Department of Plant Biology, Institute of Environmental Biology, Wrocław University of Environmental and Life Sciences, Kożuchowska 5b, 51-631, Wroclaw, Poland.
Sci Rep. 2021 Jan 15;11(1):1482. doi: 10.1038/s41598-020-80062-1.
We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km) influence ecological niche modeling. We check 13 of the available environmental niche modeling algorithms, using 30 metrics to score their validity and evaluate which are useful for the selection of the best model. The validation is made using an independent dataset comprised of presences and absences collected in a range-wide field survey of Carpathian endemic plant Leucanthemum rotundifolium (Compositae). Our analysis of models' predictive performances indicates that almost all datasets may be used for the construction of a species distributional range. Both very local and very general datasets can produce useful predictions, which may be more detailed than the original ranges. Results also highlight the possibility of using the data from manually georeferenced archival sources in reconstructions aimed at establishing species' ecological niches. We discuss possible applications of those data and associated problems. For the evaluation of models, we suggest employing AUC, MAE, and Bias. We show an example of how AUC and MAE may be combined to select the model with the best performance.
我们研究了不同数据集（包括不同范围的地理参考硬拷贝地图和地理参考植物标本）如何影响生态位模型。我们检查了 13 种可用的环境生态位建模算法，使用 30 种指标来评估它们的有效性，并评估哪些对选择最佳模型有用。验证是使用一个独立的数据集进行的，该数据集由在 Carpathian 特有植物 Leucanthemum rotundifolium（菊科）的全范围实地调查中收集的存在和缺失数据组成。我们对模型预测性能的分析表明，几乎所有数据集都可用于构建物种分布范围。非常局部和非常通用的数据集都可以产生有用的预测，这些预测可能比原始范围更详细。结果还突出了在旨在建立物种生态位的重建中使用手动地理参考档案来源数据的可能性。我们讨论了这些数据的可能应用及其相关问题。对于模型的评估，我们建议使用 AUC、MAE 和 Bias。我们展示了如何结合 AUC 和 MAE 来选择性能最佳的模型的示例。
