Abstract
Montana’s bat populations face a wide array of conservation issues, including loss of roosting sites, elimination of prey species, collision or drowning hazards at sites where they forage, drink, and mate, and a lack of baseline information on distribution and habitat use that is available to resource managers. In recent years, concerns have focused on fatalities at wind turbine facilities and those resulting from White‐nose Syndrome (WNS). WNS has killed an estimated 5.7 to 6.7 million bats in eastern North America and 600,000 to 888,000 bats are estimated to have been killed at wind energy facilities across the United States in 2012 alone. These and other sources of mortality may be having significant impacts on bat populations because bats are long‐lived and have only one or two young per year. Given these concerns, a long term acoustic detector was installed on Big Sheep Creek in the Tendoy Mountains in southwest Montana to gather baseline information on bats. This was one of the first ultrasonic acoustic detectors installed in what grew to become a regional network of detectors deployed over multiple years to document activity patterns of bats across Montana, and portions of northern Idaho, and the western Dakotas.
The overarching objectives of this project were to gather multiple years of year‐round baseline information on: (1) bat species composition and activity levels; (2) timing of species immergence to and emergence from hibernacula for non‐ migratory bat species; (3) timing of migrations by tree roosting migratory species that have been documented as having the highest levels of mortality from collisions with wind turbines; and (4) correlates of bat activity such as wind speed, temperature, precipitation, barometric pressure, and moon illumination.
We recorded bat echolocation calls from sunset to sunrise nightly with an SM2Bat+ detector/recorder mounted above Big Sheep Creek between 31 January 2012 and 24 October 2014. A total of 12,269 bat call sequences were recorded over 10,716 hours of monitoring, with 14.5 percent being auto‐identified to species by Sonobat 3.0 or Kaleidoscope Pro 2.0 software.