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Analyzing temporally correlated dolphin sightings data using generalized estimating equations


Bailey, H and Corkrey, R and Cheney, B and Thompson, PM, Analyzing temporally correlated dolphin sightings data using generalized estimating equations, Marine Mammal Science, 29, (1) pp. 123-141. ISSN 0824-0469 (2013) [Refereed Article]

Copyright Statement

Copyright 2012 Society for Marine Mammalogy

DOI: doi:10.1111/j.1748-7692.2011.00552.x


Many of the statistical techniques commonly used in ecology assume independence among responses. However, there are many marine mammal survey techniques, such as those involving time series or subgroups, which result in correlations within the data. Generalized estimating equations (GEEs) take such correlations into account and are an extension of generalized linear models. This study demonstrates the application of GEEs by modeling temporal variation in bottlenose dolphin presence from sightings data. Since dolphins could remain in the study area for several hours resulting in temporal autocorrelation, an autoregressive correlation structure was used within the GEE, each cluster representing hours within a day of survey effort. The results of the GEE model showed that there was significant diel, tidal, and interannual variation in the presence of dolphins. Dolphins were most likely to be seen in the early morning and during the summer months. Dolphin presence generally peaked during low tide, but this varied among years. There was a significantly lower probability of dolphins being present in 2003 than 2004, but not between 2004 and the other years (1991, 1992, and 2002). GEE-model fitting packages are now readily available, making this a valuable, versatile tool for marine mammal biologists.

Item Details

Item Type:Refereed Article
Keywords:bottlenose dolphin, correlations, GEE, interannual variation, temporal variation, tidal cycle, Tursiops truncatus
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Biostatistics
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Marine biodiversity
UTAS Author:Corkrey, R (Dr Ross Corkrey)
ID Code:48680
Year Published:2013
Web of Science® Times Cited:28
Deposited By:Tasmanian Institute of Agriculture
Deposited On:2007-10-25
Last Modified:2014-11-18

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