Project Grant 2449392
- This Project Grant award of $436,664 from the National Science Foundation's Biological Sciences (CFDA 47.074) program will support a four-year collaborative research project at North Carolina State University to develop Artificial Intelligence (AI) tools for analyzing animal coloration and camouflage from camera trap images collected around the world. The project aims to understand how seasonal color-changing species like snowshoe hares and willow ptarmigans cope with environmental...
- This National Science Foundation (NSF) Biological Sciences (CFDA 47.074) project grant awarded to Ohio University will develop comprehensive artificial intelligence (AI) tools to analyze camera trap images of animals from around the world. The goal is to understand animal coloration and the mismatch in seasonal camouflage as environments change due to climate change. The $850,107 award, effective September 1, 2025 through August 31, 2029, will support the research team's efforts to create...
- This $198,141 project grant awarded by the National Science Foundation's Biological Sciences program (CFDA 47.074) seeks to enhance predictive understanding of global species distributions through the development of advanced generative artificial intelligence (AI) models. The project aims to create a versatile foundation model that can be used by scientists, conservationists, and educators to better understand and protect the natural world. By training this model on a vast array of environmental...
- The National Science Foundation Division of Integrative Organismal Systems awarded a $393,627 Project Grant to the University of Chicago from April 1, 2021 through March 31, 2024. The grant supports research titled "Explaining Color Pattern Diversity through the Dynamic Analysis of Display" under the Biological Sciences program (CFDA 47.074). The project aims to advance understanding of major biological issues by promoting basic research on the evolutionary mechanisms underlying...
- This $240,000 Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop advanced computer vision (CV) approaches for global biodiversity monitoring. The project aims to: (1) robustly identify rare, visually similar, and novel categories of biodiversity data using augmented training data and active curation; (2) adapt CV models to new deployments and identify valuable data for specialized tasks;...
- This federal Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop transformative new wireless communication and artificial intelligence (AI) tools for automating biodiversity data collection, processing, and analysis. The $598,865 grant, awarded to Duke University, will fund the creation of probabilistic models to account for errors in inferring species composition from audio,...
- The National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) awarded a $500,000 Project Grant to Northwestern University to investigate how animals' use of imagination underlies their biological learning advantage compared to current artificial intelligence (AI) systems. The 3-year project, beginning September 1, 2025, will conduct first-of-its-kind experiments monitoring animal brain activity during avoidance of an autonomous robot threat. The researchers will then use...
- This Project Grant awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides $212,912 to develop novel mathematical approaches that bridge the gap between theoretical models and empirical data on animal movement and cognition. The goal is to enhance understanding of how and why animals move through different environments and habitats, which is a critical challenge in ecology, conservation biology, and wildlife management. The...
- This Project Grant award of $382,681 from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) supports research at California State University, Dominguez Hills to investigate the taxonomic and geographic distribution of near-infrared (NIR) reflectivity in birds and insects. The project aims to develop a macroecological understanding of how NIR reflectivity, which is critical for thermal adaptation, varies across different animal species and environments. This research...
- This Project Grant from the National Science Foundation's Biological Sciences program (CFDA 47.074) provides $748,624 to North Carolina State University from August 1, 2022 to July 31, 2025. The funding will support research to develop integrated distribution models for approximately 100 North American mammal species. Researchers will combine traditional museum data with new camera trap and citizen science data, including from the National Ecological Observatory Network and Snapshot USA program....
This federal Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) provides $207,291 to the University of New Hampshire to develop artificial intelligence tools that analyze camera trap images to understand animal coloration and camouflage on a changing planet. The 4-year project will create publicly available AI tools to study coat color, background color, and camouflage in seasonal color-molting species like snowshoe hares, weasels, and ptarmigans. The research aims to explore how these species cope with environmental variability and color mismatch, while also supporting public education on animal color adaptations. The project leverages camera trap data to generate insights into the functional biodiversity impacts of climate change on a global scale.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $207.3k | 8/5/25 |