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Modeling and mapping the current and future climatic-niche of endangered Himalayan musk deer

机译:建模与绘制濒危喜马拉雅麝鹿的当前和未来气候 - 利基

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摘要

Identification of geographical space enveloped by suitable climatic conditions (i.e., climatic niche) that support species survival over space and time is crucial in conservation biogeography. Numerous algorithms (e.g., Maxent, GARP) with increasing accuracy have been devised and are being employed to overcome the challenges of forecasting climatic niche of species with incomplete information. The current study was conducted to map the distribution of current and future climatic niche of endangered Himalayan musk deer, a species endemic to Asia. Maxent and GARP modeling algorithms were individually employed to forecast current and future climatic niche of the species using randomly collected occurrence records of the species and bioclimatic variables with 30 '' resolution from WorldClim' datasets. Both the modeling processes performed optimally with regard to AUC and TSS values and forecasted an increase/expansion of climatically-suitable geographical space in the future. A final climatic niche distribution map was produced by combining the binary maps generated from each of the processes to produce a relatively realistic and potentially accurate distribution of climatic niche of the species over space and time. Conservation of forecasted suitable geographical space is recommended and future survey efforts for potentially unexplored populations of the species in the forecasted suitable area are suggested.
机译:鉴定由合适的气候条件(即气候Niche)封闭的地理空间,其在空间和时间上支持物种生存是保护生物地理的至关重要。已经设计了许多具有提高准确度的算法(例如,MaxEnt,Garp),并正在采用克服不完整信息预测物种气候利基的挑战。目前的研究是对亚洲特有物种的濒危喜马拉雅麝鹿的当前和未来气候利基的分布来映射。 MaxEnt和Garp建模算法单独使用,用于预测物种的当前和未来的气候利基,使用来自WorldClim'数据集的30''分辨率的物种和生物仿真变量的随机收集的发生记录。建模过程均在最佳地进行了关于AUC和TSS值,并预测未来的基础合适地理空间的增加/扩展。通过组合从每个过程产生的二进制地图来产生最终的气候利基分布图,以在空间和时间内产生相对逼真的和可能准确地分布物种的气候利基。建议保护预测合适的地理空间,建议,提出了未来的调查努力,潜在未开发出预测合适区​​域中的物种的群体。

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