Phosphorus in agricultural soils around the Baltic Sea - comparison of laboratory methods as indices for phosphorus leaching to waters

Phosphorus in agricultural soils around the BalticSea – comparison of laboratory methods as indicesfor phosphorus leaching to waters

A. K. Eriksson1 , B. Ul en

1 , L. Berz ina3 , A. I i tal

2 , V. Janssons3 , A. S. S i le ika

4 & A. Toomsoo5

1Department of Soil and Environment, Swedish University of Agricultural Sciences, PO Box 7014, SE-750 07 Uppsala, Sweden;2Faculty of Civil Engineering, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia, 3Environmental

Engineering and Water Management, Latvia University of Agriculture, 19 Akademijas Str., LV-3001 Jelgava, Latvia, 4Institute of

Water Management, Lithuanian University of Agriculture, Parko 6, LT-5048 Vilainiai, Kedainiai, Lithuania, and 5Institute of Soil

Science and Agrochemistry, Estonian University of Life Sciences, Kreutzwaldi 1, 51014, Tartu, Estonia

Abstract

In this study we investigated the phosphorus (P) content of Baltic soils. In the first set of analyses, 99

soil samples from the Baltic states and Sweden (soil set 1, representing seven different catchments or

experimental plots) were analysed for soil P using four extraction methods: ammonium lactate (PAL),

double lactate (PDL), Mehlich 3 (PM3) and carbonate (POlsen) (r = 0.85–0.97). In absolute values,

results from PM3, PDL and POlsen gave means of 71, 61 and 20%, respectively, of the value from the

PAL extraction method. Significantly different relationships were found between P soil concentrations

and pH of the extract. In addition, soil pH and organic matter content were found to be of importance.

Secondly, we tested 110 soil samples (soil set 2) from five different Swedish monitoring fields with clay

soils where PAL clearly correlated with soil P extracted in calcium chloride (PCaCl2) (r = 0.95). Values

of a single-point phosphorus sorption index (PSI) correlated with the aluminium concentration (AlAL)

in the lactate extract (r = 0.91) and with (AlOX) in the oxalate extract (r = 0.96). None of the soil P

tests with different extraction agents – calcium chloride (PCaCl2), water (Pw), POlsen or PAL – correlated

with the mean annual flow-weighted concentration (1999–2010) of dissolved reactive P (DRP) in

drainage water. Neither was there any clear relationship between DRP concentration in drainage water

and these tests combined with PSI or with other sorption indices including extracted Al and iron (Fe).

However, DRP was related to the clay content of the topsoil (r = 0.91, P < 0.05).

Keywords: Soil phosphorus (P) test, P sorption index, P drainage loss, clay content

Introduction

High nutrient loads from agricultural soils have a major

impact on the nutrient status of the Baltic Sea (Helsinki

Commission, 2009). In this enclosed brackish water,

phosphorus (P) is considered to be the key nutrient related to

nitrogen in the current rapid eutrophication, especially in

coastal areas (Boesch et al., 2006). High concentrations of P,

mainly in inorganic form, have been observed in water from

farmed mineral soils in the region (for example, Puustinen

et al., 2007). This inorganic P occurs either as particle-bound

P, representing a continuum of size from large particle

aggregates down to fine colloids (Haygarth et al., 2006), or as

dissolved phosphates. The latter are operationally defined as

dissolved reactive P (DRP) and can be determined after pre-

filtration. During heavy rain and snowmelt events, colloids

and particles may disperse from arable clay soils (Levy et al.,

1993). Inorganically bound P may simultaneously desorb from

the actual soil or from suspended particles in the soil water

(Yli-Halla et al., 1995) and increased DRP concentrations

may be rapidly transported through macropores down to

drainage pipes (Djodjic, 2001; Jarvis, 2007). During snowmelt

in particular with low water concentrations of electrolytes,

enhanced DRP concentrations have been reported in both

surface and drainage water (Ulen, 2003).

Soil P tests are commonly used to assess plant-available P

but are also used for risk assessment of P losses from arableCorrespondence: A. K. Eriksson. E-mail: [email protected]

Received March 2011; accepted after revision February 2012

Soil Use and Management, March 2013, 29 (Suppl. 1), 5–14 doi: 10.1111/j.1475-2743.2012.00402.x

ª 2013 The Authors. Soil Use and Management ª 2013 British Society of Soil Science 5

SoilUseandManagement

land (SEPA, Swedish Environmental Protection Agency,

2010). Comparisons between soil P tests and P losses to water

have been made in field studies of surface run-off (Sharpley,

1995; Sims et al., 2002) and in lysimeter studies with leaching

water (Hesketh & Brookes, 2000; Djodjic et al., 2004).

However, very few field studies have correlated commonly

used soil P tests with P losses via tile drain water. In addition,

many different methods are being used for soil P tests and

only a very few inter-calibrations have been reported between

methods used in northern European countries. Clear

comparisons between different soil P tests are useful for risk

assessment, model development and testing as only results

from local methods are usually available.

In northern Europe where soils are frequently acidic, an

extraction method with low pH using lactate called the

‘Egner extract’ method was introduced in the 1930s (Egner

et al., 1938). This method was modified by Riehm (1943) who

doubled the concentration of lactate (hence the name ‘double

lactate’ (PDL) extraction method) for better prediction of P

availability in calcareous soils. Later, Egner et al. (1960)

presented the ‘ammonium lactate’ (PAL) extraction method,

an improved procedure for determining plant-available P and

potassium. This and similar extraction methods developed

from the original Egner extract method are commonly used

in countries around the Baltic Sea (Ulen et al., 2012a). In

Estonia, the PDL method was used for measuring plant-

available P until 2004, but since then the Mehlich 3 (M3)

extract method (Mehlich, 1984) has been introduced with the

aim of tracing several elements in one single extract (Loide

et al., 2005). For the better prediction of plant-available P in

calcareous soils, another extraction method with high pH

(POlsen) is available (Olsen et al., 1954). This extraction

method is used in northern and central Europe for soils with

high pH. However, the yearly leaching of P is only a minor

part of the plant-available P in the soil and a smaller soil P

pool has also been used in studies of soil P loss to waters.

Extraction with a weak salt solution of calcium chloride

PCaCl2 has been used to imitate the salt condition of soil

water (Bache & Williams, 1971; Borling et al., 2001) and an

extraction procedure using distilled water as the extracting

agent (Pw) has been used to determine the loss of P dissolved

by rain or snowmelt on the soil surface (Sharpley, 1982; Pote

et al., 1996).

Other indices besides plant-available P content and a

smaller P pool have been tested to assess the risk of P

leaching. The concept of degree of P saturation (DPS)

introduced by Van der Zee et al. (1990) has been adopted in

national extraction schemes and P loss studies (e.g. Sharpley,

1995; Sims et al., 2002; Ulen, 2006). In lysimeter leaching

studies, Djodjic et al. (2004) used POlsen, PAL and PCaCl2 in

relation to a single-point P sorption index (PSI) according to

Borling et al. (2004a). When studying P losses at field scale,

long-term studies are necessary as climate is a driving

parameter. In addition, relatively dense soil sampling is

necessary, as both P content and P soil sorption capacity

may vary in space (Lookman et al., 1996). For clay soils

with frequent macropore flow, P factors in topsoil

conditions are expected to be the most important for the

drainage water entering tile drainage systems (Djodjic &

Bergstrom, 2005), while for sandy soils with slower water

infiltration, P physical-chemical conditions in subsoil

become more important for P in drainage water (Van der

Zee et al., 1990).

The present study is based on two hypotheses: (i)

extraction tests used in north-east Europe give significant

different soil P concentrations which may be explained by the

extraction agent, other methodology factors or soil factors;

and (ii) results of soil P tests, single or combined with P

sorption indices, in clay topsoil are related to the long-term

DRP concentration in drainage water. The first hypothesis

was tested on a set of soil samples, representing different soil

texture classes from seven different agricultural catchments

and experimental plots from countries around the Baltic Sea

(soil set 1). The second hypothesis was tested on a second set

of soil samples from five Swedish fields with clay soils

monitored long term for P content (soil set 2).

Materials and methods

Soil samples, soil texture class, soil pH and total organic

carbon analysis

Soil samples were taken from Estonia, Latvia, Lithuania and

Sweden in varied soil regions (Figure 1). Soil set 1 comprised

99 topsoil (0–20 cm) samples taken in autumn 2008 from

agricultural catchments in Estonia (Tonga and Ragina),

Latvia (Vecauce), Lithuania (Graisupis) and Sweden (E23)

and two field trials in Estonia (Kuusiku and Tartu). This soil

set represents a range of soil types (Table 1). Soil set 2

encompassed 110 composite topsoil samples from five

observation fields, with a mean of 19–59% clay in the

Swedish field monitoring system. The latter composite

samples represented subsamples taken in autumn 2005 in a

large square grid with a mean of 1.3 samples per ha. The

samples were all air-dried, carefully milled and sieved through

a 2 mm sieve. The resulting powder was then stored under

dry conditions until analysis. Soil texture was measured

according to Day (1965) and soil pH was analysed in water

according to one of the standard methods (ISO, 2005). The

total amount of soil organic carbon was quantified by a high-

temperature combustion method using a LECO CN2000

analyser (LECO Corporation, 2003).

Soil phosphorus analysis

Soil set 1 was analysed for plant-available P using four

methods (PAL, PDL, PM3 and POlsen) commonly used in seven

countries around the Baltic Sea (Table 2). The final P

6 A. K. Eriksson et al.

ª 2013 The Authors. Soil Use and Management ª 2013 British Society of Soil Science, Soil Use and Management, 29 (Suppl. 1), 5–14

concentration in the different extracts used was analysed

according to common practice in the respective countries.

This included a colorimetric method according to Murphy &

Riley (1962), which is used in the Baltic States, and

inductively coupled plasma atomic emission spectroscopy

(ICP-AES) according to Boumans (1979), which is used in

Sweden.

Soil set 2 was P-tested by two commonly used methods,

PAL and POlsen. An additional soil test of soil P pool was

carried out with 0.01 m CaCl2 (PCaCl2) according to Borling

et al. (2004a), and correspondingly extracting with water

(Pw), but with more thorough shaking (20 h instead of 1 h)

and with filtration through Munktell OOH paper before final

analysis. The amount of P in the extract from these three

methods including POlsen was measured colorimetrically. A

larger pool (‘storage P’) was extracted in 2 m hydrochloric

acid (PHCl) (KLS, 1965). In addition, acid-digestible analysis

of P content was performed after oxidative boiling in 7 m

nitric acid (PHNO3) (SIS, 1997). The amount of P in the

extract from the methods PHCl, PHNO3 and PAL was analysed

by ICP-AES (Perkin-Elmer Optima, 7300 DV).

Phosphorus sorption parameters

Sorption capacity was measured as a PSI for all soils in the

two soil sets using the laboratory procedure of Borling et al.

(2001) and with the lower addition of 19.4 mmol P kg per

soil. Aluminium (AlAL) and iron (FeAL) content determined

in the ammonium lactate (AL) extract were analysed by ICP-

AES. In addition, Al (Alox) and Fe (Feox) in soils from soil

set 2 were extracted with oxalate in darkness according to

Van Reeuwijk (2002). Any flocculated clay colloids were

0 125 250Kilometers

500

SOIL REGIONS (characterised by dominant soils)

SOIL REGIONS WITH BOREAL CLIMATE

1. Histosol – Podzol Regions

2. Leptosol – Podzol Regions

3. Podzol – Cambrisol Regions

4. Podzol – Leptosol Regions

SOIL REGIONS WITH BOREAL TO TEMPERATE CLIMATE

5. Histosol – Podzol Regions

6. Leptosol – Podzol Regions


8. Podzol – Leptosol Regions


10. Podzol – Cambrisol – Histosol Regions

11. Podsol – Cambrisol – Leptosol Regions

12. Podsol – Histosol – Leptosol Regions

SOIL REGIONS WITH TEMPERATE CLIMATE

13. Arenosol – Podzol – Cambrisol Regions

18. Podsol – Histosol – Leptosol Regions

27. Fluvisol – Gleysol Regions

31. Fluvisol – Regosol Regions

38. Luvisol – Cambisol – Gleysol Regions

40. Luvisol – Gleysol Regions

46. Podzol – Arenosol – Regosol Regions


48. Podzol – Gleysol Regions

LOCATION FOR SOIL SAMPLING

A. Tonga H. D1B. Kuusiku C. Ragina D. TartuE. Vecauce F. Graisupis G. E23

I. M2J. O4K. E7L. E20

Quaternary marine deposits, partly with eolian sand

Fluvial deposit

Glacial deposit

Igneous and metamorphic rocks

Alternating igneous, metamorphic and sedimentary rocks

Alternating igneous, metamorphic and sedimentary rocks (partly) covered with glacial deposit

Figure 1 Soil sample sites in this study and parent material map of countries around the Baltic Sea, except Russia and Belarus (Reimann et al.,

2003). Used with permission (BZ.8 – schub ⁄ jb) from the Bundesanstalt fur Geowissenschaften und Rohstoffe, BGR ª2003, Hanover, Germany.

Phosphorus in soils around the Baltic Sea 7


Table 1 Country, sampling site, number of samples (n), soil classa, size of catchment ⁄ field (km2) for the two sets of soil

Country Site n Soil classa Size (km2) pH TOC (%) PSI (mmol ⁄ kg) AlAL FeAL Alox Feox

Soil set 1

Baltic catchments

EST Tonga 11 Clay 9.7 6.8 2.9 6.3 35.2 8.6 – –

EST Raginab 1 Silty clay loam 21.3 7.8 2.6 3.0 13.3 3.2 – –

LVA Vecauceb Sandy loam 0.6 7.4 3.1 2.7 16.1 3.3 – –

LTU Graisupis 13 Sandy loam 14.2 7.5 3.0 3.0 11.9 3.9 – –

SWE E23 30 Clay 7.6 6.7 2.5 4.6 15.9 13.6 – –

Estonian experimental fields

EST Kuusikub 6 Clay loam 7.7 2.2 3.1 14.8 4.1 – –

EST Tartu 10 Sandy loam 7.2 1.2 2.0 8.6 5.2 – –

Soil set 2

Swedish monitoring fields

SWE 2Mb 40 Loam 0.35 6.9 1.5 2.5 5.1 5.2 88 62

SWE 4O 20 Silty clay loam 0.19 6.6 1.9 4.2 11.5 4.7 165 123

SWE 7E 25 Clay loam 0.22 6.5 2.4 3.6 8.2 5.2 151 114

SWE 1D 15 Silty clay loam 0.07 5.7 1.8 3.7 7.8 7.3 128 121

SWE 20E 10 Clay 0.05 6.9 2.8 4.6 11.1 6.5 183 120

Mean soil pH, total amount of organic carbon (TOC), single-point phosphorus sorption index (PSI), aluminium (AlAL), iron (FeAL), and AlOX

and FeOX for the different sampling sites. aSoil class according to FAO-ISRIC (1990); bCalcareous soils.

Table 2 Country, method, ionic composition and pH of extraction agent, soil to solution ratio (S:S), extraction shaking time and final analysis

method used in the country in questiona (and corresponding values for methods used for the Swedish soil set 2)

Country Methoda Extraction agent pH

S ⁄ S ratio

(g ⁄mL)

Shaking

time (min) Final analysis

Soil set 1

Sweden

Norway

PAL1 0.01 m ammonium lactate 3.75 1:20 90 ICP-AESb

Lithuania 0.40 m acetic acid Colorimetric9

Latvia PDL2 0.02 m calcium lactate 3.60 1:50 90 Colorimetric9

Poland 0.02 m HCl

Estonia PM33 0.2 m acetic acid

0.25 m ammonium nitrate

0.015 m ammonium fluoride

0.013 m HNO3

0.001 m EDTA

2.45 1:10 5 Colorimetric9

Denmark POlsen4 0.5 m NaHCO3 8.50 1:20 30 ICP-AES

Soil set 2

Sweden PCaCl25 0.01 m calcium chloride – 1:3 1200 Colorimetric9

Sweden Pw6 Water – 1:3 1200 Colorimetric9

Sweden POlsen4 0.5 m NaHCO3 8.50 1:20 30 Colorimetric9

Sweden PAL1 0.01 m ammonium lactate

0.40 m acetic acid

3.75 1:20 90 ICP-AES

Sweden PHCL7 4 m chloric acid – 1:20 90 ICP-AES

Sweden PHNO38 7 m perchloric acid – 1:4 60 ICP-AES

EDTA, ethylenediamine tetra-acetic acid; ICP-AES, inductively coupled plasma atomic emission spectroscopy. 1Egner et al. (1960); SIS (1993,

1995); 2Riehm (1943); Thun & Herrmann (1953); 3Mehlich (1984); 4Olsen et al. (1954); 5Borling et al. (2004b); 6Corresponding to Borling et al.

(2004b); 7KLS (1965); 8SIS (1997); 9Colorimetric method according to Murphy & Riley (1962). aFor a definition of the methods and their

abbreviations, see the Introduction; bAdditional colorimetric analysis in this study for comparison.



excluded by filtration through 0.45-lm filters before final P

analysis, which was performed using ICP-AES.

Phosphorus risk indices and phosphorus concentration in

drain tile water

Phosphorus risk indices were calculated for soil set 2. The

degree of phosphorus saturation (DPSAL) was calculated as a

molar ratio according to Ulen (2006), where PAL specifies the

amount of sorbed P, and AlAL + FeAL the P sorption

capacity. The ratio between POlsen and PSI (Borling et al.,

2004a,b) and between PAL and PSI (Borling et al., 2004a,b;

Djodjic & Bergstrom, 2005) was adopted as an alternative

risk index, together with the ratios between PCaCl2, Pw, and

POlsen and PSI in addition to the more commonly used

indices, the molar ratios between PAL and POlsen, and

R(Alox + Feox). Drainage water was usually collected

biweekly. Detailed information about sampling and analysis

can be found in Ulen et al. (2012b). Dissolved reactive P was

measured after pre-filtration using filters with a pore diameter

of 0.2 lm (Schleicher & Schull GmbH, Dassel, Germany).

No recalculation from other pre-treatments was needed.

Mean yearly concentrations of DRP (1999–2010) in drainage

water from the Swedish monitoring fields were calculated

from yearly transport divided by yearly discharge where the

former was based on daily interpolated concentration (from

biweekly sampling) multiplied by daily discharge.

Statistical analyses

Pearson correlation was used for calculating the correlation

coefficient (r) and probability (P). In addition, linear

regression was estimated. A paired t-test with significance

level a = 0.05 was additionally used. A point was identified

as an outlier if Cook’s distance exceeded 1 (Cook & Weisber,

1982). All statistical analyses were performed using Minitab

16 (Minitab, State College, PA, USA). Any differences

between different extraction methods were additionally

analysed by the Kruskal–Wallis ranking test and the

Bonferroni post-test.

Results and discussion

Colorimetric and inductively coupled plasma atomic

emission spectroscopy determination of extracted

phosphorus

A strong correlation was found between P determined by

colorimetry and with ICP-AES in the AL extract (r = 0.98),

but PAL measured using ICP-AES was higher in 98% of

samples compared with final colorimetric analysis. The

average difference was significant, equal to +19% and

confirmed findings by Haygarth et al. (1997) and Ulen (2006).

An even larger difference, which may also include organically

bound P, was found using M3 extraction (Ziadi et al., 2009).

The use of ICP-AES may include essentially more organically

bound P, which is heated up to aerosol form with the atoms

in an ionized state (Boumans, 1979). As this P concentration

may change and be susceptible to leaching, inductively

coupled plasma (ICP) determination of P should be

recommended for soil P tests.

Soil phosphorus tests for soil set 1

The amount of P extracted increased in the order

PDL £ PM3 < PAL (colorimetric analysis) and POlsen < PAL

(ICP-AES analysis) (Table 3). The two methods with extracts

containing lactate ions (PAL and PDL) were clearly correlated

(r = 0.97) but significantly (P < 0.001) more P was

extracted using PAL than with PDL and using the same final

colorimetric analysis method. Both lactate extracts contain

acids leading to dissolution of Al and Fe from their oxides

followed by P release. In addition, the acids inhibit any

secondary resorption of P in the extracts (Otabbong et al.,

2009). However, the PDL values were only 61% of the mean

PAL values from the different sites with final P analysed

Table 3 Country, sampling site, mean soil phosphorus concentration (POlsen, PDL, PM3 and PAL) (mg ⁄ kg) and the PDL ⁄PM3, PAL ⁄POlsen and

PAL ⁄PDL ratios in soil set 1a

Country Site n POlsen PDL PM3 PAL Col. PAL ICP PAL ⁄PDL PM3 ⁄PDL PAL ⁄ POlsen

Baltic catchments

EST Tonga 11 10b 22c 17c 42c 56b 1.9c 0.8c 5.6b

EST Ragina 1 11b 33c 45c 78c 70b 2.4c 1.4c 7.1b

LVA Vecauce 28 22b 35c 56c 82c 102b 2.3c 1.6c 4.6b

LTU Graisupis 13 42b 110c 125c 155c 165b 1.4c 1.1c 3.9b

SWE E23 30 33b 81c 70c 100c 120b 1.2c 0.9c 3.6b

Estonian experimental fields

EST Kuusiku 6 20b 75c 76c 156c 176b 2.1c 1.0c 8.8b

EST Tartu 10 29b 85c 127c 113c 129b 1.3c 1.5c 1.0b

aFor a definition of the methods and their abbreviations, see the Introduction. bPhosphorus analysed by inductively coupled plasma atomic

emission spectroscopy (ICP-AES). cPhosphorus analysed using a colorimetric method (Col.), according to Murphy & Riley (1962).



colorimetrically in both cases. The different soil ⁄ solutionratio and ionic composition probably resulted in a generally

more efficient AL extract. In addition, the diverse cations

may have had different effects on the charged particles on the

diffuse double layer (Barrow & Shaw, 1979). Significantly

higher values of PAL compared with PDL were measured at

the calcareous sites at Ragina, Vecauce and the experimental

field in Kuusiku (Table 3). From the latter site, a significantly

higher intercept (P < 0.001) was observed with these soils

compared with the regression line for all other soils

(Figure 2a). In addition, significant differences were estimated

by Kruskal–Wallis ranking test and the Bonferroni post-test

(P < 0.05). Besides more effective dissolution of calcium

phosphate (CaP) in the AL extract, the alkaline compounds

from this site, which has high pH (7.7), may have neutralized

the hydrochloric acid in the double lactate (DL) extract and

reduced its effectiveness (Vuc�ans et al., 2008).

A clear correlation (r = 0.89) was also found between PM3

and PDL, in agreement with Loide et al. (2005), but PM3

values were generally higher by a mean of 17%. As

ammonium fluoride (NH4F) is included in the M3 extract, P

may be released to the solution from Al oxides (Chang &

Jackson, 1957; Mehlich, 1978, 1984). Significantly higher

values of PM3 compared with PDL were observed for the

alkaline and calcareous Baltic soil at Ragina and from several

of the soils from Vecauce but not for the acidic soil from the

Estonian catchment of Tonga and the Swedish catchment

E23 (Table 3). The reason for less efficiency for the M3

extract from the acid soils may be that NH4F had formed

CaF2, thereby inhibiting ion exchange of the fluoride ion

(Smillie & Syers, 1972; Syers et al., 1972). In addition, the

different extraction times between the methods may also have

had an influence. Higher PM3 values relative to PDL (+50%)

were additionally found for the experimental field at Tartu

(Table 3) and illustrated by a significantly higher intercept

(P < 0.001) than for the other soils (Figure 2b). Organic

acids in soil solutions facilitate the mobility of P (Hesterberg,

2006). However, less organic acid may be dissolved by the

DL extract method compared with the M3 method from soils

at Tartu which had the lowest total amount of organic

carbon (TOC) content of all sites in the present study. In

contrast, the M3 extract, with oxidizing and stronger acids, is

fairly effective for P dissolution, independent of soil organic

matter content (Loide et al., 2005).

A clear correlation was also found between PAL and PM3

(r = 0.85). In absolute values PM3 estimated a mean of 71%

of the PAL values from the different sites with the final P

analysed colorimetrically. However, for Estonia, where both

methods are in use, diverse results were indicated for both

experimental sites (Figure 2c). Phosphorus was efficiently

extracted with PAL from the calcareous soil with high pH

from the site in Kuusiku but less efficiently from the soil poor

in organic matter from the Tartu site.

Finally, a clear correlation was found between PAL and

POlsen for soil set 1 (r = 0.85) but mean values of POlsen were

just 24% of the PAL value and the difference between the two

methods was highly significant. The P desorption mechanism

takes place by the OH ions in the Olsen extract but in the AL

extract, CaP compounds are dissolved owing to its low pH,

possibly also promoted by ion exchange in the extract

(e.g., Soinne, 2009). Accordingly, PAL may overestimate

plant-available P as the CaP compounds are not easily

available to plants in the field. A clear pH effect and the

highest PAL ⁄POlsen ratios were observed from Kuusiku and

0

100

200

300

400

0 100 200 300 400

PA

L (m

g P

/kg)

PA

L (m

g P

/kg)

PA

L (m

g P

/kg)

PD

L (m

g P

/kg)

PDL (mg P/kg) PM3 (mg P/kg)

PM3 (mg P/kg) POlsen (mg P/kg)

R2 = 93%0

100

200

300

400

0 100 200 300 400

0

100

200

300

400

0 100 200 300 400

( )*

0

100

200

300

400

500

0 50 100 150

PAL = 1.3PDL + 11

R2 = 76%

PAL = 0.9PDL + 33

R2 = 71%

PAL = 3.3POlsen + 28

R2 = 79%

PDL = 0.7PM3 + 14

(a) (b)

(c) (d)

Figure 2 Regression lines between (a) PAL and PDL (Kuusiku); (b) PDL and PM3 (Tartu); (c) PAL and PM3 (Kuusiku and Tartu); and (d) PAL

and POlsen (Kuusiku). Cross-hatched line demonstrates the 1:1 relationships. One point marked with * was identified as an outlier. Tonga,

Kuusiku, Ragina, Tartu, Vecauce, Graisupis, E23.



Ragina (Table 3) from the former sites indicated by a

different regression line compared with other soils

(Figure 2d). Overall, the pH and composition of the extract

solution were identified as the main reasons for the

differences observed between the methods, while dissimilar

shaking times and soil ⁄ solution ratios probably influenced the

amount of desorbed P to a lesser extent in accordance with

Neyroud & Lischer (2003). However, soil pH and organic

matter content were also shown to be important.

In soils from soil set 1, a reasonable correlation (r = 0.83)

was found between PSI and the sorbing elements Al and Fe,

especially when the estimated sorption capacity of these

elements is corrected for P already bound [(AlAL + FeAL) –

PAL]. However, organic matter competes with phosphate for

sorption sites. For some sites, the organic matter content

seemed to influence the extraction more and a strong

correlation was found between PSI and TOC, e.g. in soil

from Vecauce (r = 0.87), the site with the highest organic

matter content (3.1%).

Soil phosphorus test from Swedish monitoring fields

Soil P, extracted by six different methods (Table 3), increased

in the order PCaCl2 < Pw < POlsen < PAL < PHCl < PHNO3

for the Swedish monitoring fields with clay soils (Table 4).

Less than 0.1% of semi-total P (PHNO3) was extracted by

CaCl2 while the corresponding value for Pw was 0.61%. The

low values of PCaCl2 compared with Pw are probably due to

the higher electrolyte concentration in the CaCl2 extract,

which may decrease the negative potential near the charged

surfaces of the clay particles (Barrow & Shaw, 1979) and thus

decrease the desorption of phosphate ions. By contrast, more

dispersion of clay colloids may have taken place in the water

extract. A part of the measured P may also be bound to small

colloids and just a minor part may be in clear dissolved P

form (Haygarth et al., 1997; Sinaj et al., 1998; Koopmans

et al., 2005). Therefore, some P bound to colloids was

probably included in the Pw analysis in spite of the

filtration. Fine colloids have also been observed in drain tile

waters from clay soil and especially from field 1D (Ulen,

2004), the site with the highest Pw values in the present

study (Table 4).

The differences between PAL and POlsen were smaller for

soil set 2 (mean POlsen ⁄PAL ratio = 0.5) than for soil set 1

(POlsen ⁄PAL ratio = 0.2) probably as set 2 only contained one

field with calcareous soils (field 2M). As the correlation found

between PCaCl2 and POlsen (r = 0.73) and between PCaCl2 and

PAL (r = 0.66) was only moderate, the three different tests

may have slightly different potential to indicate P desorption

from particles to the soil solution.

A mean of 70% of the semi-total amount of P (PHNO3) was

extracted with hydrochloric acid (PHCl). This method is

mainly used to measure P stored in the soil, which in the long

term may be used as a plant nutrient (KLS, 1965). A moderate

correlation (r = 0.74) was found between these two methods

(PHNO3 and PHCl). Moderate correlations were also found

between POlsen and PHCl (r = 0.65) and between PAL and PHCl

(r = 0.48). This indicates that soils with high concentrations

of plant-available P also have a tendency to contain a larger

pool of P available in a long-term perspective.

Phosphorus sorption parameters in soils from Swedish

monitoring fields

For the Swedish monitoring fields, only a moderate

correlation (r = 0.60) was found between AlOX and TOC

confirming findings for other Swedish soils (Borling et al.,

2001). Furthermore, PSI was only moderately correlated to

clay content (r = 0.76). Between 4 and 8% of Al and Fe was

gained in the lactate extract compared with the oxalate

extract. A clear correlation was found between AlOX and

AlAL (r = 0.81) for the entire soil set, but only a weak

correlation was found between FeOX and FeAL (r = 0.26).

One reason for the latter finding is probably the lower

solubility of Fe (III) hydroxides, which are less soluble in the

lactate extract compared with Al (III) acid, and does not

form free Fe (III) ions to the same extent in the lactate

extract (pH 3.75) compared with the oxalate one (pH 3.0).

A clear correlation was found between PSI and AlOX from

the five sites (r = 0.96, P < 0.01) but this relationship was

Table 4 The five Swedish monitoring fields,

clay content, mean annual concentrations of

dissolved reactive P (DRP) in drain water

and mean soil P concentrations (PCaCl2),

(Pw), (POlsen), (PAL), (PHCl) and (PHNO3) for

soil set 2a

Field Clay (%)

DRP

(mg ⁄L)PCaCl2

(mg P ⁄ kg soil) Pw POlsen PAL PHCl PHNO3

2M 19 0.047 0.28b 3.3b 24c 63c 300c 410c

4O 28 0.052 0.14b 1.2b 19c 33c 300c 500c

7E 37 0.055 0.31b 2.0b 32c 57c 340c 480c

1D 35 0.082 0.33b 7.4b 29c 57c 480c 620c

20E 59 0.111 0.27b 2.1b 33c 69c 330c 550c

Mean P ⁄ PHNO3 (%) 0.06 0.61 5.3 11 68 100

The last row shows mean extracted P from the soil from the different methods in per cent of

PHNO3 for the five sites. aFor a definition of the methods and their abbreviations, see the

Introduction. bAnalysed using a colorimetric method, according to Murphy & Riley (1962).cAnalysed by inductively coupled plasma atomic emission spectroscopy (ICP-AES).



weaker for FeOX (r = 0.89, P < 0.05). Similar findings have

been found (e.g. Parvage et al., 2011), and when the oxalate

extraction took place in darkness, amorphous forms of Fe

oxides and Al oxides were extracted (Pansu & Gantheyrou,

2006).

Soil phosphorus tests as risk indices for phosphorus

leaching via drainage water

Mean DRP concentration in drainage water from the selected

Swedish monitoring fields varied between 0.05 and 0.11 mg ⁄Las a mean annual flow-weighted concentration (Table 4)

while topsoil clay content varied between 19 and 59%. These

DRP concentrations have been shown to be related to the

clay content of the topsoil (r = 0.91, P < 0.05). A high soil

content of fine particles may increase the risk for erosion of

clay colloids, and such particles in the drainage water may

desorb rather than adsorb P in a corresponding way, as

demonstrated for surface water (Hartikainen et al., 2010).

None of the measured soil P concentrations (Table 4) was

directly related to the DRP concentration in drainage water.

The P tests divided into the analysed P sorption indices were

all relatively high for the calcareous site 2M (Table 5) in spite

of a fairly low P water concentration in drainage water. None

of the environmental P indices used in this study correlated

with the long-term concentration of DRP in drainage water.

This is in contrast to the clear relationships found between

DPS in soil extracts and DRP concentrations in run-off water

(Sharpley, 1995; Sims et al., 2002), or between DPS in soil

extracts and leachate from topsoil lysimeters (e.g., Sims et al.,

2002). Similarly, a clear relationship was demonstrated

between DPSAL in sandy subsoil and DRP concentrations in

drainage water (Ulen, 2006) where the water is not bypassing,

but where in slower moving water P may sorb downwards to

the subsoil. However, at the studied sites, topsoil and subsoil

DRPAL were usually similar and relatively low (Table 5). The

present findings demonstrate the difficulty in interpreting

laboratory experiments in heterogeneous clay soils with large

field variation in DPS values (Lookman et al., 1996) and

limited knowledge of subsurface water transport (Djodjic

et al., 2004). In addition, variations in soil type and climate

conditions make it even more complex to apply risk indices

for P losses from fields and catchments in different

agricultural areas loading the Baltic Sea (Figure 1).

Conclusions

For many soils, the methods used locally for determining

extractable P around the Baltic Sea give relatively similar

results and the soil test values may be recalculated by other

methods. However, for calcareous alkaline soils the acid

extracts overestimate the magnitude of soil P. The use of soil

P tests as an environmental index needs further investigation.

Variations in soil organic carbon content appear to influence

the P sorption capacity of the studied soils, an issue likewise

requiring further investigation. In addition, any differences in

efficiency of iron and aluminium to sorb P under altered

redox conditions need further evaluation.

Acknowledgements

This study was financed by the Swedish Environmental

Protection Agency (SEPA) and by Formas (the Swedish

Research Council for Sustainable Development) which are

gratefully acknowledged. The long-term monitoring system of

arable fields was initially established through funding from

the Swedish University of Agricultural Sciences and SEPA.

For more than 30 yr, the funding has been solely from SEPA.

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Phosphorus in agricultural soils around the Baltic Sea - comparison of laboratory methods as indices for phosphorus leaching to waters