Daniel Fink

Senior Research Associate

Expertise

Applied Statistics • Machine Learning

I help develop statistical models and data products to understand the broad-scale patterns of species’ distributions using data from the citizen scientist project eBird.

Recent Publications

Cohen, J. M., D. Fink, and B. Zuckerberg (2023). Spatial and seasonal variation in thermal sensitivity within North American bird species. Proceedings of the Royal Society B: Biological Sciences 290:20231398.
Davis, C. L., Y. Bai, D. Chen, O. Robinson, V. Ruiz‐Gutierrez, C. P. Gomes, and D. Fink (2023). Deep learning with citizen science data enables estimation of species diversity and composition at continental extents. Ecology 104:e4175.
Stillman, A. N., P. E. Howell, G. S. Zimmerman, E. R. Bjerre, B. A. Millsap, O. J. Robinson, D. Fink, E. F. Stuber, and V. Ruiz‐Gutierrez (2023). Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size. Journal of Applied Ecology 60:2389–2399.
Fink, D., A. Johnston, M. Strimas‐Mackey, T. Auer, W. M. Hochachka, S. Ligocki, L. Oldham Jaromczyk, O. Robinson, C. Wood, S. Kelling, and A. D. Rodewald (2023). A Double machine learning trend model for citizen science data. Methods in Ecology and Evolution 14:2435–2448.
Binley, A. D., J. R. Bennett, R. Schuster, A. D. Rodewald, F. A. La Sorte, D. Fink, B. Zuckerberg, and S. Wilson (2023). Species traits drive responses of forest birds to agriculturally‐modified habitats throughout the annual cycle. Ecography 2023:e06457.
Fuentes, M., B. M. Van Doren, D. Fink, and D. Sheldon (2023). BirdFlow: Learning seasonal bird movements from eBird data. Methods in Ecology and Evolution 14:923–938.
Keyser, S. R., D. Fink, D. Gudex‐Cross, V. C. Radeloff, J. N. Pauli, and B. Zuckerberg (2023). Snow cover dynamics: an overlooked yet important feature of winter bird occurrence and abundance across the United States. Ecography 2023.
Li, J., D. Fink, C. Wood, C. P. Gomes, and Y. Xue (2023). Provable optimization of quantal response leader-follower games with exponentially large action spaces. Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems, Richland,SC.
Min, Y., E. T. Miller, D. Fink, and C. P. Gomes (2023). Joint time–frequency scattering-enhanced representation for bird vocalization classification. NeurIPS 2023 Computational Sustainability: Promises and Pitfalls from Theory to Deployment. New Orleans, Louisiana.
Robinson, O. J., J. B. Socolar, E. F. Stuber, T. Auer, A. J. Berryman, P. H. Boersch-Supan, D. J. Brightsmith, A. H. Burbidge, S. H. M. Butchart, C. L. Davis, A. M. Dokter, et al. (2022). Extreme uncertainty and unquantifiable bias do not inform population sizes. Proceedings of the National Academy of Sciences 119:e2113862119.
La Sorte, F. A., A. Johnston, A. D. Rodewald, D. Fink, A. Farnsworth, B. M. Van Doren, T. Auer, and M. Strimas‐Mackey (2022). The role of artificial light at night and road density in predicting the seasonal occurrence of nocturnally migrating birds. Diversity and Distributions 28:992–1009.
Vincent, J. G., R. Schuster, S. Wilson, D. Fink, and J. R. Bennett (2022). Clustering community science data to infer songbird migratory connectivity in the Western Hemisphere. Ecosphere 13:e4011.
La Sorte, F. A., K. G. Horton, A. Johnston, D. Fink, and T. Auer (2022). Seasonal associations with light pollution trends for nocturnally migrating bird populations. Ecosphere 13:e3994.
Ng, W. H., D. Fink, F. A. La Sorte, T. Auer, W. M. Hochachka, A. Johnston, and A. M. Dokter (2022). Continental‐scale biomass redistribution by migratory birds in response to seasonal variation in productivity. Global Ecology and Biogeography 31:727–739.
Zhao, W., S. Kong, J. Bai, D. Fink, and C. Gomes (2021). HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders. Proceedings of the AAAI Conference on Artificial Intelligence 35:15016–15024.
Gudex-Cross, D., S. R. Keyser, B. Zuckerberg, D. Fink, L. Zhu, J. N. Pauli, and V. C. Radeloff (2021). Winter Habitat Indices (WHIs) for the contiguous US and their relationship with winter bird diversity. Remote Sensing of Environment 255:112309.
Gomes, C. P., D. Fink, R. B. van Dover, and J. M. Gregoire (2021). Computational sustainability meets materials science. Nature Reviews Materials 6:645–647.
Johnston, A., W. M. Hochachka, M. E. Strimas-Mackey, V. Ruiz Gutierrez, O. J. Robinson, E. T. Miller, T. Auer, S. T. Kelling, and D. Fink (2021). Analytical guidelines to increase the value of community science data: An example using eBird data to estimate species distributions. Diversity and Distributions 27:1265–1277.
Ruiz-Gutierrez, V., E. R. Bjerre, M. C. Otto, G. S. Zimmerman, B. A. Millsap, D. Fink, E. F. Stuber, M. Strimas, and O. J. Robinson (2021). A pathway for citizen science data to inform policy: A case study using eBird data for defining low‐risk collision areas for wind energy development. Journal of Applied Ecology 58:1104–1111.
Cohen, J. M., D. Fink, and B. Zuckerberg (2021). Extreme winter weather disrupts bird occurrence and abundance patterns at geographic scales. Ecography 44:1143–1155.
Robinson, O. J., V. Ruiz-Gutierrez, M. D. Reynolds, G. H. Golet, M. E. Strimas-Mackey, and D. Fink (2020). Integrating citizen science data with expert surveys increases accuracy and spatial extent of species distribution models. Diversity and Distributions 26:976–986.
Cohen, J. M., D. Fink, and B. Zuckerberg (2020). Avian responses to extreme weather across functional traits and temporal scales. Global Change Biology 26:4240–4250.
Fink, D., T. Auer, A. Johnston, V. Ruiz‐Gutierrez, W. M. Hochachka, and S. Kelling (2020). Modeling avian full annual cycle distribution and population trends with citizen science data. Ecological Applications 30:e02056.
Johnston, A., T. Auer, D. Fink, M. Strimas‐Mackey, M. Iliff, K. V. Rosenberg, S. Brown, R. Lanctot, A. D. Rodewald, and S. Kelling (2020). Comparing abundance distributions and range maps in spatial conservation planning for migratory species. Ecological Applications 30:e02058.
Johnston, A., N. Moran, A. Musgrove, D. Fink, and S. R. Baillie (2020). Estimating species distributions from spatially biased citizen science data. Ecological Modelling 422:108927.
Klingbeil, B. T., F. A. La Sorte, C. A. Lepczyk, D. Fink, and C. H. Flather (2020). Geographical associations with anthropogenic noise pollution for North American breeding birds. Global Ecology and Biogeography 29:148–158.
Coleman, T., L. Mentch, D. Fink, F. A. La Sorte, D. W. Winkler, G. Hooker, and W. M. Hochachka (2020). Statistical inference on Tree Swallow migration with random forests. Journal of the Royal Society of Statistics: Series C (Applied Statistics) 69:973–989.
Cardoso, G. C., B. T. Klingbeil, F. A. La Sorte, C. A. Lepczyk, D. Fink, and C. H. Flather (2020). Exposure to noise pollution across North American passerines supports the noise filter hypothesis. Global Ecology and Biogeography 29:1430–1434.
Gomes, C., T. Dietterich, C. Barrett, J. Conrad, B. Dilkina, S. Ermon, F. Fang, A. Farnsworth, A. Fern, X. Fern, D. Fink, et al. (2019). Computational sustainability: computing for a better world and a sustainable future. Communications of the ACM 62:56–65.
Johnston, A., W. Hochachka, M. Strimas-Mackey, V. R. Gutierrez, O. Robinson, E. Miller, T. Auer, S. Kelling, and D. Fink (2019). Best practices for making reliable inferences from citizen science data: Case study using eBird to estimate species distributions. bioRxiv. https://doi.org/10.1101/574392
Kelling, S., A. Johnston, A. Bonn, D. Fink, V. Ruiz-Gutierrez, R. Bonney, M. Fernandez, W. M. Hochachka, R. Julliard, R. Kraemer, and R. Guralnick (2019). Using Semistructured Surveys to Improve Citizen Science Data for Monitoring Biodiversity. BioScience 69:170–179.
Schuster, R., S. Wilson, A. D. Rodewald, P. Arcese, D. Fink, T. Auer, and Joseph. R. Bennett (2019). Optimizing the conservation of migratory species over their full annual cycle. Nature Communications 10:1754.
La Sorte, F. A., D. Fink, and A. Johnston (2019). Time of emergence of novel climates for North American migratory bird populations. Ecography 42:1079–1091.
Horton, K. G., B. M. Van Doren, F. A. La Sorte, E. B. Cohen, H. L. Clipp, J. J. Buler, D. Fink, J. F. Kelly, and A. Farnsworth (2019). Holding steady: Little change in intensity or timing of bird migration over the Gulf of Mexico. Global Change Biology 25:1106–1118.
Robinson, O. J., V. Ruiz-Gutierrez, D. Fink, R. J. Meese, M. Holyoak, and E. G. Cooch (2019). [In press] Using citizen science data in integrated population models to inform conservation decision-making. Biological Conservation.
Horton, K. G., B. M. Van Doren, F. A. La Sorte, D. Fink, D. Sheldon, A. Farnsworth, and J. F. Kelly (2018). Navigating north: How body mass and winds shape avian flight behaviours across a North American migratory flyway. Ecology Letters 21:1055–1064.
Robinson, O. J., V. Ruiz-Gutierrez, D. Fink, R. J. Meese, M. Holyoak, and E. G. Cooch (2018). Using citizen science data in integrated population models to inform conservation. Biological Conservation 227:361–368.
Dokter, A. M., A. Farnsworth, D. Fink, V. Ruiz-Gutierrez, W. M. Hochachka, F. A. La Sorte, O. J. Robinson, K. V. Rosenberg, and S. Kelling (2018). Seasonal abundance and survival of North America's migratory avifauna determined by weather radar. Nature Ecology & Evolution 2:1603–1609.
La Sorte, F. A., D. Fink, and A. Johnston (2018). Seasonal associations with novel climates for North American migratory bird populations. Ecology Letters 21:845–856.
Johnston, A., D. Fink, W. M. Hochachka, and S. Kelling (2018). Estimates of observer expertise improve species distributions from citizen-science data. Methods in Ecology and Evolution 9:88–97.
Cherel, N., J. Reesman, A. Sahuguet, T. Auer, and D. Fink (2017). "Birds in the Clouds": Adventures in Data Engineering. arXiv:1710.08521 [cs].
Chen, D., Y. Xue, D. Fink, S. Chen, and C. P. Gomes (2017). Deep Multi-Species Embedding. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). pp. 3639–3646.
La Sorte, F. A., D. Fink, P. J. Blancher, A. D. Rodewald, V. Ruiz-Gutierrez, K. V. Rosenberg, W. M. Hochachka, P. H. Verburg, and S. Kelling (2017). Global change and the distributional dynamics of migratory bird populations wintering in Central America. Global Change Biology 23:5284–5296.
La Sorte, F. A., D. Fink, J. J. Buler, A. Farnsworth, and S. A. Cabrera-Cruz (2017). Seasonal associations with urban light pollution for nocturnally migrating bird populations. Global Change Biology 23:4603–4619.
Sullivan, B. L., T. Phillips, A. A. Dayer, C. L. Wood, A. Farnsworth, M. J. Iliff, I. J. Davies, A. Wiggins, D. Fink, W. M. Hochachka, A. D. Rodewald, et al. (2017). Using open access observational data for conservation action: A case study for birds. Biological Conservation 208:5–14.
Reynolds, M. D., B. L. Sullivan, E. Hallstein, S. Matsumoto, S. Kelling, M. Merrifield, D. Fink, A. Johnston, W. M. Hochachka, N. E. Bruns, M. E. Reiter, et al. (2017). Dynamic conservation for migratory species. Science Advances 3:e1700707.
La Sorte, F. A., and D. Fink (2017). Projected changes in prevailing winds for transatlantic migratory birds under global warming. Journal of Animal Ecology 86:273–284.
La Sorte, F. A., and D. Fink (2017). Migration distance, ecological barriers and en-route variation in the migratory behaviour of terrestrial bird populations. Global Ecology and Biogeography 26:216–227.
Daniel Fink
Center Avian Population Studies
Work607-254-2401
Email df36@cornell.edu

Join Our Email List

The Cornell Lab will send you updates about birds, birding, and opportunities to help bird conservation. Sign up for email and don’t miss a thing!

Golden-cheeked Warbler by Bryan Calk/Macaulay Library