Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/15983
Title: A unifying framework for quantifying the nature of animal interactions
Authors: Potts, Jonathan R.
Mokross, Karl S.
Lewis, Mark Alun
Keywords: Birds
Statistical Mechanics
Animals Movement
Collective Behaviour
Step Selection
Territoriality
Theoretical Ecologies
Ecology
Advection
Behavior, Animals
Animals Interaction
Avoidance Behavior
Bird
Diffusion
Ecosystem
Home Range
Insectivore
Nonhuman
Organismal Interaction
Rainforest
Resource Partitioning
Simulation
Territoriality
Vocalization
Animals
Behavior, Animals
Biological Model
Physiology
Population Dynamics
Animal
Behavior, Animals
Birds
Models, Biological
Population Dynamics
Rainforest
Territoriality
Issue Date: 2014
metadata.dc.publisher.journal: Journal of the Royal Society Interface
metadata.dc.relation.ispartof: Volume 11, Número 96
Abstract: Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
metadata.dc.identifier.doi: 10.1098/rsif.2014.0333
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