A UF study analyzed python removal data, identifying optimal survey conditions and key locations for increased removals. Researchers recommend targeting the wet season, surveying at night, and using aquatic vehicles.
A groundbreaking study by University of Florida scientists used statistical analysis of extensive data from Burmese python contractors to identify the most effective strategies for removing the invasive reptiles.
The researchers applied statistical modeling to examine how various survey conditions influenced python removals. They analyzed factors such as time of day and temperature to determine their impact on successful captures. Additionally, they assessed whether the most frequently surveyed areas corresponded with the highest python removal rates. Their findings revealed regions where a small number of contractors were capturing a disproportionately high number of pythons, suggesting that deploying more contractors in these areas could significantly increase removal efficiency.
“This collaboration among the UF Institute of Food and Agricultural Sciences (IFAS), South Florida Water Management District (SFWMD), and the contractors increases our ability to detect and remove pythons by providing guidelines for when and where to survey to optimize your chances of finding a python,” said Melissa Miller, an invasion ecologist at UF/IFAS Fort Lauderdale Research and Education Center. “Targeted surveys, guided by these data, can allow us to be more efficient and successful in our efforts to control Burmese pythons.”
These data were collected as part of the SFWMD Python Elimination Program between May 2020 and April 2022. The researchers from UF/IFAS analyzed 4,092 surveys from python contractors totaling over 16,000 hours of effort.
Key Areas Identified for Increased Python Removal
Researchers identified two regions where python removals could likely be increased with more surveys. These regions occurred toward the western edge of Big Cypress National Preserve along the Tamiami Trail and a stormwater treatment area in Palm Beach County. Additionally, researchers identified optimal conditions that improve survey outcomes, providing specific guidelines for contractors.
Based on their findings, researchers developed key recommendations to enhance python removal efforts:
- Surveys are most successful and efficient during the wet season from May to October.
- A drop in barometric pressure from the previous day, increases the likelihood of successful surveys.
- The most efficient survey period is between 8 pm to 2 am.
- Aquatic vehicles, including motorboats, canoes, kayaks, and airboats, enhance survey effectiveness.
- Nighttime surveys generally yield better results than daytime surveys, except during extreme cold events, such as mean daily air temperatures of 50 degrees Fahrenheit or lower.
Scientists see this as a pivotal point in research that now provides guidelines supported by data for successful detection and removal efforts from this point forward and all thanks to citizen science, researchers said.
“Pythons disrupt food webs, altering predator-prey dynamics and reducing populations of key native species. By refining removal strategies, we’re working to give native wildlife a chance to adapt and persist,” said Alex Romer, a quantitative ecologist at UF/IFAS Fort Lauderdale Research and Education Center and corresponding author on the paper.
Published in Scientific Reports, the study highlights effective python management strategies and demonstrates how researchers, natural resource managers, and residents can collaborate to improve wildlife conservation.
“Managing pythons is an enormous effort, undertaken by Floridians deeply invested in restoring the intricate ecological processes that define the Everglades,” said Romer. “This work is about safeguarding one of the world’s most unique ecosystems—not just for today, but for generations to come.”
Reference: “Optimizing survey conditions for Burmese python detection and removal using community science data” by Kelly R. McCaffrey, Melissa A. Miller, Sergio A. Balaguera-Reina, Alexander S. Romer, Michael Kirkland, Amy Peters, Edward F. Metzger III, LeRoy Rodgers and Frank J. Mazzotti, 18 January 2025, Scientific Reports.
DOI: 10.1038/s41598-024-84641-4
