2020
DOI: 10.1002/jwmg.21975
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Landscape Connectivity Influences Survival and Resource Use following Long‐Distance Translocation of Northern Bobwhite

Abstract: Translocation is an important component of northern bobwhite (Colinus virginianus) recovery efforts, given the scale of their decline and inability to rapidly recolonize recently restored habitat. Repopulating sites in northern latitudes that are distant from reliable source populations may require long‐distance trap and transport from southern locales, potentially compounding existing obstacles for this renascent population recovery technique. The landscape connectivity hypothesis predicts that site fidelity … Show more

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Cited by 5 publications
(2 citation statements)
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“…Landscape connectivity analysis based on graph theory can well simulate landscape functional connectivity based on the characteristics of landscape structure and ecological process (Liu, Yin, et al, 2018). This method has been widely used in wildlife protection and regional spatial planning (Clauzel et al, 2018; Coppola et al, 2021; Rio‐Maior et al, 2019). In this study, we adopted the graph‐based connectivity indices including number of links (NL), number of components (NC), Harary index (H) and flux index (F) reflecting the overall level of connectivity, landscape coincidence probability (LCP), integral index of connectivity (IIC), area‐weighted flux (AWF) and probability of connectivity (PC) reflecting the possibility level of connectivity to analyse the changes of functional connectivity of grassland under different water levels and dispersal distances (Table 2).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Landscape connectivity analysis based on graph theory can well simulate landscape functional connectivity based on the characteristics of landscape structure and ecological process (Liu, Yin, et al, 2018). This method has been widely used in wildlife protection and regional spatial planning (Clauzel et al, 2018; Coppola et al, 2021; Rio‐Maior et al, 2019). In this study, we adopted the graph‐based connectivity indices including number of links (NL), number of components (NC), Harary index (H) and flux index (F) reflecting the overall level of connectivity, landscape coincidence probability (LCP), integral index of connectivity (IIC), area‐weighted flux (AWF) and probability of connectivity (PC) reflecting the possibility level of connectivity to analyse the changes of functional connectivity of grassland under different water levels and dispersal distances (Table 2).…”
Section: Methodsmentioning
confidence: 99%
“…This method has been widely used in wildlife protection and regional spatial planning (Clauzel et al, 2018;Coppola et al, 2021;Rio-Maior et al, 2019). In this study, we 2).…”
Section: Landscape Pattern Indices Selectedmentioning
confidence: 99%