The national responsibility approach to setting conservation priorities—Recommendations for its use

The implementation of conservation strategies for species and habitats is frequently hampered by the availability of the necessary resources. These should be prioritized and focused on those species and habitats most in need, but also in regard to the importance of their distribution in a certain region, country or other administrative unit. In that perspective, the concept of national responsibilities (NR) is a recently developed tool to support priority setting. It captures the impact of the loss of a particular species or habitat within the focal region (usually a country) may have on the global persistence of that species or habitat type. Although the method consists of a few simple steps and is not very demanding in regard to data availability per species and habitat type, it is still impossible to determine NRs for all species and habitats. Here, we focus on the difficulties in determining NRs due to missing distribution data, varying interpretations of definitions especially in respect to habitat types, and differences in data formats and maps using European examples of these data limitations and sources of bias. These include artificially enlarged distribution areas resulting from grid cells being reported more than once, gridded shapefiles stretching into the sea or into other biogeographic regions, and differences in the size and the shape of grid cells and hence the resolution of maps. While focusing on European examples, these sources of bias are also relevant for conservation efforts on a global scale. Our analysis stresses the importance of quickly improving data quality, availability and comparability to render conservation more efficient. We give policy relevant examples on how the NR approach can be applied, e.g. how to help attributing budgets to poorer countries, on which species and habitats to focus limited monitoring resources, and how to consider newly emerging diseases. Generally, our analyses suggests (i) to develop clear global data standards, (ii) to regularly assess data to keep up with advances in data handling, and (iii) to use downscaling approaches for biodiversity data to a higher resolution for reducing the impact of bias to a negligible level together with improving the overall quality of distribution data for conservation purposes.