Data from: Acoustic surveillance of bats along the Green and Colorado Rivers
Data files
Mar 29, 2024 version files 36.11 MB
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Green.Colorado_Bats.csv
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KPRO-output-11.15.22.csv
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README.md
Abstract
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
README: Data from: Acoustic surveillance of bats along the Green and Colorado Rivers
https://doi.org/10.5061/dryad.cfxpnvxcw
Acoustic data were collected 63 consecutive nights during a survey of the Green and Colorado Rivers (1,000-mile section of river). Data were collected using a Wildlife Acoustics SM4BAT FS Full-Spectrum Ultrasonic Recorder™ with SMM-U2 microphones (Wildlife Acoustics, Maynard, MA, USA). 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).
Description of the data and file structure
Data files are output files from Sonobat and Kaleidoscope. An R file to compare the two outputs is also included.
Data are divided into 3 files as detailed below:
- File: DD_Comparing_outputs_workflow.R
KPRO-output-11.15.22.csv - Kaleidoscope Pro output file
Column headings from Kaleidoscope Pro [Descriptions from user guide]
- INDIR - Absolute path of the input directory
- OUTDIR - Absolutely path of the output directory
- FOLDER - directory path from the input directory to the file containing the detected signal
- INFILE - Filename of the file containing the detected signal
- CHANNEL - Channel number (0 = left, 1 = right) containing the detected signal
- OFFSET - Offset into the file in seconds to the start of the detected signal
- DURATION - Duration of the detected signal in seconds
- OUTFILES - Name of the output file
- OUTFILE ZC - Name of the output file (Zero-Crossing)
- DATE - Datestamp of the recording if available
- TIME - Timestamp of the recording if available
- HOUR - Hour (from time) of recording if available
- DATE-12 - Datestamp of the recording if available less 12 hours (for nightly folders)
- TIME-12 - Timestamp of the recording if available less 12 hours (for nightly folders)
- HOUR-12 - Hour (from time) of the recording if available less 12 hours (for nightly folders)
AUTO ID - Automatic classification result
Species codes
- NoID - No species identification
- ANTPAL - Antrozous pallidus
- CORTOW - Corynorhinus townsendii
- EPTFUS - Eptesicus fuscus
- EUDMAC - Euderma maculatum
- EUMPER - Eumops perotis
- LASBLO - Lasiurus blossevillii
- LASCIN - Lasiurus cinereus
- LASNOC - Lasionycteris noctivagans
- LASXAN - Lasiurus xanthinus
- MACCAL - Macrotus californicus
- MYOCAL - Myotis californicus
- MYOCIL - Myotis ciliolabrum
- MYOEVO - Myotis evotis
- MYOLUC - Myotis lucifugus
- MYOOCC - Myotis occultus
- MYOSEP - Myotis septentrionalis
- MYOTHY - Myotis thysanodes
- MYOVEL - Myotis velifer
- MYOVOL - Myotis volans
- MYOYUM - Myotis yumanensis
- Noise - Noise file, no bat species identified
- NYCFEM - Nyctinomops femorosaccus
- NYCMAC - Nyctinomops macrotis
- PARHES - Parastrellus hesperus
- TADBRA - Tadarida brasiliensis
ID_man - Manual identification added after classification
PULSES - Number of pulses detected in the file which were identified
MATCHING - Number of pulses matching the auto classification result
MATCHING RATIO - The ratio of MATCHING over PULSES
MARGIN - Classification margin, this is an uncalibrated confidence score and should not be subject to much interpretation other than that within a given species, higher values are more confident than lower values.
ALTERNATE 1 - First alternate
ALTERNATE 2 - Second alternate, in addition to the species identification, these fields list zero or more alternate species identifications separated by semicolons based on other pulse-level classifications detected in the file ranked from highest probability to lowest probability.
N - Total number of pulses detected
Fc - Average characteristic frequency (kHz)
Sc - Average characteristic slope (Octaves per Second)
Dur - average duration (ms)
Fmax - Highest frequency signal detected in any signal frame across the detected signal
Fmin - Lowest frequency signal detected in any signal frame across the detected signal
Fmean - Mean peak frequency signal detected across the detected signal
TBC - average time between calls (ms)
Fk - Average frequency of the knee (kHz)
Tk - Average time to the knee (ms)
S1 - Average initial slope (octaves per second)
Tc - Average time to the characteristic (ms)
Qual - Average call quality (%)
FILES - The number 1, indicating one file, as a convenience for pivot tables by file count
MANUAL ID - User defined label
ORGID - Organization UUID of Managed Cloud Account who has run this batch process
USERID - Nickname or email address of Managed Cloud Account who has run this batch process
REVIEW ORGID - If Manual ID is present, this is the UUID of the organization corresponding to the Manual ID
REVIEW USERID - If Manual ID is present, this is the nickname or email address of the User who created the Manual ID
INPATHMD5 - Unique identification used internally by Kaleidoscope Pro corresponding to the input file
OUTPATHMD5FS - Unique identification used internally by Kaleidoscope Pro corresponding to a full-spectrum output file
OUTPATHMD5ZC - Unique identification used internally by Kaleidoscope Pro corresponding to a Zero-Crossing output file
Green.Colorado_Bats.csv - Sonobat output file
Column headings from Sonobat [Descriptions from user guide] with some post processing additions
- Path - directory path from the input directory to the file containing the detected signal
- Filename - file name of call sequence
- Bat_day - Post processing addition, this converts date_time to a bat day where it is sunset to sunrise
- Latitude - Post processing addition, location of detector
- Longitude - Post processing addition, location of detector
- HiF - high frequency call (0 = no, 1 = yes)
- LoF - low frequency call (0 = no, 1 = yes)
SppAccp - Species identification accepted based on Prob, #Maj and #Accp
Species Codes
- Anpa - Antrozous pallidus
- Coto - Corynorhinus townsendii
- Epfu - Eptesicus fuscus
- Euma - Euderma maculatum
- Eupe - Eumops perotis
- Idph - Idionycteris phylotis
- Labl - Lasiurus blossevillii
- Laci - Lasiurus cinereus
- Lano - Lasionycteris noctivagans
- Myca - Myotis californicus
- Myci - Myotis ciliolabrum
- Myev - Myotis evotis
- Mylu - Myotis lucifugus
- Myth - Myotis thysanodes
- Myvo - Myotis volans
- Myyu - Myotis yumanensis
- Nysp. - Nyctinomops species
- NA - No species ID
- Pahe - Parastrellus hesperus
- Tabr - Tadarida brasiliensis
Prob - probability of pulses attributed to SppAccp
#Maj - number of pulses that align with species identification identified in SppAccp
#Accp - number of pulses accepted for species identification
~Spp - suggested species classification if Prob, # Maj, #Accp are below threshold
~Prob- probability of pulses attributed to ~Spp
Fc mean - Average characteristic frequency (kHz)
Fc StdDev - Average characteristic frequency (kHz) standard deviation
Dur mean - average duration (ms)
Dur StdDev - average duration (ms) standard deviation
calls/sec - number of calls per second, inf = insufficient data
mean HiFreq - mean high frequency (kHz)
mean LoFreq - mean low frequency (kHz)
mean UpprSlp - mean upper slope
mean LwrSlp - mean lower slope
mean TotalSlp - mean total slope
Mean PrecedingIntvl - mean preceding interval
Species names are provided in the Kaleidoscope output and matched with a species acronym. Species codes in Sonobat are a four letter acronym. Species names can be found in Table 1 of the manuscript.
Kaleidoscope output has less missing species identifications than Sonobat, however, Sonobat is more conservative with species identifications.
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.