Abstract
Author SummaryEcosystems across the world are being rapidly degraded. This threatens their provision of natural goods and services, upon which all life depends. To be able to reduce—and one day reverse—this damage, we need to be able to predict the effects of human actions on ecosystems. Here, we present the first example of a General Ecosystem Model (GEM)—called the Madingley Model—a novel class of computational model that can be applied to any ecosystem, marine or terrestrial, and can be simulated at any spatial scale from local up to global. It covers almost all organisms in ecosystems, from the smallest to the largest, encoding the underlying biology and behaviour of individual organisms to capture the interactions between them and with the environment, to model the fate of each individual organism, and to make predictions about ecosystem structure and function. Predictions made by the Madingley Model broadly resemble what we observe in real-world ecosystems across scales from individuals through to communities, ecosystems, and the world as a whole. Our results show that ecologists can now begin modelling all nonhuman life on earth, and we suggest that this type of approach may hold promise for predicting the ecological implications of different future trajectories of human activity on our shared planet.
Highlights
The pace and scale of anthropogenic environmental change has caused the widespread degradation of ecosystems and the services they provide that support human life on Earth [1]
Biomass dynamics were robust to the choice of the threshold number of cohorts at which to activate merging above a threshold of 1,000 cohorts (Figure S2)
We have shown that it is possible to derive global predictions about the emergent properties of ecosystem structure and function from a General Ecosystem Model (GEM) based on processes of, and interactions among, individual organisms, without any model-imposed constraints on those properties
Summary
The pace and scale of anthropogenic environmental change has caused the widespread degradation of ecosystems and the services they provide that support human life on Earth [1] Understanding and mitigating these impacts necessitates the development of a suite of tools, including policy instruments, practical conservation measures, and empirical research. Most are correlative, relying on statistical relationships derived from limited observational data without explicit reference to the underlying mechanisms; examples include the GLOBIO model, species distribution models, and models of local extinction based on species–area relationships [2,3,4]. Mechanistic models can improve our understanding of the systems being modelled, allowing predictions to be understood in relation to the underlying mechanisms that generate them [8] This in turn might lead to novel ways to mitigate or even reverse the degradation of ecosystems
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