Improving Ecosystem Carbon Budget Estimates and Forging Linkages for Informing Decisions I
Innovations in carbon measurement technologies, platforms and coordinated networks are advancing our ability to understand carbon stores, carbon cycle feedbacks, and the level of threat they pose. For instance, interagency, multi-partner organizations such as the U.S. Carbon Cycle Science Program (CCSP) and the E.U. Integrated Carbon Observation System (ICOS) working with thousands of multi-disciplinary community scientists, produce and use tremendous amounts of high quality data and analyses for understanding, observing and monitoring the carbon cycle. This session highlights novel data sets, quantitative methods, as well as innovative and emerging partnerships employed in characterizing the carbon cycle, with special attention to understanding the uncertainty in carbon budgets across land, air and water to inform management and policy decisions from local to global scales.
Uncertainty in Measurements of Trees in the US Forest Service Forest Inventory and Analysis (FIA) Program. Ruth D. Yanai, John L Campbell, Alexander Young Gretchen A. Dillon, Mark B. Green, Charles J Barnett, Grant M Domke and Christopher W Woodall Abstract Presentation
Correcting Errors in Error Propagation for REDD+ Carbon Accounting. Craig Wayson, Ruth D. Yanai, James W Kirchner, Andrew Lister, John L Campbell, Mark Green, and John E Drake. Abstract
Detecting and accounting for allometric variation in trees: Implications for quantifying forest recovery (Invited) John Battles, Jacob Levine, Joseph Battles, and Perry de Valpine. Abstract
How to Estimate Statistically Detectable Trends in a Time Series: A Study of Soil Carbon and Nutrient Concentrations at the Calhoun LTSE (Invited) Daniel deB. Richter Jr, Megan L. Mobley, Yang Yang, Kevin A. Nelson, Allan R Bacon and Paul Heine. Abstract
Long Term-Ecological Research (LTER) Network All Scientists' MeetingSeptember 30 - October 4, 2018, Asilomar Conference Grounds, CA
Workshop: Best monitoring through uncertainty analysis: Optimize allocation of effort, save time and moneyOctober 3, 2018
Periodic evaluation of monitoring programs is important to accommodate changing objectives, technological advances, and the accumulation of information over time. Uncertainty analysis can provide a basis for making difficult decisions about reducing or redirecting sampling effort, as will be illustrated in case studies involving mercury contamination in fish and loons, measurement uncertainty in forest inventory (FIA), and the number and placement of precipitation gauges at Hubbard Brook. Please come to learn about and discuss what analyses to use in which circumstances and how they might be applied at your site.
The QUEST Session at American Geophysical Unionmerged with three other proposed sessions to get a full day of talks, Monday December 12, in Moscone West 2004. Quantifying Uncertainties and Merging Observations, Experiments, and Models for Improving Estimation, Mapping, and Forecasting of Terrestrial Ecosystem Dynamics I and II. Session: B11J and B12C
Quantifying uncertainty in studies of forests is important to establish the significance of findings, make predictions with known confidence, and guide investments in research and monitoring. This symposium will address sources of uncertainty in estimates of carbon and nutrients in forest soils, above- and belowground biomass, and ecosystem inputs and outputs. Presentations will address sources of uncertainty in forest ecosystem studies, including natural spatial and temporal variation, measurement error, model uncertainty, and model selection error. Examples include the importance of spatial variation in detecting change over time in soil stores and measurement error in forest inventory due to identifying or classifying trees, measuring them, and determining whether trees are live or dead and in or out of a plot. Model uncertainty within and across models is important in biomass estimation and climate predictions. Presentations will also address how these uncertainties influence monitoring designs or affect management and policy decisions.
Organizers: Mary Beth Adams, Craig See, Ruth Yanai, and Scott Chang
A Survey of Current Practices in Uncertainty Analysis in Ecosystem Ecology. Craig See*, Ruth Yanai and John Campbell SlideshowPDF
Horizon vs. Layer Sampling in Forest Soils: Statistical Efficiency. Chris Johnson. SlideshowPDF
Does Long-Term Storage of Air-Dried Soils Effect the Results of Chemical Analyses Commonly Performed on Forest Soils? Gregory Lawrence, Michael Antidormi*, Matthew Vadeboncoeur, Paul Hazlett, Ivan Fernandez, Scott Bailey, and Donald Ross. SlideshowPDF
How to Avoid Errors in Your Error Analyses and Gain Confidence in Your Confidence Intervals. Ruth Yanai*, Bradley Case, Hannah Buckley, and Richard Woolens. SlideshowPDF
Fake Forests and Quantifying Uncertainty in Allometric Equations for the ‘Real World'. Craig Wayson*,Oswaldo Carrillo,and Marcela Olguín. SlideshowPDF
Full Error Propagation in Carbon Stock Estimation of Mexico. Oswaldo Carrillo* and Craig Wayson. SlideshowPDF
Regional Scale Uncertainty Estimates from Fine-Scale Forest Inventory: Stored and Accumulated Forest Carbon in the Eastern US.
Bradley Tomasek*, Erin Schliep,Alan Gelfand,and James Clark. SlideshowPDF
Carbon Cycling of Forest Ecosystems As a Fuzzy System: An Attempt to Assess Uncertainties. Anatoly Shvidenko*, Florian Kraxner,Dmitry Schepaschenko,and Shamil Maksyutov. (Presentation not available)
Airborne Laser Scanning-Assisted Sampling for Remote Regions. Ronald McRobert*,Qi Chen,and Grant Domke. SlideshowPDF
International Long Term-Ecological Research Open Science Meeting
October 9-13, 2016, Kruger National Park, South Africa
The International LTER Network held its first global Open Science Meeting. QUEST collaborators organized an "Estimating Uncertainty in Measurements, Experiments, and Models Workshop.
Module 2: Experimental Design for Long-Term Monitoring Christina Staudhammer (U of Alabama)
Long Term-Ecological Research All Scientist's Meeting August 30-September 2, 2015, Estes Park, CO
This year's conference was organized around the theme "From Long-term data to understanding: toward a predictive ecology", and showcased 300 posters and more than 75 formal and ad-hoc working group meetings. QUEST collaborators meet informally, but also used their sites data in these presentations:
Intro to QUEST: uncertainty in ecosystem budgets, Ruth Yanai, SUNY ESF
Streamflow Gaps:† Why they occur and what we can do about it, Craig See, Coweeta Hydrological Laboratory
Uncertainty in net hydrologic flux of calcium, John Campbell, USFS
Spatial patterns of precipitation in complex terrain, Melissa Slater, NEON
Connecting uncertainty estimates and QA/QC methods.† Josh Roberti, NEON
Bayesian hierarchical analysis of demographic processes, Carrie Levine, UC Berkeley
UFRO World Congress: Sustaining Forests, Sustaining People, The Role of ResearchOctober 5-11, 2014 Salt Lake City, Utah, USA.
Presenters from four different countries described sources of uncertainty in estimates of forest carbon and nutrient pools and fluxes, including natural spatial and temporal variation, measurement error, model uncertainty, and model selection, and addressed how these uncertainties can guide monitoring designs and affect management and policy decisions.
Uncertainty In Forest Management Planning: Why It Will Not Go Away And What Should We Do About It, Pierre Bernier, Natural Resources Canada
Forest Carbon Stock Change Uncertainty Estimation In Mexico, Oswaldo Carrillo, Proyecto Mexico-Noruega, Comision Nacional Forestal, Mexico
Uncertainty In Forest Carbon And Nutrient Budgets Ruth Yanai, SUNY-ESF, United States
Improving Forestry Decision Making By Accounting For Uncertainty, Annika Kangas, Helsingin Ylipisto (University of Helsinki), Finland
Technical Sessions #58A & B: Quantifying Uncertainty in Forest Measurements and Models: Approaches and Applications.
Subplenary session at IUFRO World Congress, Salt Lake City. October 5-11, 2014
Presentations shared approaches to analyzing uncertainty in forest measurements and giving examples of applications of uncertainty in above- and belowground estimates of forest biomass, carbon, and nutrient pools and fluxes, as well as other ecosystem attributes.
Distribution of errors along stem in carbon estimation using hemispherical photography, Bogdan Strimbu, Louisiana Tech University, United States
Assessment of Scenario Generation Approaches for Forest Management Planning Through Stochastic Programming, Kyle Eyvindson, University of Helsinki, Finland
Modeling the Intra-Stand Variability of Carbon and Water Fluxes in Clonal Eucalyptus Plantations. Mathias Christina, French National Institue for Agricultural Research, France
Allometric Equations for Biomass Estimation in Central African Rain Forests: State of the Art and Challenges. Nicolas Picard, Cirad, France and Cameroon
Tools for Estimating Uncertainty in Ecology @ ESA August 10, 2014
Although methods are well established for statistical analysis of most experimental designs, there are fields in Ecology where it is more difficult to establish confidence in results (e.g., in catchment studies, treatments are rarely replicated). For environmental networks, using standardized approaches ensures that results are comparable, but sometimes the same statistical technique is not applicable to comparable data sets (e.g. when there are significant differences in the sample size of the same population at two geographically distinct locations). Many of these concerns can be addressed through the appropriate use of tools for uncertainty analysis. This workshop will highlight current developments in uncertainty estimation across many fields of ecology. Overview presentations will focus on practical examples of how uncertainty calculations can inform data over small-to-large scales. Data packages and software tools will be shared with the attendees. Participants are encouraged to bring their own data sets and laptop computers; we will provide data for the exercises if you donít bring your own. We welcome participation by researchers in all career stages and from a broad array of ecological disciplines.
Quantifying Measurement Uncertainty: An Introduction. Josh Roberti, NEON
Why should we be uncertain? Jeff Taylor, NEON
Using Excel and R for Uncertainty Analysis. Josh Roberti, NEON
Tools for Estimating Uncertainty in Ecology. Ruth Yanai, ESF
Paired Watershed Studies. John Campbell, USFS
American Geophysical Union Annual MeetingSan Francisco, CA, August 5, 2013
Quantifying Uncertainty in Biogeochemical Studies I session. Oral presentations by Brent Aulenbach, John Campbell, Josh Roberti, and Ruth Yanai.
Uncertainty Analysis: A Critical Step in Ecological Synthesis August 5, 2013
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 link information from disparate sources and how to identify 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 highlights current developments in uncertainty estimation across many fields of ecology and provided guidance for large-scale synthesis research. Speakers were 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 both inform ecological sampling design and equip up-and-coming ecologists with critical skills. Speakers examined sources of uncertainty and its general role in synthesis science. Case studies included a range of topics and approaches ranging from population ecology and small watershed nutrient cycling budgets to landscape carbon budgets. Methodologies presented 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.
Uncertainty analysis: An evaluation metric for synthesis science. Mark E. Harmon*, Oregon State University Abstract | Slideshare
Quantifying uncertainty in ecology: Examples from small watershed studies. John L. Campbell*, USDA Forest Service; Ruth D. Yanai, SUNY College of Environmental Science and Forestry (ESF); Mark B. Green, Plymouth State University Abstract | Slideshare
Better ignorant than misled: Including uncertainty in forecasts supporting management and policy. N. Thompson Hobbs*, Colorado State University Abstract | PDF
Global Sensitivity Analysis for Impact Assessments. Matthew Aiello-Lammens*, Stony Brook University; H. Resit Akcakaya, Stony Brook University. Abstract | Slideshare
Optimizing environmental monitoring designs. Carrie R. Levine, UC Berkeley; Ruth D. Yanai*, SUNY ESF; Gregory Lampman, NYSERDA; Douglas A. Burns, US Geologic Survey; Charles T. Driscoll, Syracuse University; Gregory B. Lawrence, USGS; Jason A. Lynch, US EPA; Nina Schoch, Biodiversity Research Institute. Abstract | Slideshare
Uncertainty in an uncertain world: Using scientific judgment for evaluating uncertainty in measurement results. Janae L. Csavina*; Jeffrey Taylor, Joshua A. Roberti, all National Ecological Observatory Network (NEON, Inc.) Abstract | Slideshare
NEON's approach to uncertainty estimation for sensor-based measurements. Joshua A. Roberti*, Jeffrey R. Taylor, Henry W. Loescher, Janae L. Csavina, Derek E. Smith, all NEON, Inc. Abstract | Slideshare
Estimating uncertainty for continental scale measurements. Jeffrey Taylor*, Joshua Roberti, Derek Smith,; Steve Berukoff, Henry W. Loescher, all NEON, Inc. Abstract
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. Abstract | Slideshare
2012 Long Term-Ecological Research (LTER) All Scientists MeetingEstes Park, CO, September 11, 2012
This preceded the first Quantifying Uncertainty in Ecosystem Studies meeting in Boston, March 14-15 2011.
The webinar and meeting were the first phases of our Long Term Ecological Research Network Office Synthesis Working Group (LTER SWG)'s evaluation of uncertainty in hydrologic inputs, outputs, and net hydrologic flux of major elements across small watersheds with diverse characteristics.
History of Quest: Ruth Yanai explains what we do, why it's important, and how it came to be.
Uncertainty Analysis of Hubbard Brook hydrologic fluxes: Mark Green explains the use of Theissen polygons and of Monte Carloand continues with Annual dissolved inorganic nitrogen stream export
Sources of Uncertainty: Mark Harmon sums up where present knowledge is lacking.