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\begin{document}

\title{Feasibility of formulating ecosystem biogeochemical models from
established physical rules}



\author[1]{Jinyun Tang}%
\author[1]{William J. Riley}%
\author[2]{Stefano Manzoni}%
\author[3]{Federico Maggi}%
\affil[1]{Lawrence Berkeley National Laboratory (DOE)}%
\affil[2]{Stockholm University}%
\affil[3]{University of Sydney}%


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  \date{May 26, 2024}


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\begin{abstract}
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 modeling 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. As an alternative to these empirical models,
we propose to formulate EBMs using established physical rules widely
used in computational physics and chemistry. 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?%
\end{abstract}%



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