The environment to the rescue: can physics help predict predator-prey interactions?
food webs
functional response
internal state
motion
movement paradigm
navigation
physical factors
predation sequence
predictability
Journal
Biological reviews of the Cambridge Philosophical Society
ISSN: 1469-185X
Titre abrégé: Biol Rev Camb Philos Soc
Pays: England
ID NLM: 0414576
Informations de publication
Date de publication:
10 Jun 2024
10 Jun 2024
Historique:
revised:
17
05
2024
received:
30
06
2023
accepted:
24
05
2024
medline:
10
6
2024
pubmed:
10
6
2024
entrez:
10
6
2024
Statut:
aheadofprint
Résumé
Understanding the factors that determine the occurrence and strength of ecological interactions under specific abiotic and biotic conditions is fundamental since many aspects of ecological community stability and ecosystem functioning depend on patterns of interactions among species. Current approaches to mapping food webs are mostly based on traits, expert knowledge, experiments, and/or statistical inference. However, they do not offer clear mechanisms explaining how trophic interactions are affected by the interplay between organism characteristics and aspects of the physical environment, such as temperature, light intensity or viscosity. Hence, they cannot yet predict accurately how local food webs will respond to anthropogenic pressures, notably to climate change and species invasions. Herein, we propose a framework that synthesises recent developments in food-web theory, integrating body size and metabolism with the physical properties of ecosystems. We advocate for combination of the movement paradigm with a modular definition of the predation sequence, because movement is central to predator-prey interactions, and a generic, modular model is needed to describe all the possible variation in predator-prey interactions. Pending sufficient empirical and theoretical knowledge, our framework will help predict the food-web impacts of well-studied physical factors, such as temperature and oxygen availability, as well as less commonly considered variables such as wind, turbidity or electrical conductivity. An improved predictive capability will facilitate a better understanding of ecosystem responses to a changing world.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : sDiv, Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig
ID : DFG FZT 118
Organisme : sDiv, Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig
ID : 202548816
Informations de copyright
© 2024 The Author(s). Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.
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