Plant responses to elevated CO2 under competing hypotheses of nitrogen and phosphorus limitations.

The future ecosystem carbon cycle has important implications for biosphere-climate feedback. The magnitude of future plant growth and carbon accumulation depends on plant strategies for nutrient uptake under the stresses of nitrogen (N) versus phosphorus (P) limitations. Two archetypal theories have been widely acknowledged in the literature to represent N and P limitations on ecosystem processes: Liebig's Law of the Minimum (LLM) and the Multiple Element Limitation (MEL) approach. LLM states that the more limiting nutrient controls plant growth, and commonly leads to predictions of dramatically dampened ecosystem carbon accumulation over the 21st century. Conversely, the MEL approach recognizes that plants possess multiple pathways to coordinate N and P availability and invest resources to alleviate N or P limitation. We implemented these two contrasting approaches in the E3SM model, and compiled 98 in situ forest N or P fertilization experiments to evaluate how terrestrial ecosystems will respond to N and P limitations. We find that MEL better captured the observed plant responses to nutrient perturbations globally, compared with LLM. Furthermore, LLM and MEL diverged dramatically in responses to elevated CO2 concentrations, leading to a two-fold difference in CO2 fertilization effects on Net Primary Productivity by the end of the 21st century. The larger CO2 fertilization effects indicated by MEL mainly resulted from plant mediation on N and P resource supplies through N2 fixation and phosphatase activities. This analysis provides quantitative evidence of how different N and P limitation strategies can diversely affect future carbon and nutrient dynamics.

Genes and genome-resolved metagenomics reveal the microbial functional make up of Amazon peatlands under geochemical gradients.

The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store ~7.07 Gt of organic carbon interacting with multiple microbial heterotrophic, methanogenic, and other aerobic/anaerobic respirations. Little is understood about the contribution of distinct microbial community members inhabiting tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic conditions. Using gene- and genome-centric approaches, we evaluate the functional potential of the underlying microbial communities. Abundance analyses show significant differences in C, N, P, and S acquisition genes. Furthermore, community interactions mediated by toxin-antitoxin and CRISPR-Cas systems were enriched in oligotrophic soils, suggesting that non-metabolic interactions may exert additional controls in low-nutrient environments. Additionally, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the geochemical gradient in the predicted microbial populations involved in degradation of organic matter, and the cycling of N and S. Notably, we observed differences in the nitric oxide (NO) reduction strategies between sites with high and low N2 O fluxes and found phyla putatively capable of both NO and sulfate reduction. Our findings detail how gene abundances and microbial populations are influenced by geochemical differences in tropical peatlands.

Nitrous oxide emissions from inland waters: Are IPCC estimates too high?

Nitrous oxide (N2 O) emissions from inland waters remain a major source of uncertainty in global greenhouse gas budgets. N2 O emissions are typically estimated using emission factors (EFs), defined as the proportion of the terrestrial nitrogen (N) load to a water body that is emitted as N2 O to the atmosphere. The Intergovernmental Panel on Climate Change (IPCC) has proposed EFs of 0.25% and 0.75%, though studies have suggested that both these values are either too high or too low. In this work, we develop a mechanistic modeling approach to explicitly predict N2 O production and emissions via nitrification and denitrification in rivers, reservoirs and estuaries. In particular, we introduce a water residence time dependence, which kinetically limits the extent of denitrification and nitrification in water bodies. We revise existing spatially explicit estimates of N loads to inland waters to predict both lumped watershed and half-degree grid cell emissions and EFs worldwide, as well as the proportions of these emissions that originate from denitrification and nitrification. We estimate global inland water N2 O emissions of 10.6-19.8 Gmol N year-1 (148-277 Gg N year-1 ), with reservoirs producing most N2 O per unit area. Our results indicate that IPCC EFs are likely overestimated by up to an order of magnitude, and that achieving the magnitude of the IPCC's EFs is kinetically improbable in most river systems. Denitrification represents the major pathway of N2 O production in river systems, whereas nitrification dominates production in reservoirs and estuaries.

Water Table Dynamics and Biogeochemical Cycling in a Shallow, Variably-Saturated Floodplain.

Three-dimensional variably saturated flow and multicomponent biogeochemical reactive transport modeling, based on published and newly generated data, is used to better understand the interplay of hydrology, geochemistry, and biology controlling the cycling of carbon, nitrogen, oxygen, iron, sulfur, and uranium in a shallow floodplain. In this system, aerobic respiration generally maintains anoxic groundwater below an oxic vadose zone until seasonal snowmelt-driven water table peaking transports dissolved oxygen (DO) and nitrate from the vadose zone into the alluvial aquifer. The response to this perturbation is localized due to distinct physico-biogeochemical environments and relatively long time scales for transport through the floodplain aquifer and vadose zone. Naturally reduced zones (NRZs) containing sediments higher in organic matter, iron sulfides, and non-crystalline U(IV) rapidly consume DO and nitrate to maintain anoxic conditions, yielding Fe(II) from FeS oxidative dissolution, nitrite from denitrification, and U(VI) from nitrite-promoted U(IV) oxidation. Redox cycling is a key factor for sustaining the observed aquifer behaviors despite continuous oxygen influx and the annual hydrologically induced oxidation event. Depth-dependent activity of fermenters, aerobes, nitrate reducers, sulfate reducers, and chemolithoautotrophs (e.g., oxidizing Fe(II), S compounds, and ammonium) is linked to the presence of DO, which has higher concentrations near the water table.

Reactive Transport Model of Sulfur Cycling as Impacted by Perchlorate and Nitrate Treatments.

Microbial souring in oil reservoirs produces toxic, corrosive hydrogen sulfide through microbial sulfate reduction, often accompanying (sea)water flooding during secondary oil recovery. With data from column experiments as constraints, we developed the first reactive-transport model of a new candidate inhibitor, perchlorate, and compared it with the commonly used inhibitor, nitrate. Our model provided a good fit to the data, which suggest that perchlorate is more effective than nitrate on a per mole of inhibitor basis. Critically, we used our model to gain insight into the underlying competing mechanisms controlling the action of each inhibitor. This analysis suggested that competition by heterotrophic perchlorate reducers and direct inhibition by nitrite produced from heterotrophic nitrate reduction were the most important mechanisms for the perchlorate and nitrate treatments, respectively, in the modeled column experiments. This work demonstrates modeling to be a powerful tool for increasing and testing our understanding of reservoir-souring generation, prevention, and remediation processes, allowing us to incorporate insights derived from laboratory experiments into a framework that can potentially be used to assess risk and design optimal treatment schemes.

Environmental factors determining ammonia-oxidizing organism distribution and diversity in marine environments.

Ammonia-oxidizing bacteria (AOB) and archaea (AOA) play a vital role in bridging the input of fixed nitrogen, through N-fixation and remineralization, to its loss by denitrification and anammox. Yet the major environmental factors determining AOB and AOA population dynamics are little understood, despite both groups having a wide environmental distribution. This study examined the relative abundance of both groups of ammonia-oxidizing organisms (AOO) and the diversity of AOA across large-scale gradients in temperature, salinity and substrate concentration and dissolved oxygen. The relative abundance of AOB and AOA varied across environments, with AOB dominating in the freshwater region of the Chesapeake Bay and AOA more abundant in the water column of the coastal and open ocean. The highest abundance of the AOA amoA gene was recorded in the oxygen minimum zones (OMZs) of the Eastern Tropical South Pacific (ETSP) and the Arabian Sea (AS). The ratio of AOA : AOB varied from 0.7 in the Chesapeake Bay to 1600 in the Sargasso Sea. Relative abundance of both groups strongly correlated with ammonium concentrations. AOA diversity, as determined by phylogenetic analysis of clone library sequences and archetype analysis from a functional gene DNA microarray, detected broad phylogenetic differences across the study sites. However, phylogenetic diversity within physicochemically congruent stations was more similar than would be expected by chance. This suggests that the prevailing geochemistry, rather than localized dispersal, is the major driving factor determining OTU distribution.

Beaver dams overshadow climate extremes in controlling riparian hydrology and water quality.

Hydrologic extremes dominate chemical exports from riparian zones and dictate water quality in major river systems. Yet, changes in land use and ecosystem services alongside growing climate variability are altering hydrologic extremes and their coupled impacts on riverine water quality. In the western U.S., warming temperatures and intensified aridification are increasingly paired with the expanding range of the American beaver-and their dams, which transform hydrologic and biogeochemical cycles in riparian systems. Here, we show that beaver dams overshadow climatic hydrologic extremes in their effects on water residence time and oxygen and nitrogen fluxes in the riparian subsurface. In a mountainous watershed in Colorado, U.S.A., we find that the increase in riparian hydraulic gradients imposed by a beaver dam is 10.7-13.3 times greater than seasonal hydrologic extremes. The massive hydraulic gradient increases hyporheic nitrate removal by 44.2% relative to seasonal extremes alone. A drier, hotter climate in the western U.S. will further expand the range of beavers and magnify their impacts on watershed hydrology and biogeochemistry, illustrating that ecosystem feedbacks to climate change will alter water quality in river systems.

Characterizing Natural Organic Matter Transformations by Microbial Communities in Terrestrial Subsurface Ecosystems: A Critical Review of Analytical Techniques and Challenges.

Determining the mechanisms, traits, and pathways that regulate microbial transformation of natural organic matter (NOM) is critical to informing our understanding of the microbial impacts on the global carbon cycle. The capillary fringe of subsurface soils is a highly dynamic environment that remains poorly understood. Characterization of organo-mineral chemistry combined with a nuanced understanding of microbial community composition and function is necessary to understand microbial impacts on NOM speciation in the capillary fringe. We present a critical review of the popular analytical and omics techniques used for characterizing complex carbon transformation by microbial communities and focus on how complementary information obtained from the different techniques enable us to connect chemical signatures with microbial genes and pathways. This holistic approach offers a way forward for the comprehensive characterization of the formation, transformation, and mineralization of terrestrial NOM as influenced by microbial communities.

Seasonal and annual reoccurrence in betaproteobacterial ammonia-oxidizing bacterial population structure.

Microbes exhibit remarkably high genetic diversity compared with plant and animal species. Many phylogenetically diverse but apparently functionally redundant microbial taxa are detectable within a cubic centimetre of mud or a millilitre of water, and the significance of this diversity, in terms of ecosystem function, has been difficult to understand. Thus it is not known whether temporal and spatial differences in microbial community composition are linked to particular environmental factors or might modulate ecosystem response to environmental change. Fifty-three water and sediment samples from upper and lower Chesapeake Bay were analysed in triplicate arrays to determine temporal and spatial patterns and relationships between ammonia-oxidizing bacterial (AOB) communities and environmental variables. Thirty-three water samples (three depths) collected during April, August and October, 2001-2004, from the oligohaline upper region of the Bay were analysed to investigate temporal patterns in archetype distribution. Using a combination of a non-weighted discrimination analysis and principal components analysis of community composition data obtained from functional gene microarrays, it was found that co-varying AOB assemblages reoccurred seasonally in concert with specific environmental conditions, potentially revealing patterns of niche differentiation. Among the most notable patterns were correlations of AOB archetypes with temperature, DON and ammonium concentrations. Different AOB archetypes were more prevalent at certain times of the year, e.g. some were more abundant every autumn and others every spring. This data set documents the successional return to an indigenous community following massive perturbation (hurricane induced flooding) as well as the seasonal reoccurrence of specific lineages, identified by key functional genes, associated with the biogeochemically important process nitrification.

Modeling geogenic and atmospheric nitrogen through the East River Watershed, Colorado Rocky Mountains.

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. In this study, we develop the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Several calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed. When accounting for recycling of N through plant litter turnover, rock weathering accounts for approximately 12% of the annual dissolved N sources to the watershed in the most probable calibration scenario (0-31% in other scenarios), and 21% (0-44% in other scenarios) when considering only "new" N sources (i.e. geogenic and atmospheric). On an annual scale, instream dissolved N elimination, plant turnover (including cattle grazing) and atmospheric deposition are the most important controls on N cycling.

Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale.

BACKGROUND: Biogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor. RESULTS: We intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO2 fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor. CONCLUSIONS: The disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change. Video abstract.

Metabolite identification in Synechococcus sp. PCC 7002 using untargeted stable isotope assisted metabolite profiling.

Metabolite profiling using mass spectrometry provides an attractive approach for the interrogation of cellular metabolic capabilities. Untargeted metabolite profiling has the potential to identify numerous novel metabolites; however, de novo identification of metabolites from spectral features remains a challenge. Here we present an integrated workflow for metabolite identification using uniform stable isotope labeling. Metabolite profiling of cell and growth media extracts of unlabeled control, (15)N, and (13)C-labeled cultures of the cyanobacterium, Synechococcus sp. PCC 7002 was performed using normal phase liquid chromatography coupled to mass spectrometry (LC-MS). Visualization of three-way comparisons of raw data sets highlighted characteristic labeling patterns for metabolites of biological origin allowing exhaustive identification of corresponding spectral features. Additionally, unambiguous assignment of chemical formulas was greatly facilitated by the use of stable isotope labeling. Chemical formulas of metabolites responsible for redundant spectral features were determined and fragmentation (MS/MS) spectra for these metabolites were collected. Analysis of acquired MS/MS spectra against spectral database records led to the identification of a number of metabolites absent not only from the reconstructed draft metabolic network of Synechococcus sp. PCC 7002 but not included in databases of metabolism (MetaCyc or KEGG).

Temporal bacterial diversity associated with metal-contaminated river sediments.

The temporal activity, abundance and diversity of microbial communities were evaluated across a metal-contamination gradient around a Superfund site in Montana. In order to analyze short-term variability, samples were collected from six sites on four occasions over 12 months. Measurements of community activity, diversity and richness, quantified by dehydrogenase activity and through denaturant gradient gel electrophoresis (DGGE), respectively, were higher at contaminated sites adjacent to the smelter, relative to reference sites. 16S rRNA gene copy numbers, measured by quantitative PCR, showed seasonal variability, yet were generally higher within polluted sediments. Jaccard similarity coefficients of DGGE profiles, found sites to cluster based primarily on geographical proximity rather than geochemical similarities. Intra-site clustering of the most polluted sites also suggests a stable metal-tolerant community. Sequences from DGGE-extracted bands were predominantly Beta and Gammaproteobacteria, although the communities at all sites generally maintained a diverse phylogeny changing in composition throughout the sampling period. Spearman's rank correlations analysis found statistically significant relationships between community composition and organic carbon (r-value = 0.786) and metals (r-values As = 0.65; Cu = 0.63; Zn = 0.62). A diverse and abundant community at the most polluted site indicates that historical contamination selects for a metal-resistant microbial community, a finding that must be accounted for when using the microbial community within ecosystem monitoring studies. This study highlights the importance of using multiple time-points to draw conclusions on the affect of metal contamination.

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term experiments.

Climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (<10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.

Phylogenetic conservation of soil bacterial responses to simulated global changes.

Soil bacterial communities are altered by anthropogenic drivers such as climate change-related warming and fertilization. However, we lack a predictive understanding of how bacterial communities respond to such global changes. Here, we tested whether phylogenetic information might be more predictive of the response of bacterial taxa to some forms of global change than others. We analysed the composition of soil bacterial communities from perturbation experiments that simulated warming, drought, elevated CO2 concentration and phosphorus (P) addition. Bacterial responses were phylogenetically conserved to all perturbations. The phylogenetic depth of these responses varied minimally among the types of perturbations and was similar when merging data across locations, implying that the context of particular locations did not affect the phylogenetic pattern of response. We further identified taxonomic groups that responded consistently to each type of perturbation. These patterns revealed that, at the level of family and above, most groups responded consistently to only one or two types of perturbations, suggesting that traits with different patterns of phylogenetic conservation underlie the responses to different perturbations. We conclude that a phylogenetic approach may be useful in predicting how soil bacterial communities respond to a variety of global changes. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

The Snowmelt Niche Differentiates Three Microbial Life Strategies That Influence Soil Nitrogen Availability During and After Winter.

Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the snowmelt period, and after snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in snowmelt timing may alter ecosystem N retention potential. Overall, we observed that snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after snowmelt.

Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle.

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.

On the Power of Uncertainties in Microbial System Modeling: No Need To Hide Them Anymore.

For decades, microbiologists have considered uncertainties as an undesired side effect of experimental protocols. As a consequence, standard microbial system modeling strives to hide uncertainties for the sake of deterministic understanding. However, recent studies have highlighted greater experimental variability than expected and emphasized uncertainties not as a weakness but as a necessary feature of complex microbial systems. We therefore advocate that biological uncertainties need to be considered foundational facets that must be incorporated in models. Not only will understanding these uncertainties improve our understanding and identification of microbial traits, it will also provide fundamental insights on microbial systems as a whole. Taking into account uncertainties within microbial models calls for new validation techniques. Formal verification already overcomes this shortcoming by proposing modeling frameworks and validation techniques dedicated to probabilistic models. However, further work remains to extract the full potential of such techniques in the context of microbial models. Herein, we demonstrate how statistical model checking can enhance the development of microbial models by building confidence in the estimation of critical parameters and through improved sensitivity analyses.

Belowground Response to Drought in a Tropical Forest Soil. II. Change in Microbial Function Impacts Carbon Composition.

Climate model projections for tropical regions show clear perturbation of precipitation patterns leading to increased frequency and severity of drought in some regions. Previous work has shown declining soil moisture to be a strong driver of changes in microbial trait distribution, however, the feedback of any shift in functional potential on ecosystem properties related to carbon cycling are poorly understood. Here we show that drought-induced changes in microbial functional diversity and activity shape, and are in turn shaped by, the composition of dissolved and soil-associated carbon. We also demonstrate that a shift in microbial functional traits that favor the production of hygroscopic compounds alter the efflux of carbon dioxide following soil rewetting. Under drought the composition of the dissolved organic carbon pool changed in a manner consistent with a microbial metabolic response. We hypothesize that this microbial ecophysiological response to changing soil moisture elevates the intracellular carbon demand stimulating extracellular enzyme production, that prompts the observed decline in more complex carbon compounds (e.g., cellulose and lignin). Furthermore, a metabolic response to drought appeared to condition (biologically and physically) the soil, notably through the production of polysaccharides, particularly in experimental plots that had been pre-exposed to a short-term drought. This hysteretic response, in addition to an observed drought-related decline in phosphorus concentration, may have been responsible for a comparatively modest CO2 efflux following wet-up in drought plots relative to control plots.

Belowground Response to Drought in a Tropical Forest Soil. I. Changes in Microbial Functional Potential and Metabolism.

Global climate models predict a future of increased severity of drought in many tropical forests. Soil microbes are central to the balance of these systems as sources or sinks of atmospheric carbon (C), yet how they respond metabolically to drought is not well-understood. We simulated drought in the typically aseasonal Luquillo Experimental Forest, Puerto Rico, by intercepting precipitation falling through the forest canopy. This approach reduced soil moisture by 13% and water potential by 0.14 MPa (from -0.2 to -0.34). Previous results from this experiment have demonstrated that the diversity and composition of these soil microbial communities are sensitive to even small changes in soil water. Here, we show prolonged drought significantly alters the functional potential of the community and provokes a clear osmotic stress response, including the production of compatible solutes that increase intracellular C demand. Subsequently, a microbial population emerges with a greater capacity for extracellular enzyme production targeting macromolecular carbon. Significantly, some of these drought-induced functional shifts in the soil microbiota are attenuated by prior exposure to a short-term drought suggesting that acclimation may occur despite a lack of longer-term drought history.