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Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate


Hansen, Malene Friis et al. (2020), Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate, Dryad, Dataset,


Background: Research of many mammal species tends to focus on single habitats, reducing knowledge of ecological flexibility. The Javan lutung (Trachypithecus auratus) is considered a strict forest primate, and little is known about populations living in savannah. In 2017–2018, we investigated the density and distribution of Javan lutung in Baluran National Park, Indonesia. We conducted ad libitum follows and line transect distance sampling with habitat suitability analysis of Javan lutung.

Results: Estimated density was 14.91 individuals km− 2 (95% CI 7.91–28.08), and estimated population size was 3727 individuals (95% CI 1979 – 7019). Long-tailed macaque (Macaca fascicularis) habitat suitability was the main driver of lutung habitat suitability as the probability of lutung occurrence increased greatly with macaque habitat suitability. Distance to roads, and distance to secondary forest had a negative relationship with lutung occurrence. Lutung habitat suitability decreased with increasing elevation, however, Mt Baluran and the primary forest on Mt Baluran was under-sampled due to treacherous conditions. Follows of six focus groups revealed considerable use of savannah, with terrestrial travel. The follows also revealed polyspecific associations with long-tailed macaques through shared sleeping sites and inter-specific vocalisations. 

Conclusions: Our study provides new knowledge on the general ecology of Javan lutung, such as use of savannah habitats, underlining our need to branch out in our study sites to understand the flexibility and adaptability of our study species. Another undocumented behaviour is the polyspecific association with long-tailed macaques. We encourage more research on this subject.


Line transect distance sampling

Species distribution modelling, MaxEnt algorithm

R code


Innovationsfonden, Award: 5189-00135B