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Scale effects in species distribution models: implications for conservation planning under climate change

机译:物种分布模型的规模效应:气候变化对保护规划的影响

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摘要

Predictions of future species' ranges under climate change are needed for conservation planning, for which species distribution models (SDMs) are widely used. However, global climate model-based (GCM) output grids can bias the area identified as suitable when these are used as SDM predictor variables, because GCM outputs, typically at least 50×50 km, are biologically coarse. We tested the assumption that species ranges can be equally well portrayed in SDMs operating on base data of different grid sizes by comparing SDM performance statistics and area selected by four SDMs run at seven grid sizes, for nine species of contrasting range size. Area selected was disproportionately larger for SDMs run on larger grid sizes, indicating a cut-off point above which model results were less reliable. Up to 2.89 times more species range area was selected by SDMs operating on grids above 50×50 km, compared to SDMs operating at 1 km2. Spatial congruence between areas selected as range also diverged as grid size increased, particularly for species with ranges between 20 000 and 90 000 km2. These results indicate the need for caution when using such data to plan future protected areas, because an overly large predicted range could lead to inappropriate reserve location selection.
机译:保护规划需要对气候变化下未来物种范围的预测,为此广泛使用了物种分布模型(SDM)。但是,基于全球气候模型(GCM)的输出网格在将这些区域用作SDM预测变量时,可能会偏向确定的合适区域,因为GCM输出(通常至少50×50?km)在生物学上是粗糙的。我们通过比较SDM性能统计数据和由四个以7个网格大小运行的SDM选择的区域(针对9个具有相反范围大小的物种)来测试在不同网格大小的基础数据上运行的SDM中可以很好地描绘物种范围的假设。对于在较大网格尺寸上运行的SDM,选择的区域不成比例地更大,这表明在临界点之上,模型结果不太可靠。与在1xkm2上运行的SDM相比,在50×50 km以上的网格上运行的SDM选择的物种范围区域最多高出2.89倍。选择范围的区域之间的空间一致性也随着网格大小的增加而发散,特别是对于范围在20 000至90 000 000 km2之间的物种。这些结果表明,在使用此类数据来规划未来的保护区时需要谨慎,因为太大的预测范围可能会导致不合适的保护区选择。

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