Not as good as they seem: the importance of concepts in species distribution modelling
Not as good as they seem: the importance of concepts in species distribution modelling
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DOI：
10.1111/j.1472-4642.2008.00496.x
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发表时间：
2008-11-01
影响因子：
4.6
通讯作者：
Hortal, Joaquin
中科院分区：
文献类型：
--
作者：
Jimenez-Valverde, Alberto;Lobo, Jorge M.;Hortal, Joaquin
目的目前，大量的物种分布数据和用于实现不同物种分布建模方法的软件可通过互联网免费获得。因此，有必要开展方法学工作，分析建模技术的相对性能，以及研究哪些物种特征影响其性能。我们讨论了在模拟物种分布时必须牢记的三个重要主题，即（i）潜在分布和已实现分布之间的区别，（ii）物种的相对发生区域对模型性能评估结果的影响，以及（iii）物种分布模型方法提供的实际分布预测普遍不准确。结果考虑到一个潜在的可实现的分布梯度，不同的建模方法可以根据它们对任何概念的建模能力而沿着这个梯度排列。复杂的技术可能比简单的技术更适合于模拟实现的分布，这可能更适合于估计潜在的分布。技术之间的比较必须考虑这种情况。物种的相对发生面积决定了评价得分的结果，这意味着稀有物种的模型必然会产生更高的区分值。此外，歧视值，通常在文献中报道可能意味着相当多的过度或低估的分布的species.Main结论这是非常重要的，以建立一个坚实的概念和方法框架上的新兴领域的物种分布建模可以站立和发展。
Aim Nowadays, large amounts of species distribution data and software for implementing different species distribution modelling methods are freely available through the internet. As a result, methodological works that analyse the relative performance of modelling techniques, as well as those that study which species characteristics affect their performance, are necessary. We discuss three important topics that must be kept in mind when modelling species distributions, namely (i) the distinction between potential and realized distribution, (ii) the effect of the relative occurrence area of the species on the results of the evaluation of model performance, and (iii) the general inaccuracy of the predictions of the realized distribution provided by species distribution modelling methods.Location Unspecific.Methods Using some recent papers as a basis, we illustrate the three issues mentioned above and discuss the negative implications of neglecting them.Results Considering a potential-realized distribution gradient, different modelling methods may be arranged along this gradient according to their ability to model any concept. Complex techniques may be more suitable to model the realized distribution than simple ones, which may be more appropriate to estimate the potential distribution. Comparisons among techniques must consider this scenario. The relative occurrence area of the species conditions the results of the evaluation scores, implying that models of rare species will unavoidably yield higher discrimination values. Moreover, discrimination values that are usually reported in the literature may imply considerable over or underestimations of the distribution of the species.Main conclusions It is extremely important to establish a solid conceptual and methodological framework on which the emergent field of species distribution modelling can stand and develop.