Point process models for presence-only analysis
MetadataShow full item record
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.
Showing items related by title, author, creator and subject.
Renner, I.; Elith, J.; Baddeley, Adrian; Fithian, W.; Hastie, T.; Phillips, S.; Popovic, G.; Warton, D. (2015)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 ...
Monk, J.; Ierodiaconou, D.; Versace, V.; Bellgrove, A.; Harvey, Euan; Rattray, A.; Laurenson, L.; Quinn, G. (2010)Improved access to multibeam sonar and underwater video technology is enabling scientists to use spatially-explicit, predictive modelling to improve our understanding of marine ecosystems. With the growing number of ...
Robinson, Todd; van Klinken, R.; Metternicht, Graciela (2010)Species distribution models (SDMs) can provide useful information for managing biological invasions,such as identification of priority areas for early detection or for determining containment boundaries.However, prediction ...