Crowdsourcing Meets Ecology: Hemisphere-Wide Spatiotemporal Species Distribution Models

  • Daniel Fink Cornell University
  • Theodoros Damoulas New York University
  • Nicholas E. Bruns Cornell University
  • Frank A. La Sorte  Cornell University
  • Wesley M. Hochachka  Cornell University
  • Carla P. Gomes Cornell University
  • Steve Kelling Cornell University


Ecological systems are inherently complex. The processes that affect the distributions of animals and plants operate at multiple spatial and temporal scales, presenting a unique challenge for the development and coordination of effective conservation strategies, particularly for wide-ranging species. In order to study ecological systems across scales, data must be collected at fine resolutions across broad spatial and temporal extents. Crowdsourcing has emerged as an efficient way to gather these data by engaging large numbers of people to record observations. However, data gathered by crowdsourced projects are often biased due to the opportunistic approach of data collection. In this article, we propose a general class of models called AdaSTEM, (for adaptive spatio-temporal exploratory models), that are designed to meet these challenges by adapting to multiple scales while exploiting variation in data density common with crowdsourced data. To illustrate the use of AdaSTEM, we produce intra-seasonal distribution estimates of long-distance migrations across the Western Hemisphere using data from eBird, a citizen science project that utilizes volunteers to collect observations of birds. Subsequently, model diagnostics are used to quantify and visualize the scale and quality of distribution estimates. This analysis shows how AdaSTEM can automatically adapt to complex spatiotemporal processes across a range of scales, thus providing essential information for full-life cycle conservation planning of broadly distributed species, communities, and ecosystems.

Author Biographies

Daniel Fink, Cornell University
Cornell Lab of Ornithology
Theodoros Damoulas, New York University
Center for Urban Science and Progress
Nicholas E. Bruns, Cornell University
Cornell University
Frank A. La Sorte , Cornell University
Cornell Lab of Ornithology
Wesley M. Hochachka , Cornell University
Cornell Lab of Ornithology
Carla P. Gomes, Cornell University
Department of Computer Science
Steve Kelling, Cornell University
Cornell Lab of Ornithology