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  • 标题:Assessing the utility and limitations of accelerometers and machine learning approaches in classifying behaviour during lactation in a phocid seal
  • 作者:Courtney R. Shuert ; Patrick P. Pomeroy ; Sean D. Twiss
  • 期刊名称:Animal Biotelemetry
  • 电子版ISSN:2050-3385
  • 出版年度:2018
  • 卷号:6
  • 期号:1
  • 页码:14
  • DOI:10.1186/s40317-018-0158-y
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:Classifying behaviour with animal-borne accelerometers is quickly becoming a popular tool for remotely observing behavioural states in a variety of species. Most accelerometry work in pinnipeds has focused on classifying behaviour at sea often quantifying behavioural trade-offs associated with foraging and diving in income breeders. Very little work to date has been done to resolve behaviour during the critical period of lactation in a capital breeder. Capital breeding phocids possess finite reserves that they must allocate appropriately to maintain themselves and their new offspring during their brief nursing period. Within this short time, fine-scale behavioural trade-offs can have significant fitness consequences for mother and offspring and must be carefully managed. Here, we present a case study in extracting and classifying lactation behaviours in a wild, breeding pinniped, the grey seal (Halichoerus grypus). Using random forest models, we were able to resolve 4 behavioural states that constitute the majority of a female grey seals’ activity budget during lactation. Resting, alert, nursing, and a form of pup interaction were extracted and classified reliably. For the first time, we quantified the potential confounding variance associated with individual differences in a wild context as well as differences due to sampling location in a largely inactive model species. At this stage, the majority of a female grey seal’s activity budget was classified well using accelerometers, but some rare and context-dependent behaviours were not well captured. While we did find significant variation between individuals in behavioural mechanics, individuals did not differ significantly within themselves; inter-individual variability should be an important consideration in future efforts. These methods can be extended to other efforts to study grey seals and other pinnipeds who exhibit a capital breeding system. Using accelerometers to classify behaviour during lactation allows for fine-scale assessments of time and energy trade-offs for species with fixed stores.
  • 关键词:Accelerometer ; Grey seal ; Maternal behaviour ; Breeding behaviour ; Machine learning ; Classification
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