Aim Indicators for biodiversity are needed to facilitate the identification of complementary reserve networks for biodiversity conservation. One widely adopted approach is to use indicator taxa, i.e. a single taxon such as birds or butterflies, despite the ongoing debate regarding their usefulness as indicators of broader biodiversity. Here we assess several aspects, such as influence of species number, of indicator taxa for three extensive data sets to improve our insight into the effectiveness of indicator taxa.
Location Denmark, sub-Saharan Africa and Uganda.
Methods First, we investigate to what extent variation in species number between indicator taxa (e.g. 488 mammal spp. vs. 210 snake spp.) is causing the differences in effectiveness between indicator taxa. Second, we investigate whether indicator taxa are capable of outperforming indicator groups composed of random sets of species chosen among all taxa. Finally, we assess the correlation of specific properties such as mean range size of the indicator taxa to their effectiveness. We investigate these aspects of the effectiveness of indicator taxa through the separate analysis of three distinct distributional species data sets: sub-Saharan Africa (4,039 spp.), Denmark (847 spp.) and Uganda (2,822 spp.).
Results We overall found that indicator taxa comprising a greater number of species tend to perform better than indicator taxa with fewer species (e.g. 488 mammal spp. outperform 210 snake spp.), although there are some exceptions. Second, we found most indicator taxa to perform worse than indicator groups consisting of a comparable number of species selected among all taxa. Finally, the effectiveness of indicator taxa was seen to correlate poorly with selected distributional properties such as mean range size of the indicator taxa, suggesting that it is difficult to predict which taxa are efficient biodiversity indicators.
Main conclusions Overall, these findings might suggest that focus should simply be on increasing the number of species among all taxa as basis for priority setting, rather than striving to obtain the ‘perfect’ indicator taxa.