A comparison of survey and focal follow methods for estimating individual activity budgets of cetaceans

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 16, 2014
Source ID
10.1111/mms.12198

Entities

People

  • Caitlin Karniski
  • Eric M. Patterson
  • Ewa Krzyszczyk
  • Janet Mann
  • Margaret A. Stanton
  • Vivienne Foroughirad

Organizations

  • Duke University
  • George Washington University
  • Georgetown University
  • National Geographic Society
  • National Science Foundation
  • Office of Naval Research

Tags

Fields of Study

  • Environmental science

Readers

  • Marine Mammal Biology
  • Public Financial Management and Budgeting
  • Regression Analysis.