Macaca nigra
estimate the proportion of sites occupied by the species of interest (Mackenzie et al., 2002), and as such is considerably less labour intensive and less costly to implement than count-based metrics (Royle & Nichols, 2003; Joseph et al., 2006). To this end, camera traps produce data that are suited to occupancy analysis and therefore present a viable survey method, especially for elusive primates living in landscapes with difficult terrain. Here, we use an occupancy based camera-trap approach to conduct a baseline assessment for the crested black macaque Macaca nigra, a hard-to- detect and mostly terrestrial species of forest-dwelling primate endemic to the northernmost peninsula of the Indonesian island of Sulawesi. The crested black macaque exemplifies the plight of
many forest-dwelling primates. Resource extraction and land requirements for agriculture in Sulawesi have resulted in the loss of most of its lowland forest habitat (Margono et al., 2014), creating a fragmented habitat mosaic that is probably restricting gene flow between subpopulations (Evans et al., 2003). Added to this are retaliatory killings in response to foraging in crops, and hunting for bush- meat consumption, which in turn makes the species shy and secretive in large parts of its range. Numerous presence-only studies have explored the dis-
tribution and status of M. nigra (Mackinnon & Mackinnon, 1980; Sugardjito et al., 1989;Lee, 1997; Rosenbaum et al., 1998; Melfi et al., 2007;Palacios et al., 2011; Kyes et al., 2013) and have estimated the population size to be 4,000–6,000 individuals (Riley, 2010). Sharp declines of up to 80%over 40 years inM. nigra populations have indicated the serious- ness of the threats facing the species (Supriatna & Andayani, 2008). Macaca nigra is now categorized as Critically En- dangered on the IUCN Red List (Supriatna & Andayani, 2008) and is one of the top 25 most threatened primates (Schwitzer et al., 2017). Although previous work has high- lighted the vulnerability of M. nigra, the limited survey efforts yielded incomplete knowledge on distribution, status and re- sponses to anthropogenic threats at a regional scale. In this study,we use camera-trap data to (1) investigate the influence of environmental and anthropogenic factors on M. nigra occupancy across its native range (2) provide an empirical baseline of its status, using occupancy as the state variable of interest, and (3) evaluate the efficacy of our protocol to monitor primates at the landscape scale.
Study area
Macaca nigra is native to North Sulawesi province, where its range extends from the northern tip and some of the small surrounding islands (Lembeh, Manadotua and Talise) to the Onggak-Dumoga River and the south-east landscape of Bogani Nani Wartabone (Johnson et al., 2019). Within this area, we used knowledge of the habitat preferences of
M. nigra (O’Brien & Kinnaird, 1997; Rosenbaum et al., 1998; Palacios et al., 2011) and recent landcover maps (KLHK, 2015) to determine the extent of potential habitat that would be ecologically capable of supporting amacaque population and use this to define our study area (Fig. 1). These included sites characterized by forest cover and/or scrub habitats. North Sulawesi has altitudes of 0–1,995 m and has a wet season during October–May and a dry season during June–September.
Methods
Data collection: camera trapping We first divided the potential habitat into sampling units (termed sites) of 2 × 2 km (n = 796 sites). This size was cho- sen as it is close to the largest recorded M. nigra home range of 4.06 km2 (O’Brien Kinnaird, 1997), but larger than the purported average of 2.16 km2 (Riley, 2010). A sample of 115 of these sites was then selected to be surveyed using camera traps (64 Reconyx HC500, Holmen, USA; 50 Cuddeback Black Flash, DePere, USA; one Bushnell Natureview HD Live View, Overland Park, USA). This was done in two phases. Firstly, during January 2016–October 2017,wesur- veyed 67 sites. This included all 28 sites across the Tang- koko Nature Reserve, and 39 sites selected with random systematic sampling within the larger region of the southern Bogani Nani Wartabone National Park landscape (Fig. 1). Secondly, during March–July 2018, we randomly selected 48 sites from across patches of potentially suitable habitat be- tween these protected areas. Although implemented in dif- ferent years because of the number of cameras available, we conducted the actual survey phases within a relatively short period of time, minimizing the risk of violating the assump- tion that the population was closed. Because of logistical constraints, camera traps were not
uniformly deployed within each site. Rather, we deployed cameras in the part of the site most accessible, provided it was.50mfrom the site’s border. Our grid-based approach ensured sufficient spacing between camera traps. We posi- tioned cameras along wildlife trails, attaching them to tree trunks at a height of c. 50 cm, with the sensor aimed parallel to the ground facing the monitoring area. On average each camera was deployed for a minimum of 3 months. Four locations, however, produced no data as the cameras were either stolen or malfunctioned; we therefore present data collected from 111 camera traps.
Data collection: covariates
Occupancy of sites by M. nigra was expected to vary across North Sulawesi according to habitat and anthropogenic factors (Rosenbaum et al., 1998). We therefore derived a
Oryx, 2020, 54(6), 784–793 © The Author(s), 2020. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605319000851
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