JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 271
Type: Invited
Date/Time: Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #303513
Title: Unifying Presence-Only Analysis Methods in Ecology
Author(s): David Iain Warton*+ and Ian Walton Renner
Companies: University of New South Wales and University of New South Wales
Address: School of Mathematics and Statistics, Sydney, International, 2052, Australia
Keywords: Ecological statistics ; Machine learning ; Maximum entropy ; Point process models ; Pseudo-absence regression
Abstract:

A hot topic in ecology is species distribution modelling using presence-only data - geographic information systems (GIS) enable the estimation of environmental variables at a spatial resolution far higher than previously possible, and new methods of data analysis are rapidly being developed for studying how such environmental variables relate to a list of species occurrence (or "presence-only") records.

In this talk, we show that three different methods of analysis, from the ecology, machine learning and statistical literatures, are all equivalent. This advance offers new insights on how to overcome methodological weaknesses of the two most widely used methods for species distribution modelling using presence-only data - pseudo-absence regression and MAXENT - via the use of a point process model specification. An example issue that can now be addressed more effectively is understanding the role of spatial resolution in species distribution modelling. The increased functionality available via point process models will be discussed, and finally, a new method for accounting for observer bias proposed.


The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program




2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.