Acadia's Bats Go Digital: Moving 16 Years of Monitoring From Paper to Apps

Acadia National Park has one of the longest-running bat monitoring programs in the National Park Service. For years its records lived on paper. A team of researchers turned them into a digital workflow — from field collection to management decisions — and learned how to survey more efficiently along the way.

Bik Wheeler (left) and Tim Divoll stretch mist nets across a brackish stream at Acadia in 2009 or 2010, hoping to catch bats that night. The nets were set close to vegetation so bats could not fly around them. NPS

Why the data mattered

Park Service biologists collect many kinds of wildlife information year after year: droppings and wing swabs, locations from tiny radio transmitters, tens of thousands of echolocation recordings, and population and body measurements. These long-term records show how wildlife is faring — but poorly organized data get harder to analyze with every added year.

From boom to bust

The Wabanaki and their ancestors surely told stories about Acadia's bats for thousands of years, and Harvard naturalists collected and studied them in the 19th century. In 2008 the park joined a regional survey of mercury in wildlife, bats included, and the next year Tim Divoll began studying Acadia's bats for his master's thesis.

Looking back, 2008–2011 were the "glory days". Little brown, northern long-eared and eastern small-footed bats filled the night sky. By 2012, capture rates were plunging — white-nose syndrome, a deadly fungal disease of bats, had reached Acadia. The team's mood turned from the thrill of finding thriving populations to a resolve to help them survive.

An eastern small-footed bat rests on a tree after being gently captured, examined and released. The band on its wing lets future researchers identify it; some Acadia bats have been recaptured 13 years after banding. NPS

Money for studying the disease came and went. Former park biologist Bruce Connery put it this way: "When funding is limited or uncertain, you start small and collect what data you can. You have to start somewhere, otherwise you get nowhere."

Sixteen years on, Acadia was among the longest-running bat monitoring sites in North America — yet most of its data sat on paper in filing cabinets, out of reach of outside scientists. Divoll, by then a data scientist at Brown University's Center for Computation and Visualization, worked with Park Service colleagues to modernize how the data were collected, cleaned and retrieved.

Paper to apps

Paper data sheets blow away, get soaked in summer storms, and come back muddy, torn, crumpled or bug-stained — and copying them into a database invites mistakes.

The old way: handwritten data are convenient in the field but prone to errors when transcribed. NPS

The team used ArcGIS Survey123 to build mobile apps that work offline for recording data in the field. They save time, cut errors, and improve quality by offering pre-set choices during entry.

An offline data collection app built with Survey123 lets technicians enter data straight into a form. NPS

Each year the data are published in the NPS DataStore for researchers and managers, run through a template that follows the Ecological Metadata Language standard, so only the new year's data need adding and unchanged information is reused.

For analysis — kept internal because the species are sensitive — the team built tools in R-Shiny and R-Notebooks whose code can be rerun each year with one more year of data. An R-Shiny app lets managers quickly filter all 16 years of data on Acadia's endangered bats to check the population's vital signs.

Surveying smarter

The analyses turned up savings:

• Fewer sites. Nets had gone up at more than 30 sites across the park — good coverage — but only about six had consistent bat activity after white-nose syndrome. Those became "core sites" for future monitoring.
• Shorter nights. Crews kept nets open an average of four hours after sunset, but most bats were caught in the first two hours. Ending surveys and getting back by midnight would still have caught about 86% of the bats a longer night would.

Bats caught vs. hours spent catching them. Blue area (right) shows staff spent avg. of about 4 hours catching bats. Pink area (left) shows they caught most bats in first few hours. Vertical dashed lines = mathematical means. We used all 16 years of data to generate this plot. Image credit: NPS / Tim.

That means less overtime, more staff time for other work, and greater safety — the risk of injury grows as energy and attention fade late at night. The team also chose tools that meet federal software security standards, with field data passing to a secure portal before processing. The mapping software comes from the world's largest geospatial software developer, so it should stay supported and easy to use; R, popular in biology and commonly taught in college ecology courses, is familiar to many staff biologists — which matters for keeping the tools running.

Wheeler (left) and Divoll gently remove a live bat from a mist net over a slightly salty coastal stream at night, 2009 or 2010. A flying beetle — bat food — is at lower left. NPS

Hope, and a model for others

"We've been at the right place and the wrong time," said Rebecca Cole-Will, Acadia's chief of resource management, of watching the park's bats decline. "Now we may be seeing some glimmers of hope that Acadia will serve as a refugia for bat recovery. To tell this story, we need to access and communicate the baseline data."

The same methods can be used by other parks and protected areas for many kinds of resources. Making long-term monitoring data easy to reach is central to modern conservation — it lets scientists and managers decide quickly how to help wildlife and habitats adapt to fast-changing conditions.

Sources

Based on Timothy Divoll, Bik Wheeler and Molly Donlan, "Why Years of Bat Population Data Got a High-Tech Upgrade," Park Science 39, no. 1 (Winter 2024–25), National Park Service; a work of the United States government in the public domain. One author was at Brown University, so the article is rewritten in hubnx's own words; the quotations are from Park Service staff. A graph of capture times, credited to the NPS and Tim Divoll jointly, is not reproduced. Pictures an earlier version of this page left out were restored on 2026-09-26.