Perspectives in modelling ecological interaction networks for sustainable ecosystem management.

Published online
18 Jun 2024
Content type
Journal article
Journal title
Journal of Applied Ecology
DOI
10.1111/1365-2664.14584

Author(s)
Quévreux, P. & Brose, U. & Galiana, N. & Potapov, A. & Thébault, É. & Travers-Trolet, M. & Wollrab, S. & Jabot, F.
Contact email(s)
pierre.quevreux@cri-paris.org

Publication language
English

Abstract

The concept of ecological interaction networks has been widely used in fundamental ecology in the last two decades and has progressively infused in a diverse array of applied studies. Classical studies represented species interactions as static interaction webs to identify generalities in the structure of ecological networks and understand the propagation of indirect effects of species on each other and the environment. More recent research demonstrates that ecological networks are emerging features of community and interaction processes. Understanding the determinants of interaction variability in space and time and its consequences for biodiversity dynamics and ecosystem functioning constitute current frontiers in ecological network science. Although these frontiers meet a variety of applied ecological questions, many network models have been developed without clear applied perspectives. We detail how we could build on them to advance three main topics. First, the spatial dimension of ecological networks has direct implications for the design of sustainable landscapes and fisheries, for agroecology and for lake management. Second, the temporal dimension of ecological networks provides important insights for projecting biodiversity changes and adapting human actions. Third, the interactions between the abiotic and biotic components of ecosystems constitute key drivers of biogeochemical cycles, thereby providing important levers for sustainable management. Synthesis and applications. Collaborative work between empirical and theoretical network ecologists could accelerate the delivery of realistic models to inform applied practices across disciplines.

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