Species occupancy modelling for detection data collected along a transect

Guillera-Arroita, Gurutzeta and Morgan, Byron J. T. and Ridout, Martin S. and Linkie, Matthew (2011) Species occupancy modelling for detection data collected along a transect. Journal of Agricultural, Biological, and Environmental Statistics, 16 (3). pp. 301-317. ISSN 1085-7117. (doi:https://doi.org/10.1007/s13253-010-0053-3) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

Abstract

The proportion of sampling sites occupied by a species is a concept of interest in ecology and biodiversity conservation. Occupancy surveys based on collecting detec- tion data along transects have become increasingly popular to monitor some species. To date, the analysis of such data has been carried out by discretizing the data, divid- ing the transects into discrete segments. Here we propose alternative occupancy models which describe the detection process as a continuous point process. These models pro- vide a more natural description of the data and eliminate the need to divide transects into segments, which can be arbitrary and may lead to increased bias in the estimator of occupancy or increased chances of obtaining estimates on the boundary of the param- eter space. We present a model that assumes independence between detections and an alternative model that describes the detection process as a Markov modulated Poisson process to account for potential clustering in the detections. The utility of these models is illustrated with the analysis of data from a recent survey of the Sumatran tiger Pan- thera tigris sumatrae. The models can also be applied to surveys that collect continuous data in time, such as those based on the use of camera-trap devices. Supplementary ma- terials for this article are available online.

Item Type:	Article
Uncontrolled keywords:	Clustered data; Markov modulated Poisson process; Wildlife monitoring; Zero-inflated Poisson process.
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics Q Science > QH Natural history > QH541 Ecology
Divisions:	Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Depositing User:	Byron Morgan
Date Deposited:	14 Jan 2013 17:07 UTC
Last Modified:	29 Apr 2014 08:48 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/32978 (The current URI for this page, for reference purposes)