Hierarchical Species Distribution Models

被引：8
作者：
Trevor J. Hefley
Mevin B. Hooten
机构：
[1] Colorado State University,Department of Fish, Wildlife, and Conservation Biology
[2] Colorado State University,Department of Statistics
[3] U.S. Geological Survey,Colorado Cooperative Fish and Wildlife Research Unit
来源：
Current Landscape Ecology Reports | 2016年 / 1卷 / 2期
关键词：
Bayesian analysis; Citizen science; Count data; Presence-absence data; Presence-only data; Spatio-temporal statistics;
D O I：
10.1007/s40823-016-0008-7
中图分类号：
学科分类号：
摘要：
Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
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收藏
页码：87 / 97
页数：10
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