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Correlating habitat suitability with landscape connectivity: A case study of Sichuan golden monkey in China

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  • Liu, Fang
  • McShea, William J.
  • Li, Diqiang

Abstract

We examined the landscape suitability of the region currently occupied by the Sichuan golden money (Rhinopithecus roxellana) using occupancy models constructed in Maxent with presence-only data and environmental variables. The aim of the study was to estimate potential dispersal corridors between presently disjunct populations. Least-cost path analysis was used to estimate its dispersal paths across the fragmented landscape. The results indicate that core areas of suitable habitat are located in the Qinling, Dabashan, and Minshan Mountains, as well as small patches in the Qionglai, Daxiangling and Liangshan Mountains; the most suitable habitats are in nature reserves of the Minshan Mountain. Elevation and density of the human settlements were the most important factors for identifying suitable habitat; and we identified location of less populated areas where some suitable forest patches offer the potential for dispersal corridors for this species. The study implies that there is potential for expansion of the species distribution, if steps are taken to preserve current forest patches that maybe too small for residency but suitable for dispersal.

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  • Liu, Fang & McShea, William J. & Li, Diqiang, 2017. "Correlating habitat suitability with landscape connectivity: A case study of Sichuan golden monkey in China," Ecological Modelling, Elsevier, vol. 353(C), pages 37-46.
    • Handle: RePEc:eee:ecomod:v:353:y:2017:i:c:p:37-46
    DOI: 10.1016/j.ecolmodel.2016.09.004
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    References listed on IDEAS

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    1. Costa, Hugo & Ponte, Nuno B. & Azevedo, Eduardo B. & Gil, Artur, 2015. "Fuzzy set theory for predicting the potential distribution and cost-effective monitoring of invasive species," Ecological Modelling, Elsevier, vol. 316(C), pages 122-132.
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    4. Václavík, Tomáš & Meentemeyer, Ross K., 2009. "Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?," Ecological Modelling, Elsevier, vol. 220(23), pages 3248-3258.
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