Land-use legacies play an important role in shaping contemporary species distributions. However, land-use legacies are rarely considered in species distribution models (SDMs) that aim to model present-day species distributions across the landscape, even though they can lead to a species absence in suitable areas. SDMs that do not account for land-use legacies will likely result in biased predictions of species distributions. We examine the importance of land-use legacies for modeling present-day distributions of tree species at a regional scale, assessing how the addition of land-use legacy variables improves predictive power of SDMs. We generated land-use legacy variables using raster layers of reconstructed historical agricultural land use and 3310 inventory plots. SDMs were developed for six forest tree species based on climatic, edaphic, and topographic variables, and with (SDMLU) and without (SDMBase) land-use legacy variables. We compared the predictive power between SDMLU and SDMBase models and then quantified the local importance of land-use legacy variables relative to other abiotic variables. Our results show that the importance of land-use legacy variables for present-day species distributions and the improvement on the predictive power of SDMs is species-specific. The inclusion of land-use legacy variables improved SDMs primarily by lowering errors of commission and increasing the overall accuracy of prediction. The influence of land-use legacies on SDMs suggests that, for some tree species, incorporating land-use legacies can accurately identify suitable areas that are not occupied by the species due to land-use legacies, and advance our understanding of their present-day distributions.

中文翻译：

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土地利用遗产对当今物种分布建模的重要性

土地利用遗产在塑造当代物种分布方面发挥着重要作用。然而，在旨在模拟当今整个景观中的物种分布的物种分布模型 (SDM) 中很少考虑土地利用遗产，即使它们可能导致合适区域中的物种缺失。不考虑土地利用遗产的 SDM 可能会导致对物种分布的有偏见的预测。我们研究了土地利用遗产在区域尺度上对当前树种分布进行建模的重要性，评估了土地利用遗产变量的添加如何提高 SDM 的预测能力。我们使用重建的历史农业土地利用和 3310 个清单地块的栅格图层生成土地利用遗留变量。SDM 是根据气候、土壤、和地形变量，以及有（SDM​​LU）和没有（SDM​​Base）土地利用遗留变量。我们比较了 SDMLU 和 SDMBase 模型之间的预测能力，然后量化了土地利用遗留变量相对于其他非生物变量的局部重要性。我们的结果表明，土地利用遗留变量对当今物种分布的重要性以及 SDM 预测能力的提高是特定于物种的。土地利用遗留变量的加入主要通过降低委托误差和提高预测的整体准确性来改进 SDM。土地利用遗产对 SDM 的影响表明，对于某些树种，结合土地利用遗产可以准确识别由于土地利用遗产而未被该物种占据的合适区域，