Point process models for presence-only analysis
Access Status
Authors
Date
2015Type
Metadata
Show full item recordCitation
Source Title
ISSN
School
Collection
Abstract
1. 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. 2. In this paper, we review point process models, some of their advantages and some common methods of fitting them to presence-only data. 3. 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. 4. 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.
Related items
Showing items related by title, author, creator and subject.
-
Sneesby, Martin G. (1998)Reactive distillation has enormous potential for the economical synthesis of tertiary ethers. Methyl tert-butyl ether (MTBE) has been commercially produced with this technology since the early 1980s and it appears that ...
-
Bertolatti, Dean (2002)The aim of this study was to examine whether Gram-positive cocci isolated from processed poultry in Western Australia provided a potential risk for the transfer of antimicrobial-resistant organisms to humans via commercially ...
-
Brearley, Darren (2003)Continued expansion of the gold and nickel mining industry in Western Australia during recent years has led to disturbance of larger areas and the generation of increasing volumes of waste rock. Mine operators are obligated ...