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Ecological drivers of variation in tool-use frequency across sea otter populations

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  • Jessica A. Fujii
  • Katherine Ralls
  • Martin Tim Tinker

Abstract

Sea otters are well-known tool users, employing objects such as rocks or shells to break open hard-shelled invertebrate prey. However, little is known about how the frequency of tool use varies among sea otter populations and the factors that drive these differences. We examined 17 years of observational data on prey capture and tool use from 8 sea otter populations ranging from southern California to the Aleutian Islands in Alaska. There were significant differences in the diets of these populations as well as variation in the frequency of tool use. Sea otters at Amchitka Island, Alaska, used tools on less than 1% of dives that resulted in the capture of prey compared with approximately 16% in Monterey, California. The percentage of individuals in the population that used tools ranged from 10% to 93%. In all populations, marine snails and thick-shelled bivalves were most likely to be associated with tool use, whereas soft-bodied prey items such as worms and sea stars were the least likely. The probability that a tool would be used on a given prey type varied across populations. The morphology of the prey item being handled and the prevalence of various types of prey in local diets were major ecological drivers of tool use: together they accounted for about 64% of the variation in tool-use frequency among populations. The remaining variation may be related to changes in the relative costs and benefits to an individual otter of learning to use tools effectively under differing ecological circumstances.

Suggested Citation

  • Jessica A. Fujii & Katherine Ralls & Martin Tim Tinker, 2015. "Ecological drivers of variation in tool-use frequency across sea otter populations," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(2), pages 519-526.
  • Handle: RePEc:oup:beheco:v:26:y:2015:i:2:p:519-526.
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    File URL: http://hdl.handle.net/10.1093/beheco/aru220
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    1. Noh, Maengseok & Lee, Youngjo, 2007. "REML estimation for binary data in GLMMs," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 896-915, May.
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    1. Elisa Bandini & Rachel A. Harrison & Alba Motes-Rodrigo, 2022. "Examining the suitability of extant primates as models of hominin stone tool culture," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.

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