0.73 0.04 0.45 0.32 0.19 4.46 7.17 0.94 0.88 1.64 0.32 2.49 0.6 0.39 1.26 0.62 2.85 1.24 0.49

12764 C 0.26 0.52 0.62 0.86 0.059 0.14 0.6 0 0.08 0.96 0.98 0.11 0.57 0.047 0 0.32 0.048 0.11 0.14 0.27 0.26 0.13 0

5852 C 0 0.16 0.38 0.26 0.066 0.013 0.04 0.03 0.05 0.34 0.65 0.087 0.075 0.13 0.1 0.17 0.09 0.058 0.09 0.076 0.27 0.09 0

6876 C 0 0.12 0.28 0.25 0.21 0.02 0.23 0 0.008 0.2 0.49 0.11 0.11 0 0 0.024 0.03 0 0.012 0.013 0.022 0 0

2780 C 0.084 0.36 0.5 0.92 0.11 0.017 0.36 0 0.06 0.34 1.07 0.11 0.075 0.01 0 0.11 0.048 0.035 0 0.056 0.09 0.05 0

7324 C 0 0 0.3 0.37 0.015 0 0.13 0 0.03 0.3 0.7 0.08 0.12 0 0.088 0.069 0.002 0.04 0.003 0 0.1 0.04 0

3228 C 0 0.14 0.44 0.46 0.13 0.013 0.15 0.02 0.05 0.26 0.67 0.11 0.25 0.06 0 0.097 0.09 0.14 0.056 0.063 0.13 0.077 0

9372 C 0 0.06 0.22 0.29 0 0 0.046 0 0.024 0.45 0.71 0.092 0.14 0.016 0 0.21 0.004 0 0.08 0 0.22 0.13 0

9916 C 0 0.21 0.36 0.21 0.65 0 0.06 0 0.015 0.098 0.4 0.12 0.054 0 0.17 0.006 0.024 0 0 0 0.006 0 0

2748 C 0.047 0.15 0.056 0.17 0 0.006 0.01 0 0.002 0.077 0.18 0.025 0.003 0 0.15 0 0 0.01 0 0.002 0 0 0

1724 C 0 0.2 0.54 0.45 1.02 0 0.08 0 0.03 0.32 0.56 0.12 0.11 0.068 0 0.06 0.08 0.045 0.068 0.053 0.11 0.065 0

4852 C 0.069 0.14 0.26 0.19 0.03 0.07 0.097 0 0.082 0.11 0.22 0.058 0 0.056 0.058 0.019 0.04 0.039 0.008 0.058 0.027 0.022 0

8948 C 0.09 0.39 0.24 0.31 0.17 0.009 0.12 0.02 0.06 0.15 0.37 0.08 0 0.058 0.12 0.013 0.045 0.07 0.02 0.12 0.067 0.011 0

9556 C 0.65 2.78 0.64 1.08 0.35 0.01 0.058 0 0.11 1.22 2.27 0.1 0.31 0.21 0 0.97 0.16 0 0.47 0.034 0.97 0.48 0

11327 C 1.14 2.45 1.24 2.01 0.33 0.27 0.36 0 0.2 1.71 3.58 0.22 0.38 0.36 0 1.48 0.27 0.085 0.61 0.085 1.55 0.65 0.14

8687 C 1.47 6.9 2.44 2.66 1.65 0.32 0.51 0 0.26 3.7 6.09 0.08 0.68 0.94 0 2.65 0.7 0.2 1.34 0.3 3.23 1.33 0.32

4591 C 8.76 33.5 12.88 13.4 2.83 1.44 1.27 0.3 0.43 17.75 31.5 0.31 2.57 4.42 0.25 12.5 3.18 0.88 7.14 0.92 14.25 6.66 0.71

5439 C 0.34 1.33 0.72 0.84 0.34 0.085 0.15 0 0.035 1.12 2.25 0.12 0.33 0.3 0.05 9.2 0.19 0.03 0.34 0.057 1.16 0.44 0

(Continued)

206



5615 C 0.33 2.02 0.62 0.53 0.35 0.11 0.1 0 0.2 0.4 0.93 0.24 0.16 0.12 0 0.26 0.08 0.13 0.056 0.1 0.2 0.11 0

12783 C 2.29 6.47 4.54 2.95 1.64 0.47 0.92 0.26 0.61 3.39 3.4 0.47 1.86 0.82 0.26 1.78 0.37 0.13 0.84 0.31 1.8 1.07 0.36

7231 C 2.43 14.44 4.06 4.84 3.43 0.46 0.92 0 0.67 5.61 7.19 0.27 0.91 1.15 0 3.78 0.92 0.084 1.68 0.21 3.75 1.62 0.16

7919 C 1.72 2.72 2.54 3.09 0.21 0.33 0.28 0.13 0.14 3.97 6.89 0.09 0.65 0.92 0 2.99 0.65 0.13 1.38 0.24 3.75 1.54 0.11

9535 C 0.74 2.81 1.04 1.72 0.5 0.18 0.3 0 0.19 1.39 3 0.22 0.24 0.3 0 1.11 0.23 0.07 0.39 0.1 1.09 0.5 0

2111 C 0.21 0.87 0.36 0.48 0.11 0.055 0.12 0 0.075 0.6 1.25 0.086 0.22 0.17 0.073 0.51 0.11 0.029 0.13 0.045 0.64 0.26 0

3135 C 0.9 4.3 1.1 1.8 0.83 0.15 0.38 0 0.18 1.71 3.32 0.36 0.51 0.44 0 1.57 0.32 0.09 0.78 0.091 1.71 0.71 0

9195 C 0.16 0.6 0.22 0.32 0.023 0.051 0.083 0 0.02 0.38 0.9 0.21 0.15 0.13 0.14 0.32 0.092 0.023 0.049 0.038 0.45 0.14 0

6891 C 0.25 1.04 0.6 0.57 0.095 0.11 0.17 0 0.094 0.67 1.3 0.098 0.22 0.19 0.08 0.49 0.097 0.074 0.13 0.082 0.65 0.27 0

1643 C 1.15 4.68 1.3 2.17 0.64 0.2 0.54 0 0.25 1.84 3.84 0.46 0.48 0.41 0 1.45 0.34 0.09 0.54 0.12 1.49 0.65 0

12075 C 0.53 2.75 1.36 1.33 0.43 0.05 1.69 0 0.18 1.14 2.22 0.31 0.25 0.2 0 0.73 0.15 0.13 0.37 0.12 0.72 0.37 0

9323 C 0.26 1.94 0.34 0.62 0.31 0.045 0.17 0 0.11 0.5 1 0.1 0.15 0.11 0 0.3 0.087 0.034 0.15 0.08 0.37 0.16 0

5803 C 0.29 2.16 0.46 0.77 0.35 0.039 0.14 0 0.3 0.71 1.34 0.16 0.21 0.16 0 0.46 0.12 0.048 0.19 0.077 0.54 0.24 0.11

11435 C 0.43 3.64 0.74 0.93 0.51 0.04 0.24 0 0.24 0.97 1.79 0.18 0.25 0.22 0 0.63 0.16 0.04 0.3 0.07 0.75 0.32 0.1

3947 C 0.57 4.11 0.9 1.53 0.62 0.12 0.81 0 0.32 1.41 3.19 0.29 0.26 0.31 0.18 1.18 0.22 0 0.51 0.075 1.22 0.57 0

8088 C 0.51 4.15 0.94 1 0.7 0.025 0.37 0 0.25 1.14 2.28 0.19 0.33 0.23 0 0.83 0.17 0.067 0.43 0.12 0.91 0.39 0.1

12888 C 0.5 1.8 0.72 1.51 0.12 0.018 0.12 0 0.14 1.25 2.27 0.2 0.12 0.14 0 0.9 0.11 0 0.32 0 0.68 0.39 0

600 C 0.32 2.5 0.52 0.82 0.26 0.014 0.25 0 0.14 0.72 2.7 0.2 0.13 0.08 0 0.47 0.06 0.01 0.21 0.01 0.48 0.21 0

4952 C 0.75 4.62 1.68 1.04 1.55 0 0.5 0 0.3 0.94 2.12 0.53 0.46 0.22 0.3 0.54 0.12 0.09 0.24 0.09 0.61 0.28 0

4248 C 1.75 9.06 2.7 1.46 2.06 0.08 1.09 0 1.86 1.71 3.51 0.77 0.77 0.44 0 1.09 0.23 0.05 0.57 0.14 1.25 0.56 0

153 C 0.66 3.58 1.12 1.04 0.57 0 0.18 0 0.38 0.9 2.08 0.25 2.04 0.18 0 0.67 0.12 0.004 0.3 0.066 0.71 0.33 0

5977 C 0.6 1.88 0.88 1.16 0.43 0.14 0.34 0 0.25 1.19 2.25 0.7 0.14 0.29 0 1.12 0.19 0.068 0.35 0.24 1.02 0.53 0

4249 C 0.26 0.41 0.42 0.44 0.082 0.11 0.18 0 0.1 0.43 0.69 0.11 0.11 0.096 0.02 0.28 0.069 0.087 0.012 0.12 0.23 0.13 0

2248 C 0.54 2.53 1.28 0.58 0.67 0.02 0.29 0 0.2 0.54 1.07 0.59 0.57 0.22 0 0.41 0.09 0.04 0.19 0.079 0.47 0.22 0

12488 C 0.49 1.55 0.68 0.95 0.16 0.13 0.52 0 0.087 0.84 1.78 0.18 0.11 0.19 0.04 0.72 0.13 0 0.27 0.064 0.71 0.32 0

4440 C 0.31 1.32 0.66 1.04 0.11 0.036 0.12 0.03 0.11 0.6 1.01 0.099 0.24 0.13 0 0.26 0.089 0.089 0.13 0.12 0.28 0.17 0

1881 C 0.45 0.86 0.4 1.02 0 0.11 0.11 0 0.25 0.9 1.77 0.1 0.15 0.09 0 0.79 0.063 0.009 0.32 0.05 0.51 0.3 0

10440 C 0.72 4.07 1.36 1.28 1.2 0.13 0.73 0 0.48 1.35 3.18 0.067 0.36 0.37 0 1.04 0.23 0 0.46 0.088 1.21 0.54 0.15

7368 C 0.51 4.07 0.98 1.23 0.86 0 0.44 0 0.94 1.07 2.62 0.18 0.19 0.25 0 1.01 0.17 0.04 0.4 0.087 1.06 0.46 0

9049 C 0.23 1.34 0.52 0.73 0 0.08 0.088 0 0.17 0.76 1.55 0.018 0.18 0.092 0 0.58 0.057 0 0.24 0 0.46 0.23 0

4953 C 0.57 2.29 1.48 1.59 0.32 0 0.27 0.58 0.25 1.77 3.44 0.11 0.43 0.31 0 1.44 0.11 0.07 0.76 0.065 1.14 0.6 0

11208 C 0.32 1.8 0.42 0.8 0.15 0.09 0.25 0 0.21 0.77 1.61 0.055 0.18 0.16 0 0.6 0.1 0 0.23 0.015 0.61 0.3 0

6617 C 0.29 1.36 0.56 0.59 0.43 0.084 0.21 0 0.25 0.5 1.19 0.13 0.15 0.11 0 0.34 0.078 0.044 0.12 0.073 0.31 0.16 0

12232 C 0.08 0.29 0.1 0.23 0 0.08 0.068 0 0.077 0.19 0.33 0 0.068 0.031 0.15 0.099 0.014 0 0.006 0.004 0.085 0.058 0

9433 C 1.5 1.59 1.34 1.9 0.23 0.11 1.87 0 0.12 1.22 2.43 0.57 0.78 0.28 0 0.55 0.17 0.24 0.07 0.46 0.5 0.26 0

6041 C 0.11 0.24 0.22 0.23 0.046 0.067 0.084 0 0.12 0.25 0.36 0.072 0.088 0.058 0 0.12 0.039 0.036 0.016 0.053 0.081 0.054 0

(Continued)

207



12505 C 0.2 0.71 0.38 0.41 0.053 0 0.28 0 0.076 0.44 0.89 0.056 0.13 0.069 0 0.16 0.037 0 0.033 0.092 0.15 0.092 0

2521 C 0.18 0.47 0.4 0.45 0.076 0.068 0.45 0 0.11 0.27 0.55 0.12 0.2 0.073 0 0.093 0.052 0.056 0.013 0.097 0.07 0.065 0

2713 C 0.13 0.42 0.24 0.48 0 0.035 0.22 0 0.02 0.21 0.45 0.12 0.2 0.042 0.083 0.027 0.014 0.053 0.015 0.14 0.069 0.017 0

7065 C 0.12 0.23 0.32 0.29 0.03 0.072 0.13 0 0.09 0.087 0.28 0.077 0.087 0.067 0 0.053 0.047 0.068 0 0.08 0.044 0.039 0

10137 C 0.072 0.27 0.26 0.14 0.052 0.068 0.093 0 0.088 0.055 0.25 0.056 0 0.062 0.026 0.035 0.044 0.056 0 0.059 0.051 0.034 0

9823 A 3.43 11.73 4.82 4.86 1.95 0.2 0.93 1.46 1.11 8.11 18.05 1.39 1.07 2.75 0.54 5.65 2.75 0.74 2.62 2.11 7.67 2.28 0

6751 A 6.77 11.87 6.18 3.51 1.47 0.22 1.11 0.4 0.41 7.85 18.96 2.23 0.88 2.97 0 6.6 3.43 0 3.58 2.75 11.99 4.31 0

10591 A 17.84 81.05 15.86 18.6 28.09 0 5.79 1.82 15.45 13.88 39.23 15.58 9.66 5.4 0 11.78 4.32 2.53 5.71 3.31 13.31 7.32 0.59

5007 A 6.32 12.98 16.42 2.67 34.15 0 8.86 0 1.38 3.33 10.33 21.5 8.89 1.19 0 1.77 0.33 0.67 0.69 2.03 1.65 0.93 0

1935 A 1.92 20.11 3.26 2.85 4.44 0.22 5.29 0 0.97 2.74 6.02 4.86 3.68 1.01 0 1.1 0.83 0.42 0.49 1.05 2.07 0.64 0.3

6031 A 7.87 20.24 9.5 3.6 8.09 0.3 13.59 0 1.38 4.02 10.83 12.69 3.58 1.43 0 1.84 0.99 0.56 0.71 2.45 2.51 1.04 0

2959 A 0.78 2.4 1.94 1.74 0.51 0.17 3.46 0 0.35 2.01 5.69 1.31 2.62 0.76 0.16 1.34 0.85 0.55 0.75 1.62 2.45 0.93 0.22

9103 A 0.9 4.24 1.28 1.3 0.86 0.04 0.92 0.08 0.26 0.66 1.6 1.77 1.08 0.11 0 0.2 0.17 0.16 0.048 0.48 0.33 0.1 0.24

9423 A 0.99 3.08 2.12 2.55 1.15 0.2 1.64 0.2 0.24 1.43 3 1.33 0 0.55 0 0.47 0.28 0.33 0.11 1.17 0.81 0.3 0.21

207 A 3.69 13.05 4.28 2.1 4.99 0.23 1.54 0 0.99 2.25 5.88 3.99 1.61 0.89 0.05 1.18 0.53 0.37 0.48 1.04 1.92 0.9 0

8079 A 0.78 3.45 0.8 0.48 1.24 0.16 0.6 0 0.46 0.66 0.92 0.18 0.3 0.5 0 0.27 0.09 0.075 0.13 0.26 0.31 0.19 0.12

12495 A 0.28 1.38 0.48 0.49 0.23 0.014 0.08 0.03 0.16 0.78 1.05 0.08 0.12 0.23 0 0.47 0.088 0 0.19 0.11 0.69 0.39 0

10607 A 1.26 4.97 1.56 1.83 1.47 0.22 0.57 0 0.36 1.9 2.97 0.19 1.41 0.42 0 1.09 0.25 0 0.43 0.19 1.11 0.59 0

7535 A 0.45 3.21 0.48 0.54 0.72 0.05 0.38 0 0.24 0.49 0.81 0.11 0.17 0.14 0.2 0.22 0.09 0.05 0.1 0.12 0.29 0.12 0

10351 A 1.37 8.95 2.28 1.89 1.37 0.14 0.88 0 0.54 2.71 3.45 0.33 0.97 0.55 0 1.55 0.38 0.069 0.73 0.25 1.59 0.75 0.2

3183 A 0.68 5.07 0.98 1.19 1.07 0.13 0.41 0 0.38 1.32 1.73 0.16 0.29 0.29 0 0.74 0.19 0.053 0.33 0.21 0.79 0.4 0.13

10863 A 1.39 4.66 1.46 1.7 1.52 0.17 0.52 0 0.36 1.94 2.75 0.074 0.29 0.38 0 1.07 0.23 0.023 0.45 0.15 1.1 0.55 0.18

3695 A 2.49 14.7 4.46 4.23 2.04 0.47 1.07 0 0.72 5.85 7.98 0.28 0.64 1.22 0 3.69 1.11 0.25 1.85 0.51 4.39 1.98 0.3

11231 A 1.86 9.59 2.38 2.65 2.24 0.33 0.88 0 0.61 3.25 3.38 0.35 0.45 0.66 0 1.64 0.42 0.086 0.62 0.24 1.42 0.77 0.27

1759 A 2.31 7.26 2.26 2.1 1.97 0.27 1.64 0 0.95 2.13 2.62 0.27 0.45 0.59 0 1 0.23 0.11 0.4 0.3 1.03 0.7 0.22

9951 A 1.26 3.36 2.1 2.07 0.14 0.06 0.27 0.15 0.37 3.05 4.58 0.19 0.39 0.99 0.11 1.9 0.36 0.09 0.82 0.26 2.02 1.05 0

10975 A 7.91 22.96 12.34 20.2 2.65 0.29 6.54 14.1 1.79 12.08 36.48 1.68 4.91 4.14 0 12.97 1.27 0.22 7.55 5.3 16.56 5.43 0

303 A 1.74 3.91 0.96 1.26 1 0.13 0.72 0 0.38 1.01 1.37 0.11 0.25 0.27 0 0.54 0.15 0.057 0.2 0.21 0.57 0.32 0.12

10287 A 6.93 68.86 10.4 5.52 29.84 0.29 5.42 0.78 2.84 8.82 15.85 6.75 8.65 2.01 0.18 6.92 1.79 0.53 3.26 0.98 6.66 2.48 0.34

2095 A 4.14 32.25 4.5 3.46 5.97 0.19 2.47 0.6 1.56 3.5 7.72 3.72 2.66 0.97 0.09 1.56 0.91 0.35 0.64 0.58 2.51 1.12 0.42

6191 A 1.45 12.69 2.76 2.87 2.68 0.21 0.61 0 0.63 3.57 3.24 0.11 0.58 0.63 0 1.74 0.44 0.07 0.71 0.14 1.6 0.85 0.24

3931 A 7.56 49.65 8.6 4.53 9.42 0.27 4.38 0.59 1.46 6.41 13.64 5.17 9.78 1.99 0 3.78 1.88 0.36 2.21 1 6.22 2.54 0.44

8347 A 0.59 3.36 0.9 0.99 0.83 0.12 0.36 0 0.25 1.03 1.4 0.14 0.31 0.23 0 0.54 0.15 0.052 0.21 0.11 0.55 0.29 0.18

9371 A 1.68 9.2 3.1 0.87 1.8 0.05 0.57 0.06 0.41 1.1 1.88 0.51 1.22 0.23 0 0.49 0.21 0 0.15 0.19 0.61 0.28 0

1179 A 0.78 3.42 1.2 0.97 1.49 0.16 0.53 0 0.36 1.06 1.33 0.32 0.18 0.21 0 0.48 0.09 0.06 0.15 0.12 0.46 0.25 0

4507 A 0.26 1.6 0.34 0.39 0.45 0.05 0.28 0 0.12 0.44 0.77 0.13 0.098 0.067 0 0.25 0.07 0 0.046 0 0.24 0.11 0

(Continued)

208



3227 A 9.63 51.77 14.46 8.76 8.61 0.63 6.94 0 1 13.77 30.26 3.67 2.03 3.63 0.3 9.56 3.74 1.41 5.17 2.11 14.76 5.41 0.5

2203 A 0.49 3.29 0.68 0.69 0.87 0.2 0.34 0.11 0.44 0.83 0.93 0.048 0.14 0.22 0 0.36 0.095 0 0.12 0.053 0.35 0.25 0.1

411 A 1.9 13.06 2.16 2.44 2.66 0.24 0.82 0.2 1.05 2.69 3.03 0.69 0.31 0.65 0 1.36 0.39 0.045 0.51 0.23 1.29 0.77 0.11

5675 A 1.42 14.86 2.8 1.83 3.56 0.22 1.14 0 0.8 1.82 3.21 0.9 0.61 0.39 0 0.61 0.33 0.14 0.23 0.22 0.79 0.36 0

9883 A 2.79 25.37 3.94 3.27 3.43 0.23 1.18 0.39 1.13 4.02 6.39 1.61 6.39 0.98 0 2.17 0.88 0.18 0.97 0.32 2.81 1.3 0

10907 A 39.14 200 22.04 13.5 5.83 0.8 9.78 0 10.11 28.49 65.5 7.08 4.77 6.62 0.28 42.9 5.36 1.93 7.32 1.07 26.5 9.05 0

3291 A 2.76 3.24 2.9 3.23 0.13 0.097 0.2 0.33 0.19 4.26 6.64 0.87 1.52 0.63 0 2.96 0.2 0.49 0.94 0.38 0.96 0.33 0

4571 A 2.12 26.33 3.9 1.94 5.29 0.17 1.67 0.33 1.26 2.93 4.92 1.49 0.43 0.68 0.034 1.47 0.46 0.09 0.65 0.35 1.85 0.84 0.19

475 A 1.52 7.82 1.38 2.01 0.79 0.29 1.03 0.31 0.93 2.11 4.19 0.98 0.26 0.61 0.07 1.24 0.74 0.18 0.46 0.71 2.22 0.85 0

5355 A 5.4 7.86 7.36 4.84 1.13 0.05 0.39 0.92 0.12 10.62 15.58 2.25 3.88 1.97 0.016 6.32 0.93 0.44 2.96 0.89 3.75 1.66 0

9451 A 7.22 46.73 15.66 7.07 8.06 0.67 2.68 1.13 3.74 18.93 42.92 2.19 2.61 7.63 0 20.3 7.11 0.8 8.34 4.82 45.1 11.45 1.7

6379 A 1.4 8.27 2.7 2.68 2.03 0.23 0.79 0 0.75 3.53 6.46 0.79 0.96 0.96 0 2.89 0.81 0.25 1.31 0.41 3.18 1.53 0.06

4155 A 1.19 7.56 0.9 1.07 1.04 0.13 0.48 0.17 0.4 0.91 1.8 0.71 0.42 0.33 0 0.48 0.26 0.061 0.11 0.24 0.7 0.29 0.1

2539 A 2.26 10.51 3.72 4.14 3.48 0.54 0.79 0 0.68 5.5 5.68 0.31 0.64 1.16 0 3.48 0.93 0.15 1.44 0.34 3.35 1.56 0.13

683 A 1.12 9.96 1.56 1.88 2.42 0.16 0.67 0 0.58 2.04 2.75 0.21 0.52 0.45 0 1.22 0.36 0.06 0.43 0.17 1.11 0.55 0

4779 A 2.1 4.6 3.5 3.33 0.31 0.34 0.58 0 0.27 4.93 10.67 0.25 0.86 1.4 0 3.76 1.24 0.08 1.81 0.35 5.51 2.19 0.25

12971 A 1.64 8.54 1.68 1.52 0.62 0.11 0.1 0 0.5 2.34 3.51 0.14 0.27 0.47 0.005 1.57 0.26 0.1 0.75 0.13 2.25 1.04 0

5803 A 2.34 18.15 3.24 3.38 4.36 0.66 1.88 0.46 1.68 3.81 4.57 0.72 0.59 0.82 0 1.95 0.51 0.21 0.92 0.53 1.95 1.13 0.36

4523 A 9.51 58.24 9.88 10.9 7.3 1.21 3.38 0.93 4.79 12.12 18.25 4.84 2.15 3.58 0 8.92 2.59 0.69 4.51 1.68 10.43 5.14 0.25

10859 A 2.6 16.93 4.6 4.64 2.87 0.17 0.9 0.3 2.5 3.58 6.75 3.35 3.48 1.03 0 2.36 0.74 0.63 0.96 0.54 2.37 1.23 0

8619 A 21.37 65.92 28.46 9.33 12.22 1.9 20.75 0 4.71 14.35 24.21 5.96 5.66 5.42 0 8.94 3.13 1.54 5.32 2.71 13.33 6.53 1.56

12715 A 11.15 53.15 12.68 10.1 5.97 0 10.14 0 2.97 14.59 33.05 11.61 3.18 3.65 0.22 9.88 3.17 3.71 5.03 2.09 12.6 5.85 0.84

12584 A 7.66 42.36 11 9.2 6.51 1.42 10.59 0 4.45 10.53 20.11 4.91 2.54 3.81 0 9.1 2.11 1.32 3.67 1.26 9.98 5.2 0.89

6872 A 13.2 69.7 11.9 15.3 6.14 1.14 2.82 0.91 2.54 15.62 27.42 2.3 3.55 4.41 0 12.33 3.19 0.92 6.47 1.66 14.36 6.9 0.48

5848 A 2.44 8.86 2.94 3.13 1.35 0.19 2.24 0.23 1.57 2.45 5.56 4.43 1.84 0.98 0 1.4 0.55 0.72 0.56 1.71 2.04 0.88 0.14

10280 A 3.03 19.98 4.16 3.04 3.55 0.21 3.05 0 1.7 4.03 8.48 3.11 2.48 0.89 0 2.17 0.75 0.46 1 0.86 2.78 1.23 0.19

7384 A 2.55 10.31 2.08 2.58 1.17 0.08 0.37 1.11 0.39 3.83 8.82 0.49 2.05 1.18 0.32 3.64 0.97 0.18 2.41 0.47 4.86 1.56 0.36

12952 A 1.54 9.43 2.08 2.82 0.59 0.17 0.48 0.23 0.77 2.56 8.57 1.45 1.13 0.71 0 2.59 0.6 0.29 1.17 0.2 2.9 1.01 0

4760 A 12.63 52.68 12.26 11.7 2.8 0.57 3.47 0 7.58 21.47 58.8 9.54 4.14 5.03 0 21.9 3.48 1.11 8.84 1.51 26.5 8.11 0.96

664 A 22.06 74.33 21.9 22.8 5.45 0.93 5.57 0 7.7 32.6 76.5 11.28 5.13 8.22 0.13 27.8 4.95 1.98 13.7 2.93 33 13.36 0.37

3736 A 38.65 83.25 33.7 33 4.81 1.335 5 2.5 9.5 42.4 125.6 35.1 18.5 9.55 0 37.35 7.1 4.5 17.5 7.2 43.5 12.35 1.23

1944 A 6.9 7.51 3.56 4.59 0.56 0.18 1.02 0.33 0.34 5.66 10.37 3.14 0.73 0.98 0.16 3.87 0.81 0.85 1.66 0.92 4.24 1.83 0

11656 A 1.79 5.85 1.86 1.79 0.32 0.19 0.27 0 0.61 2.73 6.08 0.5 0.95 1.21 0.29 1.96 0.84 0.26 1.35 0.59 2.88 1.13 0

12936 A 2.33 6.94 3.3 3.44 0.44 0.12 0.29 0 0.64 5.69 8.06 0.29 0.77 1.09 0 3.69 0.65 0.21 1.42 0.32 3.22 1.52 0

648 A 5.22 5.98 3.06 3.22 1.17 0.18 1.66 0.2 0.2 3.69 10.04 2.21 0.97 1.61 1.45 2.71 2.21 0.8 1.48 2.61 6.18 1.63 0.31

1160 A 2.27 18.11 4.72 3.34 2.41 0.17 0.74 0 2.46 7.63 15.08 0.44 1.05 1.8 0 6.1 1.54 0.47 3.26 0.71 10.9 4.65 0.57

(Continued)

209



5256 A 8.15 6.69 3.7 4.14 0.9 0.28 1 0 0.44 5.24 12.62 4.98 0.51 2 0.17 3.8 2.33 0.62 2.17 1.39 7.84 2.67 0

10376 A 5.09 6.61 4.78 4.63 0.35 0.37 1.04 0 1.3 6.31 19.42 1.82 4.19 2 0.53 4.93 1.9 0.89 2.48 1.01 7.74 2.78 0.13

2184 A 9.59 24.49 6.68 5.59 1.45 0.22 11.17 0 2.96 7.33 18.24 6.98 1.11 1.77 0.42 4.1 1.64 1.55 1.86 1.81 6.37 2.56 0.22

1032 A 10.61 21.99 9.94 10.9 1.82 0.39 2.93 1.16 0.57 17.05 34.87 5.08 1.75 4.08 0 12.46 3.82 0.58 6.41 1.4 16.95 7.75 1.7

8200 A 9.7 59.92 8.24 9.28 4.06 0.31 3.33 0 4.4 12.76 24.66 2.59 5 3.76 0 7.86 2.38 1.2 4.12 2.08 10.37 4.67 0.15

2804 A 8.58 31.27 9.74 5.48 14.88 0.44 10.4 0 1.62 6.3 13.63 7.22 2.44 2.01 0.2 2.42 1.87 0.99 1.28 3.66 5.18 1.79 0

3828 A 6.5 24.65 5.08 6.05 3.52 0.34 7.54 0 2.24 5.22 17.76 3.83 3.04 1.9 0.43 3.26 1.41 0.71 1.55 1.84 4.84 1.91 0

7924 A 12.79 64.51 12.16 10.4 6.37 0.62 5.99 1.09 2.9 15.42 34.9 9.22 4.34 4.88 0.76 10.88 3.33 1.71 5.59 3.16 15.92 6.46 0.43

12020 A 8.97 45.91 9.64 7.11 5.78 0.48 6.09 0 4.54 11.13 21.87 1.94 2.5 3.26 0.13 7.81 2.11 1.06 4.05 2.4 10.28 4.52 0.18

5356 A 4.45 16.29 6.88 6.47 4.34 0.33 3.05 0.81 2.26 7.25 14.58 2.65 2.33 3.51 0 4.15 1.83 0.74 2.23 2.72 7.44 3.16 0.71

9452 A 5.05 20.23 6.1 6.31 2.96 0.39 2.15 0 2.23 7.46 20.83 4.19 10.04 1.45 0 7.02 1.7 0.58 4.24 1.56 8.54 3.84 0.37

12524 A 2.8 14.7 3.4 3.67 2.09 0.21 2.83 0 0.72 5.16 9.13 2.06 0.89 1.2 0.053 4.39 1.14 0.57 2.13 0.58 4.61 2.05 0.25

4332 A 5.02 19.76 3.82 4.08 1.94 0.28 3.5 0 1 4.25 9.11 1.6 1.38 1.16 0 2.64 0.77 0.3 1.25 0.68 3.15 1.5 0.35

6060 A 4.43 15.23 6.52 5.81 8.57 0.31 5.17 0.7 3.49 5.51 12.99 4.73 2.77 1.66 0.2 3.36 0.89 1.44 1.52 2.49 3.31 1.67 0.46

11180 A 6.25 13.8 4.88 5.72 1.42 0.14 2.21 0.45 1.4 6.25 15.52 7.18 3.22 1.76 0 4.38 1.25 1.76 2.21 2.14 4.74 1.65 0.24

2988 A 17.91 83.67 11.9 14 9.43 0.87 19.97 1.43 4.89 12.47 36.69 14.57 10.43 4.55 1.19 7.91 3.58 1.5 3.87 3.45 11.64 4.88 0.71

5292 A 5.7 31.22 6.12 7.94 8.51 0 6.29 0.89 3.55 6.55 15.09 5.02 2.49 1.76 0.37 4.04 1.46 0.92 1.82 1.44 4.29 1.77 0.56

9644 A 4.29 16.84 5.28 5.37 7.02 0.37 11.98 0 1.69 4.23 12.48 4.95 3.21 1.24 0.61 2.04 1.41 1.09 0.96 2.63 3.26 1.2 0.41

12460 A 5.3 34.3 5.66 6.84 3.5 0.23 4.4 0 6.93 6.79 14.46 5.84 2.85 2.26 0 3.53 1.54 1.28 1.64 2.76 5.56 2.09 0.56

1708 A 5.57 21.65 3.88 2.93 1.75 0.27 7 0 1.53 4.47 9.85 1.69 0.89 1.1 0.2 2.34 0.95 0.61 1.14 1.22 3.68 1.49 0.36

5804 A 3.99 20.78 4.36 7.12 2.91 0.23 5.64 0.39 2.7 4.69 14.26 3.19 1.78 1.63 0.63 3.07 2.07 1.22 1.62 2.16 4.92 1.62 0.5

4780 A 2.83 13.88 2.82 2.94 1.02 0.09 2.74 0 2.11 4.26 9.64 1.46 0.94 1.05 0.12 2.64 0.9 0.2 1.26 0.69 3.4 1.36 0

12972 A 15.06 18.25 16.08 18.9 1.24 0.52 1.55 0.73 1.03 28.52 43.38 3 5.97 4.71 0 13.25 2.41 1.75 5.72 2.95 9.88 4.93 0.53

5596 A 9.9 11.3 18.8 13 0.46 0.07 0.67 1.26 0.64 26.25 40.5 1.31 1.17 1.92 0.79 11.82 2.43 1.57 5.17 1.71 7.52 3.9 0.26

12764 A 1.67 6.13 7.14 1.66 1.64 0.16 2.5 0.21 1.41 5.84 9.44 6.15 0.99 1.71 0.39 2.55 1.39 0 1.17 0.79 3.63 1.29 0.5

5852 A 3.13 3.7 5.5 3.14 1.61 0.13 0.41 0 1.66 5.84 9.61 1.49 3.03 3.17 1.61 3.42 2.24 0.79 1.5 1.41 3.9 1.93 2.88

6876 A 46.4 140.5 65.8 19 131.5 3.65 51 2 3.5 52 97.5 39.7 19.75 10.5 0.67 6.5 7.5 0.9 1.4 13 15.5 1.95 0.29

2780 A 7.59 29.48 5.58 4.84 2.2 0.51 12.78 0 4.82 6.05 15.49 6.03 2.1 1.54 0.47 2.93 1.56 0.9 1.43 2.89 4.8 1.88 0.47

7324 A 3.58 14.42 5.32 8.73 9.07 0.24 10.36 0 2.2 5.44 13.56 4.64 3.53 1.58 0 2.66 1.83 1.54 1.08 2.22 3.66 1.53 0.6

3228 A 10.72 35.08 13.26 6.32 10.36 0.84 18.31 0.97 8.04 7.89 24.54 9.17 2.9 2.62 0.49 4.55 2.23 1.91 2.34 6.95 8.05 3.68 0.91

9372 A 10.73 10.8 9.6 9.42 0.38 0.26 4.07 0 3.36 9.64 33.67 24.59 11.07 1.42 0.15 8.79 1.22 5.6 3.53 5.59 4.39 2.04 0.39

9916 A 65.5 189 363 48 886.5 0 108 0 10 78 171.5 53.5 18 4.65 1 10.5 4.65 6.5 2.15 11.3 2 0.55 8.4

2748 A 7.91 46.28 8.22 6.03 8.96 0.62 11.09 0.62 2.39 7.88 18.52 7.19 3.1 2.26 0.46 4.42 1.71 1.1 2.31 3.03 6.8 3.04 0.48

1724 A 18.59 78.52 16.62 9.15 67.44 0 48.36 0 2.13 13.09 25.4 27.31 3.17 2.38 0.36 2.17 1.96 10.4 1.15 10.4 4.52 0.94 0.96

4852 A 11.71 7.98 10.8 13 0.37 0.44 0.75 0.69 0.42 22.67 28.3 0.46 4 1.97 0 11.56 0.83 0.66 3.64 1.04 5.2 3.35 0.47

8948 A 8.83 57.66 18.28 6.91 43.38 0 20.68 0 2.83 7.91 15.49 9.18 2.77 1.72 0 2.17 1.38 1.05 0.91 2.22 3.74 1.85 0.8

(Continued)

210



9556 A 1.36 11.89 1.52 2.61 1.91 0.04 0.15 0.09 0.47 1.71 5.13 0.47 0.74 0.4 0 1.78 0.29 0.013 0.85 0 1.78 0.63 0

11327 A 1.23 6.35 1.54 1.6 1.08 0.24 0.65 0 0.36 1.92 3.64 0.27 0.35 0.61 0 1.63 0.44 0.2 0.89 0.23 2.07 0.9 0

8687 A 3.6 19.19 4.86 5.79 3.88 0.72 0.88 0 0.8 6.79 9 0.99 1.58 1.64 0 4.18 0.98 0.18 1.85 0.42 4.4 1.9 0.54

4591 A 6.12 12.92 10.58 10.1 0.85 1.22 0.57 0.43 0.23 14.44 24.85 0.41 2.16 3.85 0 10.65 2.88 0.7 5.93 0.74 13.74 5.79 0.73

5439 A 2.99 15.83 4.48 5.51 2.62 0.64 0.41 0.19 0.82 6.69 8.06 0.7 0.6 1.44 0 4.42 1.19 0.15 1.93 0.38 4.57 2.03 0.25

5615 A 3.12 9.48 2.66 2.7 1.75 0.33 0.3 0 0.39 3.85 5.99 0.28 0.44 0.97 0 2.92 0.85 0.1 1.22 0.22 3.4 1.36 0.24

12783 A 2.15 8.36 4.18 2.91 1.85 0.51 1.13 0.15 0.69 3.53 3.96 0.9 1.3 0.99 0.24 1.97 0.48 0.13 0.86 0.39 2.1 1.2 0

7231 A 5.51 22.81 7.88 8.07 5.85 0.85 1.32 1 1.04 9.33 12.52 0.79 2.8 2.27 0 6.43 1.39 0.25 3.16 0.44 6.73 2.91 0.28

7919 A 1.67 7.66 2.44 2.72 1.27 0.3 0.56 0 0.47 3.21 5.7 0.33 0.43 0.78 0 2.45 0.64 0.16 1.18 0.37 2.81 1.24 0

9535 A 1.01 7.5 1.3 1.32 0.84 0.14 1.01 0 0.46 1.22 2.47 1.02 0.55 0.3 0 0.66 0.24 0.16 0.21 0.32 0.85 0.41 0

2111 A 0.46 1.45 0.96 0.78 0.08 0.069 0.24 0 0.1 1.26 3.1 0.19 0.29 0.55 0.06 1.14 0.35 0.09 0.54 0.13 1.83 0.68 0

3135 A 0.37 1.4 0.36 0.32 0.038 0.044 0.15 0.05 0 0.56 1.36 0.19 0.15 0.39 0.03 0.42 0.37 0.093 0.27 0.22 1.24 0.38 0

9195 A 1.21 7.6 1.48 1.72 0.87 0.11 0.74 0.37 0.24 1.56 3.35 1.37 0.48 0.44 0 0.89 0.48 0.18 0.29 0.4 1.38 0.61 0

6891 A 1.54 3.74 3 2.97 0.61 0.41 0.41 0.23 0.14 4.21 7.83 0.16 0.48 1.27 0 3.31 1.02 0.17 1.56 0.35 4.41 1.82 0.27

1643 A 0.95 5.35 1.2 1.84 0.44 0.18 0.27 0 0.34 1.83 3.06 0.46 0.31 0.35 0 1.35 0.24 0.055 0.59 0.096 1.37 0.64 0

12075 A 1.14 6.6 1.8 1.84 0.63 0.2 0.56 0.18 0.48 2.3 4.22 0.36 0.71 0.7 0 1.58 0.54 0.1 0.7 0.37 2.29 1.06 0.21

9323 A 2.25 16.34 5.08 3.38 2.63 0.33 3.17 0 3.74 3.89 7.02 5.42 2.5 1.31 0 1.99 0.72 0.58 0.92 1.6 3.09 1.5 0.22

5803 A 2.34 18.15 3.24 3.38 4.36 0.66 1.88 0.46 1.68 3.81 4.57 0.72 0.59 0.82 0 1.95 0.51 0.21 0.92 0.53 1.95 1.13 0.36

11435 A 12.08 27.66 12.3 12.1 3.51 1.02 2.18 2.39 2.77 15.39 29.67 4.46 5 5.61 0.44 10.89 2.99 0.74 6.3 3.63 14.71 6.89 0.83

3947 A 4.05 21.06 6.28 5.26 2.61 0.29 2.92 0 2.56 5.38 14.14 5.47 3.74 1.72 0.22 3.76 1.41 0.99 1.53 1.81 5.5 2.26 0

8088 A 4.87 37.28 6.42 4.86 4.67 0.52 4 0 3.4 6.56 11.83 3.47 1.83 1.67 0 4.65 1.4 0.79 2.07 1.57 5.55 2.55 0.11

12888 A 10.92 53.08 11.68 7.93 5.77 0.62 5.86 1.65 4.12 13.29 22.51 6.91 2.64 3.33 0 7.49 1.56 1.02 3.86 2.04 9.58 4.28 0.4

600 A 3.01 13.68 3.76 5.39 1.93 0.11 1.43 0.23 0.76 3.32 9.26 2.73 2.51 0.92 0 1.74 0.61 0.64 0.65 0.75 2.12 0.9 0.18

4952 A 37.07 62.31 30.06 9.65 13.76 1.26 15.46 0 4.51 13.14 35.41 11.06 10.55 4.02 0.6 8.93 1.79 2.09 4.88 2.38 10.98 5.68 0.8

4248 A 13.69 35.94 9.22 6.36 9.53 0.53 4.95 0 2.86 7.69 12.53 2.06 0.95 1.95 0 4.46 1.48 0.49 2.3 1.26 4.98 2.61 0.52

153 A 14.19 30.47 13.52 14.4 1.12 1.16 1.76 0 1.19 20.14 36.77 1.46 2.51 4.9 0 13.65 4.21 1.2 8.03 2.31 19.8 7.78 0

5977 A 5.86 5.57 2.54 1.86 0.76 0.25 1.61 1.16 1.16 2.84 4.98 2.33 0 1.84 0 1.86 1.55 1.66 1.62 3.96 4.6 1.67 0.22

4249 A 4.42 19.28 5.42 5.64 2.16 0.44 1.8 0 1.63 6.45 12.42 0.64 0.83 1.68 0 5.73 1.36 0.59 2.72 1.25 6.73 2.8 0.22

2248 A 18.31 41.56 20.48 7.73 15.99 0.91 5.62 0 1.3 11.62 19.55 4.88 10.97 3.36 0 7.61 2 0.82 4.36 1.38 8.65 4.31 0.91

12488 A 4.31 31.09 6.1 4.86 4.81 0.28 3.46 0.56 1.75 5.17 11.93 4.23 1.94 1.73 0.35 2.57 1.11 0.48 1.25 1.15 4.08 1.61 0

4440 A 1.81 11.42 2.76 1.61 2.53 0.25 2.3 0.23 0.93 1.84 4.56 2.36 0.96 0.65 0 0.97 0.38 0.38 0.36 1.12 1.41 0.62 0

1881 A 3.06 10.49 4 4.6 0.48 0.48 1.04 0.34 0.46 5.36 10.94 0.29 0.73 1.27 0 4.36 1.23 0.4 2.18 0.71 5.85 2.26 0.17

10440 A 4.83 37.02 5.36 5.76 4.1 0.19 3.15 0 3 6.16 16.41 4.76 1.54 1.94 0.08 4.42 1.46 0.58 2.41 0.92 6.68 2.72 0.48

7368 A 31.84 118.5 16.88 13 8.88 0.75 4.8 0 5.31 17.92 40.5 6.41 12.68 4.47 0.23 12.62 4.41 1.02 6.69 1.44 17.15 7.04 0.57

9049 A 10.08 46.99 15.64 11.1 5.87 0.85 3.37 0 2.48 16.83 40.1 11.89 9.51 4.07 0.28 11.37 3.65 0.89 6.42 1.95 13.8 5.78 0.29

4953 A 0.88 4.75 1.44 1.89 0.77 0.1 0.17 0.25 0.27 1.64 3.52 0.41 0.69 0.37 0 1.39 0.32 0.11 0.59 0.093 1.33 0.58 0

(Continued)

211



11208 A 4.47 37.47 4.88 6.15 4.07 0.22 1.52 0 1.62 7.24 12.36 1.64 1.3 1.86 0.14 4.73 1.6 0.39 2.21 0.69 6.22 2.62 0

6617 A 74 138.5 28.28 15.3 8.07 4.7 28.64 0 9.12 46.5 96 9.21 7.14 7.08 0.58 19.5 4.65 3.61 7.3 6.75 21.65 8.85 0.35

12232 A 5.6 35.75 6.08 7.73 3.83 0.48 1.43 0.51 1.43 8.7 14.39 1.22 1.21 1.69 0.33 6.4 1.7 0.37 3.15 0.73 7.23 3.03 0

9433 A 7.26 38.57 5.64 4.7 1.89 0.39 7.24 0 4.65 7.38 18.37 3.7 1.56 2.46 0.56 4.94 2.38 0.82 2.59 3.04 9.71 3.15 0

6041 A 3.85 20.77 5.34 4.85 3.01 0.24 0.9 0 1.78 5.96 11.55 1.47 0.82 1.73 0 5.55 1.19 0.46 2.78 0.88 6.89 3 0

12505 A 2.3 4.45 1.68 1.42 0.74 0.26 1.74 0.32 0 2.31 5.27 0.96 0.74 2.02 0 1.22 1.64 0.43 0.47 1.98 3.38 1.36 0.46

2521 A 2.78 9.87 3.74 2.32 2.03 0.44 6.88 0 4.04 2.93 6.97 2.92 1.18 1.26 0.14 1.86 1.11 0.67 0.83 2.65 3.71 1.39 0

2713 A 4.54 6.98 3.62 3.06 0.9 0.28 7 0 0.73 2.31 9.29 2.64 1.11 1.02 0.11 1.75 1.22 1.17 0.81 2.16 3.42 1.12 0

7065 A 7 27 5.2 5.06 2.26 0.26 3.64 0.32 0.98 6.03 15.68 3.64 1.31 2.55 0.4 5.12 2.73 0.78 1.98 1.52 8.58 3.45 0

10137 A 5.79 21.31 6.12 4.1 2.36 0.21 8.53 0 1.68 5.28 11.77 2.02 1.1 1.78 0.19 3.65 1.49 1 1.93 1.4 6.02 2.44 0

“ID” in the column heading signifies unique identifier assigned by generalized random tessellation stratified design software; Asp, aspartic acid; Glu, glutamic acid; Ser, serine;

Asn, asparagine; Gly, glycine; Gln, glutamine; His, histidine; Arg, arginine; Tau, taurine; Cit, citrulline; Thr, threonine; Ala, alanine; GABA, ϒ-aminobytyric acid; Pro, proline;

Tyr, tyrosine; Cys-Cys, cystine; Val, valine; Met, methionine; Orn, ornithine HCl; Ile, isoleucine; Lys, lysine; Leu, leucine; Phe, phenylalanine; Trp, tryptophan

(Continued)

212

Appendix D. Concentrations of hydrolysable amino acids detected in soils (µmol kg-1 dry soil)

ID Horizon Asp Ser Glu Gly His Arg Thr Ala Pro Tyr Cys-Cys Val Met Lys Ile Leu Phe

10137 C 0.0225 0.0225 0.00625 0.0275 0 0 0.0075 0.0175 0 0.02625 0 0.0063 0 0.01125 0 0.00075 0

1032 C 0.0975 0.0425 0.1875 0.11625 0.03875 0.0225 0.0388 0.06875 0.03 0.06125 0.0025 0.065 0.02125 0.04875 0.01375 0.02 0.00125

10351 C 1.3388 0.3581 0.68125 0.74 0.12875 0.1138 0.405 0.71188 0.4269 0.065 0 0.4375 0 0.405 0.23063 0.34438 0.13688

10440 C 0.625 0.1288 0.42 0.59625 0.07625 0.0725 0.1913 0.445 0.1775 0.04 0 0.1688 0.00875 0.1575 0.07625 0.14375 0.04875

10591 C 0.1575 0.105 0.13 0.1 0 0.0463 0.0875 0.15438 0.0694 0.07938 0 0.055 0.00563 0.06938 0.045 0.06875 0.03188

10607 C 0.2013 0.0944 0.1975 0.19688 0.05813 0.0444 0.0881 0.23313 0.0856 0.01375 0 0.1119 0 0.08188 0.0575 0.09625 0.0375

10859 C 1.2369 0.3606 0.77938 0.80313 0.12438 0.13 0.3525 0.84563 0.4406 0.0875 0 0.4525 0.0075 0.40563 0.2125 0.33438 0.11625

10863 C 0.1288 0.0725 0.0675 0.17375 0.0225 0.0075 0.045 0.09375 0.03 0.005 0 0.0038 0.01125 0.01125 0.00375 0.01875 0.00375

10907 C 4.955 2.735 3.18125 5.505 0.50875 0.53 2.2113 4.0125 1.815 0.69625 0 1.4 0.22875 1.37125 0.775 1.38625 0.6575

10975 C 0.6888 0.2488 0.4575 0.53 0.10125 0.1013 0.2575 0.505 0.205 0.08 0 0.1838 0.01375 0.21 0.13375 0.1875 0.1

11208 C 0.1738 0.095 0.095 0.2925 0.05 0.0113 0.0688 0.1425 0.0188 0.06125 0 0.0063 0 0.03 0.01 0.025 0.00625

11231 C 1.185 0.2925 0.56 0.8475 0.06625 0.06 0.4263 0.62125 0.3163 0.03375 0 0.295 0 0.2425 0.14875 0.24625 0.0675

11327 C 0.2113 0.0838 0.14625 0.33 0.045 0.03 0.0838 0.16625 0.0238 0.00875 0 0.0075 0.0075 0.05375 0.015 0.045 0.01875

11435 C 1.0813 0.1138 0.46375 0.62 0.07 0.0625 0.1538 0.40875 0.2288 0.115 0 0.145 0.01125 0.22875 0.06625 0.1325 0.05

11656 C 0.7925 0.265 0.68 0.815 0.08875 0.0788 0.245 0.5425 0.1813 0.0475 0 0.2263 0.0225 0.28875 0.06125 0.11 0.03875

12020 C 0.2631 0.135 0.18875 0.255 0.06375 0.0425 0.1294 0.22125 0.1238 0.02125 0 0.1181 0 0.08563 0.05438 0.08438 0.03375

12075 C 1.0231 0.4119 0.65563 0.86375 0.09313 0.0994 0.6725 0.74938 0.395 0.055 0 0.3675 0 0.29813 0.17813 0.2425 0.09938

12232 C 0.0825 0.0413 0.03 0.09875 0.01 0.0038 0.0113 0.0475 0.0038 0.02625 0 0.005 0 0.00125 0.01125 0.0125 0.00125

12488 C 0.7225 0.25 0.34625 0.4925 0.03875 0.0688 0.1913 0.41375 0.2425 0.09375 0 0.1538 0.0125 0.16 0.07125 0.1575 0.06875

12495 C 0.5363 0.225 0.3825 0.565 0.0675 0.0575 0.1475 0.4125 0.1663 0.065 0 0.1013 0.00875 0.2275 0.05375 0.14375 0.03625

12505 C 0.1725 0.145 0.1425 0.2275 0.05375 0.0275 0.1038 0.14625 0.0913 0.0075 0 0.0613 0 0.05 0.03375 0.02875 0.045

12584 C 0.825 0.21 0.3625 0.525 0.075 0.0325 0.28 0.29 0.14 0.0625 0 0.1325 0.02 0.2025 0.0675 0.1425 0.05

12888 C 0.6506 0.2625 0.49125 0.47938 0.06125 0.0694 0.4288 0.55813 0.3381 0.0625 0 0.3 0 0.24 0.13563 0.17875 0.06625

1643 C 0.8481 0.2013 0.37813 0.48563 0.04625 0.0513 0.2606 0.37375 0.2294 0.05438 0 0.2113 0.0025 0.21125 0.10125 0.16938 0.06063

1708 C 0.6581 0.4131 0.46375 0.66875 0.10875 0.1331 0.32 0.545 0.3006 0.09125 0 0.2281 0.01813 0.27125 0.13688 0.23375 0.12125

1724 C 0.0925 0.0463 0.05375 0.07375 0.02125 0.0038 0.02 0.0525 0.0238 0.0025 0 0.01 0.01125 0.005 0.005 0.01 0.0025

1759 C 0.505 0.15 0.265 0.45375 0.03 0.0313 0.2225 0.345 0.125 0.02 0 0.1075 0.00625 0.1 0.0425 0.10125 0.01875

1881 C 0.5288 0.1313 0.345 0.51375 0.0575 0.0488 0.1238 0.36875 0.1275 0.045 0 0.1713 0.00625 0.10625 0.05125 0.0975 0.0425

1935 C 0.5369 0.335 0.5025 0.56813 0.08688 0.0675 0.2538 0.58313 0.1963 0.06313 0 0.1244 0.02938 0.21063 0.06625 0.11813 0.04938

2095 C 1.6413 0.4813 1.0975 1.25625 0.195 0.2038 0.7913 1.085 0.705 0.0625 0 0.835 0 0.62625 0.41375 0.6025 0.2325

2111 C 0.53 0.2975 0.27625 0.5125 0.09625 0.08 0.1813 0.32375 0.155 0.0775 0 0.0675 0.00875 0.16375 0.08625 0.115 0.0625

2184 C 0.0313 0.0225 0.03375 0.04375 0.025 0.0018 0.02 0.025 0.0238 0.00375 0 0.0088 0 0.01625 0.00375 0.0125 0.00125

2248 C 0.4463 0.165 0.275 0.50625 0.065 0.0788 0.2638 0.38375 0.1863 0.0125 0 0.2475 0 0.22125 0.10875 0.18125 0.0625

2521 C 0.24 0.1325 0.17875 0.22 0.05875 0.0413 0.135 0.1675 0.0675 0.05125 0 0.0788 0 0.0975 0.0325 0.06375 0.02375

2539 C 0.5113 0.1775 0.3375 0.4325 0.07375 0.0725 0.1588 0.355 0.1863 0.08875 0 0.16 0.01375 0.16625 0.0675 0.135 0.06125

2713 C 0.1838 0.1038 0.16375 0.23375 0.06 0.0188 0.1125 0.16125 0.0713 0.08625 0 0.1225 0 0.10875 0.04625 0.06625 0.025

213



2748 C 0.0438 0.0263 0.0525 0.075 0.03 0 0.0113 0.03125 0.0288 0.05 0 0.0838 0 0.01375 0 0.005 0

2780 C 0.3638 0.2113 0.4525 0.67125 0.06375 0.06 0.1525 0.45625 0.0788 0.085 0 0.115 0.02 0.16125 0.0275 0.075 0.035

2959 C 0.805 0.2613 0.60125 0.68 0.08375 0.1125 0.2713 0.5875 0.1963 0.065 0 0.2775 0.00875 0.21375 0.1025 0.19 0.08625

2988 C 1.26 0.48 0.795 0.705 0.14 0.17 0.525 0.7425 0.415 0.105 0 0.4025 0.0375 0.3075 0.1675 0.3625 0.1675

3135 C 1.7625 0.5363 0.96 1.15688 0.11063 0.1369 1.0144 0.99563 0.6175 0.17063 0 0.415 0.01 0.53375 0.2275 0.41563 0.16063

3228 C 0.17 0.1019 0.17188 0.18938 0.04 0.03 0.0963 0.2 0.0888 0.02188 0 0.0775 0.00625 0.06688 0.0325 0.05813 0.02813

3291 C 0.2038 0.1075 0.1975 0.2475 0.0825 0.0325 0.1063 0.21125 0.0675 0.07875 0 0.14 0 0.14875 0.03625 0.06125 0.02375

3736 C 0.41 0.2463 0.42 0.67125 0.0925 0.0813 0.2363 0.52625 0.145 0.0425 0 0.0238 0.02125 0.2375 0.05625 0.085 0.03375

3828 C 0.2594 0.1319 0.29 0.14563 0.02938 0.0325 0.2094 0.24188 0.1575 0.03938 0.005 0.1413 0 0.17625 0.05563 0.08625 0.00875

3931 C 0.4513 0.13 0.37 0.455 0.0775 0.0488 0.285 0.3625 0.1175 0.0425 0 0.0638 0.03125 0.19125 0.03625 0.07 0.01

3947 C 1.1956 0.265 0.51063 0.44625 0.085 0.0888 0.32 0.48063 0.3481 0.125 0 0.2025 0.00438 0.31063 0.12625 0.20563 0.08188

4248 C 0.5781 0.285 0.48688 0.50125 0.12625 0.1419 0.3113 0.52063 0.3656 0.07188 0 0.3419 0.00625 0.32125 0.19438 0.32188 0.1325

4249 C 0.2856 0.1125 0.15688 0.235 0.05938 0.0394 0.1338 0.1825 0.0988 0.01313 0 0.11 0 0.0975 0.04563 0.06813 0.0225

4440 C 0.5925 0.5725 0.44 0.7125 0.125 0.1413 0.355 0.515 0.245 0.09375 0 0.1913 0.02375 0.21875 0.08125 0.13875 0.0625

4507 C 0.1138 0.0588 0.07375 0.1325 0 0 0.0313 0.1225 0.0225 0.045 0 0.0213 0.00375 0.02375 0.01125 0.02375 0.00625

4571 C 0.4725 0.2988 0.3925 0.7925 0.07625 0.1225 0.23 0.5475 0.1925 0.07125 0 0.0775 0.0275 0.21 0.0525 0.15625 0.065

4760 C 1.8213 0.8831 1.35625 1.17375 0.175 0.2825 0.9456 1.46063 0.7463 0.22063 0 0.6581 0.06938 0.63875 0.34813 0.5875 0.2575

4779 C 0.5063 0.1331 0.28563 0.28688 0.02063 0.0331 0.3056 0.28563 0.1906 0.00813 0 0.1531 0.00313 0.16313 0.06875 0.13375 0.03938

4780 C 0.4213 0.38 0.53625 0.88375 0.11125 0.1163 0.3513 0.63125 0.2313 0.05375 0 0.155 0.02125 0.27625 0.11 0.1825 0.08625

4852 C 0.0838 0.0413 0.065 0.09625 0.03875 0.0188 0.0488 0.0475 0.0175 0.04375 0 0.0163 0 0.04 0.01375 0.02375 0.0075

4952 C 0.4538 0.1838 0.31 0.4375 0.0625 0.0663 0.1438 0.33375 0.1413 0.0775 0.005 0.1163 0.0075 0.1525 0.06125 0.12 0.0525

4953 C 0.9088 0.3338 0.56 0.57375 0.06 0.1025 0.3713 0.76 0.2138 0.07625 0 0.35 0.04125 0.2125 0.18625 0.285 0.1225

5256 C 2.8213 1.9175 1.9825 4.12625 0.37125 0.4775 1.11 2.68125 1.0288 0.5 0.0375 0.5813 0.17875 1.2175 0.3575 0.72625 0.34625

5355 C 1.02 0.3963 0.845 1.0775 0.175 0.1613 0.6188 0.90125 0.5163 0.05125 0 0.7263 0 0.4625 0.38875 0.53875 0.2275

5596 C 2.5525 1.6263 1.67875 2.845 0.3125 0.3088 1.2863 2.06 0.9288 0.4275 0 0.7913 0.10625 0.86625 0.445 0.7775 0.36125

5615 C 1.5975 1.06 1.0525 1.6375 0.1925 0.2225 0.75 1.625 0.7075 0.2 0 0.84 0.01 0.4675 0.4425 0.755 0.29

5675 C 2.1609 1.0173 1.74202 2.2141 0.22606 0.3657 1.4295 1.76197 0.871 0.1 0 1.1436 0 0.78457 0.64495 1.07713 0.43883

5848 C 1.0588 0.515 1.03875 1.43125 0.17 0.1638 0.5938 1.0575 0.5963 0.27625 0 0.3913 0.05625 0.46875 0.19125 0.33875 0.15875

5852 C 0.3438 0.245 0.3275 0.36125 0.11125 0.0575 0.2288 0.35375 0.1113 0.07125 0 0.2263 0 0.25625 0.08 0.11125 0.05

5977 C 0.91 0.4175 0.55625 0.9025 0.0875 0.135 0.3075 0.72125 0.3438 0.08375 0 0.2413 0.0375 0.325 0.1075 0.22125 0.015

600 C 0.5388 0.1075 0.4225 0.38 0.075 0.0613 0.1388 0.32375 0.19 0.085 0 0.1213 0 0.1875 0.05625 0.10875 0.04

6041 C 0.1288 0.0513 0.065 0.11875 0.04625 0.0125 0.0463 0.08625 0.0338 0.08125 0 0.0375 0 0.01625 0.02 0.03875 0.0125

6060 C 0.075 0.0413 0.07125 0.065 0.0625 0.0125 0.0425 0.0525 0 0.08875 0 0.0088 0.00875 0.04625 0.015 0.01875 0.0075

6379 C 0.7325 0.2138 0.385 0.36875 0.08875 0.1013 0.2738 0.37875 0.2338 0.07875 0 0.14 0.01375 0.23125 0.11125 0.17125 0.0825

648 C 0.9138 0.6763 1.0125 1.0625 0.17125 0.2238 0.6388 1.04 0.5375 0.15 0 0.4425 0.0325 0.5325 0.28125 0.48 0.21625

6617 C 0.2669 0.1088 0.145 0.21938 0.02063 0.0256 0.1144 0.22 0.1394 0.00875 0 0.0869 0.00438 0.06438 0.02938 0.0675 0.02313

(Continued)

214



6891 C 0.2875 0.0838 0.1225 0.19 0.0175 0.0038 0.065 0.13125 0.045 0.015 0 0.0275 0.00375 0.045 0.02125 0.04 0.025

7065 C 0.0625 0.0613 0.05 0.115 0.015 0.0075 0.0213 0.0725 0.0113 0.0275 0 0.0013 0 0.0125 0.01125 0.0175 0.00125

7231 C 4.0313 0.98 2.16125 2.61 0.2975 0.3975 1.505 2.03125 1 0.29875 0 1.1313 0.06125 1.1075 0.60875 1.03375 0.44625

7324 C 0.3738 0.1288 0.3175 0.31625 0.0625 0.045 0.1813 0.32125 0.1063 0.0825 0 0.2225 0 0.15875 0.0775 0.10375 0.0375

7368 C 1.1338 0.335 0.72375 1.16875 0.08625 0.11 0.2738 0.73375 0.2613 0.105 0 0.2113 0.0275 0.2875 0.09 0.175 0.08

7384 C 0.835 0.5113 0.64875 0.9525 0.1175 0.1413 0.3575 0.755 0.365 0.1825 0 0.255 0.025 0.33875 0.16125 0.295 0.13125

7919 C 1.3381 0.5381 0.83313 1.57063 0.09125 0.1688 0.4888 1.02313 0.4 0.21125 0 0.1569 0.07 0.33938 0.18188 0.31875 0.14875

8088 C 1.0688 0.2925 0.4775 0.67125 0.0775 0.0763 0.3888 0.4775 0.2425 0.1425 0 0.1825 0.03125 0.275 0.09875 0.2025 0.0725

8200 C 0.0575 0.0294 0.0675 0.055 0.01875 0.0044 0.0694 0.06813 0.0231 0.05063 0 0.0363 0.0025 0.02688 0.00875 0.01438 0

8687 C 4.1375 0.7975 1.7175 2.31 0.2175 0.2825 1.1625 1.57 0.7625 0.415 0 0.545 0.105 0.93 0.3425 0.7025 0.2975

8948 C 0.065 0.06 0.135 0.13125 0.035 0.0188 0.03 0.06375 0.02 0.08875 0.01 0.0738 0 0.0325 0.00038 0.00875 0.00125

9049 C 0.5438 0.245 0.34375 0.5375 0.06125 0.0413 0.2388 0.4425 0.1363 0.11 0 0.2 0.0075 0.09 0.0575 0.105 0.02625

9103 C 0.6663 0.33 0.58125 0.72 0.07563 0.0713 0.3369 0.5975 0.2094 0.0125 0 0.2363 0 0.28313 0.11313 0.18125 0.06375

9195 C 0.4538 0.0463 0.36875 0.4075 0.06125 0.0588 0.1238 0.26125 0.13 0.07625 0 0.1363 0.03 0.1775 0.05625 0.12 0.04875

9323 C 0.2975 0.0875 0.13625 0.29625 0.03375 0.0138 0.065 0.1475 0.0563 0.02 0 0.0263 0.01625 0.07 0.025 0.04125 0.01375

9423 C 7.265 5.5325 5.46 8.20375 1.03 1.2538 3.9013 6.38625 3.1388 0.95375 0 2.5713 0.20625 2.73125 1.58 2.68875 1.47375

9535 C 1.1488 0.3075 0.57125 0.94875 0.105 0.1213 0.5638 0.565 0.355 0.04375 0 0.4188 0 0.385 0.2225 0.3325 0.1375

9556 C 0.9938 0.2413 0.6325 0.93625 0.08625 0.1038 0.2963 0.67875 0.245 0.04875 0 0.3988 0 0.2325 0.1775 0.2925 0.13625

9644 C 0.1113 0.0769 0.11938 0.1125 0.04875 0.0281 0.0631 0.10313 0.0675 0.02563 0.005 0.065 0 0.10688 0.02563 0.03625 0.01563

9823 C 0.6288 0.3638 0.65125 0.8275 0.08875 0.13 0.4675 0.63875 0.2675 0.02 0 0.3663 0 0.4025 0.17875 0.31375 0.115

9938 C 0.3243 0.1934 0.35526 0.30921 0.075 0.0612 0.1875 0.32434 0.1566 0.01776 0 0.1849 0 0.23816 0.07368 0.09671 0.04013

10137 A 3.6013 2.0638 2.60375 4.1275 0.285 0.45 1.6775 2.96125 1.34 0.71125 0 0.785 0.23375 1.14625 0.57625 0.98625 0.4675

1032 A 4.2863 2.8175 3.25625 6.18125 0.47875 0.5988 2.325 4.35875 1.965 0.84 0 1.1588 0.335 1.4725 0.69 1.34625 0.585

10351 A 2.0925 1.0288 1.6325 2.2025 0.2575 0.3413 1.0988 1.88 0.9263 0.2425 0 0.6713 0.0775 0.71375 0.44625 0.8525 0.3475

10440 A 3.47 2.1863 2.885 4.41125 0.39625 0.5088 2.26 3.5225 1.76 0.32 0 1.4888 0.11375 1.43625 0.83375 1.37375 0.53875

10591 A 13.863 9.6375 12.7125 17.5375 1.65 3.15 8.6875 15.4875 8.0375 1.875 0 8.475 0.5375 5.6 5.375 9.7375 4.375

10607 A 0.245 0.1425 0.29375 0.42625 0.04125 0.0575 0.0863 0.33625 0.0863 0.00625 0 0.0725 0.0125 0.095 0.0125 0.07125 0.00625

10859 A 4.965 3.13 4.6925 5.81 0.44875 0.7688 3.22 4.80125 2.8638 0.445 0 2.5138 0.16625 1.82 1.65375 2.76125 1.12875

10863 A 0.6175 0.215 0.69125 0.89375 0.07125 0.1675 0.255 0.735 0.2563 0.05625 0 0.215 0.01875 0.22375 0.13625 0.28625 0.10875

10907 A 8.8188 5.5813 6.55625 10.1875 1.00625 1.2625 4.4938 8.06875 3.95 1.325 0 2.8375 0.5 3.18125 1.81875 3.4375 1.375

10975 A 0.5575 0.395 0.53875 1.07375 0.0525 0.1275 0.2638 0.6775 0.18 0.12 0 0.0988 0.075 0.18375 0.05125 0.20125 0.065

11208 A 4.7538 2.8063 3.46875 5.48 0.385 0.5988 2.4413 4.37875 2.1363 0.595 0 1.4688 0.25625 1.5525 0.83 1.49375 0.64

11231 A 4.1725 1.49 3.1625 4.43 0.34 0.6675 1.19 3.2575 1.245 0.4375 0 0.935 0.11 1.115 0.5375 1.26 0.555

11327 A 2.7875 0.91 1.5975 1.95625 0.25 0.3188 1.0375 1.4625 0.8163 0.3175 0 0.6113 0.05 0.815 0.395 0.6825 0.3225

11435 A 5.1388 1.9025 3.905 5.28875 0.48 0.9188 2.7875 3.96375 2.05 0.35625 0 2.8713 0 2.01875 1.69625 2.64125 1.2625

11656 A 5.5125 3.2625 3.6025 5.47 0.51375 0.7688 2.7313 4.195 2.3688 1.14 0 1.6275 0.16375 1.845 0.9975 1.835 0.93625

(Continued)

215



12020 A 5.5945 3.5747 4.32927 7.35518 0.42683 0.8841 2.8963 5.05335 3.0183 0.43445 0 2.4238 0.15244 1.39482 1.46341 2.78963 1.1814

12075 A 1.0288 0.5575 0.79875 1.185 0.07625 0.17 0.4763 0.9675 0.4538 0.155 0 0.1913 0.05125 0.3875 0.1625 0.3675 0.13625

12232 A 14.279 2.658 8.24176 10.0069 0.75549 1.2706 4.2995 7.87088 3.6607 0.40522 0 6.0508 0 4.3544 3.35852 4.19643 2.16346

12488 A 3.3575 1.905 2.86125 3.13375 0.40875 0.5525 1.7213 3.085 1.7513 0.42875 0 1.3538 0.0725 1.40625 0.74625 1.2825 0.53125

12495 A 0.57 0.2538 0.425 0.61625 0.06 0.1013 0.445 0.52 0.1275 0.0175 0 0.1475 0.0175 0.17375 0.07375 0.17375 0.055

12505 A 3.47 3.6738 2.5125 4.9625 0.66875 0.7313 2.5 3.88625 2.18 0.6375 0 1.5938 0.08625 1.3525 1.07875 1.91 0.895

12584 A 2.2938 1.1538 1.8325 2.8025 0.2375 0.39 0.8163 2.05125 0.905 0.405 0 0.5388 0.1125 0.7725 0.305 0.7525 0.31875

12888 A 3.6225 2.8138 3.16875 4.805 0.455 0.7263 2.5013 3.8775 2.0488 0.65 0 1.5425 0.08375 1.4525 0.95125 1.7475 0.7675

1643 A 2.515 1.0863 1.825 2.40125 0.24625 0.38 1.5688 1.90625 1.1075 0.13 0 1.3275 0.0075 0.93375 0.7325 1.18375 0.45125

1708 A 1.8888 1.4888 1.50625 2.91 0.27375 0.3388 1.0525 2.085 0.9038 0.3775 0 0.59 0.175 0.75875 0.37625 0.7425 0.34125

1724 A 6.1063 3.6375 4.30625 6.79375 1.25 1.2563 3.35 4.875 2.7938 0.64375 0 3.4875 0.09375 2.14375 2.0875 3.0125 1.50625

1759 A 1.865 0.8275 1.855 2.77 0.2075 0.4625 0.785 2.15 0.9175 0.2625 0 0.8175 0.03 0.6075 0.4475 1.025 0.38

1881 A 6.36 2.5063 3.63 5.53125 0.28375 0.6288 2.4275 3.9825 1.7875 0.61625 0 1.63 0.17625 1.56375 1.065 1.635 0.82625

1935 A 8.8088 6.2925 6.29375 11.1025 1.06 1.1563 3.9038 8.0325 3.6738 1.07625 0 2.3225 0.49875 2.74625 1.37875 2.7625 1.02625

2095 A 3.7925 3.5525 3.0825 7.17 0.53125 0.8088 2.055 4.65 2.0488 0.84625 0 1.3025 0.29625 1.43 0.81 1.8925 0.84875

2111 A 1.185 0.5588 0.82875 1.11375 0.11375 0.175 0.64 0.92 0.505 0.1375 0 0.3713 0.02125 0.40625 0.2025 0.4225 0.17375

2184 A 2.5625 1.8375 2.1075 4.0625 0.3175 0.4038 1.5225 2.81 1.3063 0.365 0 0.7738 0.12375 1.02875 0.5325 0.92875 0.36875

2248 A 2.23 1.2188 1.74375 2.26125 0.315 0.43 1.1913 2.1975 1.3988 0.3275 0 0.8425 0.08875 0.985 0.52125 0.99375 0.42875

2521 A 3.6588 2.4938 2.4925 4.19 0.5075 0.6713 1.9213 3.08375 1.7263 0.51125 0 1.3338 0.11 1.53625 0.76625 1.39375 0.6825

2539 A 3.1438 1.1725 2.08125 2.76375 0.25125 0.3388 1.46 2.30625 1.2388 0.275 0 1.0575 0.05125 0.84375 0.59125 1.04125 0.4075

2713 A 3.4125 2.2975 2.54125 3.92625 0.5275 0.5663 1.9075 2.95625 1.4563 0.4475 0 1.1575 0.105 1.4075 0.67625 1.2 0.5325

2748 A 3.4575 2.615 2.91375 4.5475 0.52625 0.6725 2.23 3.3925 1.8025 0.08 0 1.5 0.0675 1.2775 0.85875 1.525 0.64625

2780 A 2.7238 2.1688 2.2525 4.42625 0.41375 0.5 1.5013 3.17125 1.4113 0.56875 0 0.8363 0.15375 1.2575 0.51625 1.02625 0.43875

2959 A 1.2013 0.6938 1.06125 1.2125 0.1025 0.2025 0.5438 1.14625 0.4288 0.33875 0 0.205 0.06125 0.44875 0.21125 0.4025 0.15

2988 A 10.544 6.5688 8.2125 11.1688 1.325 1.4438 5.9563 9.75 5.2313 1.275 0 4.0438 0.5375 4.10625 2.38125 4.2125 1.7125

3135 A 2.8825 1.0213 2.55375 3.39375 0.365 0.52 2.2863 2.79875 1.4775 0.13625 0 2.22 0.0125 1.34125 1.27375 1.94875 0.77

3228 A 5.5813 4.4363 4.24875 7.98 0.68625 0.8313 2.7125 5.5975 2.5675 0.6575 0 1.8163 0.24375 2.145 1.1675 2.08625 0.97375

3291 A 3.0088 2.0238 2.535 3.55125 0.3475 0.445 1.8113 2.90125 1.3363 0.37 0 1.0538 0.1375 1.1875 0.74875 1.28375 0.5125

3736 A 9.0975 6.8025 7.1725 14.6638 0.99875 1.3613 5.0338 10.0388 4.7025 1.49375 0 2.555 0.91 3.59875 1.74625 3.89375 1.52625

3828 A 6.175 2.5375 4.96875 5.725 0.925 1.1125 3.175 4.975 2.9688 0.3625 0 4.0313 0.11875 2.9125 2.39375 3.46875 1.75

3931 A 3.0975 3.3163 2.105 6.57125 0.4425 0.7425 1.6688 3.9325 1.7138 0.55375 0 1.0638 0.23125 1.315 0.765 1.57875 0.725

3947 A 2.0025 1.3763 1.535 2.61 0.1675 0.2875 1.0788 2.1225 1.0925 0.415 0 0.4475 0.1075 0.84125 0.36625 0.7675 0.3

4248 A 3.8238 2.1788 3.0675 4.535 0.4425 0.7075 2.0488 3.51 2.0675 0.65125 0 1.3213 0.21125 1.40125 0.84875 1.62625 0.6625

4249 A 5.4053 1.8447 3.56061 5.76894 0.54167 0.947 2.6439 4.04924 2.072 0.33712 0 2.9129 0.03409 2.01515 1.58712 2.2197 1.16288

4440 A 1.8488 0.84 1.5425 2.47375 0.2875 0.435 1.0363 1.78875 1.08 0.23125 0 1.3588 0.03625 0.88875 0.7875 1.17375 0.5075

4507 A 0.2838 0.1138 0.21375 0.325 0.03875 0.0388 0.0988 0.24375 0.0725 0.0275 0 0.0388 0.03125 0.09875 0.045 0.085 0.03125

(Continued)

216



4571 A 2.2763 1.6363 2.15875 2.33125 0.2725 0.58 1.32 2.605 1.1963 0.4325 0 0.965 0.16125 0.8675 0.665 1.315 0.55125

4760 A 4.8563 3.2788 3.76 6.275 0.35625 0.655 2.4588 5.0025 2.38 0.77 0 1.18 0.38875 1.57125 0.915 1.77375 0.73625

4779 A 4.0472 1.3137 2.76672 3.61598 0.44453 0.6635 2.289 2.93259 1.5393 0.3052 0 2.2293 0 1.6189 1.26725 2.02362 0.92224

4780 A 3.8588 2.8388 3.10375 4.58 0.46875 0.6525 2.2138 3.63875 2.1588 0.38 0 1.7613 0.17125 1.36 1.08625 1.89 0.79

4852 A 6.1458 1.7188 3.45238 5.625 0.42411 0.692 2.1429 3.31101 1.8452 0.40179 0.0125 2.3438 0.0425 1.79315 1.36905 1.94196 0.95982

4952 A 8.2563 3.2875 5.46875 6.35625 0.9125 1.0938 4.4 5.7 3.6375 0.43125 0.025 4.55 0.10625 2.99375 2.59375 3.75 1.6125

4953 A 3.5875 1.65 2.50875 3.73875 0.2525 0.4588 1.5025 3.02 1.2675 0.33125 0 0.9975 0.125 1.065 0.6075 1.0525 0.42375

5256 A 9.1938 3.8688 6.4375 9.0875 1.06875 1.2563 4.9688 6.86875 3.9063 0.5375 0 5.1875 0 3.4125 3.00625 4.15 2

5355 A 4.8313 3.6875 3.8125 5.92875 0.5275 0.755 2.8225 4.7975 2.5713 0.64125 0 2.03 0.17375 1.39 1.33625 3.1 0.98875

5596 A 3.435 2.3913 2.24125 4.74875 0.40125 0.4638 1.7513 3.05375 1.28 0.49125 0 0.87 0.17875 1.22375 0.5525 1.0575 0.53125

5615 A 1.8775 0.7125 1.42 2.1975 0.155 0.3 1.1825 1.75 0.71 0.1375 0 0.5725 0.08 0.63 0.3225 0.68 0.235

5675 A 2.1713 1.5225 2.0825 2.2 0.21 0.4288 1.48 2.41625 1.1163 0.2825 0 0.8863 0.10625 0.83875 0.5775 1.11625 0.425

5848 A 3.1225 1.825 2.62125 4.135 0.44375 0.71 2.0488 3.1325 1.6763 0.21625 0 2.1588 0.01375 1.49125 1.34375 2.07875 0.95375

5852 A 7.0438 5.0825 4.90375 6.95625 0.99375 0.7763 4.3725 5.89375 3.2163 0.825 0 3.1588 0.29875 2.2825 1.74625 2.62125 1.40125

5977 A 3.6925 2.7188 3.08875 5.58625 0.51875 0.6638 2.4438 4.515 1.68 0.83875 0 1.1638 0.15375 1.79375 0.72375 1.32625 0.45625

600 A 2.245 1.5538 1.99875 4.085 0.325 0.3925 0.9063 2.33625 1.0088 0.46875 0 0.5875 0.16375 1.00875 0.32375 0.69125 0.305

6041 A 5.945 1.79 4.5125 6.2125 0.56 1.0888 2.8113 5.16125 2.875 0.38375 0 3.8388 0.13375 2.37125 2.3475 3.10625 1.44625

6060 A 5.2125 3.59 3.98625 5.3825 0.62 0.8038 2.9325 4.2975 2.7013 0.6475 0 2.06 0.0975 2.02875 1.265 2.14625 1.0525

6379 A 3.7788 1.5225 2.4525 3.57125 0.295 0.555 1.3013 2.715 1.2725 0.2825 0 1.2763 0.03125 1.03375 0.72875 1.3725 0.5825

648 A 7.535 5.4388 6.175 9.1225 1.075 1.2625 4.4513 7.6575 4.2288 0.805 0 3.345 0.2875 2.9675 2.0975 4.54375 1.4875

6617 A 6.355 5.7088 7.645 10.4413 1.4 2.065 5.9813 8 5.285 0.8625 0.0375 5.5 0.27625 3.52375 3.5 5.25 2.37375

6891 A 4.0663 1.2775 2.4075 3.42 0.2975 0.3475 1.825 2.5825 1.25 0.10625 0 1.0013 0.09 1.055 0.56 1.0225 0.41

7065 A 6.8638 3.9775 4.45125 6.94375 0.71625 0.78 3.4925 5.28625 2.36 0.76375 0 2.1 0.1975 2.2125 1.1625 1.9725 0.9825

7231 A 4.6675 1.4425 2.71 3.84 0.3225 0.4225 1.9725 2.7525 1.26 0.3825 0 1.385 0.025 1.165 0.6675 1.0325 0.4375

7324 A 4.4763 3.6063 3.86 6.75375 0.62 0.5263 2.3063 4.9825 2.0463 0.79375 0 1.21 0.335 1.7025 0.8 1.44 0.55875

7368 A 9.2735 3.4513 7.73637 10.9919 1.29785 1.4936 5.757 9.60702 5.0537 0.6018 0 6.6995 0.07251 4.57512 3.64704 4.9449 1.97216

7384 A 3.64 2.545 3.0475 5.34875 0.47 0.6163 1.6813 3.75875 1.8863 0.88375 0 0.98 0.245 1.44375 0.6 1.405 0.705

7919 A 1.4075 0.6063 0.9025 1.57875 0.105 0.16 0.575 1.10125 0.4925 0.28625 0 0.2013 0.03125 0.3725 0.17625 0.37375 0.14875

8088 A 2.9838 1.9763 2.3525 3.88875 0.3825 0.5663 1.855 2.9675 1.51 0.54875 0 1.06 0.1375 1.1525 0.64375 1.2125 0.52625

8200 A 5.9713 4.2225 5.44125 7.93125 0.75375 1.03 3.7325 6.2575 4.0638 0.63375 0.145 2.75 0.1725 2.26875 1.53375 2.8075 1.19875

8687 A 4.6625 1.1038 2.37625 2.96125 0.3625 0.4638 1.755 2.2225 1.1988 0.3375 0 1.23 0.0425 1.3525 0.66875 1.165 0.5025

8948 A 3.745 2.7863 3.795 4.46625 0.65125 0.9175 2.0088 3.76125 2.0688 0.94875 0 1.3213 0.2175 1.87625 0.98625 1.8625 0.89625

9049 A 6.0563 3.6738 4.8275 6.00125 0.52125 0.8075 2.7013 6.14625 2.8475 0.74875 0 1.8963 0.30625 1.955 1.09 2.21625 0.90875

9103 A 1.6038 1.1213 1.445 1.72 0.18625 0.3513 0.8813 1.62875 0.735 0.22875 0 0.7563 0.03625 0.44375 0.5075 1.005 0.41375

9195 A 0.4888 0.2663 0.39625 0.54875 0.06 0.0863 0.2488 0.45875 0.2 0.0575 0 0.06 0.025 0.22 0.05625 0.14375 0.04

9323 A 1.6775 1.0888 1.08 2.19625 0.1825 0.2788 0.605 1.49875 0.69 0.19625 0 0.4413 0.0625 0.6425 0.225 0.5975 0.26

(Continued)

217



9423 A 3.7438 2.72 3.79 5.10625 0.585 0.7463 1.85 3.95875 1.83 0.7275 0 1.2575 0.18875 1.66375 0.9525 1.7075 0.82125

9535 A 1.0575 0.4963 0.87375 1.355 0.165 0.27 0.7425 0.9625 0.4475 0.075 0 0.6963 0 0.47875 0.37375 0.58125 0.255

9556 A 3.1725 1.66 2.8325 3.5625 0.3 0.575 1.1975 2.8 1.4 0.3975 0.05 1.175 0.0725 0.965 0.855 1.635 0.7625

9644 A 3.7188 2.5575 2.9225 4.7425 0.47625 0.435 2.0238 3.60125 1.4375 0.6175 0 0.9738 0.21625 1.35625 0.58625 1.09 0.475

9823 A 2.64 2.1225 2.38625 4.665 0.41625 0.4813 1.5913 3.2025 1.2725 0.4425 0 0.7663 0.1975 1.23125 0.5225 1.03375 0.4575

9938 A 0.5599 0.2904 0.41763 0.40813 0.0675 0.0801 0.247 0.4335 0.1904 0.01938 0 0.2294 0.00438 0.20488 0.11513 0.16075 0.07438

“ID” in the column heading signifies unique identifier assigned by generalized random tessellation stratified design software; Asp, aspartic acid; Glu, glutamic acid; Ser, serine;

Gly, glycine; His, histidine; Arg, arginine; Thr, threonine; Ala, alanine; Pro, proline; Tyr, tyrosine; Cys-Cys, cystine; Val, valine; Met, methionine; Lys, lysine; Ile, isoleucine; Leu,

leucine; Phe, phenylalanine

(Continued)

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