利用开源数据预测法国卫生联盟的适用范围

G. Perrin, Clémence Rozo, F. Bioret, L. Hubert‐Moy, S. Rapinel
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引用次数: 0

摘要

虽然植被联盟的精细地图是保护的必要条件,但它们的分布通常是在大尺度上已知的。开放获取的野外和空间数据在世界范围内越来越多,但它们对模拟植被联盟的贡献仍有待评估。本研究旨在绘制法国境内沿生态梯度分布的6个健康联盟的适宜性分布区。我们使用了来自WorldClim、欧盟DEM、SoilGrids和全球风能和太阳能地图集的20个广泛和局部变量来描述生物气候和环境条件。对于每个联盟,使用存档的野外数据对两个嵌套的MaxEnt模型进行校准和验证:一个在大尺度(1000 × 1000 m)上定义其生物气候区域,另一个在局部尺度(25 × 25 m)上预测其环境区域。结果表明,空间模型在大尺度(AUC = 0.83-0.99)和局部尺度(AUC = 0.91-0.99)上具有很强的互补性。他们还强调了区分这些联盟的大陆性和温度的梯度。这些新地图提供了关于联盟分布区域的额外知识,可以支持全国范围内的自然植被保护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting the suitability area of heath alliances over France using open-source data
Abstract While fine-scale maps of vegetation alliances are required for conservation, their distribution is usually known at broad scales. Open-access field and spatial data are increasingly available worldwide, but their contribution to modelling vegetation alliances remains to be assessed. This study aimed to map the suitability area of six heath alliances distributed along ecological gradients throughout France. We used 20 broad and local variables derived from WorldClim, the European Union DEM, SoilGrids, and the Global Wind and Solar Atlases that describe bioclimatic and environmental conditions. For each alliance, two nested MaxEnt models were calibrated and validated using archive field data: one at a broad scale (1000 × 1000 m) to define its bioclimatic area, and the second at a local scale (25 × 25 m) to predict its environmental area. The results showed complementarity of the variables used to discriminate the alliances, and the accuracy of spatial modelling at broad (AUC = 0.83–0.99) and local scales (AUC = 0.91–0.99). They also highlighted the gradients of continentality and temperature that differentiate the alliances. These new maps provide additional knowledge about alliance distribution areas and could support natural vegetation conservation at a national scale.
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