Corridor ObservatoryCorridor Observatory
Developing a model for collecting big data for animal ecology, to provide insight on the values and impacts of the Florida Wildlife Corridor
The Corridor Observatory project uses camera traps and autonomous recording units (ARUs) to collect data to help us analyze occupancy and activity patterns for many species of wildlife, providing new insight into how our management shapes landscapes and impacts wildlife populations. Our research focuses primarily on large bodied, wide-ranging wildlife such as feral pigs, black bear, and Florida panther.
Major Findings & Impact
Project Details
More about this project
Primary Location(s)
DeLuca Preserve, Archbold Biological Station, Buck Island Ranch, Lake Wales Ridge, Headwaters of the Everglades Watershed, Florida Wildlife Corridor
Years Active
2022 - Current
Data and Analysis Types
Occupancy studies, distribution and abundance for several species of terrestrial and semi-terrestrial birds and mammals
Related People
Funders & Collaborators
UF/IFAS Range Cattle Research & Education Center (RCREC): Dr. Hance Ellington at RCREC collaborates in the design, field deployment, and scientific analysis of Corridor Observatory monitoring arrays across working ranchlands. University of Florida researchers bring field and technical expertise to our work, recruit and mentor graduate students, and applied research linking wildlife communities to agricultural landscapes.
Environmental Data Science Innovation & Impact Lab (ESIIL), University of Colorado-Boulder: Our Corridor Observatory collaboration is powered in large part through ESIIL, which provides critical infrastructure for large-scale data processing, storage and reproducible analysis. The Observatory’s image and acoustic data are developed, standardized, and published through collaboration with ESIIL’s environmental data science community.
USDA-APHIS & USDA-ARS Research Units: Collaborations with USDA research units support the development, benchmarking and evaluation of machine learning tools used to classify wildlife images. These partnerships allow the Observatory to rigorously test AI applications in real-world ecological monitoring contexts, strengthening conservation outcomes and providing cost-saving solutions for land managers in working landscapes like that of the Everglades Headwaters region.
