Umbrella index as a conservation tool across pondscapes: A case study using frogs, aquatic insects, and plants in South Africa

Biological surrogates are valuable for conservation when they are easy and cost-effective to sample, sensitive to anthropogenic change, and show similar assemblage patterns to other taxa. The umbrella index (UI) developed by Fleishman et al. (2000), aims to conserve most species in an ecosystem by focusing on a single or small group of co-occurring species to represent all species present. Here we focus on various lentic aquatic insects (‘aquatic insects’ henceforth refers to aquatic beetles, aquatic bugs, and dragonfly larvae), adult dragonflies, frogs, and aquatic plants as potential surrogates for pond communities in the Midlands, KwaZulu-Natal Province, South Africa. There were some cross-taxon correlations, but these were too weak to consider for surrogacy, largely due to dissimilar responses to the same environmental gradients. However, using UI we identified five dragonfly species, nine aquatic insect species, and three frog species as potential umbrella groups for their own taxa. The UI for same-group surrogates was flexible and covered most taxa, ranging from co-occurring habitat generalists to rare specialist species. Furthermore, all four endemic species sampled here were effective surrogate species for other local taxa, with two of them ranking top in their own taxonomic group. The lack of congruence among the different taxa means that one taxon cannot be used to stand in for another. However, the UI allowed efficient site prioritization, so long as a multi-taxon approach is used. We recommend the UI approach when selecting surrogates to represent aquatic fauna within a pondscape of the Midlands of South Africa. • Here we use the umbrella index for pond prioritization. • Dragonflies, frogs, aquatic insects and plants were assessed in ponds. • Cross-taxon responses were weak due to differential environmental drivers. • Within taxa responses were strong highlighting the need for a multi-taxon approach.