Current rates of climatic change will affect the structure and function of community assemblages on Earth. In recent decades, advances in modelling techniques have illuminated the potential effects of various climatic scenarios on biodiversity hotspots, including community assemblages in the Himalayas. These techniques have been used to test the effects of representative concentration pathways (RCPs) AR5-2050, based on future greenhouse gas emission trajectories of climate change scenario/year combinations, on pheasants. Current bioclimatic variables, Miroc-esm, Hadgem2-AO and Gfdl-cm3, in future climate change scenario models, were used to predict the future distribution and the gain/loss of future habitat area, within the Himalayas, of the pheasant, Satyr Tragopon (Tragopan satyra). The results indicate that future climatic conditions may significantly affect the future distribution of Satyr Tragopon and the effectiveness of protective areas (PAs). Using the python based GIS toolkit, SDM projection, regions of high risk under climate change scenarios were identified. To predict the present distribution of the species, environment parameters of bioclimatic variables, red reflectance, blue reflectance, solar azimuth angle, altitude, slope, aspect, NDVI, EVI, VI, and LCLU were used. The forest cover (NDVI) and the canopy cover (EVI), and variables affecting forest structure, namely altitude, slope, solar azimuth angle and Bio7, were the primary factors dictating the present distribution of T. satyra. The predicted trend of habitat shifting of T. satyra in the Himalayas to higher altitudes and latitudes will gradually become more prominent with climate warming.

中文翻译：

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预测喜马拉雅山近危色狼（Tragopan satyra；鸡形目）的气候驱动栖息地转移

当前的气候变化速度将影响地球上群落组合的结构和功能。近几十年来，建模技术的进步阐明了各种气候情景对生物多样性热点的潜在影响，包括喜马拉雅山的群落组合。基于气候变化情景/年份组合的未来温室气体排放轨迹，这些技术已被用于测试代表性浓度路径 (RCP) AR5-2050 对野鸡的影响。在未来的气候变化情景模型中，当前的生物气候变量 Miroc-esm、Hadgem2-AO 和 Gfdl-cm3 用于预测雉鸡 Satyr Tragopon 在喜马拉雅山脉内的未来分布和未来栖息地的获得/损失（Tragopan satyra）。结果表明，未来的气候条件可能会显着影响 Satyr Tragopon 的未来分布和保护区（PA）的有效性。使用基于 python 的 GIS 工具包，SDM 投影，确定了气候变化情景下的高风险区域。为了预测物种的当前分布，使用了生物气候变量的环境参数、红色反射率、蓝色反射率、太阳方位角、高度、坡度、坡向、NDVI、EVI、VI 和 LCLU。森林覆盖率 (NDVI) 和冠层覆盖率 (EVI) 以及影响森林结构的变量，即海拔、坡度、太阳方位角和 Bio7，是决定 T. satyra 目前分布的主要因素。T.栖息地转移的预测趋势。