Place and Time: Data Mapping in Research on Aquaculture Siting Locations

Melissa Kimble Works to Unify Qualitative and Quantitative Data in New Research on Aquaculture Siting Locations

When Melissa Kimble first came to Maine, her partner insisted she buy a copy of the  “Maine Atlas & Gazetteer.” He told her that she needed the thick blue book filled with maps of roadways and trails, the best camping spots, and the highest peaks of the Appalachian Mountains. The pages covered in highway routes, scenic trail markers and town lines attempted to fully describe the geography of the State of Maine, but to Kimble, they represented a much more fascinating perspective. The map of overlapping explanations and ideas based on the human perspective was an open field for research on the way the people view and describe their world.

Kimble was a child of the Air Force, moving all around the country throughout her youth. She has lived across the United States, from the wilderness of Anchorage, Alaska, to sunny Northern California where she attended Humboldt State University to study anthropology and geospatial science. Before graduating from her Master’s program, Kimble found herself in the U.S. Virgin Islands working on various projects that involved applying geographic information system (GIS) data to environmental and marine science research. This work in the Virgin Islands inspired Kimble. She was encouraged to obtain her Ph.D., and thus she was introduced to the University of Maine.

The NSF EPSCoR Track-1 Grant, Sustainable Ecological Aquaculture Network (SEANET), needed someone with an interdisciplinary background in both social and ecological sciences to help gather, analyze, and map data into comprehensive charts that other academics, stakeholders, and community members could read and understand. Their goal was to minimize the divide that often occurs between the work of social scientists, who focus heavily on qualitative data, and other researchers, who focus on more traditional quantitative values. Now, as a Ph.D. student studying Spatial Information Science and Engineering at the University of Maine, with faculty advisor, Dr. Kate Beard, Kimble works with SEANET to establish better integration between different data types in order to tell a more cohesive story.

Kimble sometimes refers to her work as “cleaning up data” that might otherwise be messy with jargon or confused meanings. “That’s all it is, cleaning. Cleaning information so that it can be digested in a similar manner for everybody,” said Kimble. “Being able to give consumers a whole picture, something they can make sense of, so they can make a decision based on the information I provide.”

During her time at Humboldt State University, Kimble worked to bridge the gap between scientists and stakeholders by ridding the decision-making process of data uncertainty. Data uncertainty stems from whether or not a researcher used the correct method to collect or test data, made any errors throughout their process, or explained their findings in a way that is different than others would. During this project, she worked to establish the best location for a wildlife corridor that would provide the Humboldt marten, an endangered species, with a safe way to cross a highway that divided their habitat.

“We ran a simulation several times, created multiple potential corridors, and tweaked the information that went into why a marten would select a particular path. We had the collared locations of some female martens and their habitat preferences, but uncertainty persisted because they are difficult to find,” said Kimble. “So we tweaked that information and ran simulations over and over again to figure out what would be the best case scenario, and found one location that had the greatest potential for a corridor.” Now, years after the corridor has been built at her suggested location, evidence of martens successfully crossing and living on the other side of the corridor has been found.

Now Kimble serves as a mediator in SEANET projects that are looking at siting decisions and behaviors of aquaculture farms, connecting qualitative data from lease applications, agreements, and town hearings to quantitative data such as the number of sites or environmental conditions in a certain location. “On one hand, you have the productivity view, which includes what location has the best temperature or salinity for the animal you are trying to grow. If the species has optimal conditions, then hopefully it’s a productive site and you can make money off of it,” explained Kimble. “But then you have to add other considerations, such as whether the space is actually available or if you can get a lease for that location, and the decision becomes less to do with the biophysical factors and more to do with looking at the social constraints for the location.”

Kimble’s work uses the lens of the Social-Ecological Framework that was developed within SEANET to look at the interactions between resources, the environment, governance and policies, and users of resources. The common link between researchers using this framework is the need to effectively communicate the needs, concerns, and suggested solutions for all parties involved. Kimble’s work clarifies definitions and combines the way researchers understand and communicate into comprehensive charts so that everyone is on the same page.

Currently, Kimble is examining locations in Maine where new aquaculture leases are starting up. She considers how far apart the leases are, both in geological distance and time of establishment. If new farms are setting up shop in the same general areas, there are many possible explanations to consider, such as level of community support, lack of other available spaces, water quality, or a combination of reasons. Kimble uses this information to create GIS maps that capture a wide variety of information about aquaculture lease locations.

Creating GIS maps for aquaculture leases requires an analysis of both quantitative and qualitative data. After analyzing the geological distance and time between leases, Kimble assigns numerical values to certain words when reading through documents to gauge community support. “Let’s say you have a transcript, you might code a specific word to mean a particular thing and give it a particular value,” said Kimble. “If you are trying… to analyze a number of [transcripts] and see if they are [overall] negative, positive, or neutral, then you might code a bunch of words with negative or positive values, and then give [the documents] a grade.”

Together, these analyses create GIS maps that paint an entire picture for stakeholders and community members who want to identify any problems, monitor changes, and identify trends in aquaculture leasing in their coastal communities.

By clarifying data uncertainty and combining qualitative and quantitative data, Kimble’s GIS work assures researchers that they are conducting their project work to the best of their ability with all of the available types of data included, strengthening research processes as a whole. Further, SEANET’s GIS research provides decision-makers with recommendations for their problems after considering the most possibilities.