Journal article 170 views 23 downloads
Beyond resource selection: emergent spatio–temporal distributions from animal movements and stigmergent interactions
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Valeria Giunta ,
Mark A. Lewis
Oikos, Volume: 2022, Issue: 6
Swansea University Author:
Valeria Giunta
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© 2022 The Authors. Oikos published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos. Distributed under the terms of a Creative Commons Attribution 3.0 Unported License (CC BY 3.0).
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DOI (Published version): 10.1111/oik.09188
Abstract
A principal concern of ecological research is to unveil the causes behind observed spatio–temporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models. In r...
| Published in: | Oikos |
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| ISSN: | 0030-1299 1600-0706 |
| Published: |
Wiley
2022
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa64698 |
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| Abstract: |
A principal concern of ecological research is to unveil the causes behind observed spatio–temporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models. In reality, however, the distribution of any population both affects and is affected by those surrounding it, creating a complex network of feedbacks causing emergent spatio–temporal features that may not correlate with any particular aspect of the underlying environment. Here, we study the way in which the movements of populations in response to one another can affect the spatio–temporal distributions of ecosystems. We construct a stochastic individual-based modelling (IBM) framework, based on stigmergent interactions (i.e. organisms leave marks which cause others to alter their movements) between and within populations. We show how to gain insight into this IBM via mathematical analysis of a partial differential equation (PDE) system given by a continuum limit. We show how the combination of stochastic simulations of the IBM and mathematical analysis of PDEs can be used to categorise emergent patterns into homogeneous versus heterogeneous, stationary versus perpetually-fluctuating and aggregation versus segregation. In doing so, we develop techniques for understanding spatial bifurcations in stochastic IBMs, grounded in mathematical analysis. Finally, we demonstrate through a simple example how the interplay between environmental features and between-population stigmergent interactions can give rise to predicted spatial distributions that are quite different to those predicted purely by accounting for environmental covariates. |
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| Keywords: |
Animal movement, animal space use, individual based models, partial differential equations, resource selection, species distribution models, stigmergy |
| College: |
Faculty of Science and Engineering |
| Funders: |
JRP and VG acknowledge support of Engineering and Physical Sciences Research Council (EPSRC) grant EP/V002988/1. MAL acknowledges support from the NSERC Discovery and Canada Research Chair programs. |
| Issue: |
6 |