No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation

By Huijie Qiao, Jorge Soberón, A. Townsend Peterson. 2015

370 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/69b8f98dc35a24e1fa13f9983daca496afb9fba3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance (2018, background): “In practice, this case occurs when the sampling is perfectly random throughout the landscape and species detectability is equal to one, or when evaluating SDM performance with virtual species (e.g. Qiao, Sober ó n, & Peterson, 2015).”
Effect of the Maxent model’s complexity on the prediction of species potential distributions (2016, neutral): “…利用物种已知的分布数据和相关环境变量, 根据一定的算法来构建模型, 判断物种的生态需求, 并将运算结果投射到不同的时间或地理空间中来预测物种的现实分布(realized distribution)和潜在分布(potential distribution)。与实验机理性方案生态位模型相比, 相关性方案的生态位模型具有开放性、构建相对简单、所需参数较少等特点, 从而被越来越多的学者所采用。与分子系统学的发展历程不同, 生态位模型的广泛应用推动着其理论基础不断向前发展, 其中生态位概念、生…”
Dynamic ensemble models to predict distributions and anthropogenic risk exposure for highly mobile species (2019, result): “In contrast to machine learning mod‐ els, regression models like GAMMs may have lower descriptive per‐ formance but have been shown to have good predictive performance (Derville et al., 2018; Gregr et al., 2018; Qiao et al., 2015).”
Sampling biases shape our view of the natural world (2020, background): “However, if occurrence records are biased in their collection, models may be unrealistic (Beck et al. 2014, Costello et al. 2015a, Qiao et al. 2015).”