A global assessment of endemism and species richness across island and mainland regions.
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ABSTRACT:
SUBMITTER: Kier G
PROVIDER: S-EPMC2685248 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Many oceanic islands are notable for their high endemism, suggesting that islands may promote unique assembly processes. However, mainland assemblages sometimes harbour comparable levels of endemism, suggesting that island biotas may not be as unique as is often assumed. Here, we test the uniqueness of island biotic assembly by comparing the rate of species turnover among islands and the mainland, after accounting for distance decay and environmental gradients. We modelled species turnover as a function of geographical and environmental distance for mainland (M-M) communities of Anolis lizards and Terrarana frogs, two clades that have diversified extensively on Caribbean islands and the mainland Neotropics. We compared mainland-island (M-I) and island-island (I-I) species turnover with predictions of the M-M model. If island assembly is not unique, then the M-M model should successfully predict M-I and I-I turnover, given geographical and environmental distance. We found that M-I turnover and, to a lesser extent, I-I turnover were significantly higher than predicted for both clades. Thus, in the first quantitative comparison of mainland-island species turnover, we confirm the long-held but untested assumption that island assemblages accumulate biodiversity differently than their mainland counterparts.
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Project description:High numbers of threatened species might be expected to occur where overall species richness is also high; however, this explains only a proportion of the global variation in threatened species richness. Understanding why many areas have more or fewer threatened species than would be expected given their species richness, and whether that is consistent across taxa, is essential for identifying global conservation priorities. Here, we show that, after controlling for species richness, environmental factors, such as temperature and insularity, are typically more important than human impacts for explaining spatial variation in global threatened species richness. Human impacts, nevertheless, have an important role, with relationships varying between vertebrate groups and zoogeographic regions. Understanding this variation provides a framework for establishing global conservation priorities, identifying those regions where species are inherently more vulnerable to the effects of threatening human processes, and forecasting how threatened species might be distributed in a changing world.
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Project description:Patterns of biodiversity and endemism are important and form the foundation for biogeography and conservation studies. Hormaphidinae is an aphid group mainly distributed in the Sino-Japanese, Oriental, and Nearctic zoogeographic realms. To infer the areas of endemism of Hormaphidinae aphids in the Sino-Japanese and Oriental realms, we employed a geographical distribution dataset covering all 225 species in subfamily Hormaphidinae. In total, 1,245 distribution occurrence records for all species were analyzed in addition to the number of species in a certain grid cell to calculate species richness. Two methods (parsimony analysis of endemicity (PAE) and the use of an optimization criterion-NDM/VNDM) using a total of 6 grid sizes were applied to detect possible areas of endemism and to assess the probable effects of the 2 different methods and 6 grid sizes on the results of the patterns of the areas of endemism. The results revealed that islands presented most of the areas with high species richness and endemic species, particularly Japan, Taiwan Island, Java Island, the Malaysian Peninsula, southeast Himalaya, and the Hengduan Mountains. Most of these areas of endemism were located on islands or a peninsula. Islands were therefore shown to play an essential role in facilitating the formation of high species richness and endemism. Different grid sizes directly determined the regions of the areas of endemism, with small grid sizes tending to detect small and discrete areas of endemism and large grid sizes identifying continuous areas of endemism. In terms of the two methods, NDM/VNDM was found to identify more areas of endemism than PAE.
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