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A general meta-ecosystem model to predict ecosystem function at landscape extents

Authors :
Cassidy C. D’Aloia
Marie-Josée Fortin
Frédéric Guichard
Colette L. Ward
Eric Harvey
Shawn J. Leroux
Cindy Chu
Dominique Gravel
Florian Altermatt
Carina Rauen Firkowski
Kevin S. McCann
Kevin Cazelles
Isabelle Gounand
Justin N. Marleau
Jonathan L. W. Ruppert
F. Guillaume Blanchet
Louis Donelle
Department of Biological Sciences, Université du Québec à Montréal
Department of Biology, McGill University, Montreal, Canada
Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris )
Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Department of Biology, Memorial University of Newfoundland
Institut d'écologie et des sciences de l'environnement de Paris (iEES)
Institut National de la Recherche Agronomique (INRA)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)
Department of Biology [McGill University]
McGill University = Université McGill [Montréal, Canada]
Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

The integration of meta-ecosystem processes over large spatial extent is critical to predicting whether and how global changes might impact biodiversity and ecosystem functions. Yet, there remains an important gap in meta-ecosystem models to predict multiple ecosystem functions (e.g., carbon sequestration, elemental cycling, trophic efficiency) across different ecosystem types (e.g., terrestrial-aquatic, benthic-pelagic). We derive a generic meta-ecosystem model to predict ecosystem function 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. This model partitions 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 as well as the interaction(s) between them. The model predicts that cross-ecosystem flows maximize the realization of multiple functions at landscape extent. Spatial flows, even the ones that significantly reduce the overall amount of nutrients in the meta-ecosystem, can reallocate nutrients to more efficient ecosystems, leading to greater levels of productivity at both local and regional scales. This ‘cross-ecosystem efficiency hypothesis’ is a general and testable hypothesis emphasizing the complementarity and interconnectedness among ecosystems and the importance of addressing ecosystem diversity for meta-ecosystem function.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....bda18442ed4a697cbb6bcb9d3e49ac7c