Estimating the population size of the Sanje mangabey (<i>Cercocebus sanjei</i>) using acoustic distance sampling

Paddock, Christina; Bruford, Michael William; McCabe, Gráinne

doi:10.1002/ajp.23083

Cited by 10 publications

(17 citation statements)

References 36 publications

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“…Line distance sampling is frequently used for monitoring ungulates in East Africa [19,20], and it is also a common tool for estimating the size of primate populations [21][22][23][24][25][26][27]. While this method explicitly accounts for imperfect detectability [28], line distance surveys are occasionally carried out along existing path or road networks due to safety concerns, restrictions on off-road driving in protected areas, or logistical or budgetary constraints associated with walking transects [29].…”

Section: Introductionmentioning

confidence: 99%

Road-based line distance surveys overestimate densities of olive baboons

et al. 2022

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Estimating population density and population dynamics is essential for understanding primate ecology and relies on robust methods. While distance sampling theory provides a robust framework for estimating animal abundance, implementing a constrained, non-systematic transect design could bias density estimates. Here, we assessed potential bias associated with line distance sampling surveys along roads based on a case study with olive baboons (Papio anubis) in Lake Manyara National Park (Tanzania). This was achieved by comparing density estimates of olive baboons derived from road transect surveys with density estimates derived from estimating the maximum number of social groups (via sleeping site counts) and multiplying this metric with the estimated average size of social groups. From 2011 to 2019, we counted olive baboons along road transects, estimated survey-specific densities in a distance sampling framework, and assessed temporal population trends. Based on the fitted half-normal detection function, the mean density was 132.5 baboons km-2 (95% CI: 110.4–159.2), however, detection models did not fit well due to heaping of sightings on and near the transects. Density estimates were associated with relatively wide confidence intervals that were mostly caused by encounter rate variance. Based on a generalized additive model, baboon densities were greater during the rainy seasons compared to the dry seasons but did not show marked annual trends. Compared to estimates derived from the alternative method (sleeping site survey), distance sampling along road transects overestimated the abundance of baboons more than threefold. Possibly, this overestimation was caused by the preferred use of roads by baboons. While being a frequently used technique (due to its relative ease of implementation compared to spatially randomized survey techniques), inferring population density of baboons (and possibly other species) based on road transects should be treated with caution. Beyond these methodological concerns and considering only the most conservative estimates, baboon densities in LMNP are among the highest across their geographic distribution range.

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Section: Introductionmentioning

confidence: 99%

Road-based line distance surveys overestimate densities of olive baboons

et al. 2022

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“…Estimates included in the analyses were truncated at 1 km as it was unlikely calls were accurately detectable over this distance. Data collection was carried out in the morning, between 07:00 and 09:00, when the Sanje mangabey is known to call at the highest frequencies (Ehardt et al, 2005), and every survey was conducted once (further details in Paddock et al, 2020).…”

Section: Study Areamentioning

confidence: 99%

“…We reanalyzed data from Paddock et al (2020) with the aim of building density estimation models with account of anthropogenic and environmental covariates. We used the package "Distance" (Miller et al, 2019) in R (R Core Team, 2018) to model the probability of detection and estimate Sanje mangabey groups' density from distance data.…”

Section: Group Density Estimatesmentioning

confidence: 99%

Calibrating occupancy to density estimations to assess abundance and vulnerability of a threatened primate in Tanzania

Greco

Paddock

McCabe³

et al. 2023

Ecosphere

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The current decline of mammals worldwide makes quantitative population assessments crucial, especially for range‐restricted and threatened species. However, robust abundance estimations are challenging for elusive or otherwise difficult to detect species. Alternative metrics requiring only presence/absence data, that is, occupancy, are possible but calibration with independent density estimates should be foreseen, although rarely performed. Here, we calibrated density estimates from acoustic surveys to occupancy estimates from camera‐trapping detections to derive the abundance of the endangered Sanje mangabey (Cercocebus sanjei) across its entire range in the Udzungwa Mountains of Tanzania. We found marked occupancy–density relationships for the two forest blocks where this primate occurs and used them to derive spatially explicit density estimates. Occupancy increased in montane forest zones at mid‐elevation but decreased slightly with proximity to forest borders. We predicted an average density (±SE) of 0.26 ± 0.05 groups/km2 in the national park and 0.24 ± 0.06 in the nature reserve. Accordingly, and given the much larger area of the reserve, the average predicted individual abundance was 1555 ± 325 and 2471 ± 571 in the national park and nature reserve, respectively. We found higher density and abundance in the nature reserve compared with previous studies. Given the past disturbance and poorer protection in the nature reserve relative to the national park, our results instill optimism for the status of the species, although occupancy analysis highlighted the potential vulnerability of this primate to human disturbance. Our approach appears valuable for spatially explicit density estimations of elusive species, and provides robust assessments of vulnerability and identification of priority areas for conservation of threatened populations.

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“…In recent years methods of survey of primate populations have been undergoing reassessment with the objective of improving efficiency and statistical reliability (e.g., Brockelman, 2019; Buckland et al, 2010). The introduction of Distance methods (Thomas et al, 2010) to acoustic sampling of primates is a welcome improvement to account for loss of detectability with distance (Dacier et al, 2011; Gilhooly et al, 2015; Paddock et al, 2019; Phoonjampa et al, 2011; Vu et al, 2018a). Using the point transect method within the Distance software program, it is not assumed that all groups are detected within a “listening area” selected beforehand; a detection function [g(y)] is determined from the distribution of distances from the central sample point.…”

Section: Introductionmentioning

confidence: 99%

Comparison of point transect distance and traditional acoustic point‐count sampling of hoolock gibbons in Htamanthi Wildlife Sanctuary, Myanmar

Brockelman

Tun

et al. 2020

American J Primatol

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Effective conservation demands more accurate and reliable methods of survey and monitoring of populations. Surveys of gibbon populations have relied mostly on mapping of groups in "listening areas" using acoustical point-count data. Traditional methods of estimating density in have usually used counts of gibbon groups within fixed-radius areas or areas bounded by terrain barriers to sound transmission, and have not accounted for possible decline in detectability with distance. In this study we sampled the eastern hoolock gibbon (Hoolock leucogenys) population in Htamanthi Wildlife Sanctuary (WS), Myanmar, using two methods: the traditional pointcount method with fixed-radius listening areas, and a newer method using pointtransect Distance analysis from a sample point established in the center of each listening point array. The basic data were obtained by triangulating on singing groups from four LPs for 4 days, in 10 randomly selected sample areas within the sanctuary. The point transect method gave an average density of 3.13 groups km −2 , higher than the estimates of group density within fixed-radius areas without correction for detectability. A new method of analysis of singing probability per day (p[1]) gave an estimate of 0.547. Htamanthi WS is an important conservation area containing an estimated 7000 (95% confidence interval: 5000-10,000) hoolock groups. Surveys at Htamanthi WS and locations in the Hukaung Valley suggest that the extensive evergreen forests in northern Myanmar have the capacity to support 2-4 (average about 3) groups of hoolock gibbons per km 2 , but most forests in its range have yet to be surveyed.

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Estimating the population size of the Sanje mangabey (Cercocebus sanjei) using acoustic distance sampling

Cited by 10 publications

References 36 publications

Road-based line distance surveys overestimate densities of olive baboons

Road-based line distance surveys overestimate densities of olive baboons

Calibrating occupancy to density estimations to assess abundance and vulnerability of a threatened primate in Tanzania

Comparison of point transect distance and traditional acoustic point‐count sampling of hoolock gibbons in Htamanthi Wildlife Sanctuary, Myanmar

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