Why do we care about where bats are detected?
Bats are critically important animals that play a key role in many ecosystems and provide significant benefits to human populations. Among other beneficial activities, they consume large quantities of insects, which would otherwise have major impacts on agriculture and human health. However, due to their nocturnal habits, we do not know as much about them as we should. This knowledge is particularly important when trying to understand the impacts of climate change, land-use change, wind energy development, and other factors on the health of bat populations.
While it is more common to associate bats with caves, some bat species roost in trees and migrate over large areas. These species are particularly affected by wind energy development, leading to concerns about the long term viability of their populations. As a society, we understand relatively little about the population size, population health, and migration patterns of these species — making it particularly difficult to know how best to change human activities to reduce our impacts.
We can learn more about how bats use the landscape over time — over broad scales such as all of North America — by using devices known as “bat detectors.” Bats use high-frequency sound pulses to help them navigate their environment and find prey. This is known as echolocation. Because bats are active at night and fairly difficult to observe — compared to other species such as birds that you can easily identify during the day — people use bat detectors to listen for these echolocation calls. These devices can be handheld, strapped to a car, or installed at specific locations to monitor bat activity for a few nights up to several years. We will focus on the last type, which are known as stationary acoustic bat detectors.
Bat scientists, conservation organizations, wind energy developers, and others operate thousands of stationary acoustic bat detectors across North America every year. However, until recently, there was not an easy way to share these data in order to understand patterns in bat activity at the continental scale. Through a partnership between the USDA Forest Service Pacific Southwest Research Station (USFS) and the Conservation Biology Institute (CBI; where I used to work), we launched the Bat Acoustic Monitoring Portal (BatAMP) in 2013 as a centralized place for people to share bat acoustic detection data. Led by bat ecologist Ted Weller, BatAMP has received nearly 30 million bat detections from more than 90 contributors so far.
BatAMP is built on Data Basin — one of the world’s largest geospatial conservation data-sharing platforms. Data Basin is more focused on the general capabilities you need to share and explore spatial data. It made it possible for people to easily contribute their data. Unfortunately, it doesn’t show off bat acoustic data particularly well. We needed a specialized tool to help us better visualize bat detection data to help us answer some of our primary questions, including:
- where are certain bat species detected?
- when are certain species active in a particular area?
A new tool for visualizing bat detections
Based on the data shared through BatAMP, we (USFS & CBI) developed a data visualization tool specifically focused on bat acoustic data. The Bat Acoustic Monitoring Visualization Tool, launched in 2019, provides a visually-compelling tool for exploring bat detection data across North America. It brings together data for nearly 2,000 stationary detectors operated for a total of over 200,000 nights.
This tool allows you to explore detections for 34 species across North America, especially within the contiguous United States. The geographic and temporal scope of the tool is only limited by the data that have been contributed so far. As more data are contributed, we make them available in the tool.
You can explore species detections in two main ways:
- You can drill down into detection data for a single species, which enables you to easily see when and where that species was detected (based on the data that are available).
- You can explore across all species, and find out where species co-occur:
You can filter bat detections by season, to gain a greater understanding of where and when bats may be active (based on the available data). This has already revealed interesting patterns in winter activity, such as Silver-haired Bats — a migratory tree-dwelling species — that are active in Montana during December:
You can drill down for more details from a specific detector. In addition to basic statistics about overall detections per species at this location, it also allows you to compare activity between species over time:
This visualization tool is targeted at members of the bat science and conservation communities. It is already being used by bat scientists to explore patterns in seasonal activity across the continent. They are also investigating detections that may indicate some species are expanding their ranges into new areas. We think this is just the beginning of interesting information that will come out of data aggregation efforts like BatAMP.
This tool is also being used to catalyze new data-sharing efforts. It visually demonstrates the value of aggregating continent-wide monitoring data to discover new insights about bats. This makes it easier to convince decision-makers and funders to allocate resources toward collecting and aggregating bat monitoring data.
It helps highlight the contributions of individuals and organizations, which gives much needed public recognition to members of the bat monitoring community for their hard work:
One of the challenges underlying the data we have aggregated so far is that of sampling effort. Because operating stationary acoustic detectors over the long term can grow to be quite expensive in terms of equipment and staff costs, year-round monitoring at a given location is relatively rare. Detectors are often deployed during warmer seasons, sometimes for as little as a single night. This leads to a strong sampling bias in both the location and time of bat detections — because you can’t detect a bat if you don’t have a detector running. It is important to keep this in mind while exploring the tool: there were far fewer detectors operating during the winter months, especially at more northern latitudes. The absence of evidence is not the evidence of absence, if you will.
We expect the value of this tool to grow as more data are contributed to centralized platforms like BatAMP. In particular, we are working to combine the overlapping goals of BatAMP and the North American Bat Monitoring Program (NABat). Led by ecologist Brian Reichert at the U.S. Geological Survey, NABat seeks to centralize a broad collection of bat monitoring data, from bat colony surveys in caves to driving surveys (detectors strapped to cars, surveying a pre-defined route), as well as stationary acoustic detector data. Importantly, NABat introduces statistical rigor through a sampling framework and monitoring protocol. Data collected using those methods can be used to quantify the status and trend of most bat species that inhabit North America. By collating several different types of bat data, NABat will provide a critical baseline for understanding the current condition of bat populations as well as their trends over time.
One of our primary goals with BatAMP was to make it relatively easy to share bat acoustic data. While the upload process could certainly be improved further, we believe that the ease of contributing data has been key to its success so far. We are leveraging our lessons learned from BatAMP to help make it easier to contribute data to NABat, including data that would have previously only been supported by BatAMP. Through these combined efforts, we expect to grow the breadth of data available in NABat. Likewise, we are working with NABat to integrate their data into our visualization tool, which will further amplify the impact of sharing bat data into these systems.
While broad-scale monitoring, data aggregation, and data visualization have been a mainstay for bird species for several years thanks to eBird and related efforts, we are not aware of other continental-scale tools that have achieved something similar for bat species. Thus, we think that our visualization tool provides a major contribution to the bat conservation community in North America. It has also helped catalyze a vision for what can be achieved by sharing bat data into a centralized system. We hope that this tool inspires similar applications in other regions, which ultimately will improve society’s understanding of bat activity and distribution over space and time.
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