Today, we say thank you to everyone who helped classify wildlife photos on snapshotwisconsin.org. Over the past four years, you’ve helped scientists model species distributions, measure vegetation phenology, study how deer use habitats to escape extreme temperatures, and much more. Below is a partial list of scientific publications to which your work has contributed since 2019.
Even though its partnership with NASA is coming to an end, Snapshot Wisconsin shows no signs of slowing down! Volunteers from Snapshot Wisconsin set up and monitor trail cameras, which take photos of passing wildlife. With more than 2,000 cameras deployed and counting, these photos contribute to an extensive database that helps the Wisconsin Department of Natural Resources make wildlife management decisions. Volunteers receive trail cameras and check them every few months. Over 63 million photos have been collected to date! After uploading the images, volunteers join a community around the world to classify by consensus the animals found in the photos. Anyone, anywhere can help categorize photos here at Snapshot Wisconsin. Learn more about getting your own trail camera here: https://dnr.wisconsin.gov/topic/research/projects/snapshot.
Study how deer use habitats to escape extreme temperatures
Gilbert, NA, JL Stenglein, TR Van Deelen, PA Townsend, and B. Zuckerberg. 2022. Behavioral flexibility facilitates the use of spatial and temporal refuges during extreme winter weather. Behavioral ecology, arab154.
As a model for future ecological monitoring
Townsend, PA, JDJ Clare, N. Liu, JL Stenglein, CM Anhalt-Depies, TR Van Deelen, NA Gilbert, A. Singh, KJ Martin, and B. Zuckerberg. 2021. Snapshot Wisconsin: Networking Community Scientists and Remote Sensing to Improve Ecological Monitoring and Management. Ecological applications 31(8): e02436
Modeling of species distributions, integrated with existing data streams (hunter harvest records)
Gilbert, NA, BS Pease, CM Anhalt-Depies, JDJ Clare, JL Stenglein, PA Townsend, TR Van Deelen, and B. Zuckerberg. 2021. Integration of catch and camera trap data into species distribution models. Biological Conservation 258:109147.
Measure vegetation phenology from “bycatch” data from photos
Liu, N., M. Garcia, A. Singh, JDJ Clare, JL Stenglein, B. Zuckerberg, EL Kruger, and PA Townsend. 2021. Trail camera networks provide satellite-derived phenology information for ecological studies. International Journal of Applied Earth Observations and Geoinformation 97:102291
Advancing the science of abundance estimation using camera trap data
Gilbert, NA, JD Clare, JL Stenglein, and B. Zuckerberg. 2021. Estimated abundance of unmarked animals based on camera trap data. Conservation Biology 35(1): 88-100
Assess privacy and data management issues for large-scale citizen science data flows
Anhalt-Depies, C., JL Stenglein, B. Zuckerberg, PM Townsend, and AR Rissman. 2019. Trade-offs and Tools for Data Quality, Privacy, Transparency and Trust in Citizen Science. Biological Conservation 3238: 108195.
Plan citizen science surveys
CM Locke, CM Anhalt-Depies, S. Frett, JL Stenglein, S. Cameron, V. Malleshappa, T. Peltier, B. Zuckerberg and PA Townsend. 2019. Managing a large citizen science project to monitor wildlife. Bulletin of the Wildlife Society, 43: 4-10.
NASA Citizen Science Program:
Learn more about NASA Citizen Science Projects
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