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Understanding patterns of species distribution and diversity plays a vital role in biodiversity conservation. Such documentation is frequently lacking for bats, which are relatively little studied and often threatened. The Western Ghats biodiversity hotspot in peninsular India is a bat hotspot with 63 species. We conducted a comprehensive bat survey across the southern Western Ghats and used maximum entropy modeling (MaxEnt) to model the potential distribution of 37 bat species for which sufficient data were available. We generated binary maps of each species using species-specific thresholds to estimate suitable habitat areas and overlaid binary maps of species to produce bat hotspots (we use the term "bat hotspot" for regions that were suitable for more than 25 bat species). We also estimated species richness across protected area networks in the southern Western Ghats to assess the level of protection. The highest levels of species richness were found mainly along the southmost Periyar–Agastyamalai landscape. The study also identified a 1,683 km2 area of potential bat hotspot and 726 km2 (43%) of the total bat hotspots are currently within the protected area network. However, more than 50% of suitable habitats for each of the 37 species remain unprotected. Therefore, conservation decisions are needed to take into account both bat hotspots and species with restricted distributions. [ABSTRACT FROM AUTHOR]

Background and goal: The study is conducted to facilitate conservation of migratory wader species along the East Asian-Australasian Flyway, particularly to 1) Identify hotspots of wader species richness along the flyway and effectively map how these might change between breeding, non-breeding and migratory phases; 2) Determine if the existing network of protected areas (PA) is sufficient to effectively conserve wader biodiversity hotspots along the EAAF; 3) Assess how species distribution models can provide complementary distribution estimates to existing BirdLife range maps. Methods: We use a species distribution modelling (SDM) approach (MaxEnt) to develop temporally explicit individual range maps of 57 migratory wader species across their annual cycle, including breeding, non-breeding and migratory phases, which in turn provide the first biodiversity hotspot map of migratory waders along the EAAF for each of these phases. We assess the protected area coverage during each migration period, and analyse the dominant environmental drivers of distributions for each period. Additionally, we compare model hotspots to those existing range maps of the same species obtained from the BirdLife Internationals’ database. Results: Our model results indicate an overall higher and a spatially different species richness pattern compared to that derived from a wader biodiversity hotspot map based on BirdLife range maps. Field observation records from the eBird database for our 57 study species confirm many of the hotspots revealed by model outputs (especially within the Yellow Sea coastal region), suggesting that current richness of the EAAF may have been underestimated and certain hotspots overlooked. Less than 10% of the terrestrial zones area (inland and coastal) which support waders are protected and, only 5% of areas with the highest 10% species richness is protected. Main conclusions: The study results suggest the need for new areas for migratory wader research and conservation priorities including Yellow Sea region and Russian far-East. It also suggests a need to increase the coverage and percentage of current PA network to achieve Aichi Target 11 for Flyway countries, including giving stronger consideration to the temporal dynamics of wader migration. [ABSTRACT FROM AUTHOR]

The IUCN Red List has assessed the global distributions of the majority of the world’s amphibians, birds and mammals. Yet these assessments lack explicit reference to widely available, remotely-sensed data that can sensibly inform a species’ risk of extinction. Our first goal is to add additional quantitative data to the existing standardised process that IUCN employs. Secondly, we ask: do our results suggest species of concern—those at considerably greater risk than hitherto appreciated? Thirdly, these assessments are not only important on a species-by-species basis. By combining distributions of species of concern, we map conservation priorities. We ask to what degree these areas are currently protected and how might knowledge from remote sensing modify the priorities? Finally, we develop a quick and simple method to identify and modify the priority setting in a landscape where natural habitats are disappearing rapidly and so where conventional species’ assessments might be too slow to respond. Tropical, mainland Southeast Asia is under exceptional threat, yet relatively poorly known. Here, additional quantitative measures may be particularly helpful. This region contains over 122, 183, and 214 endemic mammals, birds, and amphibians, respectively, of which the IUCN considers 37, 21, and 37 threatened. When corrected for the amount of remaining natural habitats within the known elevation preferences of species, the average sizes of species ranges shrink to <40% of their published ranges. Some 79 mammal, 49 bird, and 184 amphibian ranges are <20,000km2—an area at which IUCN considers most other species to be threatened. Moreover, these species are not better protected by the existing network of protected areas than are species that IUCN accepts as threatened. Simply, there appear to be considerably more species at risk than hitherto appreciated. Furthermore, incorporating remote sensing data showing where habitat loss is prevalent changes the locations of conservation priorities. [ABSTRACT FROM AUTHOR]