中文摘要：

生态位模型是利用物种已知的分布数据和相关环境变量,根据一定的算法来推算物种的生态需求,然后将运算结果投射至不同的空间和时间中来预测物种的实际分布和潜在分布。近年来,该类模型被越来越多地应用在入侵生物学、保护生物学、全球气候变化对物种分布影响以及传染病空间传播的研究中。然而,由于生态位模型的理论基础未被深入理解,导致得出入侵物种生态位迁移等不符合实际的结论。作者从生态位与物种分布的关系、生态位模型构建的基本原理以及生态位模型和生态位的关系等方面探讨了生态位模型的理论基础。非生物的气候因素、物种间的相互作用和物种的迁移能力是影响物种分布的3个主要因素,它们在不同的空间尺度下作用于物种的分布。生态位模型是利用物种分布点所关联的环境变量来模拟物种的分布,这些分布点本身关联着该物种和其他物种间的相互作用,因此生态位模型所模拟的是现实生态位（realized niche）或潜在生态位（potential niche）,而不是基础生态位（fundamental niche）。Grinnell生态位和Elton生态位均在生态位模型中得到反映,这取决于环境变量类型的选择、所采用环境变量的分辨率以及物种自身的迁移能力。生态位模型在生物多样性保护中的应用主要包括物种的生态需求分析、未知物种或种群的探索和发现、自然保护区的选择和设计、物种入侵风险评价、气候变化对物种分布的影响、近缘物种生态位保守性及基于生态位分化的物种界定等方面。

英文摘要：

Based on the environmental variables that associated with species’ occurrence records, eco- logical niche modeling （ENM） seeks to characterize environmental conditions suitable for a particular species and then identify where suitable environmental habitats are distributed in the space. Recently, ENM has been used increasingly in biological invasion, conservation biology, biological responses to climate change, disease spatial transmission, and variety aspects of ecology and evolutionary biology research. However, the theoretical background of these applications is generally poorly understood, leading to artifactual conclusions in some studies （e.g. niche differentiation during species’ invasion）. In this paper we discuss the relationship between niche and geographic distribution and introduce the theoretical basis of ENM, along with relationships between the niche and ENM. Abiotic/biotic, historical and dispersal factors are three key elements that determine species’ geographic distributions at different scales. By using environmental variables derived from distributional records, ENM is based on observations that already include effects of biotic interactions, therefore ENM is used to characterize somewhere between the realized niche and potential niche, not the fundamental niche. Grinnellian and Eltonian niches are both manifested in ENM calibration, depending on the types of variables used to fit model, the natural spatial scale at which they can be measured, and the dispersal of individuals throughout the environment. Applications of ENM in understanding ecological requirements of species, discovery of new species or populations, nature reserve design, predicting potential invasion, modeling biological responses to climate change, niche conservatism, and species delimitation are discussed in this paper.