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Seasonal variation in energy balance of wild Japanese macaques (Macaca fucata yakui) in a warm-temperate forest: a preliminary assessment in the coastal forest of Yakushima.

Yosuke KuriharaKodzue KinoshitaIzumi ShiroishiGoro Hanya
Published in: Primates; journal of primatology (2020)
Food scarcity is a major challenge for primates living in temperate forests, where food availability varies markedly among seasons. In Japanese macaques, which are exclusively distributed in temperate zones, the fat accumulation ability has been highlighted as an adaptation for survival during the lean season and for reproductive success. However, the knowledge of energetic strategies of Japanese macaques has been mainly derived from data on cool-temperate forests, where fallback foods comprise winter buds and bark. Data on Japanese macaques in warm-temperate forests where fallback foods comprise mature leaves are still lacking. We aimed to identify seasonal variations in energy balance and the relative importance of ingestion rates (dry matter intake per feeding time), energy content of the food, and feeding time in energy intake of Japanese macaques in the coastal forest of Yakushima. We estimated energy balance of 6-12 adult females from October 2012 to October 2013. We estimated energy intake based on the data on feeding behavior and energy content of the diet and calculated energy expenditure based on the previously established relationship between body mass and total energy expenditure. We also quantified urinary C-peptide, which is a non-invasive biomarker of energetic conditions. We demonstrated that energy balance was more positive in the fruit/seed-feeding period than in the mature-leaf-feeding and fruit/fungi-feeding periods and that ingestion rates were the most important component of energy intake. The present study suggests that the fat accumulation ability is an essential adaptation in Japanese macaques even in warm-temperate forests.
Keyphrases
  • climate change
  • healthcare
  • adipose tissue
  • weight gain
  • risk assessment
  • body composition
  • big data
  • postmenopausal women
  • fatty acid
  • bone mineral density