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A comparison of survey and focal follow methods for estimating individual activity budgets of cetaceans
Authors:Caitlin Karniski  Eric M. Patterson  Ewa Krzyszczyk  Vivienne Foroughirad  Margaret A. Stanton  Janet Mann
Affiliation:1. Department of Biology, Georgetown University, NW, Washington, DC, U.S.A;2. Marine Science and Conservation Division, Duke University, Beaufort, North Carolina, U.S.A;3. Center for the Advanced Study of Hominid Paleobiology, George Washington University, NW, Washington, DC, U.S.A;4. Department of Biology and Department of Psychology, Georgetown University, NW, Washington, DC, U.S.A
Abstract:Activity budget data are essential for determining behavioral responses to physiological and ecological variables. Yet, few studies are available to investigate the robustness, accuracy, and biases of the methods used to estimate activity budgets for cetaceans. In this study, we compare activity budgets of 55 adult female bottlenose dolphins in Shark Bay, Australia derived from two methods: surveys (n = 6,903) and focal follows (n = 1,185, totaling 2,721 h of observation). Activity budgets estimated from survey data differed in all behavioral states compared to focal follow data. However, when controlling for temporal autocorrelation, only time spent socializing and time spent traveling remained disparate between the methods. To control for biases associated with assigning group‐level behavior to individuals, we also compared survey and focal follow activity budgets for lone females. Here we found differences between methods in time spent foraging and traveling regardless of whether we controlled for temporal autocorrelation, which suggests detection biases likely play a role in explaining differences in activity budget estimates between the two methodologies. Our results suggest that surveys are less representative of individual‐level activity budgets, and thus, when individual‐level knowledge about behavior is needed, focal follows are preferred.
Keywords:sampling method  protocol  behavior  observational method  group size  observational bias  detection bias  temporal autocorrelation
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