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

The Sanje mangabey (Cercocebus sanjei) is endemic to the Udzungwa Mountains, Tanzania, and is classified as Endangered due to its putatively declining population size, habitat degradation and fragmentation. Previous population size estimates have ranged from 1,350 to 3,500 individuals, with the last direct survey being conducted 15 years before the present study. Previous estimates are now thought to have underestimated the population due to a limited knowledge of group and habitat size, nonsystematic approaches and the use of visual methods that are not suitable for surveying the Sanje mangabey with its semi-terrestrial and elusive behaviors. We used an acoustic survey method with observers recording the distinctive "whoop-gobble" vocalization produced by mangabeys and point transect distance sampling to model a detection function and estimate abundance. Twenty-eight surveys were conducted throughout the two forests where Sanje mangabeys are found: Mwanihana forest in the Udzungwa Mountains National Park (n = 13), and the Uzungwa Scarp Nature Reserve (n = 15). Group density was found to be significantly lower in the relatively unprotected Uzungwa Scarp forest (0.15 groups/km2 ; 95% CI: 0.08-0.27) compared to the well-protected Mwanihana forest (0.29 groups/km2 ; 95% CI: 0.19-0.43; p = .03). We estimate that there are 1,712 (95% CI: 1,141-2,567) individuals in Mwanihana and 1,455 (95% CI: 783-2,702) in the Uzungwa Scarp, resulting in a total population size of 3,167 (95% CI: 2,181-4,596) individuals. The difference in group density between sites is likely a result of the differing protection status and levels of enforcement between the forests, suggesting that protection of the Uzungwa Scarp should be increased to encourage recovery of the population, and reduce the threat of degradation and hunting. Our results contribute to the reassessment of the species' IUCN Red List status and informing management and conservation action planning.

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

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 point-count method with fixed-radius listening areas, and a newer method using point-transect 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 km2 , but most forests in its range have yet to be surveyed.

Distance sampling detection functions: 2D or not 2D?

Conventional distance sampling (CDS) methods assume that animals are uniformly distributed in the vicinity of lines or points. But when animals move in response to observers before detection, or when lines or points are not located randomly, this assumption may fail. By formulating distance sampling models as survival models, we show that using time to first detection in addition to perpendicular distance (line transect surveys) or radial distance (point transect surveys) allows estimation of detection probability, and hence density, when animal distribution in the vicinity of lines or points is not uniform and is unknown. We also show that times to detection can provide information about failure of the CDS assumption that detection probability is 1 at distance zero. We obtain a maximum likelihood estimator of line transect survey detection probability and effective strip half-width using times to detection, and we investigate its properties by simulation in situations where animals are nonuniformly distributed and their distribution is unknown. The estimator is found to perform well when detection probability at distance zero is 1. It allows unbiased estimates of density to be obtained in this case from surveys in which there has been responsive movement prior to animals coming within detectable range. When responsive movement continues within detectable range, estimates may be biased but are likely less biased than estimates from methods that assuming no responsive movement. We illustrate by estimating primate density from a line transect survey in which animals are known to avoid the transect line, and a shipboard survey of dolphins that are attracted to it.

Accounting for spatial habitat and management boundaries when estimating forest bird population distribution and density: inferences from a soap film smoother.

Birds are often obligate to specific habitats which can result in study areas with complex boundaries due to sudden changes in vegetation or other features. This can result in study areas with concave arcs or that include holes of unsuitable habitat such as lakes or agricultural fields. Spatial models used to produce species' distribution and density estimates need to respect such boundaries to make informed decisions for species conservation and management. The soap film smoother is one model for complex study regions which controls the boundary behaviour, ensuring realistic values at the edges of the region. We apply the soap film smoother to account for boundary effects and compare it with thin plate regression spline (TPRS) smooth and design-based conventional distance sampling methods to produce abundance estimates from point-transect distance sampling collected data on Hawai'i 'Akepa Loxops coccineus in the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex, Hawai'i Island, USA. The soap film smoother predicted zero or near zero densities in the northern part of the domain and two hotspots (in the southern and central parts of the domain). Along the boundary the soap film model predicted relatively high densities where 'Akepa occur in the adjacent forest and near zero elsewhere. The design-based and soap film abundance estimates were nearly identical. The width of the soap film confidence interval was 16.5% and 0.8% wider than the width of the TPRS smooth and design-based confidence intervals, respectively. The peaks in predicted densities along the boundary indicates leakage by the TPRS smooth. We provide a discussion of the statistical methods, biological findings and management implications of applying soap film smoothers to estimate forest bird population status.