Estimated differences in stoichiometric scaling of microbial C, N, and P by land use/vegetation categories.

<p>Estimated SMA regression fit lines for each land use and vegetation category are shown to express habitat level differences in scaling of microbial biomass A) C∶N ratios, B) C∶P ratios, and C) N∶P ratios, with data log₁₀ transformed for normality. Bold lines are colored by land use and vegetation category, and treatments without significant fits are not shown. Colored solid lines indicate relationships where slopes were not equal to 1, while slopes not significantly different from 1 are are displayed as bold colored dotted lines. Thin black dotted lines show the regression fits for all groups combined (the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone-0057127-g001" target="_blank">Fig. 1</a>), while thin black solid lines indicate the Redfield ratios (C∶N∶P = 106∶16∶1). Individual plots for each regression fit by land use and vegetation categories are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s004" target="_blank">Figure S4</a>, with parameters estimated by SMA provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s008" target="_blank">Tables S3</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s009" target="_blank">S4</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s010" target="_blank">S5</a>, along with results of intercept and slope tests, and multiple comparisons of these parameters.</p

Factors influencing microbial metabolic quotients (<i>q</i>CO₂) of soil incubations.

<p>Significant factors included A) microbial C∶P ratios, B) available inorganic P, and C) soil pH. <i>q</i>CO₂ was calculated as the mol/mol ratio of C mineralization rates measured in glass jar incubations per unit microbial biomass C obtained from the same soils, with units of mmol CO₂-C/h/mol MBC-C/g soil. Relationships of <i>q</i>CO₂ with microbial C∶P (A), and inorganic P (B) were fit without data from litter or soil humic horizons. Data were log₁₀ transformed for normality and parameters estimated by SMA are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone-0057127-t001" target="_blank">Table 1</a>. SMA regressions fit using only forest and pasture soils (parameters in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s006" target="_blank">Table S1</a>) are not shown as they were essentially the same as the global relationships.</p

Scaling of soil microbial biomass C (MBC) with soil C, N, and P pools.

<p>Relationships in plots show variation in MBC with A) soil C, B) soil N, and C) soil P. Outliers from the general relationship between MBC and soil C in A), including floodplain mineral soils <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127-Schilling1" target="_blank">[95]</a> and arctic tundra <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127-Jonasson1" target="_blank">[96]</a> were removed prior to fitting regressions, and data were log₁₀ transformed to improve normality. Solid lines are the 1∶1 isometric lines based on the geometric mean ratio of each scaling relationship. Dashed lines are regression fits for all global soils, with correlation coeficients in plain text and parameters estimated by SMA given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone-0057127-t001" target="_blank">Table 1</a>. Global relationships were compared with fits obtained using only data from forests and pastures, and where slopes were significantly different from all combined treatments we plotted fits as dotted lines, with correlation coeficients given in italics. SMA regression parameters fit using only forest and pasture soils are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s006" target="_blank">Table S1</a>. Regressions were also tested seperately with only litter and organic soils data, but were these relationships were not significant.</p

Differential Nutrient Limitation of Soil Microbial Biomass and Metabolic Quotients (<em>q</em>CO₂): Is There a Biological Stoichiometry of Soil Microbes?

<div><p>Background</p><p>Variation in microbial metabolism poses one of the greatest current uncertainties in models of global carbon cycling, and is particularly poorly understood in soils. Biological Stoichiometry theory describes biochemical mechanisms linking metabolic rates with variation in the elemental composition of cells and organisms, and has been widely observed in animals, plants, and plankton. However, this theory has not been widely tested in microbes, which are considered to have fixed ratios of major elements in soils.</p> <p>Methodology/Principal Findings</p><p>To determine whether Biological Stoichiometry underlies patterns of soil microbial metabolism, we compiled published data on microbial biomass carbon (C), nitrogen (N), and phosphorus (P) pools in soils spanning the global range of climate, vegetation, and land use types. We compared element ratios in microbial biomass pools to the metabolic quotient <i>q</i>CO₂ (respiration per unit biomass), where soil C mineralization was simultaneously measured in controlled incubations. Although microbial C, N, and P stoichiometry appeared to follow somewhat constrained allometric relationships at the global scale, we found significant variation in the C∶N∶P ratios of soil microbes across land use and habitat types, and size-dependent scaling of microbial C∶N and C∶P (but not N∶P) ratios. Microbial stoichiometry and metabolic quotients were also weakly correlated as suggested by Biological Stoichiometry theory. Importantly, we found that while soil microbial biomass appeared constrained by soil N availability, microbial metabolic rates (<i>q</i>CO₂) were most strongly associated with inorganic P availability.</p> <p>Conclusions/Significance</p><p>Our findings appear consistent with the model of cellular metabolism described by Biological Stoichiometry theory, where biomass is limited by N needed to build proteins, but rates of protein synthesis are limited by the high P demands of ribosomes. Incorporation of these physiological processes may improve models of carbon cycling and understanding of the effects of nutrient availability on soil C turnover across terrestrial and wetland habitats.</p> </div

Differences in N∶P stoichiometry of soil microbial biomass among global vegetation and land use categories.

<p>Letters on x-axis above the plot show group differences among vegetation types (using Tukey's tests), and number of samples for each vegetation type are given on the lower x-axis. Overall variance described by vegetation (R² = 0.193, p<0.001) was determined using a general linear model. Solid horizontal line is the Redfield (1958) ratio N∶P = 16∶1, dashed line is average microbial N∶P (6.9) reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127-Cleveland1" target="_blank">[10]</a>.</p

Carbon mineralization rates (CO₂) varied with A) microbial biomass C (MBC) and B) soil pH.

<p>C mineralization rates were measured in glass jar incubations in studies with concurrent measurements of microbial biomass C, N, and P. Dashed line in A) is the regression fit, and solid line is the 1∶1 isometric line based on the geometric mean ratio of CO₂ to MBC (mean <i>q</i>CO₂). Parameters estimated by SMA are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone-0057127-t001" target="_blank">Table 1</a>. SMA regressions fit using only forest and pasture soils (parameters in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s006" target="_blank">Table S1</a>) are not shown as they were essentially the same as the global relationships.</p

Summary of SMA regressions of log₁₀-transformed C, N, and P contents in soil and microbial pools, along with predictors of soil C mineralization (CO₂) and microbial metabolism (<i>q</i>CO₂).

<p>Bivariate relationships were significant (P<0.001) for all relationships shown. Slopes significantly different from one (P>0.05) are shown in boldface font. Slopes not different from one (not bold) indicate an isometric (linear) relationship among parameters. The geometric mean and standard errors (SE) of stoichiometric ratios (x∶y ratio, x∶y mean) are given for reference, but are not representative where allometric slopes are different than 1. The coefficient of variation (CV) of these stoichiometric ratios is provided as a dimensionless index of dispersion about the mean. Single asterisks (*) indicate where different slopes are observed by considering only forest and pasture soils (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057127#pone.0057127.s006" target="_blank">Table S1</a>), and ** indicates relationships fit for all soils excluding litter and humus.</p

Map of the Los Amigos peatland in Madre de Dios, Peru, with sampling locations marked by stars.

<p>Basin Periphery: -12.55664 S, -70.1117 W; Basin Interior: -12.55926 S, -70.11702 W; Intrabasin Flats: -12.55947 S, -70.12037 W. Background image from ArcMap 10.3.</p

Mean (± standard deviation) surface soil (0–40 cm) chemistry (total nitrogen, total carbon, total phosphorus, phenolic compounds, extractable nitrate/nitrite, extractable ammonia/ammonium, water pH, salt pH) from three sites at the Los Amigos peat swamp in Madre de Dios, Peru.

<p>Letters (^a,b) refer to Tukey groupings and bold indicates where Tukey’s honest significant differences were found between sites. The data used to generate these values can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187019#pone.0187019.s002" target="_blank">S2 Table</a>.</p

Appendix A. Tables showing supplemental data including (1) watershed characteristics, (2) temperature and hydrology treatments, (3) plant species, and (4) chemical and physical properties of the study sites.

Tables showing supplemental data including (1) watershed characteristics, (2) temperature and hydrology treatments, (3) plant species, and (4) chemical and physical properties of the study sites