0

5

10

15

20

25

30

35

40

SEV Am

bient

SEV +N

KNZ Am

bient

KNZ +N

SAF Am

bient

SAF +N1

SAF +N2

mg

N /

kg

dry

so

il

NO3-NNH4-N

0

50

100

150

200

250

300

350

400

450

SEV Am

bient

SEV +N

KNZ Am

bient

KNZ +N

SAF Am

bient

SAF +N1

SAF +N2

mg

bio

ma

ss

C /

kg

dry

so

il

Microbial function and response to nitrogen addition in grassland soils

L. H. Zeglin*, M. Stursova, R. L. Sinsabaugh, S. L. Collins

Department of Biology, University of New Mexico, Albuquerque, NM 87131

(How) do grassland soil microbial communities respond to increased

inorganic nitrogen availability?

Results• Extractable soil inorganic N was higher in treatment plots at SEV and KNZ, but not SAF. (Figure 1)

• Although the sum EEA data show functional community structure was not different in control and N-addition treatments (Figure 3, MANOVA not shown), individual enzyme activity response was variable and often considerable (Table 2). For example, CBH activity consistently increased by about 14% at KNZ.

• Soil microbial biomass C decreased with N addition at all sites (MANOVA, significant treatment effect, Figure 2; within-site ANOVA significant only at SAF). However, other C pools (total OM, total ) did not change (not shown).

Many thanks to:

Cliff Dahm, Chris Lauber, Melinda Smith, John Blair, Alan Knapp, Rich Fynn, Marcy Gallo, Chelsea Crenshaw, Nathan Daves-Brody, Kylea Odenbach, Kris Mossberg and John Craig; Sevilleta LTER, Konza LTER, Ukulinga Research Farm and University of KwaZulu-Natal, Pietermartizburg. Funding for this work was provided by the National Science Foundation through NSF-DEB, FSIDP-IGERT at UNM and NSF-PDF.

Please direct questions/comments to Lydia Zeglin, lzeglin@unm.edu.

• One composite sample of 0 – 20 cm soil cores collected from each plot at all sites (SEV, n = 20; SAF, n = 3; KNZ, n = 24). For each sample:

• Quanitify KCl-extractable inorganic N, total N and C, K2SO4-extractable DOC, microbial biomass C (*not yet analyzed for SEV) and soil OM

• Measure soil potential extracellular enzyme activity (EEA) for key litter-breakdown and nutrient-acquiring enzymes (see box below).• Spike soil slurry subsamples with fluorescently / colorimetrically-labeled substrate and

incubate at 20° C• Level of fluorescence / color after incubation is converted to amount of substrate

utilized by soil enzyme• Reported units: nmol substrate utilized per hour per gram soil organic matter (nmol / hr

/ g OM); the standardization by soil OM allows valid cross-system comparisons• Statistical methods

• Principal components analysis (PCA): reduce 7 EEA variables to 2, assess differences between sites / treatments within a “functional community space”

• Multiple analysis of variance & analysis of variance (MANOVA, ANOVA) to test for treatment differences across and within sites, respectively

** EEA data were log-transformed to fit assumptions of normality

• Grassland soil microbial community function is variable, perhaps linked to soil pH rather than nutrient availability

• At each site, all soil microbial communities invest more in P uptake when N is added, and other individual enzyme responses are apparent

• However, across sites, functional communities seem resistant to N addition

• No direct or indirect evidence for belowground C accumulation in response to increased N in grassland systems

Table 3. Select enzyme activity parameters, vegetation type and pH in grassland and forest soils, and an aquatic system.

• Decrease of mycorrhizzal infection & growth (from decreased plant

allocation of belowground carbon) decrease in soil microbial biomass

• Lower oxidative enzyme activities accumulation of (recalcitrant) OM

• Higher bioavailability of nitrogen in soil- microbial energy allocation toward

acquisition of other nutrients (C, P) increased Phos, CBH, βG activity.

Dampened response in old P-limited SAF soil.

Predictions

KNZSEV

SAF

ENZYMES ASSAYED. Name (abbreviation). Process catalyzed; functional community interpretation, nutrient acquired.

Phosphatase (Phos). Pulls phosphate (PO43-) from larger

molecules; microbial effort to obtain P

N-acetylglucosaminidase (NAG). Pulls amines (NH3) from cell walls; microbial effort to obtain N, microbial loop N processing

L-aminopeptidase (LAP). Breaks apart amino acids; microbial effort to obtain labile N and C

-glucosidase (BG). Breaks apart simple sugars; microbial effort to obtain labile C

Cellobiohydrolase (CBH). Breaks apart cellulose; microbial effort to decompose plant litter, obtain C

Phenol oxidase (Phenox), Peroxidase (Perox). Oxidation of bonds in organic molecules; microbial effort to break down

lignin, other recalcitrant plant derivatives and humic complexes

Site MAP(mm)

Soil character

Soil order OM content(g / g dry soil)

SoilpH

SoilC:N

SoilN:P

N added(kg / ha / year)

Experiment length(years)

SEV 250 loam sand, calcareous

Aridisol 0.017 7.6 13 5 10 10

KNZ 835 Silty clay loam

Mollisol 0.082 5.5 13 20 10 2

SAF 694 Clay-rich, acidic

Alfisol 0.127 4.8 14 48 7 (+N1)14 (+N2)

55

Table 1. Site information. SEV = Sevilleta National Wildlife Refuge, New Mexico, USA; KNZ = Konza Prairie, Kansas, USA; SAF = Ukulinga Research Farm, KwaZulu-Natal, South Africa. MAP = mean annual precipitation, OM = organic matter, N added as ammonium nitrate (NH4NO3) at all sites. Of these variables, only pH showed a significant response (negative) to N enrichment.

Methods

Figure 1. Extractable N. * indicates ANOVA p < 0.05 for treatment effect

Table 2. Response magnitudes and PCA loadings & eigenvalues for all EEA data. Response magnitude = mean

((Treatment - Ambient) / Ambient); * indicates ANOVA-significant treatment response.

Figure 2. Microbial biomass carbon. * indicates ANOVA p < 0.05 for treatment effect

More microbial investment in C, P acquisition? some +All sites: Phos activities increase

Inhibition of mycorrhizzal infection / growth? +Overall lower biomass in N amended soils, strongest response at SAF

Lowers oxidative activities? -No common response of Perox, Phenox to N addition

Implications for belowground C storage? No changeNo treatment effect in bulk OM or total C pool

Figure 3. PCA variable reduction of all EEA data. Microbial community function has been characterized using suites of EEA analyses in many types of ecosystems, but not grasslands.

PCA shows a strong grouping of grassland soil microbial functional community by site (Figure 3). PC1 correlates most strongly with pH (Pearson’s r = -0.909, p = 0.000) and is loaded negatively by LAP, Phenox and Perox enzyme activity (Table 2). Unlike the other enzymes assayed, these three catalyze reactions most efficiently at high pH.

Table 3 illustrates how the grasslands characterized here show a huge variability in EEA relative to forested systems (even across a wide range of forest vegetation type).

Taxonomic diversity of soil microbial communities has been related (positive correlation) to variation in soil pH. A synthesis of EEA data from many ecosystems might reveal a similar pattern for functional diversity.

Conclusions

-2

-1.5

-1

-0.5

0

0.5

1

1.5

-2 -1.5 -1 -0.5 0 0.5 1 1.5

PC1 (68.1%)

PC

2 (

21

.7%

)

SEV Ambient SEV +N KNZ Ambient KNZ +N SAF Ambient SAF +N1 SAF +N2

Phos LAP NAG §G CBH Phenox Perox

SEV Response

ratio 0.086 -0.18* 0.56* 0.35* 0.53 0.022 -0.024

KNZ Response

ratio 0.12** 0.023 0.069 0.10

+ 0.14* 0.068 2.76

SAF Response

ratios (N1, N2)

0.11 0.12

-0.056 0.42

0.042 -0.24*

-0.028 -0.095

-0.022 -0.022

0 0

3.63 -0.67

PC1 68.1% 4.766

.918 -.870 .973 .799 .654 -.739 -.781

PC2 21.7% 1.517

.258 .453 -.129 .575 .721 .503 .354

§G LAP Perox §G:LAP §G:Perox pH Reference

SEV (NM) 1842 6306 1837000 0.29 0.0010 7.6 This study

KNZ (KS) 3008 200 831 15.0 3.62 5.5 This study

Ukulinga (South Africa) 2612 45 2077 58.0 1.26 4.8 This study

Manistee (MI) SMBW 4920 396 25000 12.4 0.197 5.5 Sinsabaugh et al. 2005

Manistee (MI) ROWO 2220 131 83500 16.9 0.027 5.5 Sinsabaugh et al. 2005

Niwot Ridge (CO) 2260 39 1480 57.9 1.53 5.5 M. Weintraub, pers. comm.

Duke FACE (NC) 4570 96 80900 47.6 0.057 5.5 Finzi et al. 2006

ORNL FACE (TN) 13500 561 124000 24.1 0.011 5.5 Sinsabaugh et al. 2003

Hudson River (NY) 0.10 Sinsabaugh et al. 1997

* **

*