chfleming

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Funding Links: https://github.com/sponsors/chfleming

• Name: Christen H. Fleming
• Company: Smithsonian Conservation Biology Institute
• Kind: user
• Followers: 12
• Following: 1
• Total stars: 0
• Repositories count: 0
• Created at: 2024-11-24T19:33:29.282Z
• Updated at: 2024-11-24T19:33:29.282Z
• Last synced at: 2024-11-24T19:33:29.096Z

GitHub Sponsors Profile

Greetings,
I am an associate research scientist at the University of Maryland and fellow at the Smithsonian Conservation Biology Institute. I develop statistical methods and open-source software for research biologists and wildlife managers all over the world. My software has been used to analyze data from many species, including the Sumatran elephant, white-lipped peccary, Persian leopard, long-tailed macaque, African elephant, domestic cat, yellow-spotted river turtle, gray wolf, raccoon, giant armadillo, Australian wood duck, jaguar, scimitar-horned oryx, Afrotropical birds, eastern whip-poor-will, Tagula honeyeater, European eel, Amazonian birds, Kordofan giraffe, brown tree snake, African leopard, mottled duck, swallows and swifts, Mongolian gazelle, hawksbill sea turtle, fish and stingray, capuchin monkey, white-tailed deer, monarch butterfly, barn owl, common noddy, and yellow-billed loon.
I specialize in the analysis of animal tracking data, which is being collected at an increasing rate, all over the world. These data are becoming easier and easier to collect over time, because they benefit from all of the technological progress being made with cell phones and lithium-ion batteries. These data can also answer important conservation questions, such as how much space animals require. However, these data are very difficult to analyze correctly because they represent irregularly- and erroneously-sampled timeseries. And having correct answers can make a big difference, especially in larger species. Conventional methods were not developed with these kinds of data in mind and have a strong tendency to underestimate how much space animals use. Furthermore, these estimates are used to inform management decisions for reserves and protected areas, and biased analyses lead to biased management decisions.
My work consists of developing statistical methods and corresponding computational algorithms that address important conservation questions. I implement these methods in an easy-to-use open-source software package that is maintained here on GitHub. Because this kind of analysis involves a lot of high-level statistics, I also do a lot of free and non-profit teaching. I am currently supported by an NSF grant. As long I am able to maintain funding and support, this work will continue.

• Current Sponsors: 0
• Past Sponsors: 0
• Total Sponsors: 0
• Minimum Sponsorship: $1.00

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• User: 1