OOS 5
Uncertainty Analysis: A Critical Step in Ecological Synthesis

Monday, August 5, 2013: 1:30 PM-5:00 PM
101E, Minneapolis Convention Center
Organizer:
Ruth D. Yanai
Co-organizers:
Jeffrey Taylor and Mark E. Harmon
Moderator:
John J. Battles
Ecology is entering an exciting era in which the number and availability of long-term data sets are increasing exponentially. There is an unprecedented need to synthesize these data to address current scientific and societal problems. Great progress has been made on linking data and theory, including spatial integration and interdisciplinary combination. The question is no longer how to synthesize, but how well we are linking information from disparate sources and how to indentify the most important areas for improvement. These synthetic approaches will demand increased proficiency and rigor in uncertainty analysis, to provide a metric of progress in synthesis science. This OOS will highlight current developments in uncertainty estimation across many fields of ecology and provide guidance for large-scale synthesis research. Speakers will be encouraged to provide recommendations for standardized approaches to uncertainty estimation and a vision for meeting future needs. Further development, understanding, and dissemination of the latest statistical techniques for deriving these estimates will both inform ecological sampling design and equip up-and-coming ecologists with critical skills. Speakers will examine sources of uncertainty and its general role in synthesis science. Case studies will include a range of topics and approaches ranging from population ecology and small watershed nutrient cycling budgets to landscape carbon budgets. Methodologies presented will include parametric statistical approaches, bootstrap analysis, Monte Carlo sampling, and Bayesian hierarchical analysis. Uncertainty introduced by spatial and temporal interpolation are common themes across scales from plots to the continental ecological observatory network.
1:30 PM
1:50 PM
 Quantifying uncertainty in ecology: Examples from small watershed studies
John L. Campbell, United States Department of Agriculture Forest Service; Ruth D. Yanai, SUNY College of Environmental Science and Forestry; Mark B. Green, Plymouth State University
2:30 PM
 Global Sensitivity Analysis for Impact Assessments
Matthew Aiello-Lammens, Stony Brook University; H. Resit Akcakaya, Stony Brook University
2:50 PM
 Optimizing environmental monitoring designs
Carrie R. Levine, UC Berkeley; Ruth D. Yanai, SUNY College of Environmental Science and Forestry; Gregory Lampman, NYSERDA; Douglas A. Burns, US Geologic Survey; Charles T. Driscoll, Syracuse University; Gregory B. Lawrence, U.S. Geological Survey; Jason A. Lynch, US Environmental Protection Agency; Nina Schoch, Biodiversity Research Institute
3:10 PM
3:20 PM
 Uncertainty due to gap-filling in long-term hydrologic datasets
Craig R. See, SUNY College of Environmental Science and Forestry; Ruth D. Yanai, SUNY College of Environmental Science and Forestry; Mark B. Green, Plymouth State University; Douglas I. Moore, University of New Mexico
3:40 PM
 Uncertainty in an uncertain world: Using scientific judgment for evaluating uncertainty in measurement results
Janae L. Csavina, National Ecological Observatory Network (NEON, Inc.); Jeffrey Taylor, National Ecological Observatory Network (NEON, Inc.); Joshua A. Roberti, National Ecological Observatory Network (NEON, Inc.)
4:00 PM
 NEON's approach to uncertainty estimation for sensor-based measurements
Joshua A. Roberti, National Ecological Observatory Network (NEON, Inc.); Jeffrey R. Taylor, National Ecological Observatory Network (NEON, Inc.); Henry W. Loescher, National Ecological Observatory Network (NEON, Inc.); Janae L. Csavina, National Ecological Observatory Network (NEON, Inc.); Derek E. Smith, National Ecological Observatory Network (NEON, Inc.)
4:20 PM
 Estimating uncertainty for continental scale measurements
Jeffrey Taylor, National Ecological Observatory Network (NEON, Inc.); Joshua Roberti, NEON, Inc.; Derek Smith, National Ecological Observatory Network (NEON, Inc.); Steve Berukoff, National Ecological Observatory Network; Henry W. Loescher, National Ecological Observatory Network (NEON, Inc.)
4:40 PM
 Reducing uncertainty through data-driven model development
David S. LeBauer, University of Illinois; Michael Dietze, Boston University; Deepak Jaiswal, University of Illinois; Rob Kooper, University of Illinois; Stephen P. Long, University of Illinois at Urbana-Champaign; Shawn P. Serbin, University of Wisconsin - Madison; Dan Wang, University of Illinois