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Gland, Switzerland

Platts P.J.,University of York | Garcia R.A.,Copenhagen University | Garcia R.A.,CSIC - National Museum of Natural Sciences | Garcia R.A.,University of Evora | And 9 more authors.
Diversity and Distributions | Year: 2014

Aim: Species distribution modelling (SDM) is commonly used to predict spatial patterns of biodiversity across sets of taxa with sufficient distributional records, while omitting narrow-ranging species due to statistical constraints. We investigate the implications of this dichotomy for conservation priority setting in Africa, now and in the future. Location: Sub-Saharan Africa (excluding islands). Methods: We use multivariate ordination to characterize climatic niches of 733 African amphibians, distinguishing between species eligible for large-scale correlative SDM (≥ 10 records at 1° resolution) and those omitted due to insufficient records. Species distributions are projected under current and future climates using simple niche envelopes. Empirical priorities are derived separately on the eligible and omitted sets and compared with three existing large-scale conservation schemes. Results: Of the 733 amphibian species, 400 have too few records for correlative SDM, including 92% of those threatened with extinction (VU/EN/CR). Omitted species typically occupy topographically complex areas with cooler, wetter and less seasonal climates, which are projected to experience lower rates of climatic change. Priorities derived from omitted species have greater congruence with existing conservation schemes. Under future climate, priorities for eligible species shift towards those for omitted species. Similarly, while omitted species often lose climate space at 1° resolution, persistent populations tend to coincide with existing conservation schemes. Main conclusions: Under current climate, statistical restrictions on SDM systematically downplay important sites for narrow-ranging and threatened species. This issue spans taxonomic groups and is only partially mitigated by modelling at finer scales. Effective biodiversity conservation, now and in the future, relies on our capacity to project geographic determinants of all species, and thus, a wider range of approaches is essential. We conclude, however, that future persistence among narrow- and wide-ranging species alike will be highest within sites already identified for conservation investment and that the focus on these sites ought to be maintained. © 2014 John Wiley & Sons Ltd.

Pacifici M.,University of Rome La Sapienza | Pacifici M.,Climate Change Specialist Group | Foden W.B.,Climate Change Specialist Group | Foden W.B.,University of Witwatersrand | And 38 more authors.
Nature Climate Change | Year: 2015

The effects of climate change on biodiversity are increasingly well documented, and many methods have been developed to assess species' vulnerability to climatic changes, both ongoing and projected in the coming decades. To minimize global biodiversity losses, conservationists need to identify those species that are likely to be most vulnerable to the impacts of climate change. In this Review, we summarize different currencies used for assessing species' climate change vulnerability. We describe three main approaches used to derive these currencies (correlative, mechanistic and trait-based), and their associated data requirements, spatial and temporal scales of application and modelling methods. We identify strengths and weaknesses of the approaches and highlight the sources of uncertainty inherent in each method that limit projection reliability. Finally, we provide guidance for conservation practitioners in selecting the most appropriate approach(es) for their planning needs and highlight priority areas for further assessments.

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