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UT’s Department of Electrical Engineering and Computer Science and School of Art have partnered with the Great Smoky Mountains National Park Inventory and Monitoring Branch to create a new web application, Species Mapper.

Everyone from park managers to school groups can use Species Mapper to explore suitable habitats for species for more than 1,800 species.

Species Mapper uses locations where species have been found to help predict additional places they may occur in the park. These predictions, or models, are based on observations made during ongoing resource monitoring as well as research studies conducted by scientists from all over the world.

The result of the model is a reliable distribution of where each species lives in the park. The model uses supercomputers managed by the Joint Institute for Computational Sciences, a collaboration of UT and Oak Ridge National Laboratory, to analyze the location of observations as well as the characteristics of the environment such as slope, forest type, geology, elevation, temperature, and sun exposure.

Will Godsoe and his colleagues at UT’s National Institute for Mathematical and Biological Synthesis have guided the team on the ecological analysis of the data and the models.

“This application allows park managers to use the vast amount of biological data collected over the past three decades to protect park resources and assess the potential impact from disturbances like hemlock woolly adelgid and emerald ash borer,” said Inventory and Monitoring Program Manager Tom Remaley. “Visitors can use this site to explore what lives in the park and what they might see during their visit.”

“This project is about plowing through large quantities of data and an immense computational space to bring scientific insights to the fore,” said EECS Professor Jian Huang. “It is remarkable because of the technical challenges, the truly interdisciplinary nature of the work, and the fact that, together with the National Park Service, we completed the last mile to deliver on the promise of making science relevant, accessible, and exciting to as many people as possible.”

Huang added that the success of the project was measured by more than just the new app.

He said that some of the excitement comes from continuing to build a long-term partnership with the National Park Service to help students, teachers, and managers alike to make effective use of big data in order to better connect people to the nature and preserve America’s special places.

The project started under the National Science Foundation­–funded Remote Data Analysis and Visualization Center at UT when Huang was its associate director.

Professor Sarah Lowe of the School of Art is served as co-principal investigator on the project, focused on its design and user interface.

“An interface intended for a range of audiences is best conceived by an interdisciplinary team who works together to address all aspects of the project throughout its evolution,” said Lowe. “In the case of the Species Mapper, this included discussions across the core team of computer scientists, designers, and National Park staff.

“This work is exciting as it not only taps into the extensive data that the GSMNP has collected, but in the ways that such data, which can be quite complicated to understand, can be displayed and made meaningful for those who come to visit the park.”

John Duggan, an EECS doctoral student who is working on the project, made the point that the tool was an important storytelling method due to the visualization it provided.

“In our case, the story we want to tell is how rich the biodiversity in the Smokies is,” said Duggan. “It can also help the general public better connect with and experience this richness.”

Park managers will continue to add observations to the application, making it more reflective of all species found within the park and increasing the accuracy of the prediction model.

The species presence data used by Species Mapper is managed by All Taxa Biodiversity Inventory project — a park-wide biological inventory of all life forms. Currently, more than nineteen thousand species have been recorded in the park, including one thousand species never before seen anywhere in the world.

The ATBI in the Smokies is coordinated by Discover Life in America, a non-profit partner of the park service, with a history of providing data dating back to 1950s.

DLIA and park managers will continue to add observations to the application making it more reflective of all species found within the park and increasing the accuracy of the prediction model.

For more information about biological diversity in the park, visit the park website or Discover Life in America.


JICS was founded in 1991 to use computational modeling and simulation to aid in scientific discovery and to help researchers gain better understanding of particular problems.

NIMBios began in 2009 and is a National Science Foundation–backed research center that fosters collaboration and investigation across disciplines.  

C O N T A C T :

Kevin Bogle (865-974-9149,