254 J. Mohd‐Azlan et al.
FIG. 1 Locations of the 31 study areas in Sarawak covering both protected and unprotected areas. (1) Tanjung Datu National Park, (2) Samunsam Wildlife Sanctuary, (3) Gunung Pueh National Park, (4) Gunung Gading National Park, (5) Kubah National Park, (6) Kuching Wetland National Park, (7) Santubong National Park, (8) Bako National Park, (9) Sama Jaya Nature Reserve, (10) Dered Krian National Park, (11) Bungoh Range National Park, (12) Gunung Penrissen, (13) Ulu Sebuyau National Park, (14)Gunung Lesung National Park, (15)Maludam National Park, (16) Batang Ai National Park, (17) Lanjak EntimauWildlife Sanctuary, (18) Ulu Kapit ForestMangement Unit, (19) Pelagus National Park, (20)Hose Mountain, (21) Ulu Baleh, (22)Baleh National Park, (23) Similajau National Park, (24) SungaiMeluang National Park, (25)Oil Palm Plantation matrix, (26) Loagan Bunut National Park, (27)LambirHills National Park, (28) GunungMulu National Park, (29)Ulu Trusan,(30)Pulong Tau National Park, (31)Baram.
Native peoples still live and hunt in Sarawak as they have for millennia, with the whole community of a village occupying a single longhouse. We assumed the intensity of anthropo- genic activities would be greatest near a longhouse and thus measured the distance from a camera trap to the nearest longhouse as an indicator of the intensity of anthropogenic disturbance that could influence species distributions. Occur- rence probabilities were estimated using the Dorazio–Royle community model (Kéry & Royle, 2015;Huang et al., 2020). This hierarchical model assesses responses to ecological and anthropogenic factors based on the suite of detection histories across the species community (Brodie et al., 2015b; Kéry&Royle, 2015;Huang et al., 2020). It can overcome errors stemming from unequal sampling efforts and produce reli- able and precise results that accommodate imperfect detec- tions (Dorazio & Rodriguez, 2012; Taylor-Rodriguez et al., 2017). The model was therefore suitable for investigating a community of species that differed in their probabilities of occurrence and
detection.Wedivided camera-trap data into 7-day sampling occasions (N= 277; Bisi et al., 2019). The re- sponses of each species to the covariates were determined through mean and variance hyperparameters. We treated the original detection histories of species k at site i during occasion j (yijk) as Bernoulli random variables:
Logit(Cik) =Ck +Bl(Ck)×elevationi +Bl(C2k) ×longhousei +Bl(C3k)×roadi +Bl(C4k)×riveri
where B denotes estimated coefficients and l(Ψk) are the logit occupancies of species k. We ran seven chains with 100,000 iterations for the
Dorazio–Royle community model after a burn-in of 5,000. We generated 89% credible intervals as these have been suggested to be more stable than 95% credible intervals when sample sizes are ,10,000 (Huang et al., 2020). We predicted species occurrence as a function of covariates when there was a significant relationship (P,0.05) be- tween them. We then applied the estimated linear model parameters with identical scaling to calculate predictions, using three chains with 22,000 iterations after a burn-in of 2,000.We plotted the 6,000 posterior summaries of the pre- dictions for each species into a single array against the ori- ginal (i.e. unscaled) values of the covariate.
Analysis of species distributions 2
We assessed species distribution using occurrence coordi- nates (presence data only) of felids, which were pooled and overlain with GIS layers of habitat type to assess suitable areas for each felid species. We obtained the GIS layer for terrestrial ecoregions from The Nature Conservancy (TNC, 2020) and defined five habitat types: (1) lowland forest, (2) lower montane forest, (3) peat swamp forest, (4) mangrove forest and (5) tropical heath forest. We did not assess oil palm plantations as potential parts of species ranges. The GIS layers were categorized and clipped with the Sarawak map to a cell size of c. 1 km2 (Jennings et al.,
Oryx, 2023, 57(2), 252–261 © The Author(s), 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605321001484
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