Analyzing temporally correlated dolphin sightings data using generalized estimating equations

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.