A general meta‐ecosystem model to predict ecosystem functions at landscape extents

Author:

Harvey Eric1ORCID,Marleau Justin N.2,Gounand Isabelle3ORCID,Leroux Shawn J.4ORCID,Firkowski Carina R.5,Altermatt Florian67ORCID,Guillaume Blanchet F.8910ORCID,Cazelles Kevin11,Chu Cindy12,D'Aloia Cassidy C.13,Donelle Louis5,Gravel Dominique8ORCID,Guichard Frédéric2,McCann Kevin11,Ruppert Jonathan L. W.514,Ward Colette12,Fortin Marie‐Josée5

Affiliation:

1. Département des Sciences de l'Environnement, Université du Québec à Trois‐Rivières Trois‐Rivières QC Canada

2. Department of Biology, McGill University Montreal QC Canada

3. Sorbonne Université, CNRS, UPEC, CNRS, IRD, INRA, Institut d'Ecologie et des Sciences de l'Environnement, IEES Paris France

4. Department of Biology, Memorial University of Newfoundland and Labrador St. John's NL Canada

5. Department of Ecology and Evolutionary Biology, University of Toronto Toronto ON Canada

6. Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and Technology Dübendorf Switzerland

7. Department of Evolutionary Biology and Environmental Studies, University of Zurich Zürich Switzerland

8. Département de Biologie, Université de Sherbrooke Sherbrooke QC Canada

9. Département de Mathématique, Université de Sherbrooke Sherbrooke QC Canada

10. Département des Sciences de la Santé Communautaire, Université de Sherbrooke Sherbrooke QC Canada

11. Department of Integrative Biology, University of Guelph Guelph ON Canada

12. Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada Burlington ON Canada

13. Department of Biology, University of Toronto Mississauga Mississauga ON Canada

14. Ecosystem and Climate Science, Toronto and Region Conservation Authority Vaughan ON Canada

Abstract

The integration of ecosystem processes over large spatial extents is critical to predicting whether and how local and global changes may impact biodiversity and ecosystem functions. Yet, there remains an important gap in meta‐ecosystem models to predict multiple functions (e.g. carbon sequestration, elemental cycling, trophic efficiency) across ecosystem types (e.g. terrestrial‐aquatic, benthic‐pelagic). We derive a flexible meta‐ecosystem model to predict ecosystem functions at landscape extents by integrating the spatial dimension of natural systems as spatial networks of different habitat types connected by cross‐ecosystem flows of materials and organisms. We partition the physical connectedness of ecosystems from the spatial flow rates of materials and organisms, allowing the representation of all types of connectivity across ecosystem boundaries. Through simulating a forest‐lake‐stream meta‐ecosystem, our model illustrates that even if spatial flows induced significant local losses of nutrients, differences in local ecosystem efficiencies could lead to increased secondary production at regional scale. This emergent result, which we dub the ‘cross‐ecosystem efficiency hypothesis', emphasizes the importance of integrating ecosystem diversity and complementarity in meta‐ecosystem models to generate empirically testable hypotheses for ecosystem functions.

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

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