Methods in Ecology and Evolution· 2015Q1
Point process models for presence‐only analysis
- 461citations
- Q1SCImago
- 2015year
Short summary
Point process regression models offer a flexible framework for analyzing presence-only species distribution data, clarifying the response variable and enabling objective selection of background points.
AI-generated from the title and abstract; the full text is not read.
Key points
- Point process models clarify the response variable in presence-only data analysis.
- They offer an objective framework for selecting quadrature points (pseudo-absences).
- These models can explicitly account for spatial dependence between points.
- They provide tools for checking model assumptions and addressing sampling bias.
AI-generated from the title and abstract; the full text is not read.
Abstract
Summary Presence‐only data are widely used for species distribution modelling, and point process regression models are a flexible tool that has considerable potential for this problem, when data arise as point events. In this paper, we review point process models, some of their advantages and some common methods of fitting them to presence‐only data. Advantages include (and are not limited to) clarification of what the response variable is that is modelled; a framework for choosing the number and location of quadrature points (commonly referred to as pseudo‐absences or ‘background points’) objectively; clarity of model assumptions and tools for checking them; models to handle spatial dependence between points when it is present; and ways forward regarding difficult issues such as accounting for sampling bias. Point process models are related to some common approaches to presence‐only species distribution modelling, which means that a variety of different software tools can be used to fit these models, including maxent or generalised linear modelling software.
The authors' abstract, as published at the source. Methods in Ecology and Evolution, 2015 · DOI ↗
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Field: Applied Mathematics
Applied MathematicsMathematics