DOI: 10.5061/dryad.zs7h44jbn
title: Number of terrestrial leeches with human-bait method and environmental variables in peninsular Malaysia

description: This is the data on the number of terrestrial leeches (brown Haemadipsa
 sp.) collected and environmental variables at the sampling site in Endau
 Rompin National Park in Malaysia. We investigated relative
 abundance of terrestrial leeches repeatedly at 99 sampling points in the
 tourism area of ERNP from February 2019 to September 2020. We
 counted the number of leeches at each sampling point based on the
 human-bait method, wherein the researcher is considered as the bait
 (Schnell et al. 2015, Fahmy et al. 2019). To activate the leeches before
 sampling, the leaf litter was blown upon and stirred with a twig in a
 1.5-m radius from the sampling point. A researcher then stood at the
 sampling point and collected all the leeches attracted and attached to the
 body in a five-minute sampling session (Kendall, 2012). We collected the
 leeches in a vial and measured the diameter of the sucking cup of each
 individual as a proxy for leech size: &lt;1.5 mm = small, 1.5–3.0 mm =
 medium, and &gt;3.0 mm = large. At the start of the sampling session,
 any leeches on the researcher’s body were removed and discarded. The
 leeches collected in the vial were all released at the sampling point
 after being counted and measured. Since leeches could detect host up to
 2.0 m in our pilot survey, the relative abundance here can be regarded as
 a rough estimate of density of active leeches per 12.6 m2 (an area within
 2-m radius). The microenvironmental variables at each sampling point and
 time were measured to examine their effects on active leech relative
 abundance. These variables included air humidity, air temperature (°C),
 light intensity (lux), altitude (m), distance to the nearest river (m),
 distance to the nearest rain flow path (i.e., small valley through which
 water would flow in heavy rain) (m), percentage of bare ground (%),
 percentage of canopy openness (%), mean litter layer depth (mm), and
 topsoil moisture (%). Air humidity, air temperature, and light intensity
 were measured using a handheld Illuminance UV recorder (TR-74Ui). The
 distances to the nearest stream and river were calculated using ArcMap
 10.2.2. (ESRI Inc.). The altitude was measured using a handheld Garmin
 geographic positioning system (GPS). The percentage of canopy openness and
 bare ground were measured using hemispherical photography via smartphone
 cameras equipped with “fisheye” lenses (Bianchi et al. 2017) in the
 near-vertical skyward and downward directions, respectively. The litter
 layer depths were visually measured using a ruler. Soil moisture was
 measured directly at every sampling point using a soil moisture meter
 (Takemura Soil Moisture Meter DM 18). The percentages of bare ground,
 canopy openness, litter layer depth, and topsoil moisture, were recorded
 three times at randomly selected points around the sampling point, and the
 average value was considered for the analyses. To measure human and
 wildlife relative abundance, we installed passive infrared camera traps
 (O'Connell et al. 2011) (Ltl Acorn Ltl-6210MC, Cams Co., Ltd., Tokyo,
 Japan), which were triggered automatically by movement, at 24 on-trail
 sampling points. The camera was operated from February 2019 to September
 2020 (560 days and 8,230 trap nights). The sampling points included trails
 with a gradient of tourist-use frequency. Each camera was mounted
 approximately 30–40 cm above the ground (Luo et al. 2019) to capture a
 wide range of animals of different sizes (Mugerwa et al. 2013). The
 cameras were set up in video mode with 15 s in video length and 30 s in
 the interval between videos, which was sufficient to record the group
 activity of potential hosts (wildlife or humans). The number of
 individuals in each video was counted. To prevent double-counting
 individuals, a one-hour interval sequence was introduced between videos of
 a specific individual of the same species (Azlan & Sharma 2006).
 Each animal in the videos was identified at the species level, based on
 Francis (2008). Due to low image resolution, we could not identify smaller
 animals, such as bats and rats at the species level.