Microbial function and response to nitrogen addition in
grassland soils
SEV
KNZ
L. H. Zeglin*, M. Stursova, R. L. Sinsabaugh, S. L. Collins
Department of Biology, University of New Mexico, Albuquerque, NM 87131
• Decrease of mycorrhizzal infection &
(How) do grassland soil
Predictions
growth (from decreased plant
microbial communities • Higher bioavailability of nitrogen in soil allocation of belowground carbon) 
respond to increased
- microbial energy allocation toward
decrease in soil microbial biomass
acquisition of other nutrients (C, P) 
inorganic nitrogen
increased Phos, CBH, βG activity. Dampened • Lower oxidative enzyme activities 
availability?
response in old P-limited SAF soil.
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
• 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.
ENZYMES ASSAYED. Name (abbreviation). Process catalyzed;
functional community interpretation, nutrient acquired.
-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
mg N / kg dry soil
NO3-N
NH4-N
*
35
Ph os
30
*
25
SE
V
KN
Z
SA
F
Am
bi
en
t
KN
Z
+N
Am
bi
en
t
SE
V
+N
0
§G
CBH
Ph e n ox
0.086
-0.18*
0.56*
0.35*
KNZ
Response
ratio
0.12**
0.023
0.069
SAF
Response
ratios
(N1, N2)
0.11
0.12
-0.056
0.42
0.042
-0.24*
P C1
68.1%
4.766
.918
-.870
.973
.799
.654
-.739
-.781
P C2
21.7%
1.517
.258
.453
-.129
.575
.721
.503
.354
0.53
0.022
-0.024
0.10
0.14*
0.068
2.76
-0.028
-0.095
-0.022
-0.022
0
0
3.63
-0.67
+
Table 2. Response magnitudes and PCA loadings &
eigenvalues for all EEA data. Response magnitude = mean
((Treatment - Ambient) / Ambient); * indicates ANOVAsignificant treatment response.
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.
0.5
0
-0.5
SEV
SEV
KNZ
KNZ
SAF
SAF
SAF
-1
Ambient
+N
Ambient
+N
Ambient
+N1
+N2
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).
-2
-2
-1.5
-1
-0.5
0
0.5
1
PC1 (68.1%)
1.5
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.
Figure 2. Microbial biomass carbon. * indicates
ANOVA p < 0.05 for treatment effect
450
Perox
Response
ratio
15
5
NAG
SEV
20
10
LAP
400
350
300
* *
250
200
150
100
50
0
Conclusions
•
1
-1.5
Phenol oxidase (Phenox), Peroxidase (Perox). Oxidation of
bonds in organic molecules; microbial effort to break down
lignin, other recalcitrant plant derivatives and humic complexes
40
1.5
PC2 (21.7%)
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
Figure 1. Extractable N. * indicates
ANOVA p < 0.05 for treatment effect
Figure 3. PCA variable reduction of all EEA data.
Phosphatase (Phos). Pulls phosphate (PO43-) from larger
molecules; microbial effort to obtain P
Implications for belowground C storage? No change
No treatment effect in bulk OM or total C pool
• 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).
Methods
• 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
Lowers oxidative activities? No common response of Perox, Phenox to N addition
+N
2
7.6
SA
F
0.017
+N
1
Aridisol
SA
F
loam sand,
calcareous
Inhibition of mycorrhizzal infection / growth? +
Overall lower biomass in N amended soils, strongest response at SAF
bi
en
t
250
but not SAF. (Figure 1)
Am
SEV
• Extractable soil inorganic N was higher in treatment plots at SEV and KNZ,
SA
F
Experiment
length
(years)
+N
N added
(kg / ha / year)
KN
Z
Soil
N:P
bi
en
t
Soil
C:N
Am
Soil
pH
KN
Z
OM content
(g / g dry soil)
Am
bi
en
t
SE
V
+N
Soil order
More microbial investment in C, P acquisition? some +
All sites: Phos activities increase
SE
V
Soil
character
bi
en
t
SA
F
+N
1
SA
F
+N
2
MAP
(mm)
Am
Site
Results
mg biomass C / kg dry soil
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.
accumulation of (recalcitrant) OM
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.
SAF
§G
LAP
Perox
§G :LAP
§G :Perox
pH
Ref erence
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
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.