气候变化领域集成服务门户(CCPortal): Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

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DOI	10.1029/2023JG007674
	Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules
	Tang, Jinyun; Riley, William J.; Manzoni, Stefano; Maggi, Federico
发表日期	2024
ISSN	2169-8953
EISSN	2169-8961
起始页码	129
结束页码	6
卷号	129 期号:6
英文摘要	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. Robust ecosystem biogeochemical models are needed to provide humanity with predictions to understand and manage interactions between terrestrial ecosystems and the climate. However, existing models do not fully achieve this target because of their wide use of statistical relationships derived from empirical observations. We argue that wider adoption of physical rules can help develop better ecosystem biogeochemical models to meet with society's needs. This can be achieved by deeper interdisciplinary collaboration between scientists from fields in soils, biology, chemistry, physics, and mathematics. Development of improved biogeochemical models will better position society to adapt to climate change. The popular empirically based modeling approaches limit improvement of existing ecosystem biogeochemical model predictions Physical rules-based approaches will help develop scaling consistent ecosystem biogeochemical models Inter-disciplinary collaboration can accelerate development and adoption of physical rules-based ecosystem biogeochemical models
英文关键词	ecosystem biogeochemistry; empirical response function; physical rules; biogeochemical modeling; soil carbon dynamics
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary
WOS记录号	WOS:001238734700001
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305639
作者单位	United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; Stockholm University; University of Sydney
推荐引用方式 GB/T 7714	Tang, Jinyun,Riley, William J.,Manzoni, Stefano,et al. Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules[J],2024,129(6).
APA	Tang, Jinyun,Riley, William J.,Manzoni, Stefano,&Maggi, Federico.(2024).Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,129(6).
MLA	Tang, Jinyun,et al."Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 129.6(2024).