LaliberteStLaurent2020

Référence

Laliberté, J., St-Laurent, M.-H. (2020) Validation of functional connectivity modeling: The Achilles’ heel of landscape connectivity mapping. Landscape and Urban Planning, 202. (Scopus )

Résumé

Modeling functional connectivity in altered landscapes is one of the growing fields of expertise in landscape ecology, and many research teams have proposed different methods to evaluate it for a wide range of species. However, very few have empirically validated the efficiency of such models in discriminating real corridors from theoretical ones. Models that are not validated or those only based on structural connectivity could result in inefficient management decisions. Moreover, validation could potentially reveal that functional connectivity differs between focal species and spatial scales. Here we empirically compared different validation methods for two commonly used connectivity models applied to two cervid species (i.e. moose Alces americanus and white-tailed deer Odocoileus virginianus) during a road enlargement project. For both species, we built functional connectivity maps using CircuitScape (circuit-based model) and LinkageMapper (least-cost path model). We then validated them empirically using four different metrics: density of cervid-vehicle collisions, distance to the nearest wintering ground and detection rate calculated with automated cameras and with sand traps. Validation was carried out at various spatial scales (150, 500, 1000, 1500, 2000 and 2500 m). The circuit-based models performed better at identifying functional corridors of connectivity for moose. Validation strength differed greatly between the four metrics used, and the spatial scale at which the correlation between connectivity and data was assessed had little effect. Our study emphasizes the importance of validating functional connectivity models to provide the best decision-making tools. © 2020 Elsevier B.V.

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@ARTICLE { LaliberteStLaurent2020,
    AUTHOR = { Laliberté, J. and St-Laurent, M.-H. },
    JOURNAL = { Landscape and Urban Planning },
    TITLE = { Validation of functional connectivity modeling: The Achilles’ heel of landscape connectivity mapping },
    YEAR = { 2020 },
    NOTE = { cited By 0 },
    VOLUME = { 202 },
    ABSTRACT = { Modeling functional connectivity in altered landscapes is one of the growing fields of expertise in landscape ecology, and many research teams have proposed different methods to evaluate it for a wide range of species. However, very few have empirically validated the efficiency of such models in discriminating real corridors from theoretical ones. Models that are not validated or those only based on structural connectivity could result in inefficient management decisions. Moreover, validation could potentially reveal that functional connectivity differs between focal species and spatial scales. Here we empirically compared different validation methods for two commonly used connectivity models applied to two cervid species (i.e. moose Alces americanus and white-tailed deer Odocoileus virginianus) during a road enlargement project. For both species, we built functional connectivity maps using CircuitScape (circuit-based model) and LinkageMapper (least-cost path model). We then validated them empirically using four different metrics: density of cervid-vehicle collisions, distance to the nearest wintering ground and detection rate calculated with automated cameras and with sand traps. Validation was carried out at various spatial scales (150, 500, 1000, 1500, 2000 and 2500 m). The circuit-based models performed better at identifying functional corridors of connectivity for moose. Validation strength differed greatly between the four metrics used, and the spatial scale at which the correlation between connectivity and data was assessed had little effect. Our study emphasizes the importance of validating functional connectivity models to provide the best decision-making tools. © 2020 Elsevier B.V. },
    AFFILIATION = { Département de Biologie, Chimie et Géographie, Center for Forest Research, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski (Québec), G5L 3A1, Canada; Département de Biologie, Chimie et Géographie, Center for Forest Research, Center for Northern Studies, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski (Québec), G5L 3A1, Canada },
    ART_NUMBER = { 103878 },
    AUTHOR_KEYWORDS = { Functional connectivity; Landscape ecology; Moose; Road ecology; Validation; White-tailed deer },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1016/j.landurbplan.2020.103878 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087393534&doi=10.1016%2fj.landurbplan.2020.103878&partnerID=40&md5=0f9eb1d491e01ba45b51eee56304b4fc },
}

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