Gopher tortoises are a keystone species in the Floridian ecosystem. In fact, over 300 other species depend on gopher tortoise burrows to live, and it is imperative to protect them. A greater number of gopher tortoise burrows can help gauge the health of the ecosystem as a whole. Why gopher tortoise burrows are distributed the way they are can help conservation efforts. Areas that tend to favor tortoise burrows more should be protected from human development.
Yuliang first got his idea to use GIS to study gopher tortoises when he was attending the ESRI User Conference, a GIS conference that is held in San Diego every year, with his father in 2016. GIS stands for “Geographic Information Systems,” and adds a new dimension to the traditional methods of analysis: location. A showcase of the new features released that year had given him an idea. That year was also the year he was invited to join Hundred Acre Hollows, a nonprofit with the goal of educating the public about sustainability and threatened species in the Floridian ecosystem with the 114 acres of land granted to them by Brevard County. He combined these two opportunities into one idea: using location-based GIS to analyze gopher tortoise data. Over the course of two months, Yuliang Huang and 4 other volunteers collected over 500 data points of gopher tortoise burrows all over Hundred Acre Hollows were collected with survey software. Out of these burrows, over 400 were found to be active, and the median burrow size was 29 cm.
The results were then analyzed using a GIS tool known as “hot spot analysis” to find if there was clustering. Knowing if there is clustering based on the variables studied (including soil type, annual received solar energy, elevation, etc.) is important to verify if there is a pattern in the data based on all the variables chosen. “I was actually kind of nervous at this step,” Yuliang recalls, “If no clustering was found, it would mean that the computer didn’t find a pattern in the density based on the variables that it was given, and it would be back to the drawing board for me.” In Figure 2, the blue areas represent “cold spots,” where there were unusually few burrows in an area and the red areas represent “hot spots,” where there were unusually many burrows in an area. The darker the color, the higher the confidence of the computer that clustering did indeed exist. These areas would be potential points of interest for study.
He then performed a correlation analysis of the location density of the burrows with a tool known as “Forest Based Classification and Regression,” comparing the distribution against variables like location, elevation, soil type, and annual received solar energy. His results? The variable with the highest correlation (in other words, most impact) on the locations of gopher tortoise burrows seemed to be the annual received solar energy. “At first I was expecting the soil type to have the highest impact on the density of tortoise burrows. This is a very interesting and unexpected result,” Yuliang says. “It might be worth conducting a future analysis to find out why this is the case.”
The results of Yuliang’s work are available online! You can check out an interactive story map and learn more about the project here.