National bird species maps can help protect biodiversity

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Researchers mapped the number of bird species found in contiguous blue areas of the United States that support fewer bird species than green or yellow areas. Images by Kathleen Carroll and Anna Pidgeon

New, highly detailed and rigorous maps of bird biodiversity could help protect rare or endangered species.

Researchers from the University of Wisconsin-Madison developed the maps at a fine enough resolution to help conservation managers focus their efforts where they are most likely to help birds – in individual counties or forests. , rather than entire states or regions.

The maps cover the contiguous United States and predict the diversity of birds that live in a given area, linked by traits such as ground-nesting or endangerment. These predictions are based on both detailed bird observations and environmental factors that affect bird ranges, such as the degree of forest cover or temperature in an area.

Anna Pigeon

“With these maps, managers have a tool that they did not have before that allows them to obtain both a broad perspective and information at the level of detail necessary for their action plans”, says Anna Pidgeon, professor of forestry and wildlife ecology at UW-Madison who helped lead the development of the maps.

Pidgeon worked with UW-Madison Professor Volker Radeloff, postdoctoral researcher and lead author Kathleen Carroll and others to publish the research and final maps April 11 in the journal Ecological Applications. The maps are available for public download on the Dryad open-access website.

The research was designed to address two outstanding conservation issues.

“All over the world, we are witnessing huge losses of species. In North America, 3 billion birds have been lost since 1970. That’s in virtually every type of habitat,” says Carroll. “And we’re seeing a disconnect between what scientists produce for conservation and how that translates into on-the-ground management.”

Many resources previously available to conservation managers, such as species range maps, are both at too large a scale to be useful and have not been rigorously tested for accuracy.

To overcome these challenges, Carroll and his team wanted to develop maps based on existing bird biodiversity data. They produced the maps by extrapolating bird sightings from scientific surveys to mile-by-mile predictions of where different species actually live. These predictions were based on factors such as rainfall, the degree of forest cover, and the extent of human influence on the environment, such as the presence of cities or farms.

To improve the predictive power of their maps, the scientists grouped individual species by behavior, habitat, diet or conservation status, such as frugivores or forest dwellers. These groups are called guilds. Many conservation decisions are made at the guild level rather than the species level. Guilds can also compensate for limited information on the most endangered species.

The final maps cover 19 different guilds at 0.5, 2.5, and 5 kilometer resolutions. While the finest maps weren’t as accurate, the 2.5 kilometer resolution maps offered a good balance of accuracy and usefulness for realistic conservation needs, the scientists say. At 5 kilometer resolution, the maps offer the highest accuracy and are useful for conservationists operating over large areas.

“We think that really applies to things like forest management action plans for the US Forest Service,” Carroll says. “They can display these maps for an interest group, and they can get a very clear indication of areas where they might want to limit human use.”

Maps can also help private land conservation agencies decide where to prioritize limited resources to maximize biodiversity protection.

Carroll is now working to extend the analysis to individual species, rather than guilds made up of multiple species. The increased level of detail could help specialist conservation managers improve their work, especially those aiming to protect a single species.

This work was supported in part by the Landsat Science Team of the U.S. Geological Survey (G17PS00256 grant) and NASA’s Biodiversity and Ecology Prediction Program (Grant 20-BIODIV20-00460.

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