Assessment of landscape‐scale distribution of sympatric great apes in African rainforests: Concurrent use of nest and camera‐trap surveys

Abstract

Information on the distribution and abundance of sympatric great apes (Pan troglodytes troglodytes and Gorilla gorilla gorilla) are important for effective conservation and management. Although much research has been done to improve the precision of nest-surveys, trade-offs between data-reliability and research-efficiency have not been solved. In this study, we used different approaches to assess the landscape-scale distribution patterns of great apes. We conducted a conventional nest survey and a camera-trap survey concurrently, and checked the consistency of the estimates. We divided the study area (ca. 500 km²), containing various types of vegetation and topography, into thirty 16-km² grids (4 km × 4 km) and performed both methods along 2-km transects centered in each grid. We determined the nest creator species according to the definitions by Tutin & Fernandez [Tutin & Fernandez, 1984, Am J Primatol 6:313-336] and estimated nest-site densities of each species by using the conventional distance-sampling approach. We calculated the mean capture rate of 3 camera traps left for 3 months at each grid as the abundance index. Our analyses showed that both methods provided roughly consistent results for the distribution patterns of the species; chimpanzee groups (parties) were more abundant in the montane forest, and gorilla groups were relatively homogeneously distributed across vegetation types. The line-transect survey also showed that the number of nests per nest site did not vary among vegetation types for either species. These spatial patterns seemed to reflect the ecological and sociological features of each species. Although the consistent results may be largely dependent on site-specific conditions (e.g., high density of each species, distinct distribution pattern between the two species), conventional nest-surveys and a subsequent check of their consistency with independent estimates may be a reasonable approach to obtain certain information on the species distribution patterns. Further analytical improvement is necessary for camera-traps to be considered a stand-alone method.

Towards Automated Visual Monitoring of Individual Gorillas in the Wild

“…It has great potential to provide unique and valuable data on the impacts of conservation threats [71], sociodemographics [23], behavioural plasticity [32,55,3], disease mapping and screening [9], species interactions [23], habitat use [53,24], feeding ecology [24,51,59], activity patterns [32,55], and ranging patterns [48].…”

“…The long-term data on the demographics and group structure of dozens of known gorilla units from Mbeli Bai could form a unique and novel combination with spatially-explicit capture-recapture data that, when combined, could tackle a myriad of socioecological questions (e.g. ranging patterns, habitat use, seasonal activity patterns, disease screening) as well as population estimates for the wider area, potentially at a park-wide or landscape level [35,53,23,24].…”

Etude de la Relation entre l’abondance des grands mammifères frugivores et celle des fruits dans le Parc National de Moukalaba-Doudou, Gabon

“…L'abondance des mammifères a été exprimée en taux moyen de capture calculé selon la formule suivante (Tobler et al, 2008 ;Nakashima, 2013b) :…”

Inventorying medium- and large-sized mammals in the African lowland rainforest using camera trapping

“…Recently, some studies have been using camera-traps for a various purpose, e.g. making a species list of large ground-dwelling mammals (Treves et al 2010); monitoring animals visiting "bai" (large forest clearings with mineral-rich soil and water) (Gessner et al 2014); estimating the relative and absolute abundance of animals such as leopards (Henschel et al 2011), or great apes and elephants (Head et al 2012, Nakashima et al 2013b; detecting rare monkeys (Coad et al 2010, Easton et al 2011 or golden cats (Aronsen 2010); monitoring die-off of large ungulates (Elkan et al 2009); and identifying seed disperser/predators (Babweteera et al 2007, Nyiramana et al 2011, Beaune et al 2012, Moupela et al 2013. Given that a lot of limitations have not been solved in conventional methods including direct sightings (e.g.…”