678 V. Aditya et al.
the species’ status, distribution and habitat preferences across the Indian subcontinent (but see Srinivasulu et al., 2004; Mahmood et al., 2012, 2014; Trageser et al., 2017). This paucity of information potentially hinders the conser- vation of the species. The Indian pangolin occurs across a range of habitat
types, from natural forests to timber plantations, and over 0–2,000 m altitude (Perera et al., 2017; Karawita et al., 2018). The species is secretive, cryptic and nocturnal (Karawita et al., 2018). Previous studies have shown that standard ecological monitoring techniques are not effective for surveying pangolins and that there is a need for second- ary sources of information on presence (Newton et al., 2008; Nash et al., 2016; Karawita et al., 2018). Determining pres- ence using a combination of field surveys and local com- munity knowledge is critical to prioritize habitats for the species’ conservation (Yoccoz et al., 2001; Newton et al., 2008;O’Brien, 2008). The northern Eastern Ghats landscape of Andhra
Pradesh and Odisha in southern India has vast stretches of contiguous forests (Aditya & Ganesh, 2019). Although there have been few biodiversity studies in this landscape and only 3.53% of the total area is protected (Cardillo et al., 2006; Aditya & Ganesh, 2019), it supports several rare, endemic and threatened species including the Jeypore ground gecko Cyrtodactylus jeyporensis (Agarwal et al., 2012), yellow-throated bulbul Pycnonotus xantholaemus (Sreekar & Srinivasulu, 2010), forest owlet Heteroglaux blewetti (Kumar et al., 2010), leopard cat Prionailurus benga- lensis, rusty-spotted cat Prionailurus rubiginosus, and stripe- necked mongoose Herpestes vitticollis (Aditya & Ganesh, 2016, 2017), highlighting the conservation significance of this landscape. Although pangolins are known to be hunted in this landscape (Mohapatra et al., 2015; Aditya, 2019), sys- tematic information on their occurrence in this region is lacking (Srinivasulu et al., 2004). To address this, we used a combination of camera traps and local reports to assess the occurrence of the Indian pangolin in the northern Eastern Ghats. We also highlight the main patterns and drivers of hunting in this region.
Study area
The 16,948 km2 northern Eastern Ghats of Andhra Pradesh, India, are a series of discontinuous hills oriented in a north– south direction; they include one protected area, the 1,012km2 Papikonda National Park. There are several Reserve Forests, and amosaic of other non-forest land uses surrounding the Park, including plantations and farmland (Fig. 1). The topog- raphy ismountainous,with altitudes of 20–1,
680m.Mean an- nual precipitation is 1,309 mm (Goswami et al., 2018). The dominant forest type is southern tropical mixed moist de- ciduous, with some semi-evergreen patches (Champion &
Seth, 1968). The flora is dominated by large trees such as Anogeissus latifolia, Terminalia tomentosa, Terminalia ar- juna and Tectona grandis. The northern Eastern Ghats is an important forested cor-
ridor between theWestern Ghats and north-east Indian bio- diversity hotspots (Goswami et al., 2018). Various Indigenous communities inhabit the landscape, mainly the plains dwell- ing Koyas, who are cultivators, and the hill dwelling Konda Reddis, who subsist on non-timber forest produce and shift- ing cultivation. Other communities include the Parajas, Bagathas and Valmikis, all of whom depend on the forests for their livelihoods. The study area consists of various Reserve Forests around Papikonda National Park in East Godavari and Visakhapatnam districts, encompassing dry deciduous, moist deciduous and semi-evergreen forests, plantations, some agricultural fields and 30 villages (Fig. 1).
Methods
Camera-trap surveys We procured LANDSAT 8 satellite imagery from Google Earth Engine (Gorelick et al., 2017). The image was used to generate a classified habitat map based on pre-existing maps (Buckland et al., 2001) and ground-based training points, through supervised classifica- tion (Jha et al., 2000; Vaidyanathan et al., 2010), using the classification and regression tree classifier in Google Earth Engine. We divided the study area into 512, 5 × 5 km grid cells and used stratified random sampling to select 30 cells (a total of 750 km2) from dry and moist deciduous forest patches. We also identified villages within the 30 selected grid cells for conducting interviews. The cells are at altitudes of 200–1,000 m. We used a total of 16 motion-activated Trinetra (REAP, Bangalore, India), Bushnell Aggressor (Bushnell, Kansas City, USA) and ScoutGuard Attack (ScoutGuard, Molendinar, Australia) digital camera traps with a passive infrared sensor, with the sensitivity set to high, at a height of c. 0.5 m above ground, during December 2017–April 2018. Camera traps were placed with- in each cell based on local information regarding areas with a high likelihood of pangolin occurrence, such as pangolin burrows, hill slopes, streams and near salt licks. Camera traps were set for a minimum of 7 days at each location and then moved to another cell. Indirect signs of pangolins, such as scrape marks on termite mounds, were noted but were not considered a definitive indication of presence. The total survey effort was 840 trap-days (20,160 trap- hours).
Interviews We identified and mapped all villages in the study area using topographical sheets from the Survey of India, and obtained data on the village populations, tribal groups (as identified by the Census of India, 2001) and
Oryx, 2021, 55(5), 677–683 © The Author(s), 2020. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605319001303
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