Next‐generation Soil Biogeochemistry Model Representations

Riley, William J.; Sierra, Carlos; Tang, Jinyun; Bouskill, Nicholas J.; Zhu, Qing; Abramoff, Rose

doi:10.1002/9781119480419.ch11

Cited by 3 publications

(2 citation statements)

References 224 publications

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“…Fourth, we acknowledge that EBMs formulated using physical rules-based approaches will usually be computationally more complex and demanding, and therefore may be more difficult to apply at large scales. This scalability issue could be solved in two steps: (a) creating an open-source numerical library that consists of processes that are formulated using physical rules, but are provided with user friendly software interfaces to be used in other models (Riley et al, 2022;Tang et al, 2022), and (b) improving the numerical efficiency of these model formulations by leveraging new developments in machine learning and artificial intelligence. The first idea has led to software like OpenFOAM (Jasak, 2009) and COMSOL (Pryor, 2012) that are able to solve computational fluid dynamics problems in various configurations.…”

Section: How To Make Physical Rules-based Approaches Easily Accessible?mentioning

confidence: 99%

“…Thus, effective management should modulate these interactions holistically for SOM storage to be maintained or even enhanced. Models that account for many of these mechanisms are being developed (Abramoff et al., 2022; Grant et al., 2017; Riley et al., 2022; Wang et al., 2022), yet implementing them comprehensively in coupled EBMs is still a far‐off goal.…”

Section: Introductionmentioning

confidence: 99%

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Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Tang,

Riley,

Manzoni

et al. 2024

JGR Biogeosciences

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To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. Instead, we propose that EBM parameterizations, as a lossy data compression problem, can be better formulated using established physical rules widely used in computational physics and chemistry, and different biogeochemical processes can be more robustly integrated within a reactive‐transport framework. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process‐level hypotheses to test in empirical studies. Finally, while empirical models with more parameters are often less robust, physical rules‐based models can be more robust and show lower predictive equifinality, stemming from their enhanced consistency in representations of processes, interactions and spatial scaling.

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Section: How To Make Physical Rules-based Approaches Easily Accessible?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Tang,

Riley,

Manzoni

et al. 2024

JGR Biogeosciences

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Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO₂ Fluxes Upon Soil Warming

Van de Broek,

Riley,

Tang

et al. 2024

JGR Biogeosciences

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Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO2 effluxes during the initial years of soil warming. The bias against observed CO2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models.

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Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)

2022

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Abstract. Reliable soil biogeochemical modeling is a prerequisite for credible projections of climate change and associated ecosystem feedbacks. This recognition has called for frameworks that can support flexible and efficient development and application of new or alternative soil biogeochemical modules in Earth system models (ESMs). The the Biogeochemical Transport and Reaction model version 1 (BeTR-v1) code (i.e., CLM4-BeTR) is one such framework designed to accelerate the development and integration of new soil biogeochemistry formulations into ESMs and to analyze structural uncertainty in ESM simulations. With a generic reactive transport capability, BeTR-v1 can represent multiphase (e.g., gaseous, aqueous, and solid), multi-tracer (e.g., nitrate and organic carbon), and multi-organism (e.g., plants, bacteria, and fungi) dynamics. Here, we describe the new version, Biogeochemical Transport and Reaction model version 2 (BeTR-v2), which adopts more robust numerical solvers for multiphase diffusion and advection and coupling between biogeochemical reactions and improves code modularization over BeTR-v1. BeTR-v2 better supports different mathematical formulations in a hierarchical manner by allowing the resultant model be run for a single topsoil layer or a vertically resolved soil column, and it allows the model to be fully coupled with the land component of the Energy Exascale Earth System Model (E3SM). We demonstrate the capability of BeTR-v2 with benchmark cases and example soil biogeochemical (BGC) implementations. By taking advantage of BeTR-v2's generic structure integrated in E3SM, we then found that calibration could not resolve biases introduced by different numerical coupling strategies of plant–soil biogeochemistry. These results highlight the importance of numerically robust implementation of soil biogeochemistry and coupling with hydrology, thermal dynamics, and plants – capabilities that the open-source BeTR-v2 provides. We contend that Earth system models should strive to minimize this uncertainty by applying better numerical solvers.

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Next‐generation Soil Biogeochemistry Model Representations

Cited by 3 publications

References 224 publications

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO₂ Fluxes Upon Soil Warming

Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)

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Next‐generation Soil Biogeochemistry Model Representations

Cited by 3 publications

References 224 publications

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)

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Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO₂ Fluxes Upon Soil Warming