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1. Limitations of the Q 10 Coefficient for Quantifying Temperature Sensitivity of Anaerobic Organic Matter Decomposition: A Modeling Based Assessment

   https://doi.org/10.1029/2021JG006264  

   Wu, Qiong ; Ye, Rongzhong ; Bridgham, Scott D. ; Jin, Qusheng ( August 2021 , Journal of Geophysical Research: Biogeosciences)

   TheQ₁₀coefficient is the ratio of reaction rates at two temperatures 10°C apart, and has been widely applied to quantify the temperature sensitivity of organic matter decomposition. However, biogeochemists and ecologists have long recognized that a constantQ₁₀coefficient does not describe the temperature sensitivity of organic matter decomposition accurately. To examine the consequences of the constantQ₁₀assumption, we built a biogeochemical reaction model to simulate anaerobic organic matter decomposition in peatlands in the Upper Peninsula of Michigan, USA, and compared the simulation results to the predictions withQ₁₀coefficients. By accounting for the reactions of extracellular enzymes, mesophilic fermenting and methanogenic microbes, and their temperature responses, the biogeochemical reaction model reproduces the observations of previous laboratory incubation experiments, including the temporal variations in the concentrations of dissolved organic carbon, acetate, dihydrogen, carbon dioxide, and methane, and confirms that fermentation limits the progress of anaerobic organic matter decomposition. The modeling results illustrate the oversimplification inherent in the constantQ₁₀assumption and how the assumption undermines the kinetic prediction of anaerobic organic matter decomposition. In particular, the model predicts that between 5°C and 30°C, the decomposition rate increases almost linearly with increasing temperature, which stands in sharp contrast to the exponential relationship given by theQ₁₀coefficient. As a result, the constantQ₁₀approach tends to underestimate the rates of organic matter decomposition within the temperature ranges whereQ₁₀values are determined, and overestimate the rates outside the temperature ranges. The results also show how biogeochemical reaction modeling, combined with laboratory experiments, can help uncover the temperature sensitivity of organic matter decomposition arising from underlying catalytic mechanisms.

    

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2. Emergent temperature sensitivity of soil organic carbon driven by mineral associations

   https://doi.org/10.1038/s41561-024-01384-7  

   Georgiou, Katerina ; Koven, Charles D. ; Wieder, William R. ; Hartman, Melannie D. ; Riley, William J. ; Pett-Ridge, Jennifer ; Bouskill, Nicholas J. ; Abramoff, Rose Z. ; Slessarev, Eric W. ; Ahlström, Anders ; et al ( February 2024 , Nature Geoscience)

   Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived global estimates of soil carbon pools to quantify their relative proportions and compute their climatological temperature sensitivities as the decline in carbon with increasing temperature. We find that the climatological temperature sensitivity of particulate carbon is on average 28% higher than that of mineral-associated carbon, and up to 53% higher in cool climates. Moreover, the distribution of carbon between these underlying soil carbon pools drives the emergent climatological temperature sensitivity of bulk soil carbon stocks. However, global models vary widely in their predictions of soil carbon pool distributions. We show that the global proportion of model pools that are conceptually similar to mineral-protected carbon ranges from 16 to 85% across Earth system models from the Coupled Model Intercomparison Project Phase 6 and offline land models, with implications for bulk soil carbon ages and ecosystem responsiveness. To improve projections of carbon cycle–climate feedbacks, it is imperative to assess underlying soil carbon pools to accurately predict the distribution and vulnerability of soil carbon.

    

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

   https://doi.org/10.1029/2023MS004156  

   Wieder, William_R ; Hartman, Melannie_D ; Kyker‐Snowman, Emily ; Eastman, Brooke ; Georgiou, Katerina ; Pierson, Derek ; Rocci, Katherine_S ; Grandy, A_Stuart ( June 2024 , Journal of Advances in Modeling Earth Systems)

   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.

    

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4. Wet-dry cycling influences the formation of mineral-associated organic matter and its sensitivity to simulated root exudates

   https://doi.org/10.1016/j.geoderma.2024.116869  

   Jilling, Andrea ; Sokol, Noah W ; Morán-Rivera, Karen ; Grandy, A Stuart ( May 2024 , Geoderma)

   Mineral particles provide reactive sites for organic carbon (C) to bind in soil; this ‘mineral-associated organic matter’ (MAOM) may persist for centuries to millennia or cycle rapidly in minutes to days. The conditions and processes that influence short and long-term cycling of MAOM are poorly constrained. Soil moisture is one key control on organic matter cycling in soil, and projected shifts in moisture regimes towards more intense rainfall and prolonged drought under climate change may alter MAOM formation and cycling. Here, in a 3-week laboratory incubation study, we evaluated how two contrasting moisture regimes affected the formation and cycling of 13C-labeled MAOM from two mineralogically-distinct soil types. Repeated wet-dry cycling (between 3% and 60% of water-holding capacity) enhanced the formation of 13C-MAOM relative to constant moisture conditions. The two soil types differed in rates of MAOM formation and the sensitivity of newly-formed and pre-existing MAOM to subsequent priming in the presence of simulated exudates (glucose and/or oxalic acid). Wet-dry cycling enhanced the decomposition of newly-formed MAOM and it further accelerated the potential priming of pre-existing MAOM. Therefore, while repeated cycles between drought-like and “optimal” moisture conditions may promote the formation of MAOM, they may also undermine the stability of pre-existing MAOM and limit opportunities for new C inputs to enter more persistent forms. 

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5. Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones

   https://doi.org/10.5194/gmd-16-3581-2023  

   Bianchi, Daniele ; McCoy, Daniel ; Yang, Simon ( January 2023 , Geoscientific Model Development)

   Abstract. Nitrogen (N) plays a central role in marine biogeochemistry by limiting biological productivity in the surface ocean; influencing the cycles of other nutrients, carbon, and oxygen; and controlling oceanic emissions of nitrous oxide (N2O) to the atmosphere. Multiple chemical forms of N are linked together in a dynamic N cycle that is especially active in oxygen minimum zones (OMZs), where high organic matter remineralization and low oxygen concentrations fuel aerobic and anaerobic N transformations. Biogeochemical models used to understand the oceanic N cycle and project its change often employ simple parameterizations of the network of N transformations and omit key intermediary tracers such as nitrite (NO2-) and N2O. Here we present a new model of the oceanic N cycle (Nitrogen cycling in Oxygen Minimum Zones, or NitrOMZ) that resolves N transformation occurring within OMZs and their sensitivity to environmental drivers. The model is designed to be easily coupled to current ocean biogeochemical models by representing the major forms of N as prognostic tracers and parameterizing their transformations as a function of seawater chemistry and organic matter remineralization, with minimal interference in other elemental cycles. We describe the model rationale, formulation, and numerical implementation in a one-dimensional representation of the water column that reproduces typical OMZ conditions. We further detail the optimization of uncertain model parameters against observations from the eastern tropical South Pacific OMZ and evaluate the model's ability to reproduce observed profiles of N tracers and transformation rates in this region. We conclude by describing the model's sensitivity to parameter choices and environmental factors and discussing the model's suitability for ocean biogeochemical studies. 

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