Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Approaches to quantifying and predicting soil biogeochemical cycles mostly consider microbial biomass and community composition as products of the abiotic environment. Current numerical approaches then primarily emphasise the importance of microbe-environment interactions and physiology as controls on biogeochemical cycles. Decidedly less attention has been paid to understanding control exerted by community dynamics and biotic interactions. Yet a rich literature of theoretical and empirical contributions highlights the importance of considering how variation in microbial population ecology, especially biotic interactions, is related to variation in key biogeochemical processes like soil carbon formation. We demonstrate how a population and community ecology perspective can be used to (1) understand the impact of microbial communities on biogeochemical cycles and (2) reframe current theory and models to include more detailed microbial ecology. Through a series of simulations we illustrate how density dependence and key biotic interactions, such as competition and predation, can determine the degree to which microbes regulate soil biogeochemical cycles. The ecological perspective and model simulations we present lay the foundation for developing empirical research and complementary models that explore the diversity of ecological mechanisms that operate in microbial communities to regulate biogeochemical processes.

Understanding the role of soil microbial communities in coupled carbon and nitrogen cycles has become an area of great interest as we strive to understand how global change will influence ecosystem function. In this endeavor, microbially explicit decomposition models are being adopted because they include microbial stoichiometry- and biomass-mediated mechanisms that may be important in shaping ecosystem response to environmental change. Yet there has been a dearth of empirical tests to verify the predictions of these models and hence identify potential improvements. We measured the response of soil microbes to multiple rates of carbon and nitrogen amendment in experimental microcosms, and used the respiration and nitrogen mineralization responses to assess a well-established, single-pool, microbial decomposition model. The model generally predicted the empirical trends in carbon and nitrogen fluxes, but failed to predict the empirical trends in microbial biomass. Further examination of this discontinuity indicated that the model successfully predicted carbon and nitrogen cycling because stoichiometry overrode microbial biomass as a regulator of cycling rates. Stoichiometric control meant that the addition of carbon generally increased respiration and decreased nitrogen mineralization, whereas nitrogen had the opposite effects. Biomass only assumed importance as a control on cycling rates when stoichiometric ratios of resource inputs were a close match to those of the microbial biomass. Our work highlights the need to advance our understanding of the stoichiometric demands of microbial biomass in order to better understand biogeochemical cycles in the face of changing organic- and inorganic-matter inputs to terrestrial ecosystems.

Extreme climate events such as droughts, cold snaps, and hurricanes can be powerful agents of natural selection, producing acute selective pressures very different from the everyday pressures acting on organisms. However, it remains unknown whether these infrequent but severe disruptions are quickly erased by quotidian selective forces, or whether they have the potential to durably shape biodiversity patterns across regions and clades. Here, we show that hurricanes have enduring evolutionary impacts on the morphology of anoles, a diverse Neotropical lizard clade. We first demonstrate a transgenerational effect of extreme selection on toepad area for two populations struck by hurricanes in 2017. Given this short-term effect of hurricanes, we then asked whether populations and species that more frequently experienced hurricanes have larger toepads. Using 70 y of historical hurricane data, we demonstrate that, indeed, toepad area positively correlates with hurricane activity for both 12 island populations of Anolis sagrei and 188 Anolis species throughout the Neotropics. Extreme climate events are intensifying due to climate change and may represent overlooked drivers of biogeographic and large-scale biodiversity patterns.

Soil carbon (C) storage is a major component of the carbon cycle. Consensus holds that soil C uptake and storage is regulated by plant-microbe-soil interactions. However, the contribution of animals in aboveground food webs to this process has been overlooked. Using insights from prior long-term experimentation in an old-field ecosystem and mathematical modeling, we predicted that the amount of soil C retention within a field should increase with the proportion of active hunting predators comprising the aboveground community of active hunting and sit-and-wait predators. This comes about because predators with different hunting modes have different cascading effects on plants. Our test of the prediction revealed that the composition of the arthropod predator community and associated cascading effects on the plant community explained 41% of variation in soil C retention among 15 old fields across a human land use gradient. We also evaluated the potential for several other candidate factors to explain variation in soil C retention among fields, independent of among-field variation in the predator community. These included live plant biomass, insect herbivore community composition, soil arthropod decomposer community composition, degree of land use development around the fields, field age, and soil texture. None of these candidate variables significantly explained soil C retention among the fields. The study offers a generalizable understanding of the pathways through which arthropod predator community composition can contribute to old-field ecosystem carbon storage. This insight helps support ongoing efforts to understand and manage the effects of anthropogenic land use change on soil C storage.

Soil organic matter (SOM) is central to soil carbon (C) storage and terrestrial nutrient cycling. New data have upended the traditional model of stabilization, which held that stable SOM was mostly made of undecomposed plant molecules. We now know that microbial by-products and dead cells comprise unexpectedly large amounts of stable SOM because they can become attached to mineral surfaces or physically protected within soil aggregates. SOM models have been built to incorporate the microbial to mineral stabilization of organic matter, but now face a new challenge of accurately capturing microbial productivity and metabolism. Explicitly representing stoichiometry, the relative nutrient requirements for growth and maintenance of organisms, could provide a way forward. Stoichiometry limits SOM formation and turnover in nature, but important nutrients like nitrogen (N), phosphorus (P), and sulfur (S) are often missing from the new generation of SOM models. In this synthesis, we seek to facilitate the addition of these nutrients to SOM models by (1) reviewing the stoichiometric biasthe tendency to favor one element over another-of four key processes in the new framework of SOM cycling and (2) applying this knowledge to build a stoichiometrically explicit budget of C, N, P, and S flow through the major SOM pools. By quantifying the role of stoichiometry in SOM cycling, we discover that constraining the C:N:P:S ratio of microorganisms and SOM to specific values reduces uncertainty in C and nutrient flow as effectively as using microbial C use efficiency (CUE) parameters. We find that the value of additional constraints on stoichiometry vs. CUE varies across ecosystems, depending on how precise the available data are for that ecosystem and which biogeochemical pathways are present. Moreover, because CUE summarizes many different processes, stoichiometric measurements of key soil pools are likely to be more robust when extrapolated from soil incubations to plot or biome scale estimates. Our results suggest that measuring SOM stoichiometry should be a priority for future empirical work and that the inclusion of new nutrients in SOM models may be an effective way to improve precision.

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Numerous biotic mechanisms can control ecosystem nutrient cycling, but their full incorporation into ecological models or experimental designs can result in inordinate complexity. Including organismal nutrient limitation in models of highly dimensional systems (i.e., those with many nutrient pools/species) presents a critical challenge. We evaluate the importance of explicitly considering microbial and animal nutrient limitation to predict ecosystem nitrogen cycling across plant‐based and detritus‐based food chains. We investigate how eight factorial scenarios of microbial, herbivore, and microbi‐detritivore (i.e., omnivores consuming microbes and detritus) nitrogen or carbon limitation alter the stocks and flows of nitrogen in an ecosystem model. We used a combination of partial derivatives of model equilibrium solutions and numerical simulations using randomly drawn parameter sets to explore the impact of each nutrient limitation scenario on nutrient stocks and flows. We show that switching microbes, herbivores, or microbi‐detritivores from nitrogen to carbon limitation consistently altered the ecosystem response to changes in inorganic nitrogen supply, plant C:N ratio, and microbial C:N ratio. Organism nutrient limitation changed ecosystem nitrogen flows by altering the feedbacks between the abiotic and biotic pools. For example, microbi‐detritivore nutrient limitation determined whether the microbial response to changes in inorganic nitrogen supply and C:N ratios was dependent on the size of detrital carbon or detrital nitrogen pool. Such correlated responses among biotic and abiotic pools set up a network of predictable changes in ecosystem properties sensitive to organism nutrient limitation. Scenarios with microbial limitation were generally sufficient to capture the suite of ecosystem responses to increasing inorganic nitrogen supply, while scenarios with animal limitation added new behavior whenever C:N ratios changed. We make the case for explicitly considering both microbial and animal nutrient limitation when predicting the flow and distribution of nitrogen across green and brown food chains.