DOI: 10.5061/dryad.73n5tb34t
title: Habitat occupancy of the critically endangered Chinese pangolin (Manis pentadactyla) under human disturbance in an urban environment: Implications for conservation

description: Globally, urban expansion has led to habitat fragmentation and altered
 resource availability thus posing significant challenges for wildlife.
 This study analyzed spatial distribution, habitat use patterns, and
 anthropogenic impacts on habitat occupancy of the Critically Endangered
 Chinese pangolin (Manis pentadactyla) in the urban landscape of Dharan
 Sub-metropolitan City, Nepal. Using a single-season occupancy modelling
 approach, we investigated the factors influencing the detection
 probability and habitat occupancy of Chinese pangolins in 134 grids of
 each 600 m × 600 m. Our study identified the role of termite mounds in
 influencing detection probability, emphasizing the species'
 myrmecophilous behavior. Additionally, the Human Disturbance Index (HDI)
 emerged as a significant factor negatively affecting habitat occupancy of
 Chinese pangolins. We observed a medium level of anthropogenic
 disturbances in the grids where pangolin presence was detected. The
 findings emphasize the need for targeted conservation efforts, considering
 the fine-scale ecological and anthropogenic factors impacting Chinese
 pangolins in urban and peri-urban areas. The results underscore the
 urgency of implementing effective conservation measures to ensure the
 long-term survival of Critically Endangered Chinese pangolins in urban
 environments, not only in Dharan but also in similar lowlands areas and
 the Churia range of Nepal.
description: Field surveys in Dharan Sub-metropolitan City dividing the area
 into grids of each 600m * 600m. A subset of grids (n-152) were randomly
 selected and surveyed using the line transect of 600m length. Within every
 600 m of each transect, Chinese pangolin detection/non-detection data
 along with field-based covariates (described below) were collected in
 every 100 m segment. For each 100 m alternate segment within 600 m
 transects, we gathered quantified data on environmental variables and
 threats, including vegetation destruction (VD), forest fires (F),
 livestock grazing and related signs (L), human presence, foot and
 vehicular trails (H), and evidence of pangolin killing (K).
 We utilized the Unmark package (Kellner et al., 2023) in R
 software to conduct a single-season occupancy hierarchical
 model. 
description: # Habitat Occupancy of the Critically Endangered Chinese Pangolin (Manis
 pentadactyla) under Human Disturbance in an Urban Environment:
 Implications for Conservation
 [https://doi.org/10.5061/dryad.73n5tb34t](https://doi.org/10.5061/dryad.73n5tb34t) ## Description of the data and file structure This *.csv data file contains the field data collected during the Chinese pangolin surveys in the selected 152 study grids. It contains 14 columns and 153 rows. * On each grid, there were six replicates (Replicate 1 - Replicate 6). The values in these columns indicate pangolin sign presence as '1' and absence as '0'.  - Distance to the nearest water body was calculated as the distance from the centroid of the study grid to the nearest water sources using Euclidean distance tool in ArcGIS 10.5. All the distances were measured in meter.  - The terrain Ruggedness Index (TRI) was calculated from SRTM-DEM data. - NDVI was derived from 30 m resolution Landsat 8 imagery captured during November 2020. - Habitat type was categorized based on the habitat types including dominant *Shorea robusta* forests (SF), mixed forests (MF), riverine forests (RF), human settlement areas (HS), and agricultural land (AG). - Habitat structure were categorized as Terai (T) and Churia/Siwalik (C) based on the area where the grids fell.  - Human Disturbance Index was calculated as HDI = (VD×0.2) + (F×0.2) + (L×0.2) + (H×0.2) + (K×0.2), where, VD= vegetation destruction; F = Forest fire; L = livestock grazing and related indicators; H= human presence, foot and vehicle trails; and K= signs of pangolin poaching. The HDI values from six replicates were then averaged for each study grid. - Termite mounds indicate the total number of termite mounds within each grid.  ## Sharing/Access information Data was derived from the following sources: * Field surveys and remote sensing data ## Code/Software We utilized the Unmark package (version 1.4.1; Kellner et al., 2023) in R software v.4.4.1 (R Core Team, 2023).