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      Threatened medicinal plants in China: Distributions and conservation priorities

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          Biodiversity hotspots for conservation priorities.

          Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.
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            Patterns, determinants and models of woody plant diversity in China.

            What determines large-scale patterns of species richness remains one of the most controversial issues in ecology. Using the distribution maps of 11 405 woody species in China, we compared the effects of habitat heterogeneity, human activities and different aspects of climate, particularly environmental energy, water-energy dynamics and winter frost, and explored how biogeographic affinities (tropical versus temperate) influence richness-climate relationships. We found that the species richness of trees, shrubs, lianas and all woody plants strongly correlated with each other, and more strongly correlated with the species richness of tropical affinity than with that of temperate affinity. The mean temperature of the coldest quarter was the strongest predictor of species richness, and its explanatory power for species richness was significantly higher for tropical affinity than for temperate affinity. These results suggest that the patterns of woody species richness mainly result from the increasing intensity of frost filtering for tropical species from the equator/lowlands towards the poles/highlands, and hence support the freezing-tolerance hypothesis. A model based on these results was developed, which explained 76-85% of species richness variation in China, and reasonably predicted the species richness of woody plants in North America and the Northern Hemisphere.
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              Global distribution and conservation of rare and threatened vertebrates.

              Global conservation strategies commonly assume that different taxonomic groups show congruent geographical patterns of diversity, and that the distribution of extinction-prone species in one group can therefore act as a surrogate for vulnerable species in other groups when conservation decisions are being made. The validity of these assumptions remains unclear, however, because previous tests have been limited in both geographical and taxonomic extent. Here we use a database on the global distribution of 19,349 living bird, mammal and amphibian species to show that, although the distribution of overall species richness is very similar among these groups, congruence in the distribution of rare and threatened species is markedly lower. Congruence is especially low among the very rarest species. Cross-taxon congruence is also highly scale dependent, being particularly low at the finer spatial resolutions relevant to real protected areas. 'Hotspots' of rarity and threat are therefore largely non-overlapping across groups, as are areas chosen to maximize species complementarity. Overall, our results indicate that 'silver-bullet' conservation strategies alone will not deliver efficient conservation solutions. Instead, priority areas for biodiversity conservation must be based on high-resolution data from multiple taxa.
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                Author and article information

                Journal
                Biological Conservation
                Biological Conservation
                Elsevier BV
                00063207
                June 2017
                June 2017
                : 210
                : 89-95
                Article
                10.1016/j.biocon.2017.04.015
                56af32bb-45bc-4a71-b9bc-a1f0187f9065
                © 2017

                https://www.elsevier.com/tdm/userlicense/1.0/

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