Making the mammal protection level indicator meaningful for planning and policy
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2018-06-21
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Protected areas remain the cornerstone of conservation. Evaluating whether they effectively perform their function has received much attention in the scientific literature and is implicit in the Aichi 2020 targets and global biodiversity indicators, but measurement lacks quantifiable and consistent metrics. Here we describe the first attempt at populating the headline indicator of mammal protection level in South Africa for the forthcoming National Biodiversity Assessment and discuss the issues surrounding data availability and quality, monitoring frameworks, target setting, spatial context and links to international policy tools and indicator development. We compare various approaches of calculating the indicator through sensitivity analysis and expert opinion. We argue that the indicator can become greatly more informative for planning if it incorporates species-specific targets and the spatial orientation and connectivity between populations (scaled by each species’ population structure). While this may appear to be a data-intensive and timeconsuming process, it can be easily achieved by compiling existing data and information from across the South African National Biodiversity Institute’s (SANBI) network of partners and by keeping the database periodically updated. This is in line with SANBI’s mandate as a national biodiversity informatics hub.
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Mammals, Conservation, Biodiversity, Planning
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Protected areas remain the cornerstone of conservation. Evaluating whether they effectively perform their function has received much attention in the scientific literature and is implicit in the Aichi 2020 targets and global biodiversity indicators, but measurement lacks quantifiable and consistent metrics. Here we describe the first attempt at populating the headline indicator of mammal protection level in South Africa for the forthcoming National Biodiversity Assessment and discuss the issues surrounding data availability and quality, monitoring frameworks, target setting, spatial context and links to international policy tools and indicator development. We compare various approaches of calculating the indicator through sensitivity analysis and expert opinion. We argue that the indicator can become greatly more informative for planning if it incorporates species-specific targets and the spatial orientation and connectivity between populations (scaled by each species’ population structure). While this may appear to be a data-intensive and timeconsuming process, it can be easily achieved by compiling existing data and information from across the South African National Biodiversity Institute’s (SANBI) network of partners and by keeping the database periodically updated. This is in line with SANBI’s mandate as a national biodiversity informatics hub.
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