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Abstract Increasing fine root carbon (FRC) inputs into soils has been proposed as a solution to increasing soil organic carbon (SOC). However, FRC inputs can also enhance SOC loss through priming. Here, we tested the broad-scale relationships between SOC and FRC at 43 sites across the US National Ecological Observatory Network. We found that SOC and FRC stocks were positively related with an across-ecosystem slope of 7 ± 3 kg SOC m⁻²per kg FRC m⁻², but this relationship was driven by grasslands. Grasslands had double the across-ecosystem slope while forest FRC and SOC were unrelated. Furthermore, deep grassland soils primarily showed net SOC accrual relative to FRC input. Conversely, forests had high variability in whether FRC inputs were related to net SOC priming or accrual. We conclude that while FRC increases could lead to increased SOC in grasslands, especially at depth, the FRC-SOC relationship remains difficult to characterize in forests. 

ABSTRACT Litter decomposition is an important ecosystem process and global carbon flux that has been shown to be controlled by climate, litter quality, and microbial communities. Process‐based ecosystem models are used to predict responses of litter decomposition to climate change. While these models represent climate and litter quality effects on litter decomposition, they have yet to integrate empirical microbial community data into their parameterizations for predicting litter decomposition. To fill this gap, our research used a comprehensive leaf litterbag decomposition experiment at 10 temperate forest U.S. National Ecological Observatory Network (NEON) sites to calibrate (7 sites) and validate (3 sites) the MIcrobial‐MIneral Carbon Stabilization (MIMICS) model. MIMICS was calibrated to empirical decomposition rates and to their empirical drivers, including the microbial community (represented as the copiotroph‐to‐oligotroph ratio). We calibrate to empirical drivers, rather than solely rates or pool sizes, to improve the underlying drivers of modeled leaf litter decomposition. We then validated the calibrated model and evaluated the effects of calibration under climate change using the SSP 3–7.0 climate change scenario. We find that incorporating empirical drivers of litter decomposition provides similar, and sometimes better (in terms of goodness‐of‐fit metrics), predictions of leaf litter decomposition but with different underlying ecological dynamics. For some sites, calibration also increased climate change‐induced leaf litter mass loss by up to 5%, with implications for carbon cycle‐climate feedbacks. Our work also provides an example for integrating data on the relative abundance of bacterial functional groups into an ecosystem model using a novel calibration method to bridge empiricism and process‐based modeling, answering a call for the use of empirical microbial community data in process‐based ecosystem models. We highlight that incorporating mechanistic information into models, as done in this study, is important for improving confidence in model projections of ecological processes like litter decomposition under climate change. 

Abstract Unabated 21st-century climate change will accelerate Arctic-Subarctic permafrost thaw which can intensify microbial degradation of carbon-rich soils, methane emissions, and global warming. The impact of permafrost thaw on future Arctic-Subarctic wildfires and the associated release of greenhouse gases and aerosols is less well understood. Here we present a comprehensive analysis of the effect of future permafrost thaw on land surface processes in the Arctic-Subarctic region using the CESM2 large ensemble forced by the SSP3-7.0 greenhouse gas emission scenario. Analyzing 50 greenhouse warming simulations, which capture the coupling between permafrost, hydrology, and atmosphere, we find that projected rapid permafrost thaw leads to massive soil drying, surface warming, and reduction of relative humidity over the Arctic-Subarctic region. These combined processes lead to nonlinear late-21st-century regime shifts in the coupled soil-hydrology system and rapid intensification of wildfires in western Siberia and Canada. 

ABSTRACT Managing soils to increase organic carbon storage presents a potential opportunity to mitigate and adapt to global change challenges, while providing numerous co‐benefits and ecosystem services. However, soils differ widely in their potential for carbon sequestration, and knowledge of biophysical limits to carbon accumulation may aid in informing priority regions. Consequently, there is great interest in assessing whether soils exhibit a maximum capacity for storing organic carbon, particularly within organo–mineral associations given the finite nature of reactive minerals in a soil. While the concept of soil carbon saturation has existed for over 25 years, recent studies have argued for and against its importance. Here, we summarize the conceptual understanding of soil carbon saturation at both micro‐ and macro‐scales, define key terminology, and address common concerns and misconceptions. We review methods used to quantify soil carbon saturation, highlighting the theory and potential caveats of each approach. Critically, we explore the utility of the principles of soil carbon saturation for informing carbon accumulation, vulnerability to loss, and representations in process‐based models. We highlight key knowledge gaps and propose next steps for furthering our mechanistic understanding of soil carbon saturation and its implications for soil management. 

Summary Predicting shifts in species composition with global change remains challenging, but plant functional traits provide a key link to scale from plant to community and ecosystem levels. The extent to which functional trait shifts may mediate ecosystem response to climate change remains a critical question.We ran point‐scale Community Land Model (CLM) simulations with site‐specific functional trait and phenology observations to represent alpine tundra growth strategies. We validated our results with site observations and compared parameterized results to those using the default parameterization. We then quantified the relative contribution of plant functional trait shifts vs climate change scenarios (and the resulting phenological shifts) to uncertainty in future tundra ecosystem productivity outcomes.We found that using community‐specific functional traits and phenology observations significantly improved productivity estimates compared with overestimates in a default simulation. Uncertainty in potential plant trait shifts often had a larger effect on ecosystem productivity responses than uncertainty in the forced response from different climate change scenarios.These findings highlight the key role of functional traits in shaping vegetation responses to climate change and the value of incorporating site‐level measurements into land models to more accurately forecast climate change impacts on ecosystem function. 

Nutrient limitation is widespread in terrestrial ecosystems. Accordingly, representations of nitrogen (N) limitation in land models typically dampen rates of terrestrial carbon (C) accrual, compared with C‐only simulations. These previous findings, however, rely on soil biogeochemical models that implicitly represent microbial activity and physiology. Here we present results from a biogeochemical model testbed that allows us to investigate how an explicit versus implicit representation of soil microbial activity, as represented in the MIcrobial‐MIneral Carbon Stabilization (MIMICS) and Carnegie‐Ames‐Stanford Approach (CASA) soil biogeochemical models, respectively, influence plant productivity, and terrestrial C and N fluxes at initialization and over the historical period. When forced with common boundary conditions, larger soil C pools simulated by the MIMICS model reflect longer inferred soil organic matter (SOM) turnover times than those simulated by CASA. At steady state, terrestrial ecosystems experience greater N limitation when using the MIMICS‐CN model, which also increases the inferred SOM turnover time. Over the historical period, however, warming‐induced acceleration of SOM decomposition over high latitude ecosystems increases rates of N mineralization in MIMICS‐CN. This reduces N limitation and results in faster rates of vegetation C accrual. Moreover, as SOM stoichiometry is an emergent property of MIMICS‐CN, we highlight opportunities to deepen understanding of sources of persistent SOM and explore its potential sensitivity to environmental change. Our findings underscore the need to improve understanding and representation of plant and microbial resource allocation and competition in land models that represent coupled biogeochemical cycles under global change scenarios. 

Abstract Increased plant growth under elevated carbon dioxide (CO₂) slows the pace of climate warming and underlies projections of terrestrial carbon (C) and climate dynamics. However, this important ecosystem service may be diminished by concurrent changes to vegetation carbon‐to‐nitrogen (C:N) ratios. Despite clear observational evidence of increasing foliar C:N under elevated CO₂, our understanding of potential ecological consequences of foliar stoichiometric flexibility is incomplete. Here, we illustrate that when we incorporated CO₂‐driven increases in foliar stoichiometry into the Community Land Model the projected land C sink decreased two‐fold by the end of the century compared to simulations with fixed foliar chemistry. Further, CO₂‐driven increases in foliar C:N profoundly altered Earth's hydrologic cycle, reducing evapotranspiration and increasing runoff, and reduced belowground N cycling rates. These findings underscore the urgency of further research to examine both the direct and indirect effects of changing foliar stoichiometry on soil N cycling and plant productivity.