A quantitative analysis of biodiversity and the recreational value of potential national parks in Denmark.

Denmark has committed itself to the European 2010 target to halt the loss of biodiversity. Currently, Denmark is in the process of designating larger areas as national parks, and 7 areas (of a possible 32 larger nature areas) have been selected for pilot projects to test the feasibility of establishing national parks. In this article, we first evaluate the effectiveness of the a priori network of national parks proposed through expert and political consensus versus a network chosen specifically for biodiversity through quantitative analysis. Second, we analyze the potential synergy between preserving biodiversity in terms of species representation and recreational values in selecting a network of national parks. We use the actual distribution of 973 species within these 32 areas and 4 quantitative measures of recreational value. Our results show that the 7 pilot project areas are not significantly more effective in representing species than expected by chance and that considerably more efficient networks can be selected. Moreover, it is possible to select more-effective networks of areas that combine high representation of species with high ranking in terms of recreational values. Therefore, our findings suggest possible synergies between outdoor recreation and biodiversity conservation when selecting networks of national parks. Overall, this Danish case illustrates that data-driven analysis can not only provide valuable information to guide the decision-making process of designating national parks, but it can also be a means to identify solutions that simultaneously fulfill several goals (biodiversity preservation and recreational values).

Improving the performance of indicator groups for the identification of important areas for species conservation.

Indicator groups may be important tools with which to guide the selection of networks of areas for conservation. Nevertheless, the literature provides little guidance as to what makes some groups of species more suitable than others to guide area selection. Using distributional data on all sub-Saharan birds and mammals, we assessed factors that influence the effectiveness of indicator groups. We assessed the influence of threatened, endemic, range-restricted, widespread, and large-bodied species by systematically varying their number in indicator groups. We also assessed the influence of taxonomic diversity by systematically varying the number of distinct genera and families within the indicator groups. We selected area networks based on the indicator groups and tested their ability to represent a set of species, which, in terms of species composition, is independent of the indicator group. Increasing the proportion of threatened, endemic, and range-restricted species in the indicator groups improved effectiveness of the selected area networks; in particular it improved the effectiveness in representing other threatened and range-restricted species. In contrast increasing the proportion of widespread and large-bodied species decreased effectiveness. Changes in the number of genera and families only marginally affected the performance of indicator groups. Our results reveal that a focus on species of special conservation concern, which are legitimate conservation targets in their own right, also improves the effectiveness of indicator groups, in particular in representing other species of conservation concern.