A stochastic movement simulator improves estimates of landscape connectivity

A. Coulon*, J. Aben, S. C. F. Palmer, V. M. Stevens, T. Callens, D. Strubbe, L. Lens, E. Matthysen, M. Baguette, Justin Mark John Travis

*Corresponding author for this work

Research output: Contribution to journalArticle

26 Citations (Scopus)
4 Downloads (Pure)

Abstract

Conservation actions often focus on restoration or creation of natural areas designed to facilitate the movements of organisms among populations. To be efficient, these actions need to be based on reliable estimates or predictions of landscape connectivity. While circuit theory and least-cost paths (LCPs) are increasingly being used to estimate connectivity, these methods also have proven limitations. We compared their performance in predicting genetic connectivity with that of an alternative approach based on a simple, individual-based "stochastic movement simulator'' (SMS). SMS predicts dispersal of organisms using the same landscape representation as LCPs and circuit theory-based estimates (i.e., a cost surface), while relaxing key LCP assumptions, namely individual omniscience of the landscape (by incorporating perceptual range) and the optimality of individual movements (by including stochasticity in simulated movements). The performance of the three estimators was assessed by the degree to which they correlated with genetic estimates of connectivity in two species with contrasting movement abilities (Cabanis's Greenbul, an Afrotropical forest bird species, and natterjack toad, an amphibian restricted to European sandy and heathland areas). For both species, the correlation between dispersal model and genetic data was substantially higher when SMS was used. Importantly, the results also demonstrate that the improvement gained by using SMS is robust both to variation in spatial resolution of the landscape and to uncertainty in the perceptual range model parameter. Integration of this individual-based approach with other developing methods in the field of connectivity research, such as graph theory, can yield rapid progress towards more robust connectivity indices and more effective recommendations for land management.

Original languageEnglish
Pages (from-to)2203-2213
Number of pages11
JournalEcology
Volume96
Issue number8
Early online date1 Aug 2015
DOIs
Publication statusPublished - Aug 2015

Keywords

  • Cabanis's Greenbul
  • circuit theory
  • dispersal
  • Epidalea calamita
  • individual-based models
  • landscape genetics
  • least-cost paths
  • natterjack toad
  • Phyllastrephus cabanisi
  • maximum-likelihood-estimation
  • gene flow
  • habitat fragmentation
  • functional connectivity
  • coalescent approach
  • migration rates
  • circuit-theory
  • climate-change

Cite this

A stochastic movement simulator improves estimates of landscape connectivity. / Coulon, A.; Aben, J.; Palmer, S. C. F.; Stevens, V. M.; Callens, T.; Strubbe, D.; Lens, L.; Matthysen, E.; Baguette, M.; Travis, Justin Mark John.

In: Ecology, Vol. 96, No. 8, 08.2015, p. 2203-2213.

Research output: Contribution to journalArticle

Coulon, A, Aben, J, Palmer, SCF, Stevens, VM, Callens, T, Strubbe, D, Lens, L, Matthysen, E, Baguette, M & Travis, JMJ 2015, 'A stochastic movement simulator improves estimates of landscape connectivity', Ecology, vol. 96, no. 8, pp. 2203-2213. https://doi.org/10.1890/14-1690.1
Coulon A, Aben J, Palmer SCF, Stevens VM, Callens T, Strubbe D et al. A stochastic movement simulator improves estimates of landscape connectivity. Ecology. 2015 Aug;96(8):2203-2213. https://doi.org/10.1890/14-1690.1
Coulon, A. ; Aben, J. ; Palmer, S. C. F. ; Stevens, V. M. ; Callens, T. ; Strubbe, D. ; Lens, L. ; Matthysen, E. ; Baguette, M. ; Travis, Justin Mark John. / A stochastic movement simulator improves estimates of landscape connectivity. In: Ecology. 2015 ; Vol. 96, No. 8. pp. 2203-2213.
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abstract = "Conservation actions often focus on restoration or creation of natural areas designed to facilitate the movements of organisms among populations. To be efficient, these actions need to be based on reliable estimates or predictions of landscape connectivity. While circuit theory and least-cost paths (LCPs) are increasingly being used to estimate connectivity, these methods also have proven limitations. We compared their performance in predicting genetic connectivity with that of an alternative approach based on a simple, individual-based {"}stochastic movement simulator'' (SMS). SMS predicts dispersal of organisms using the same landscape representation as LCPs and circuit theory-based estimates (i.e., a cost surface), while relaxing key LCP assumptions, namely individual omniscience of the landscape (by incorporating perceptual range) and the optimality of individual movements (by including stochasticity in simulated movements). The performance of the three estimators was assessed by the degree to which they correlated with genetic estimates of connectivity in two species with contrasting movement abilities (Cabanis's Greenbul, an Afrotropical forest bird species, and natterjack toad, an amphibian restricted to European sandy and heathland areas). For both species, the correlation between dispersal model and genetic data was substantially higher when SMS was used. Importantly, the results also demonstrate that the improvement gained by using SMS is robust both to variation in spatial resolution of the landscape and to uncertainty in the perceptual range model parameter. Integration of this individual-based approach with other developing methods in the field of connectivity research, such as graph theory, can yield rapid progress towards more robust connectivity indices and more effective recommendations for land management.",
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author = "A. Coulon and J. Aben and Palmer, {S. C. F.} and Stevens, {V. M.} and T. Callens and D. Strubbe and L. Lens and E. Matthysen and M. Baguette and Travis, {Justin Mark John}",
note = "Acknowledgments This publication issued from the project TenLamas funded by the French Minist{\`e}re de l'Energie, de l'Ecologie, du D{\'e}veloppement Durable et de la Mer through the EU FP6 BiodivERsA Eranet; by the Agence Nationale de la Recherche (ANR) through the open call INDHET and 6th extinction MOBIGEN to V. M. Stevens, M. Baguette, and A. Coulon, and young researcher GEMS (ANR-13-JSV7-0010-01) to V. M. Stevens and M. Baguette; and by a VLIR-VLADOC scholarship awarded to J. Aben. L. Lens, J. Aben, D. Strubbe, and E. Matthysen are grateful to the Research Foundation Flanders (FWO) for financial support of fieldwork and genetic analysis (grant G.0308.13). V. M. Stevens and M. Baguette are members of the “Laboratoire d'Excellence” (LABEX) entitled TULIP (ANR-10-LABX-41). J. M. J. Travis and S. C. F. Palmer also acknowledge the support of NERC. A. Coulon and J. Aben contributed equally to the work.",
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AU - Coulon, A.

AU - Aben, J.

AU - Palmer, S. C. F.

AU - Stevens, V. M.

AU - Callens, T.

AU - Strubbe, D.

AU - Lens, L.

AU - Matthysen, E.

AU - Baguette, M.

AU - Travis, Justin Mark John

N1 - Acknowledgments This publication issued from the project TenLamas funded by the French Ministère de l'Energie, de l'Ecologie, du Développement Durable et de la Mer through the EU FP6 BiodivERsA Eranet; by the Agence Nationale de la Recherche (ANR) through the open call INDHET and 6th extinction MOBIGEN to V. M. Stevens, M. Baguette, and A. Coulon, and young researcher GEMS (ANR-13-JSV7-0010-01) to V. M. Stevens and M. Baguette; and by a VLIR-VLADOC scholarship awarded to J. Aben. L. Lens, J. Aben, D. Strubbe, and E. Matthysen are grateful to the Research Foundation Flanders (FWO) for financial support of fieldwork and genetic analysis (grant G.0308.13). V. M. Stevens and M. Baguette are members of the “Laboratoire d'Excellence” (LABEX) entitled TULIP (ANR-10-LABX-41). J. M. J. Travis and S. C. F. Palmer also acknowledge the support of NERC. A. Coulon and J. Aben contributed equally to the work.

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N2 - Conservation actions often focus on restoration or creation of natural areas designed to facilitate the movements of organisms among populations. To be efficient, these actions need to be based on reliable estimates or predictions of landscape connectivity. While circuit theory and least-cost paths (LCPs) are increasingly being used to estimate connectivity, these methods also have proven limitations. We compared their performance in predicting genetic connectivity with that of an alternative approach based on a simple, individual-based "stochastic movement simulator'' (SMS). SMS predicts dispersal of organisms using the same landscape representation as LCPs and circuit theory-based estimates (i.e., a cost surface), while relaxing key LCP assumptions, namely individual omniscience of the landscape (by incorporating perceptual range) and the optimality of individual movements (by including stochasticity in simulated movements). The performance of the three estimators was assessed by the degree to which they correlated with genetic estimates of connectivity in two species with contrasting movement abilities (Cabanis's Greenbul, an Afrotropical forest bird species, and natterjack toad, an amphibian restricted to European sandy and heathland areas). For both species, the correlation between dispersal model and genetic data was substantially higher when SMS was used. Importantly, the results also demonstrate that the improvement gained by using SMS is robust both to variation in spatial resolution of the landscape and to uncertainty in the perceptual range model parameter. Integration of this individual-based approach with other developing methods in the field of connectivity research, such as graph theory, can yield rapid progress towards more robust connectivity indices and more effective recommendations for land management.

AB - Conservation actions often focus on restoration or creation of natural areas designed to facilitate the movements of organisms among populations. To be efficient, these actions need to be based on reliable estimates or predictions of landscape connectivity. While circuit theory and least-cost paths (LCPs) are increasingly being used to estimate connectivity, these methods also have proven limitations. We compared their performance in predicting genetic connectivity with that of an alternative approach based on a simple, individual-based "stochastic movement simulator'' (SMS). SMS predicts dispersal of organisms using the same landscape representation as LCPs and circuit theory-based estimates (i.e., a cost surface), while relaxing key LCP assumptions, namely individual omniscience of the landscape (by incorporating perceptual range) and the optimality of individual movements (by including stochasticity in simulated movements). The performance of the three estimators was assessed by the degree to which they correlated with genetic estimates of connectivity in two species with contrasting movement abilities (Cabanis's Greenbul, an Afrotropical forest bird species, and natterjack toad, an amphibian restricted to European sandy and heathland areas). For both species, the correlation between dispersal model and genetic data was substantially higher when SMS was used. Importantly, the results also demonstrate that the improvement gained by using SMS is robust both to variation in spatial resolution of the landscape and to uncertainty in the perceptual range model parameter. Integration of this individual-based approach with other developing methods in the field of connectivity research, such as graph theory, can yield rapid progress towards more robust connectivity indices and more effective recommendations for land management.

KW - Cabanis's Greenbul

KW - circuit theory

KW - dispersal

KW - Epidalea calamita

KW - individual-based models

KW - landscape genetics

KW - least-cost paths

KW - natterjack toad

KW - Phyllastrephus cabanisi

KW - maximum-likelihood-estimation

KW - gene flow

KW - habitat fragmentation

KW - functional connectivity

KW - coalescent approach

KW - migration rates

KW - circuit-theory

KW - climate-change

U2 - 10.1890/14-1690.1

DO - 10.1890/14-1690.1

M3 - Article

VL - 96

SP - 2203

EP - 2213

JO - Ecology

JF - Ecology

SN - 0012-9658

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ER -