Abstract

Understanding how dispersal movements are motivated and executed is the core business of dispersal evolutionary ecology, which is an active research field in environmental sciences. However, recent advances in dispersal research have not yet been confronted to the movement ecology paradigm (MEP) that was introduced to unify the study of all types of movements of all organisms. Here we aim at doing this exercise to investigate if the MEP is sufficiently general to provide sound predictions on dispersal causes, modalities and consequences. We begin by briefly summarizing the main concepts of the MEP that are relevant to our analysis. A part of some examples, many studies focusing on animal movements share a common, two step procedures: (1) record movement paths, and (2) test post-hoc functional assumptions to identify the relationships between the four basic components listed above. Then we present some important results from dispersal evolutionary ecology research. Next we turn to two groups of model organisms (butterflies and lizards), in which dispersal has been thoroughly studied in the field for decades. These organisms have contrasted dispersal modes: the causes of dispersal are mainly related to the social context in lizards, whereas they are mainly dependent on the environmental context in butterflies. Lizards disperse most often once in their life soon after birth, whereas butterflies generally disperse all over their adult life. We investigate if and how the MEP provides an added value to the study of dispersal on these organisms. Although the MEP is in principle encapsulates almost every variation acting on movement, its ability to incorporate variation in anything else than pure movement trajectories appears to be mixed: dispersal is extremely phenotype- and context-dependent, which rends difficult the use of the MEP as an operational tool to incorporate variation across individuals and situations. We propose that a mixed approach combining the Eulerian and Lagrangian viewpoints could deal with this high dispersal variability. We conclude by providing perspectives for the integration of ecological and evolutionary processes affecting dispersal into the MEP that could increase its efficiency to study dispersal.

Highlights

  • Dispersal, movements potentially leading to gene flow [1], is inherently associated with changes of location of gametes, zygotes or individuals

  • We propose a mixed approach where the Eulerian approach based on genetic data provides a backbone for the predictions of effective dispersal within a given metapopulation

  • We focused so far on the predictions of dispersal in metapopulations without referring that much to the four components of the movement ecology paradigm (MEP)

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Summary

Introduction

Movements potentially leading to gene flow [1], is inherently associated with changes of location of gametes, zygotes or individuals. The Lagrangian approach seems a powerful tool in modelling dispersal in metapopulations: by first simulating individual trajectories according to the social and spatial contexts and integrating their net results, it should be possible to predict the dispersal rates between local populations I.e. costs of moving through a particular element can be effectively assessed by experiments [89] or by statistical inferences on real paths coupled to population genetic structure [90] The corollary of this basic assumption is that dispersers have an innate, global knowledge of the landscape to navigate to neighbor populations by minimizing their travel costs in the matrix, which may be the case if optimal dispersal directions are selected over several generations or if they derived information from immigrants about the quality and location of their population of origin [91]. We want to stress that the relative advantages of the Lagrangian/Eulerian approaches in capturing the dispersal process may be dependent both on the research questions and the study system

Conclusions
Ronce O
16. Baker RR
24. Nathan R
28. Kaiser J
52. Dingle H
59. Spieth HR
Findings
79. Turchin P
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