Analyzing temporally correlated dolphin sightings data using generalized estimating equations

Helen Rebecca Bailey, Ross Corkrey, Barbara Jean Cheney, Paul Michael Thompson

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)123-141
Number of pages19
JournalMarine Mammal Science
Volume29
Issue number1
Early online date19 Mar 2012
DOIs
Publication statusPublished - Jan 2013

Fingerprint

dolphin
dolphins
marine mammals
marine mammal
Tursiops truncatus
autocorrelation
biologists
tides
temporal variation
time series analysis
linear models
annual variation
tide
ecology
time series
summer
methodology
modeling

Keywords

  • bottlenose dolphin
  • correlations
  • GEE
  • interannual variation
  • temporal variation
  • tidal cycle
  • Tursiops truncatus

Cite this

Analyzing temporally correlated dolphin sightings data using generalized estimating equations. / Bailey, Helen Rebecca; Corkrey, Ross; Cheney, Barbara Jean; Thompson, Paul Michael.

In: Marine Mammal Science, Vol. 29, No. 1, 01.2013, p. 123-141.

Research output: Contribution to journalArticle

@article{f562a2b1b61d4512b2455a1869b59bc2,
title = "Analyzing temporally correlated dolphin sightings data using generalized estimating equations",
abstract = "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.",
keywords = "bottlenose dolphin, correlations, GEE, interannual variation, temporal variation, tidal cycle, Tursiops truncatus",
author = "Bailey, {Helen Rebecca} and Ross Corkrey and Cheney, {Barbara Jean} and Thompson, {Paul Michael}",
year = "2013",
month = "1",
doi = "10.1111/j.1748-7692.2011.00552.x",
language = "English",
volume = "29",
pages = "123--141",
journal = "Marine Mammal Science",
issn = "0824-0469",
publisher = "Wiley-Blackwell",
number = "1",

}

TY - JOUR

T1 - Analyzing temporally correlated dolphin sightings data using generalized estimating equations

AU - Bailey, Helen Rebecca

AU - Corkrey, Ross

AU - Cheney, Barbara Jean

AU - Thompson, Paul Michael

PY - 2013/1

Y1 - 2013/1

N2 - 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.

AB - 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.

KW - bottlenose dolphin

KW - correlations

KW - GEE

KW - interannual variation

KW - temporal variation

KW - tidal cycle

KW - Tursiops truncatus

U2 - 10.1111/j.1748-7692.2011.00552.x

DO - 10.1111/j.1748-7692.2011.00552.x

M3 - Article

VL - 29

SP - 123

EP - 141

JO - Marine Mammal Science

JF - Marine Mammal Science

SN - 0824-0469

IS - 1

ER -