Factors influencing transferability in species distribution models
Factors influencing transferability in species distribution models
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DOI：
10.1111/ecog.06060
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发表时间：
2022-04
期刊：
影响因子：
5.9
通讯作者：
Josée S. Rousseau;M. Betts
中科院分区：
文献类型：
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作者：
Josée S. Rousseau;M. Betts
物种分布模型（SDM）提供了对物种生态和分布的见解，并经常用于指导保护优先级。然而，SDM的许多用途需要模型可移植性，这是指在一个地方或时间建立的模型可以成功预测不同地方或时间的分布的程度。如果一个物种的模型具有很高的空间可转移性，那么丰度和预测变量之间的关系在整个地理分布中应该是一致的。我们使用繁殖鸟类调查，气候和遥感数据，以及一种新的方法来量化模型的可移植性，以测试SDM是否可以在129种北美鸟类的地理范围内转移。我们还评估了物种的性状是否与模型的可移植性相关。我们预计，模型区域之间的预测精度应该随着1）地理距离，2）外推程度和3）与物种分布区核心的距离而降低。我们的研究结果表明，很少有物种有一个高的模型可转移性指数（MTI）。分布范围大、分布在地形起伏小的地区和寿命短的物种更有可能表现出低的可转移性。模拟区域之间的可转移性也随着地理距离和外推程度而下降。我们预计SDM的低可转移性可能是由生态非平稳性（即物种范围内的生物学差异）和过度外推造成的。考虑到非平稳性和外推法应该大大提高物种分布模型的预测成功率，从而提高保护工作的成功率。
Species distribution models (SDMs) provide insights into species' ecology and distributions and are frequently used to guide conservation priorities. However, many uses of SDMs require model transferability, which refers to the degree to which a model built in one place or time can successfully predict distributions in a different place or time. If a species' model has high spatial transferability, the relationship between abundance and predictor variables should be consistent across a geographical distribution. We used Breeding Bird Surveys, climate and remote sensing data, and a novel method for quantifying model transferability to test whether SDMs can be transferred across the geographic ranges of 129 species of North American birds. We also assessed whether species' traits are correlated with model transferability. We expected that prediction accuracy between modeled regions should decrease with 1) geographical distance, 2) degree of extrapolation and 3) the distance from the core of a species' range. Our results suggest that very few species have a high model transferability index (MTI). Species with large distributions, with distributions located in areas with low topographic relief, and with short lifespans are more likely to exhibit low transferability. Transferability between modeled regions also decreased with geographical distance and degree of extrapolation. We expect that low transferability in SDMs potentially resulted from both ecological non‐stationarity (i.e. biological differences within a species across its range) and over‐extrapolation. Accounting for non‐stationarity and extrapolation should substantially increase the prediction success of species distribution models, therefore enhancing the success of conservation efforts.