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Rocci, Katherine S.

Publications and source records attributed to Rocci, Katherine S..

Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles With Implicit and Explicit Representations of Soil Microbial Activity

Abstract 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.

54 ENVIRONMENTAL SCIENCES↗

Bridging 20 Years of Soil Organic Matter Frameworks: Empirical Support, Model Representation, and Next Steps

Abstract In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics.

54 ENVIRONMENTAL SCIENCES↗

Aligning theoretical and empirical representations of soil carbon-to-nitrogen stoichiometry with process-based terrestrial biogeochemistry models

Soil carbon-nitrogen (C:N) stoichiometry acts as a control over decomposition and soil organic matter formation and loss, making it a key soil property for understanding ecosystem dynamics and projected ecosystems responses to global environmental change. However, the controls of soil C:N and how they respond to increasing pressures from global change agents are not fully understood. The “foundational” controls on soil C:N, namely plant and microbial C:N, have been used to predict soil C:N, but fail to accurately simulate all ecosystems and may be insufficient for predictions under global environmental change. Here we present an “emerging” representation of controls of soil C:N that includes plant-microbe-mineral feedbacks that have been shown to regulate soil C:N. We argue that including representation of these emerging drivers in process-based terrestrial biogeochemistry models, which include biological N fixation, mycorrhizae, priming, root exudation of organic acids, and mineralogy (including soil texture, mineral composition, and aggregation), will improve mechanistic representation of soil C:N and associated processes. Such improvements will produce models that will better simulate a variety of ecological states and predict soil C:N when global changes modify plant-microbe-mineral interactions. Here, we align our empirical understanding of controls of soil C:N with those controls represented in models, identifying contexts where emerging drivers might be particularly important to represent (e.g., priming and root exudation in nutrient-limited conditions) and areas of future work. Additionally, we show that implementing emerging drivers of soil C:N results in different simulated outcomes at steady state and in response to elevated atmospheric CO2. Our review and preliminary simulations support the need to incorporate emerging drivers of soil C:N into process-based terrestrial biogeochemistry models, allowing for both theoretical exploration of mechanisms and potentially more accurate predictions of land biogeochemical responses to global change.

54 ENVIRONMENTAL SCIENCES↗