Steven D. Allison

Resistance, resilience, and redundancy in microbial communities

Although it is generally accepted that plant community composition is key for predicting rates of ecosystem processes in the face of global change, microbial community composition is often ignored in ecosystem modeling. To address this issue, we review recent experiments and assess whether microbial community composition is resistant, resilient, or functionally redundant in response to four different disturbances. We find that the composition of most microbial groups is sensitive and not immediately resilient to disturbance, regardless of taxonomic breadth of the group or the type of disturbance. Other studies demonstrate that changes in composition are often associated with changes in ecosystem process rates. Thus, changes in microbial communities due to disturbance may directly affect ecosystem processes. Based on these relationships, we propose a simple framework to incorporate microbial community composition into ecosystem process models. We conclude that this effort would benefit from more empirical data on the links among microbial phylogeny, physiological traits, and disturbance responses. These relationships will determine how readily microbial community composition can be used to predict the responses of ecosystem processes to global change.

Stoichiometry of soil enzyme activity at global scale

Extracellular enzymes are the proximate agents of organic matter decomposition and measures of these activities can be used as indicators of microbial nutrient demand. We conducted a global-scale meta-analysis of the seven-most widely measured soil enzyme activities, using data from 40 ecosystems. The activities of beta-1,4-glucosidase, cellobiohydrolase, beta-1,4-N-acetylglucosaminidase and phosphatase g(-1) soil increased with organic matter concentration; leucine aminopeptidase, phenol oxidase and peroxidase activities showed no relationship. All activities were significantly related to soil pH. Specific activities, i.e. activity g(-1) soil organic matter, also varied in relation to soil pH for all enzymes. Relationships with mean annual temperature (MAT) and precipitation (MAP) were generally weak. For hydrolases, ratios of specific C, N and P acquisition activities converged on 1 : 1 : 1 but across ecosystems, the ratio of C : P acquisition was inversely related to MAP and MAT while the ratio of C : N acquisition increased with MAP. Oxidative activities were more variable than hydrolytic activities and increased with soil pH. Our analyses indicate that the enzymatic potential for hydrolyzing the labile components of soil organic matter is tied to substrate availability, soil pH and the stoichiometry of microbial nutrient demand. The enzymatic potential for oxidizing the recalcitrant fractions of soil organic material, which is a proximate control on soil organic matter accumulation, is most strongly related to soil pH. These trends provide insight into the biogeochemical processes that create global patterns in ecological stoichiometry and organic matter storage.

Fundamentals of microbial community resistance and resilience.

Microbial communities are at the heart of all ecosystems, and yet microbial community behavior in disturbed environments remains difficult to measure and predict. Understanding the drivers of microbial community stability, including resistance (insensitivity to disturbance) and resilience (the rate of recovery after disturbance) is important for predicting community response to disturbance. Here, we provide an overview of the concepts of stability that are relevant for microbial communities. First, we highlight insights from ecology that are useful for defining and measuring stability. To determine whether general disturbance responses exist for microbial communities, we next examine representative studies from the literature that investigated community responses to press (long-term) and pulse (short-term) disturbances in a variety of habitats. Then we discuss the biological features of individual microorganisms, of microbial populations, and of microbial communities that may govern overall community stability. We conclude with thoughts about the unique insights that systems perspectives – informed by meta-omics data – may provide about microbial community stability.

Drivers of bacterial β-diversity depend on spatial scale

The factors driving β-diversity (variation in community composition) yield insights into the maintenance of biodiversity on the planet. Here we tested whether the mechanisms that underlie bacterial β-diversity vary over centimeters to continental spatial scales by comparing the composition of ammonia-oxidizing bacteria communities in salt marsh sediments. As observed in studies of macroorganisms, the drivers of salt marsh bacterial β-diversity depend on spatial scale. In contrast to macroorganism studies, however, we found no evidence of evolutionary diversification of ammonia-oxidizing bacteria taxa at the continental scale, despite an overall relationship between geographic distance and community similarity. Our data are consistent with the idea that dispersal limitation at local scales can contribute to β-diversity, even though the 16S rRNA genes of the relatively common taxa are globally distributed. These results highlight the importance of considering multiple spatial scales for understanding microbial biogeography.

Nitrogen and Nature

Abstract Anthropogenic changes to the global N cycle are important in part because added N alters the composition, productivity, and other properties of many natural ecosystems substantially. Why does added N have such a large impact? Why is N in short supply in so many natural ecosystems? Processes that slow the cycling of N relative to other elements and processes that control ecosystem-level inputs and outputs of N could cause N supply to limit the dynamics of ecosystems. We discuss stoichiometric differences between terrestrial plants and other organisms, the abundance of protein-precipitating plant defenses, and the nature of the C–N bond in soil organic matter as factors that can slow N cycling. For inputs, the energetic costs of N fixation and their consequences, the supply of nutrients other than N, and preferential grazing on N-fixers all could constrain the abundance and/or activity of biological N-fixers. Together these processes drive and sustain N limitation in many natural terrestrial ecosystems.

A trait‐based approach for modelling microbial litter decomposition

Trait-based models are an emerging tool in ecology with the potential to link community dynamics, environmental responses and ecosystem processes. These models represent complex communities by defining taxa with trait combinations derived from prior distributions that may be constrained by trade-offs. Herein I develop a model that links microbial community composition with physiological and enzymatic traits to predict litter decomposition rates. This approach allows for trade-offs among traits that represent alternative microbial strategies for resource acquisition. The model predicts that optimal strategies depend on the level of enzyme production in the whole community, which determines resource availability and decomposition rates. There is also evidence for facilitation and competition among microbial taxa that co-occur on decomposing litter. These interactions vary with community investment in extracellular enzyme production and the magnitude of trade-offs affecting enzyme biochemical traits. The model accounted for 69% of the variation in decomposition rates of 15 Hawaiian litter types and up to 26% of the variation in enzyme activities. By explicitly representing diversity, trait-based models can predict ecosystem processes based on functional trait distributions in a community. The model developed herein illustrates that traits influencing microbial enzyme production are some of the key controls on litter decomposition rates.

Quantifying global soil carbon losses in response to warming

The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

Microbial abundance and composition influence litter decomposition response to environmental change

Rates of ecosystem processes such as decomposition are likely to change as a result of human impacts on the environment. In southern California, climate change and nitrogen (N) deposition in particular may alter biological communities and ecosystem processes. These drivers may affect decomposition directly, through changes in abiotic conditions, and indirectly through changes in plant and decomposer communities. To assess indirect effects on litter decomposition, we reciprocally transplanted microbial communities and plant litter among control and treatment plots (either drought or N addition) in a grassland ecosystem. We hypothesized that drought would reduce decomposition rates through moisture limitation of decomposers and reductions in plant litter quality before and during decomposition. In contrast, we predicted that N deposition would stimulate decomposition by relieving N limitation of decomposers and improving plant litter quality. We also hypothesized that adaptive mechanisms would allow microbes to decompose litter more effectively in their native plot and litter environments. Consistent with our first hypothesis, we found that drought treatment reduced litter mass loss from 20.9% to 15.3% after six months. There was a similar decline in mass loss of litter inoculated with microbes transplanted from the drought treatment, suggesting a legacy effect of drought driven by declines in microbial abundance and possible changes in microbial community composition. Bacterial cell densities were up to 86% lower in drought plots and at least 50% lower on litter derived from the drought treatment, whereas fungal hyphal lengths increased by 13-14% in the drought treatment. Nitrogen effects on decomposition rates and microbial abundances were weaker than drought effects, although N addition significantly altered initial plant litter chemistry and litter chemistry during decomposition. However, we did find support for microbial adaptation to N addition with N-derived microbes facilitating greater mass loss in N plots than in control plots. Our results show that environmental changes can affect rates of ecosystem processes directly through abiotic changes and indirectly through microbial abundances and communities. Therefore models of ecosystem response to global change may need to represent microbial biomass and community composition to make accurate predictions.

A framework for representing microbial decomposition in coupled climate models

Accurate prediction of future atmospheric CO2 concentrations is essential for evaluating climate change impacts on ecosystems and human societies. One major source of uncertainty in model predictions is the extent to which global warming will increase atmospheric CO2 concentrations through enhanced microbial decomposition of soil organic carbon. Recent advances in microbial ecology could help reduce this uncertainty, but current global models do not represent direct microbial control over decomposition. Instead, all of the coupled climate models reviewed in the most recent Intergovernmental Panel on Climate Change (IPCC) report assume that decomposition is a first-order decay process, proportional to the size of the soil carbon pool. Here we argue for the development of a new generation of models that link decomposition directly to the size and activity of microbial communities in coupled global models. This process begins with the formulation and validation of fine-scale models that capture fundamental microbial mechanisms without excessive mathematical complexity. These mechanistic models must then be scaled up through an aggregation process and validated at ecosystem to global scales prior to incorporation into global climate models (GCMs). Parameterizing microbial models at the global scale is challenging because some microbial properties such as in situ extracellular enzyme activities are very difficult to measure directly. New parameter fitting procedures may therefore be needed to infer the values of important microbial variables. Validating decomposition models at the global scale is also a challenge, and has not yet been accomplished with the land carbon models embedded in current GCMs. Fortunately new global datasets on soil carbon stocks and fluxes offer promising opportunities to validate both existing land carbon models and new microbial models. If challenges in scaling, parameterization, and validation can be overcome, a new generation of microbially-based decomposition models could substantially improve predictions of carbon–climate feedbacks in the Earth system. Development of new models structures would also reduce any bias due to the assumption of first-order decomposition across all of the models currently referenced in reports of the IPCC.

Fungal Taxa Target Different Carbon Sources in Forest Soil

Soil microbes are among the most abundant and diverse organisms on Earth. Although microbial decomposers, particularly fungi, are important mediators of global carbon and nutrient cycling, the functional roles of specific taxa within natural environments remain unclear. We used a nucleotide-analog technique in soils from the Harvard Forest to characterize the fungal taxa that responded to the addition of five different carbon substrates—glycine, sucrose, cellulose, lignin, and tannin-protein. We show that fungal community structure and richness shift in response to different carbon sources, and we demonstrate that particular fungal taxa target different organic compounds within soil microcosms. Specifically, we identified eleven taxa that exhibited changes in relative abundances across substrate treatments. These results imply that niche partitioning through specialized resource use may be an important mechanism by which soil microbial diversity is maintained in ecosystems. Consequently, high microbial diversity may be necessary to sustain ecosystem processes and stability under global change.