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The Best of Two Worlds: Using Stacked Generalisation for Integrating Expert Range Maps in Species Distribution Models
Global Ecology and Biogeography ( IF 6.3 ) Pub Date : 2024-09-10 , DOI: 10.1111/geb.13911 Julian Oeser 1 , Damaris Zurell 2 , Frieder Mayer 3 , Emrah Çoraman 3, 4 , Nia Toshkova 5 , Stanimira Deleva 5 , Ioseb Natradze 6 , Petr Benda 7, 8 , Astghik Ghazaryan 9 , Sercan Irmak 4, 10 , Nijat Hasanov 11 , Gulnar Guliyeva 11 , Mariya Gritsina 12 , Tobias Kuemmerle 1, 13
Global Ecology and Biogeography ( IF 6.3 ) Pub Date : 2024-09-10 , DOI: 10.1111/geb.13911 Julian Oeser 1 , Damaris Zurell 2 , Frieder Mayer 3 , Emrah Çoraman 3, 4 , Nia Toshkova 5 , Stanimira Deleva 5 , Ioseb Natradze 6 , Petr Benda 7, 8 , Astghik Ghazaryan 9 , Sercan Irmak 4, 10 , Nijat Hasanov 11 , Gulnar Guliyeva 11 , Mariya Gritsina 12 , Tobias Kuemmerle 1, 13
Affiliation
Species distribution models (SDMs) are powerful tools for assessing suitable habitats across large areas and at fine spatial resolution. Yet, the usefulness of SDMs for mapping species' realised distributions is often limited since data biases or missing information on dispersal barriers or biotic interactions hinder them from accurately delineating species' range limits. One way to overcome this limitation is to integrate SDMs with expert range maps, which provide coarse-scale information on the extent of species' ranges and thereby range limits that are complementary to information offered by SDMs.
中文翻译:
两全其美:使用堆叠泛化在物种分布模型中集成专家范围图
物种分布模型 (SDM) 是评估大面积和精细空间分辨率适宜栖息地的强大工具。然而,SDM 在绘制物种实际分布图方面的用处往往是有限的,因为数据偏差或缺少有关扩散屏障或生物相互作用的信息会阻碍它们准确划定物种的范围限制。克服这一限制的一种方法是将 SDM 与专家范围图相结合,这些地图提供了有关物种范围的粗略信息,从而提供了与 SDM 提供的信息相辅相成的范围限制。
更新日期:2024-09-10
中文翻译:
两全其美:使用堆叠泛化在物种分布模型中集成专家范围图
物种分布模型 (SDM) 是评估大面积和精细空间分辨率适宜栖息地的强大工具。然而,SDM 在绘制物种实际分布图方面的用处往往是有限的,因为数据偏差或缺少有关扩散屏障或生物相互作用的信息会阻碍它们准确划定物种的范围限制。克服这一限制的一种方法是将 SDM 与专家范围图相结合,这些地图提供了有关物种范围的粗略信息,从而提供了与 SDM 提供的信息相辅相成的范围限制。