Soil and environmental influences on post-fire recovery in the southern Nevada Mojave Desert

Cayenne Engel and Scott R. AbellaUNLV School of Environmental and Public Affairs

Photo credit: Troy Phelps, Las Vegas BLM

Background

• Large fires are becoming increasingly common and destructive across the Mojave Desert landscape.

• Little is documented about the natural progression of post-fire recovery in the Mojave that specifically focuses on soil and environmental factors that may influence natural successional processes

• Vegetative recovery may (in part) be affected by variation in soil, climate, etc. across the landscape

Elevation Ecosystem classification

(m)

Low

High

Objective

Questions

• How are soil texture and nutrients affected by fire?• Is post-fire recovery predicted by abiotic factors?

Correlate abiotic factors with post-fire recovery at the landscape scale (look for explanatory variables)

2004 - 20061993 - 19951980-1988

Years of burns

US Forest ServiceBureau of Land MgmtFish and Wildlife ServiceNational Park Service

Las Vegas

Nevada

Fire chronosequence approach

Fire Chronosequence Study Methods

• 32 fires ranging from 2 – 30 years post-burn• 2007 – 2009 we sampled perennial plant community

composition (foliar cover) within burned and adjacent unburned Mojave Desert shrublands

Larrea tridentata (creosote) and Coleogyne ramosissima (blackbrush) dominated communities

• At each site we collected soil samples from interspaces and had them analyzed for texture and nutrients

• We related post-burn plant composition to abiotic site characteristics (elevation, aspect, slope gradient, and UTMs), soil texture and chemistry using ANOVA (perMANOVA), and multiple regressions

Fork (2005)

1980 Burn (RRCNCA)

Burned

Unburned

How are soil texture and nutrients affected by fire?

Soil variables measured • Soil texture: % clay, % sand, % silt• Soil nutrients:

• pH, electrical conductivity, bulk density

Statistical Approach• PerMANOVA (soil “community”), ANOVA (inivid vars)

• B• Ca• CaCO3• Cd• Cl

• Co• Cu• Fe• K• Mg

• Mn• Mo• Na• Ni• NO3

• P• Pb• SO4• Zn

• Total C• Inorganic C• Total organic C• Total N

How are soil texture and nutrients affected by fire?

• PerMANOVA: burn x comm type x decade• Overall, no effects of fire on soils (only on two variables) • Soils differ between plant communities

Termnum

dfden df

pseudo-F

P (perm)

P (Monte Carlo)

Prop. Var

Plant Community 1 24 4.06 0.003 0.014 0.141

Decade 1 24 1.92 0.092 0.107 0.067

Plant Comm X Decade 1 24 0.46 0.753 0.759 0.016

Burn 1 24 1.75 0.152 0.142 0.011

Plant Comm. X Burn 1 24 1.18 0.343 0.311 0.008

Decade X Burn 1 24 1.52 0.209 0.199 0.010

Plant Comm. X Decade X Burn 1 24 0.57 0.673 0.677 0.004

Few overall responses to burns, some responses mediated by community type

P = 0.04

P = 0.04

*

*

Blackbrush Creosote

Po

tass

ium

(m

g/g

)

0

5

10

Ele

ctri

cal

con

du

ctiv

ity

(µS

/cm

)

0

100

200

300

Burned Unburned

Fire × community type:

To

tal

org

an

ic C

(%

)

0.0

0.5

1.0

1.5

Burned Unburned

To

tal

N (

%)

0.00

0.05

0.10

P = 0.03

P = 0.0009

Effects of fire:

, some responses only in blackbrush communities

Is post-fire recovery predicted by abiotic factors?

Approach 1:• Examine whether soil and environmental variables predict

similarity of vegetation between burned and unburned plots. Multiple regression using the Sørensen similarity index

with individual environmental and soil variables (from unburned plots)

Approach 2:• Looked for relationships between burned and unburned

veg communities (Hellinger distance, used for perMANOVA) and the unburned – burn value for each soil variable Multiple regression

Is post-fire recovery predicted by abiotic factors? Sørensen similarity approach

• Similarity in perennial vegetation between burned and unburned sites was largely attributed to elevation and year since fire

Variable Direction Partial r2

Elevation - 0.31

YSF + 0.14

Model r2 = 0.45

• Soil texture and nutrient composition had little influence (adding less than 7% to the partial r2).

• Some interesting associations emerged within different age groups (need more information to properly interpret)

Variable Direction Partial r2

Zn + 0.63

NO3 + 0.18

UTMx - 0.12

Model r2 = 0.93

Full model mult reg

1980s fires mult reg

Elevation (m)600 800 1000 1200 1400 1600

Sim

ilar

ity

(%)

0

20

40

60

80

Mean min temp (C)4 6 8 10 12 14 16

Mean annual precip (mm)150 200 250 300 350

Blackbrush 1980Blackbrush 1990Blackbrush 2000Creosote 1980Creosote 1990Creosote 2000

Mean max temp (C)18 20 22 24 26 28

Sim

ilar

ity

(%)

0

20

40

60

80

r2 = 0.31

r2 = 0.12

r2 = 0.30r2 = 0.32

Is post-fire recovery predicted by abiotic factors? Hellingers distance = unburned – burned soils

  df Estimate SE t P-value VIF

Intercept 1 1.10 0.03 32.0 <.0001 0.0

BulkDensity 1 0.09 0.28 0.3 0.7515 1.6

pH 1 -0.48 0.18 -2.7 0.0133 1.8

Na 1 0.04 0.05 0.9 0.3909 1.2

K 1 0.00 0.01 0.0 0.9844 2.7

NO3 1 -0.03 0.03 -1.1 0.2766 2.2

SO4 1 0.00 0.00 0.0 0.9690 1.7

P 1 0.00 0.00 0.5 0.5921 1.4

InorganicC 1 -0.04 0.05 -0.9 0.3614 1.4

TotalorgC 1 -0.04 0.06 -0.6 0.5624 1.7

TotalN 1 -1.55 1.12 -1.4 0.1838 2.7

Does vegetation track differences among soils?

• PerMANOVA indicates that vegetation responses do not track soil responses (sig. responses don’t match)

Vegetation data Soil data

Termnum

dfden df

pseudo-F

P (perm) P (M.C)

pseudo-F

P (perm) P (M.C)

Plant Community 1 24 1.95 0.001 0.004 4.06 0.003 0.014Decade 1 24 1.18 0.054 0.220 1.92 0.092 0.107Plant Comm X Decade 1 24 0.96 0.593 0.526 0.46 0.753 0.759Burn 1 24 2.56 0.001 0.001 1.75 0.152 0.142Plant Comm. X Burn 1 24 1.26 0.048 0.148 1.18 0.343 0.311Decade X Burn 1 24 1.35 0.022 0.099 1.52 0.209 0.199Plant Comm. X Decade X Burn 1 24 1.23 0.063 0.176 0.57 0.673 0.677

Summary

• Soil – vegetation relationships are swamped when looking at the landscape scale by influences of site location and plant community identity.

• Elevation/precip/temp are the most consistent abiotic predictors of community composition and of amount of recovery (similarity) between burned and unburned plots.

• Overall, at the landscape scale, relatively little was predicted by specific nutrients or soil texture across the landscape, and long term effects of fire on the soil properties that we measured were few.

• Information about fire characteristics (intensity, severity, etc.) would likely correlate with plant recovery…

Acknowledgements

• Funding: This study was supported through cooperative agreements between the University of Nevada Las Vegas (UNLV) and the Bureau of Land Management (Southern Nevada District) and National Park Service (Lake Mead National Recreation Area)in part funded by the Joint Fire Science Program. We thank Christina Lund (formerly of SND), and Kevin Oliver and Nora Caplette of SND, and Alice Newton (LMNRA) for facilitating work under these agreements; Tim Rash (formerly of SND) for supplying fire records.

• Cheryl Vanier for statistical help (perMANOVA)• Field Assistance: Nick Bechtold, Teague Embry, Adria

DeCorte, Kate Prengaman, Chris Roberts, and Sarah Schmid

• Soil samples were analyzed by the Environmental Soil Analysis Laboratory at UNLV.

Photo credit: Troy Phelps, Las Vegas BLM

Are patterns of post-fire recovery within fires influenced by site-specific parameters more than time since burn,

location, and initial community type?

• Similarity among plots is greater within burns than among burns

Within burns

Similarity (Sørensen) CV (%)

Burned 0.39 42Unburned 0.50 35

Among burns

Burned 0.24 69Unburned 0.27 76

All sites, vegetation ordination

Does post-fire plant community composition correlate with certain soil or environmental variables?

• Strongest influences are elevation and community type

• Easting and Na each explain 20% of the variation in the distribution

• Silt (13%) and P (12%) follow

Comm. type

Creosote Cover

Blackbrush Cover

Elev. (m)

Annual Precip (mm)

Tmin (C)

Tmax (C)

Creosote 28% 2% 975 205 11.1 24.4

Blackbrush 2% 49% 1296 266 8.4 22.3

Associated Species

Blackbrush:• Nevada jointfir• Banana Yucca• Mohave Yucca• Big galleta grass• Spiny menodora

Creosote:• Bursage• Nevada jointfir• Rhatany• Desert Almond• Mohave Yucca

Sites throughout Southern NV (Northern AZ) in Mojave Desert shrub communities including creosote and blackbrush dominated communities

Creosote

Elevation (m)

600 900 1200 1500

Sim

ilarit

y (%

)

0

20

40

60

801980s1990s2000s

Blackbrush

Elevation (m)

600 900 1200 1500 1800

Elevation predicts similarity only in creosote communities

r2 = 0.26