Abstract
Accurate estimations of the abundance of threatened animal populations are required for assessment of species’ status and vulnerability and conservation planning. However, density estimation is usually difficult and resource demanding, so researchers often collect data at local scales. However, anthropogenic pressures most often have landscape‐level effects, for example, through habitat loss and fragmentation. We applied hierarchical distance sampling (HDS) to transect count data to determine the effect of habitat and anthropogenic factors on the density of 3 arboreal primate species inhabiting 5 distinct tropical forests across a landscape of 19,000 km 2 in the Udzungwa Mountains of Tanzania. We developed a novel, multiregion extension of HDS that allowed us to model density and detectability jointly across forests without losing site‐specific information. For all species, the effect of anthropogenic disturbance on density was overwhelmingly negative among metapopulations: −0.63 Angolan colobus (Colobus angolensis palliatus) (95% Bayesian CI −1.03 to −0.27), −0.54 Udzungwa red colobus (Procolobus gordonorum) (−0.89 to −0.22), and −0.33 Sykes' monkey (Cercopithecus mitis monoides) (−0.63 to −0.07). Some responses to habitat factors were shared, notably the negative effect of elevation and the positive effect of climber coverage. These results are important for conservation science and practice because: the among‐populations negative responses to anthropogenic disturbance provides a foundation for development of conservation plans that hold at the landscape scale, which is a comprehensive and cost‐efficient approach; the among‐species consistency in responses suggests conservation measures may be generalized at the guild level, which is especially relevant given the functional importance of primates in tropical rainforests; and the greater primate densities in areas at low elevation, which are closer to human settlements, point to specific management recommendations, such as the creation of buffer zones and prioritization of areas for protection.