Considerations for using occupancy surveys to monitor forest primates: a case study with Sclater's monkey (Cercopithecus sclateri)

Abstract

Count-based indices and distance sampling are widely used to monitor primate populations. Indices are often confounded by variation in detectability, whereas distance sampling is generally ineffective with species that flee or hide from observers and where it is difficult to accurately measure detection distances. We tested occupancy modeling as a means to monitor Sclater's monkey (Cercopithecus sclateri), an endemic of Nigeria. We evaluated effects of survey methodology, habitat, and human disturbance on detection probability and site occupancy. Average detectability was high (p = 0.81), but varied substantially between two observers. Occupancy was highest in areas with intermediate levels (20-40%) of farmland and secondary forest, and was unaffected by human disturbance. Sampling plots (4 and 6.25 ha) did not concurrently contain [1 monkey group, were likely closed to monkey movements during the replicate surveys of each plot, and were spatially separated so that it was unlikely the same group was observed in [1 plot. These conditions enabled the conversion of occupancy to group density. Scaled to 6.25 ha, model-weighted occupancy averaged 0.230 (SE 0.103), yielding an estimate of 3.7 groups/km 2 (95% CI 1.4-7.7 groups/km 2 ). Because some groups straddled plot boundaries, we assumed that half of these groups were inside the plots, resulting in an adjusted estimate of 3.1 groups/km 2 . Our results illustrate that occupancy can be suitable for monitoring vigilant forest primates where detection distances are difficult to measure. However, special attention is required to choose spatial and temporal scales that accommodate the method's closure and independent-detection assumptions.

Fine-Scale Habitat Heterogeneity Influences Occupancy in Terrestrial Mammals in a Temperate Region of Australia

“…Due to convergence issues within our full models, we also were unable to use a backward stepwise approach [ 65 ]. Thus, we used a multi-step process with a forward stepwise selection approach to determine the best ranked model [ 66 ]. First, we used forward stepwise selection to consider the effect of all single variables on species detection probability.…”

Sacred populations of Cercopithecus sclateri: Analysis of apparent population increases from census counts

“…Because many primates have relatively low population densities and are wide ranging and visible, researchers typically estimate abundance or density using line‐transect distance sampling [e.g., Ferrari et al, ; Quinten et al, ] or simple index counts such as detections per kilometer walked [e.g., Baker & Olubode, ; Butynski & Koster, ]. Each of these methods has some disadvantages and may be unsuitable for certain populations or in particular habitats [see Baker et al, for a summary of disadvantages]. With distance sampling, for example, researchers may detect primates more often aurally instead of visually [Defler & Pintor, ], which precludes reliable distance measurements.…”

“…With distance sampling, for example, researchers may detect primates more often aurally instead of visually [Defler & Pintor, ], which precludes reliable distance measurements. Where neither method is feasible, investigators have evaluated the viability of alternative approaches such as site‐occupancy modeling [Baker et al, ; Guillera‐Arroita et al, ; Keane et al, ].…”

Integrating occurrence and detectability patterns based on interview data: a case study for threatened mammals in Equatorial Guinea

“…As a consequence of rapid human population growth and agriculture development, most large mammal species are threatened globally by overhunting and habitat fragmentation, leading to a loss of biodiversity and species extinctions, especially in Africa and south-east Asia 3 4 . Potential factors of occupancy can be modelled as a function of covariate information 5 , such as landscape characteristics or human densities 6 7 , enabling researchers to focus on different aspects of conservation and at different scales, ranging from global 8 or regional 6 to local 9 10 11 .…”