Florian Hartig Theoretical Ecology & Ecological Data Science

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Advancing general ecosystem models (GEMs): towards a mechanistic understanding of the biosphere in the light of the Anthropocene

Joachim P. Töpper, Selwyn Hoeks, Florian Hartig, Anders Kolstad, Marlee A. Tucker, Jesamine Bartlett, Kim Magnus Bærum, Joseph Chipperfield, Michael Harfoot, Mark Antonius Jan Huijbregts, Jens-Christian Svenning

Ecological Solutions and Evidence, 6(2), e70053 (2025)
Cite this
@article{topper2025advancing,
  author = {Joachim P. Töpper and Selwyn Hoeks and Florian Hartig and Anders Kolstad and Marlee A. Tucker and Jesamine Bartlett and Kim Magnus Bærum and Joseph Chipperfield and Michael Harfoot and Mark Antonius Jan Huijbregts and Jens-Christian Svenning},
  title = {Advancing general ecosystem models (GEMs): towards a mechanistic understanding of the biosphere in the light of the Anthropocene},
  journal = {Ecological Solutions and Evidence},
  volume = {6},
  number = {2},
  pages = {e70053},
  year = {2025},
  doi = {10.1002/2688-8319.70053},
}

DOI: 10.1002/2688-8319.70053
Cited by 4 (Google Scholar) · 2 (OpenAlex), as of 07 September 2026

View article (DOI)

Abstract

General ecosystem models (GEMs) are process-based simulations of ecosystems functioning worldwide. They represent all essential processes in an ecosystem, going beyond a focus on specific biomes or organismal groups. GEMs are a comparably young development, and currently, there is still only one GEM available: the Madingley model, which was first announced in 2013. GEMs allow studying ecosystem mechanisms that are difficult or impossible to investigate empirically, and to perform simulation experiments to assess impacts of human pressures on ecosystems. As such, GEMs can be seen as the nature equivalent to ‘climate models’. As managers and policymakers urgently need good information on nature values and human impacts on them for policy design and decision-making, they have much to gain from GEMs, which allow understanding current and predicting future outcomes of human actions on biodiversity and ecosystem functioning. To increase the applicability of GEMs for informing management and policy, we argue for an acceleration and diversification in model development, and we suggest a range of developments to propel GEMs forward not only towards improved global representativeness but also towards applicability for more landscape-level problems, a scale at which actual decision-making often takes place. In addition, we argue for more accessible implementations and better documentation to increase both the transparency and credibility of GEMs, as well as the user basis applying GEMs.

What the paper shows and why it matters (AI-generated)

Only one general ecosystem model exists worldwide — the Madingley model, first proposed in 2013 — despite over a decade of arguing that these whole-ecosystem simulations are what policymakers actually need to anticipate combined climate and land-use pressures. This paper sets out what has to change for that to shift: faster, more diverse model development, applicability at the landscape scale where decisions actually get made, and enough transparency and documentation that more than a handful of specialists can use and trust the results.