Figure Legends
FIgure 1: Sampling schedule and illustrations of bat sampling
methods. Bat point counts were compared simultaneously against
automated ultrasound recording and mist-netting in three oil palm
plantation sites (Plots BP1, BP2, and BP3) for nine nights. Drawings by
JABU studio.
Figure 2: Identification workflow of bat taxa sampled in oil
palm plantations in Sumatra (Indonesia) with bat point counts, as well
as traditional mist-netting and ultrasound recording methods. Bat point
counts were used for a quarter of the sampling duration of the other
methods. Call interval, start and end frequency were also used for the
identification but are not shown here. Representative near-infrared
photographs are shown; they belong to sequences of multiple pictures.
Putative identification pathways are shown with a lighter gray tone.
Asterisks denote near-infrared imagery that was not strictly needed for
identification but that was used for identity confirmation. For
mist-netting, numbers denote captures, and for bat point counts and
ultrasound recordings, detections.
Figure 3: Rarefaction and extrapolation sampling curves for bat
point counts, compared to established bat sampling methods. Shaded areas
show 83% confidence intervals; differences in species richness are
statistically significant when they do not overlap
(Krzywinski & Altman,
2013). Extrapolated values are only shown up to double the reference
sampling size to avoid large prediction errors.
Figure 4 : Detection ranges and sampling locations for
bat point counts, mist nets, and automated ultrasound recorders. The
sampling rig and ultrasound recorder were set up at the sampling center.
The thermal scope’s field of view was scanning the thermal detection
area. The curved ranges for ultrasound were drawn manually between the
measured range directions. The ultrasound detection ranges are scaled to
a maximum of 50 m as they are only representative of our 40 kHz
ultrasound emitter otherwise (SPL 48 dB @ 30 cm).