Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study ...
Land-use change and climate change are recognized as two main drivers of the current biodiversity decline. Protected areas help safeguard the landscape from additional anthropogenic disturbances and, when properly designed, can help species cope with climate change impacts. When designed to protect...
Main Authors: | , , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
Dryad
2020
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5061/dryad.612jm641c https://datadryad.org/stash/dataset/doi:10.5061/dryad.612jm641c |
Summary: | Land-use change and climate change are recognized as two main drivers of the current biodiversity decline. Protected areas help safeguard the landscape from additional anthropogenic disturbances and, when properly designed, can help species cope with climate change impacts. When designed to protect the regional biodiversity rather than to conserve focal species or landscape elements, protected areas need to cover a representative sample of the regional biodiversity and be functionally connected, facilitating individual movements among protected areas in a network to maximize their effectiveness. We developed a methodology to define effective protected areas to implement in a regional network using ecological representativeness and functional connectivity as criteria. We illustrated this methodology in the Gaspésie region of Québec, Canada. We simulated movements for the endangered Atlantic-Gaspésie caribou population (Rangifer tarandus caribou), using an individual-based model, to determine functional ... : Starting from a published individual based model (Bauduin et al. 2016; Ecological Modelling), we simulated movements for the endangered Atlantic-Gaspésie caribou population (Rangifer tarandus caribou) to determine functional connectivity based on this large mammal. We created multiple protected areas network scenarios and evaluated their ecological representativeness and functional connectivity for the current and future conditions. We selected a subset of the most effective network scenarios and extracted the protected areas included in them. ... |
---|