Species undersampling in tropical bat surveys: effects on emerging biodiversity patterns

Abstract

1. Undersampling is commonplace in biodiversity surveys of species-rich tropical assemblages in which rare taxa abound, with possible repercussions for our ability to implement surveys and monitoring programs in a cost-effective way. 2. We investigated the consequences of information loss due to species undersampling (missing subsets of species from the full species pool) in tropical bat surveys for the emerging patterns of species richness and compositional variation across sites. 3. For 27 bat assemblage datasets from across the tropics, we used correlations between original datasets and subsets with different numbers of species deleted either at random, or according to their rarity in the assemblage, to assess to what extent patterns in species richness and composition in data subsets are congruent with those in the initial dataset. We then examined to what degree high sample representativeness (r >= 0.8) was influenced by biogeographic region, sampling method, sampling effort, or structural assemblage characteristics. 4. For species richness, correlations between random subsets and original datasets were strong (r >= 0.8) with moderate (ca. 20%) species loss. Bias associated with information loss was greater for species composition; on average ca. 90% of species in random subsets had to be retained to adequately capture among-site variation. For non-random subsets, removing only the rarest species (on average ~10% of the full dataset) yielded strong correlations (r > 0.95) for both species richness and composition. Eliminating greater proportions of rare species resulted in weaker correlations and large variation in the magnitude of observed correlations among datasets. 5. Species subsets that comprised ca. 85% of the original set can be considered reliable surrogates, capable of adequately revealing patterns of species richness and temporal or spatial turnover in many tropical bat assemblages. Our analyses thus demonstrate the potential as well as limitations for reducing survey effort and streamlining sampling protocols, and consequently for increasing the cost-effectiveness in tropical bat surveys or monitoring programs. The dependence of the performance of species subsets on structural assemblage characteristics (total assemblage abundance, proportion of rare species), however, underscores the importance of adaptive monitoring schemes and of establishing surrogate performance on a site-by-site basis based on pilot surveys. This article is protected by copyright. All rights reserved.