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      Proposed biodiversity conservation areas: gap analysis and spatial prioritization on the inadequately studied Qinghai Plateau, China

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      Nature Conservation

      Pensoft Publishers

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          Abstract

          Global biodiversity priorities are primarily addressed through the establishment or expansion of conservation areas (CAs). Spatial prioritization of these CAs can help minimize biodiversity loss by accounting for the uneven distribution of biodiversity and conservation considerations (e.g., accessibility, cost, and biodiversity threats). Furthermore, optimized spatial priorities can help facilitate the judicious use of limited conservation resources by identifying cost effective CA designs. Here, we demonstrate how key species and ecosystems can be incorporated into systematic conservation planning to propose the expansion and addition of new CAs in the biodiversity-unique and data-poor region of Qinghai Plateau, China. We combined species distribution models with a systematic conservation planning tool, MARXAN to identify CAs for biodiversity on Qinghai Plateau. A set of 57 optimal CAs (273,872 km2, 39.3 % of this Province) were required to achieve the defined conservation targets in Qinghai Province. We also identified 29 new CAs (139,216 km2, 20% of Qinghai Province) outside the existing nature reserve (NRs) that are necessary to fully achieve the proposed conservation targets. The conservation importance of these 29 new CAs was also indicated, with 10 labeled as high priority, 11 as medium priority, and 8 as low priority. High priority areas were more abundant in the eastern and southeastern parts of this region. Our results suggest that many species remain inadequately protected within the Qinghai Plateau, with conservation gaps in eastern and northwestern regions. The proposed more representative and effective CAs can provide useful information for adjusting the existing NRs and developing the first National Park in China.

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          The future of biodiversity.

          Recent extinction rates are 100 to 1000 times their pre-human levels in well-known, but taxonomically diverse groups from widely different environments. If all species currently deemed "threatened" become extinct in the next century, then future extinction rates will be 10 times recent rates. Some threatened species will survive the century, but many species not now threatened will succumb. Regions rich in species found only within them (endemics) dominate the global patterns of extinction. Although new technology provides details of habitat losses, estimates of future extinctions are hampered by our limited knowledge of which areas are rich in endemics.
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            ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar

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              Predicting species distributions for conservation decisions

              Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
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                Author and article information

                Journal
                Nature Conservation
                NC
                Pensoft Publishers
                1314-3301
                1314-6947
                January 04 2018
                January 04 2018
                : 24
                : 1-20
                Article
                10.3897/natureconservation.24.20942
                © 2018

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