Incorporating connectivity in protected area prioritization
Protected areas are foundational to the conservation of populations, species, ecosystems, and landscapes. Methods and mathematical models have been and continue to be developed for identifying spatial areas that optimize multiple spatially-explicit inputs. However, the developed frameworks tend to focus on either species ranges or measures of landscape connectivity separately. We investigated:
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How can multiple inputs that cover varying ecological values be combined within a single prioritization with equal influence to identify optimal new protected areas within a landscape of protected/non-protected area matrix?
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How will incorporating connectivity measures simultaneously with species range inputs impact coverage of ranges in priotitzed areas?
We leveraged existing comprehensive mathematical and spatial methodologies for determining optimal areas to establish protections (the R package 'prioritizr') and developed a process for incorporating multiple types of inputs (with varying numbers of individual input layers per type). Using a case study in the highly biodiverse Malaysian state of Sabah, we showed that inclusion of connectivity measure inputs along with species distributions and other measures of ecological function in protected area prioritization can provide for large increases in the protection of landscape connectivity while sustaining minimal reduction of other conservation targets, which maximizes opportunities for the persistence of biodiversity.
