No abstract

With the declines in abundance and changing distribution of white-nose syndrome–affected bat species, increased reliance on acoustic monitoring is now the new “normal.” As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. We assessed rates of disagreement between the three U.S. Fish and Wildlife Service–approved acoustic identification software programs (Kaleidoscope Pro 4.2.0, Echoclass 3.1, and Bat Call Identification 2.7d) and manual visual identification using acoustic data collected during summers from 2003 to 2017 at Fort Drum, New York. We assessed the percentage of agreement between programs through pairwise comparisons on a total nightly count level, individual file level (e.g., individual echolocation pass call file), and grouped maximum likelihood estimate level (e.g., probability values that a species is misclassified as present when in fact it is absent) using preplanned contrasts, Akaike Information Criterion, and annual confusion matrices. Interprogram agreement on an individual file level was low, as measured by Cohen's Kappa (0.2–0.6). However, site-night level pairwise comparative analysis indicated that program agreement was higher (40–90%) using single season occupancy metrics. In comparing analytical outcomes of our different datasets (i.e., how comparable programs and visual identification are regarding the relationship between environmental conditions and bat activity), we determined high levels of congruency in the relative rankings of the model as well as the relative level of support for each individual model. This indicated that among individual software packages, when analyzing bat calls, there was consistent ecological inference beyond the file-by-file level at the scales used by managers. Depending on objectives, we believe our results can help users choose automated software and maximum likelihood estimate thresholds more appropriate for their needs and allow for better cross-comparison of studies using different automated acoustic software.

No abstract

In North America, Myotis septentrionalis (Northern Long-eared Bat) has experienced precipitous declines from white-nose syndrome. As these bats become rare and difficult to capture, additional day-roost assessments to inform management may fill gaps in our understanding, particularly in habitats and regions where such roosts have never been surveyed. Over 2 summers, we radio-tracked 16 individuals from a maternity colony on Long Island, NY, in a small forested patch surrounded by development and ocean. These bats disproportionately selected small, suppressed Robinia pseudoacacia (Black Locust) trees or snags for roosting. Generally, roosts occurred within the interior or edges of this forest patch, rather than surrounding suburbia, reinforcing the hypothesis that Northern Long-eared Bats are forest adapted. Our study shows even small tracts of forest in coastal, urban areas may have conservation value in providing day-roost and foraging habitat.