Hiding in the dark: Local ecological knowledge about slow loris in Sarawak sheds light on relationships between human populations and wild animals

Knowledge, Beliefs, and Experience Regarding Slow Lorises in Southern Thailand: Coexistence in a Developed Landscape

Natural landscapes are being converted for agriculture and other human uses across Asia and this development presents potential threats for specialist species of primates, like the Endangered slow lorises of Thailand (Nycticebus bengalensis and N. coucang). It is crucial to understand the interface between humans and slow lorises in order to conserve these primates. Local ecological knowledge provides valuable information about these cryptic nocturnal species. We conducted 36 semi-structured interviews in Khao Lak, in southern Thailand, asking (1) where slow lorises were seen, (2) what they were doing, (3) how often people see slow lorises, and (4) what people knew about them. We converted the interviews to free lists and determined the importance of key words. Our results show that the informants saw lorises frequently in six general locations: forests/trees (58%), electric wires (47%), towns/villages (36%), plantations (33%), homesteads (28%), and roads (17%). The most prominent places were forests/trees, wires, and plantations. Eleven key concepts defined local beliefs, with the most prominent being that lorises are awake at night (69%), eat fruit (42%), are not aggressive (25%), are bad omens (25%), and there used to be more of them (25%). Due to a minimal presence of persecution or exploitation of slow lorises by humans in the study area and general tolerance in the face of competition for the same resources and spaces, we suggest that, despite extensive persecution for the illegal photo prop trade in nearby Phuket, the people of Khao Lak seem to live in a state of passive coexistence with slow lorises. However, we did find some evidence that the pet and photo prop trade are still present in the area. It is crucial that coexistence be struck within the context of deforestation and urbanization so that conservation initiatives can take place within the community to further improve the lives of humans and the status of lorises.

Assessment of survey protocol for estimates of abundance for elusive nocturnal primates

Abstract ContextEstimates of a species abundance and habitat preferences provide vital information on their status and the appropriate conservation management. For nocturnal arboreal primates, obtaining reliable estimates of these parameters is particularly challenging because of their cryptic behaviour, often resulting in a small number of detections. Although techniques are available for assessing the abundance of species with a low probability of detection, most require strict assumptions that are difficult to meet. AimsHere, we aimed to explore the possibility of improving nocturnal-primate abundance estimates when detection probability is low and to determine the minimal effort required to calculate reasonable estimates of their overall abundance and the effect of habitat type on abundance estimates. MethodsWe used count data obtained from spotlighting along line transects for estimating density of Bengal slow loris (Nycticebus bengalensis) in north-eastern Thailand with N-mixture hierarchical modelling, to run simulations of varying survey parameters and asses the effort needed to produce robust estimates based on the relative bias from each simulation. Key resultsN-mixture analysis showed that the data obtained from our study were still biased (9%), with a lambda of 1.79 lorises, detection probability of 0.11, 50 survey sites and a maximum of 12 sample occasions. The simulation results found that increasing the number of sample occasions to 14 per transect would produce an acceptable bias (<5%). ConclusionsWe recommend that future studies on nocturnal arboreal species should use preliminary surveys to gauge the specific lambda and probability of detection so as to establish the effort needed to produce reasonable estimates of abundance. ImplicationsOur study showed that count data obtained from spotlighting can be used to produce robust abundance estimates of nocturnal arboreal species. Unlike simple encounter rate, this method incorporates detection probability and habitat preferences, yet does not require additional trained field technicians.