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Pattern-recognition ecological niche models fit to presence-only and presence-absence data

机译:模式识别生态位模型适合仅在场和不在场的数据

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摘要

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable.
机译:1.从观察和环境数据中确定物种生态位的边界是生态学和保护生物学中的一个普遍问题,并且已经开发出多种技术或将各种技术应用于生态位模型和预测分布。在这里,我们研究了某些模式识别方法作为生态位模型(ENM)的性能。特别是,一类模式识别是一种灵活的方法,很少使用,它仅用于从存在数据中模拟生态位和分布。一类方法的发展与两类方法(存在/不存在数据)的性能类似,将在缺少缺缺点时消除有关采样伪缺或背景数据点的建模决策。

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