We conduct data-intensive research on lake ecosystems. We have steadily increased the size and complexity of the datasets that we use to develop the knowledge and theories around landscape limnology and macrosystems ecology. In conducting this research, we have developed two focus areas to address the challenges of conducting data-intensive research in ecology.
(A) Developing novel quantitative tools to analyze ecological research questions at broad scales. For this focus area, we collaborate with computer scientists and statisticians to develop needed computational approaches for analyzing large ecological datasets to answer fundamental questions at broad spatial and temporal extents.
(B) Studying the cultural issues surrounding the increased use of data-intensive methods in ecology and the challenges these methods pose to how science in ecology has been and will be conducted in the future. For this focus area, we collaborative with philosophers and historians of science and psychologists to analyze the challenges and offer solutions to address them.
(A) Developing novel quantitative tools
Example publications emphasizing data-intensive research approaches
Lottig, N., P.-N. Tan, T. Wagner, K.S. Cheruvelil, P.A. Soranno, E. Stanley, C. Scott, C. Stow, S. Yuan. 2017. Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers. Ecosphere 8(12):e02024. https://doi.org/10.1002/ecs2.2024
Yuan, S., J. Zhou, P.N. Tan, C.E. Fergus, T. Wagner, T., P.A. Soranno. 2017. Multi-Level Multi-Task Learning for Modeling Cross-Scale Interactions in Nested Geospatial Data. Proceedings of the IEEE International Conference on Data Mining. New Orleans, Louisiana. November 18-21 (2017).
Soranno, P.A., L.C. Bacon, M. Beauchene, K.E. Bednar, E.G. Bissell, C.K. Boudreau, M.G. Boyer, M.T. Bremigan, S.R. Carpenter, J.W. Carr, K.S. Cheruvelil, S.T. Christel, M. Claucherty, S.M. Collins, J.D. Conroy, J.A. Downing, J. Dukett, C.E. Fergus, C.T. Filstrup, C. Funk, M.J. Gonzalez, L.T. Green, C. Gries, J.D. Halfman, S.K. Hamilton, P.C. Hanson, E.N. Henry, E.M. Herron, C. Hockings, J.R. Jackson, K. Jacobson-Hedin, L.L. Janus, W.W. Jones, J.R. Jones, C.M. Keson, K.B.S. King, S.A. Kishbaugh, J.-F. Lapierre, B. Lathrop, J.A. Latimore, Y. Lee, N.R. Lottig, J.A. Lynch, L.J. Matthews, W.H. McDowell, K.E.B. Moore, B.P. Neff, S.J. Nelson, S.K. Oliver, M.L. Pace, D.C. Pierson, A.C. Poisson, A.I. Pollard, D.M. Post, P.O. Reyes, D.O. Rosenberry, K.M. Roy, L.G. Rudstam, O. Sarnelle, N.J. Schuldt, C.E. Scott, N.K. Skaff, N.J. Smith, N.R. Spinelli, J.J. Stachelek, E.H. Stanley, J.L. Stoddard, S.B. Stopyak, C.A. Stow, J.M. Tallant, P.-N. Tan, A.P. Thorpe, M.J. Vanni, T. Wagner, G. Watkins, K.C. Weathers, K.E. Webster, J.D. White, M.K. Wilmes, S. Yuan. 2017. LAGOS-NE: A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. lakes. Gigascience 6(12) https://doi.org/10.1093/gigascience/gix101
Yuan, S., P.-N. Tan, K.S. Cheruvelil, C.E. Fergus, N.K. Skaff, and P.A. Soranno. 2017. Hash-based feature learning for incomplete continuous-valued data. Proceedings of the 2017 SIAM International Conference on Data Mining. Houston, Texas. April 27-29, 2017. PDF
Cheruvelil, K.S., S. Yuan, K.E. Webster, P.-N. Tan, J.-F. Lapierre, S.M. Collins, C.E. Fergus, C.E. Scott, E.N. Henry, P.A. Soranno, C.T. Filstrup, T. Wagner. 2017. Creating multi-themed ecological regions for macrosystems ecology: Testing a flexible, repeatable, and accessible clustering method. Ecology and Evolution 7: 3046–3058. doi: 10.1002/ece3.2884 Open access
Ruegg, J., C. Gries, B. Bond-Lamberty, G.J. Bowen, B.S. Felzer, N.E. McIntyre, P.A. Soranno, K.L. Vanderbilt, K.C. Weathers. 2014. Completing the data life cycle: Using information management in macrosystems ecology research. Frontiers in Ecology and the Environment. 12(1):24-30. Open-access
Levy, O., B.A. Ball, B. Bond-Lamberty, K.S. Cheruvelil, A.O. Finley, N. Lottig, S. Punyasena, J. Xiao, J. Zhou, L.B. Buckley, J. Clark, C.T. Filstrup, T. Keitt, J.R. Kellner, A.K. Knapp, A. Richardson, C. Stow, D. Tcheng, M. Toomey, R. Vargas, J.W. Voordeckers, T. Wagner, J.W. Williams. 2014. Approaches for advancing scientific understanding of macrosystems.Frontiers in Ecology and the Environment 12: 15-23. Open-access
(B) The cultural issues related to data-intensive ecology
Example publications focused on the cultural issues surrounding data-intensive ecology
Resnik, D.B., K.C. Elliott, P.A. Soranno, and E.M. Smith. 2017. Data-intensive science and research integrity. Accountability in Research. 24(6):344-358. doi: 10.1080/08989621.2017.1327813
Elliott, K.C., K.S. Cheruvelil, G.M. Montgomery, and Soranno, P.A.. 2016. Conceptions of good science in our data-rich world. BioScience 66(10) 1-10. 10.1093/biosci/biw115 Open access *Selected to be Editors’ Choice.
Data Intensive Landscape Limnology Lab 