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Distinguishing mobility and immobility when establishing species-specific activity budgets: A case study with gorillas (Gorilla berengei berengei and Gorilla gorilla gorilla).

Jean D NsekanaboAustin LeedsWinnie EckardtDeogratias TuyisingizeAisha NyiramanaKristen E Lukas
Published in: Zoo biology (2022)
Activity budgets characterize the distribution of behavior over a specified time period. In some cases, having comparable data from free-ranging populations can help inform the management of wildlife in zoos and sanctuaries. For example, although variations exist across subspecies, seasons, and study sites, diurnal activity budgets for free-ranging gorillas largely consist of feeding and resting. Unfortunately, most studies do not consistently differentiate between the type of activities gorillas exhibit while locomoting versus stationary. Therefore, it can be difficult to characterize optimal levels of aerobic activity that might enhance body condition or promote gorilla health in zoos and sanctuaries. In this study, we concurrently measured the mobility state and activity of mountain gorillas (Gorilla beringei beringei) in Volcanoes National Park, Rwanda. From June to August 2015, behavioral data were collected using group scan sampling with 15-min intervals in two groups (N = 29 gorillas) monitored by the Dian Fossey Gorilla Fund International. Overall, gorillas spent significantly more time immobile (85.2% of observations) than mobile (14.8%), revealing energy expenditure levels comparable to western lowland gorillas living in zoos. There was no difference in behavioral diversity when gorillas were mobile versus immobile but adult females exhibited substantially less behavioral diversity while immobile than other age-sex classes. There was more diversity in behaviors following the transition from immobile to mobile than vice versa, particularly for adult females. Future studies should concurrently measure mobility state and behavior to improve the precision of activity budget data and serve as a more useful tool for evaluating optimal activity levels for wildlife in human care.
Keyphrases
  • healthcare
  • public health
  • computed tomography
  • magnetic resonance imaging
  • endothelial cells
  • machine learning
  • climate change
  • high intensity
  • current status
  • genetic diversity