Data from: Acoustic surveillance of bats along the Green and Colorado Rivers
Description
Aim: Emerging research shows how bioindicators, specifically bats, can serve as a means for monitoring conservation and management of riparian corridors for multiple taxonomic groups. To track changes in composition or abundance of bioindicator species, researchers must attain a baseline in species presence and relative activity. We examined the spatial and temporal patterns of bat community composition and activity along a 1,000-mile river corridor to determine species diversity trends by latitude and habitat.
Location: Colorado River Basin
Methods: Here we describe the results from an acoustic bat survey conducted opportunistically on the 2019 Sesquicentennial Colorado River Exploring Expedition. This broad, 1,000-mile survey provides a baseline for species distributions over a large geographic range.
Results: In total, we collected 63 nights of acoustic data over 70-days and recorded over 59,000 files equating to 45,363 call files (≥2 pulses). 18,490 (41% of call files) were identified to species (n = 19 bat species). We applied non-metric multidimensional scaling to characterize spatiotemporal patterns of activity between species, as well as compared bat activity among river features and local environmental conditions (i.e., temperature and time since sunset) using an information theoretic approach.
Conclusion: Species composition varied by physiographic region and adjacent river habitat, thus providing a quantifiable measure of determining habitat quality along this major river system and providing baseline information for using bats as bioindicators of habitat quality
Notes
Methods
Bat surveys were spatially independent (between 7 and 30 river miles between camps) and conducted using a Wildlife Acoustics SM4BAT FS Full-Spectrum Ultrasonic Recorder™ with SMM-U2 microphones (Wildlife Acoustics, Maynard, MA, USA). According to the manufacturer's guide (Wildlife Acoustics 2019), the SMM-U2 can cover up to 8x the amount of airspace as the SMM-U1 (maximum detection range of older units [SM3Bat + SMM-U1] estimated at ~40m; (Cortes & Gillam 2020).
We identified species based on echolocation calls and call sequences using two methods: semi-automated identification software paired with manually vetting. Acoustic files were run through both Kaleidoscope Pro 5.1.9 Analysis Software (Bats of North America classifier 5.1; Wildlife Acoustics, Maynard, MA, USA) and SonoBat version 4.4.5 (North America, Great Basin North, Great Basin, and Southwest regional classifiers; DNDesign, Arcata, California, USA) to compare and vet bat species identification. We then compared the two outputs using the comparedf function in the 'compare' package (Murrell 2022) in Program R and manually vetted all calls that were identified as two different species in Sonobat and Kaleidoscope Pro (1,948 calls) and 10% of calls that were identified in one software but left blank in the other (21,375 calls = 2,138 vetted calls). We also cross-checked species identification with known records of each species distribution and state observations.
Files
Files
(6.0 kB)
Name | Size | Download all |
---|---|---|
md5:d0b6bbee8cddb8a88f586d75788c2265
|
6.0 kB | Download |
Additional details
Related works
- Is source of
- 10.5061/dryad.cfxpnvxcw (DOI)