Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change
Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change
复制标题
走进利基市场：微气候数据对于准确评估物种对气候变化的脆弱性至关重要
DOI：
10.1098/rsbl.2014.0576
复制
发表时间：
2014
期刊：
影响因子：
3.3
通讯作者：
S. Williams
中科院分区：
文献类型：
--
作者：
C. Storlie;A. Merino‐Viteri;B. Phillips;J. VanDerWal;J. Welbergen;S. Williams
为了评估一个物种对气候变化的脆弱性，我们通常使用在时间和空间上粗略解决的地图环境数据。粗略解决的温度数据通常是不准确的预测温度的微生境所使用的生物体，也可能表现出空间偏差，在地形复杂的地区。这些不准确性的一个后果是，粗略解析的层可能预测超过物种已知热极限的站点处的热状况。在这项研究中，我们使用统计降尺度来考虑环境因素，并制定高分辨率的日最高温度估计为36 000平方公里的研究区域在38年的时间。然后，我们证明，这种统计降尺度提供的温度估计，始终把焦点物种在其基本的热生态位，而粗解决层没有。我们的研究结果强调了将精细尺度的天气数据纳入物种脆弱性分析的必要性，并表明统计降尺度方法可以产生生物相关的热制度的估计。
To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km2 study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes.