Evaluation and Demonstration of Autonomous Bat Dataloggers and Bat Detectors for Long-Term Monitoring of Roost Activity
Rey Farve, Project Leader
For FY 2013, Jason Walz, cave specialist with the Lincoln National Forest, submitted a proposal to the Technology and Development Program, Inventory and Monitoring Steering Committee to test and demonstrate the efficacy and cost-effectiveness of using bat dataloggers. The proposal's intent is to test the ability of bat datalogging devices to monitor bat activity and environmental conditions within the bat hibernaculum and to monitor nightly and seasonal bat activity to and from the cave.
Figure 1 - Bats roosting in a cave. (Photo by U.S. Fish & Wildlife Service)
Long-term monitoring of bat activity can provide life history information in areas that are currently only poorly understood, for instance:
- Survival of bats during hibernation is a critical issue across the country, especially with the recent spread of white nose syndrome (WNS) disease among roosting bats. (For details about WNS see disease_information/white-nose_syndrome). Hibernation data is currently absent or very-poor in non-WNS areas (i.e., the western half of the country). Long-term, continuous monitoring can potentially provide information concerning arousal patterns during hibernation, population changes, emergence date, and erratic activity that might be associated with WNS.
- Bat activity during the fall (September-November) swarm (i.e., the simultaneous emergence of millions of bats from roosts) is unknown locally and only poorly understood nationally. Widespread long-term monitoring could provide information on this unknown activity.
- Bat activity within a summer maternity colony also is poorly understood. Information on bats during this sensitive time is very difficult to obtain as repeated site visits by monitors can stress pregnant/nursing females and cause neonatal mortality.
- Changes in bat activity in caves and roosts relative to physical factors, such as, climate change, precipitation, pressure changes, temperature, moon phase, etc. is largely unknown.
Figure 2 - Caves in the Lincoln National Forest.
Biologists currently monitor bat activity in caves and roosts by direct observation or by using bioacoustical devices. Long-term, repeated monitoring by direct observation of caves and roosts are time consuming, expensive, and can induce stress to bats during sensitive times of their life cycle. Bioacoustic monitoring (using bat detectors) can only realistically be used for short-term monitoring (a few weeks at best) as these devices typically have a high-power requirement to operate and require a considerable amount of digital memory (which is necessary for species identification). These two demands (power and memory) tend to severely limit the amount of time they can be deployed.
In several circumstances, bat biologists have a good understanding of the species of bats in caves and roosts but would like more information on long-term movements (activity) in and out of the cave - either nightly or seasonally. For those instances, a device that could monitor bioacoustic (ultrasonic) activity may provide a cost-effective method for long term, continuous monitoring of bat activity.
To meet this specific need, two manufactures have developed devices that autonomously record and log ultrasonic activity over long periods to help biologists study nightly (or seasonal) activity. The two devices are: the Bat Logger II manufactured by Tony Messina, and the recently released AnaBat Roost Logger manufactured by Titley Scientific.
Figure 3 - Bat detectors: Bat Logger II (left) and AnaBat Roost Logger (right).
As such, the Technology & Development Program's Inventory & Monitoring Steering Committee directed San Dimas Technology and Development Center to:
"Investigate and demonstrate autonomous devices (that are not labor intensive, intrusive, or expensive), which can detect and/or quantify the use of caves by bats. Note: Commercial models record/identify the bat sounds; this proposer just wants to count calls."
The objective is to demonstrate the efficacy of bat dataloggers as an autonomous (unattended), cost-effective tool to monitor bat activity over long periods (i.e., months) in caves and roosts.