QUEST Paper in Journal of Forestry

QUEST Authors Ruth Yanai, Carrie Rose Levine, Mark Green, and John Campbell have published an article in this month’s Journal of Forestry titled “Quantifying uncertainty in forest nutrient budgets”

ABSTRACT: Nutrient budgets for forested ecosystems have rarely included error analysis, in spite of the importance of uncertainty to interpretation and extrapolation of the results. Uncertainty derives from natural spatial and temporal variation and also from knowledge uncertainty in measurement and models. For example, when estimating forest biomass, researchers commonly report sampling uncertainty but rarely propagate the uncertainty in the allometric equations used to estimate tree biomass, much less the uncertainty in the selection of which allometric equations to use. Change over time may have less uncertainty than a single measurement, if the measures are consistently biased, as by the use of inaccurate allometric equations or soil sampling techniques. Quantifying uncertainty is not as difficult as is sometimes believed. Here, we describe recent progress in quantifying uncertainty in biomass, soils, and hydrologic inputs and outputs, using examples from the Hubbard Brook Experimental Forest, New Hampshire, USA.

Click here to download the pdf. 

QUEST Workshop at LTER All Scientists Meeting

Members of QUEST held a two hour workshop entitled “Quantifying Uncertainty in Ecosystem Studies” at the 2012 LTER All Scientists Meeting.  The two hour discussion-based workshop started with a round of introductions in which the 40 participants identified their system of study, and the biggest source of uncertainty they face.  The rest of the time was devoted by ten “lightening round” presentations on uncertainty in different ecosystem components (see presenters below).  Each five minute talk was followed up by a group discussion.   We received positive feedback from many of the workshop participants, and a proposal has been submitted for an organized oral session at next years ESA conference in Minneapolis. Full meeting notes are available for download below

List of presenters:

John Campbell:  Intro to QUEST, Participant introductions (what's your biggest uncertainty?)
Harmon:  Intro to sources of uncertainty
Adam Skibbe: Precipitation Uncertainty

Xuesong Zhang: Precipitation Uncertainty
John Battles: Biomass Uncertainty
Mark Green: Streamflow Uncertainty
Ruth Yanai: Uncertainty in Soils
Jeff Taylor: NEON products and their uncertainty
Craig See: Uncertainty in Data Gaps
Carrie Rose Levine: Monitoring Uncertainty

Atmospheric deposition working group meets in Oregon

The LTER synthesis working group on quantifying uncertainty in wet atmospheric deposition convened last week in Oregon.   Participants met May 21-23 at HJ Andrews Experimental Forest to share current research and coordinate future efforts.  The first day included presentations on long-term collection of deposition data, variability in monsoon precipitation (Sevilleta LTER), uncertainty in data gap filling, a hierarchical Bayesian analysis of precipitation patterns, and an analysis of monitoring intensity.  Presentations were followed up with discussion and planning sessions.

The following day included a presentation by Dr. Chris Daly (OSU) on the PRISM model, and the uncertainties associated with large-scale spatiotemporal precipitation estimates and predictions.  The rest of the time was devoted to planning papers and future workshops.  Products coming out of this meeting will include a paper on uncertainty sources in unreplicated measurements (small watersheds), a paper on the effects of monitoring intensity on uncertainty, and a paper on gap filling in long-term hydrologic datasets.  Also coming out of this meeting are plans to host a workshop on uncertainty in ecosystem studies at this year’s LTER All Scientists Meeting in September (more on this when the date is confirmed).  After discussing precipitation for two days, participants were given a rainy tour of HJ Andrews Experimental Forest.

People in attendance: Dr. John Campbell (USFS), Dr. Ruth Yanai (SUNY-ESF), Dr. Shannon LaDeau (Cary Institute), Doug Moore (Sevilleta LTER), Adam Skibbe (Konza LTER), Craig See (SUNY-ESF)
Attending remotely (via video conference call): Dr. Kathleen Weathers (Cary Institute), Mathew Petrie (University of New Mexico), Dr. Mark Green (Plymouth State), Stephanie Laseter (USFS), Dr. Jennifer Knoepp (USFS), Carrie Rose Levine (SUNY-ESF)

Precipitation working group (left to right): John Campbell, Shannon Ladeau, Ruth Yanai, Doug Moore, Craig See

NEON Uncertainty Workshop at ESA 2012

Workshop:  Estimating Uncertainty and Trend Detection in Ecological Data Sets Collected by the National Ecological Observatory Network

Organizers: Jeffery Taylor, Steve Berukoff, Andrew Fox, Katherine Thibault

Description: Ecology is entering a particularly exciting phase, in which the number and availability of long-term data-sets are increasing and the construction of the nation’s first ecological observatory (NEON) has begun. This unprecedented opportunity requires a departure from traditional approaches to ecological data analyses, which have not emphasized uncertainty characterization. New approaches will demand increased proficiency and rigor in both the design of NEON sampling and the analysis of existing and forthcoming long-term ecological data. For example, NEON will collect continental-scale observations of over 500 different ecological variables at 70 sites across the country. Developing a unified approach to estimating uncertainty and detecting trends for all of these data products is therefore a significant challenge faced in the design process. Further development, understanding, and dissemination of the latest statistical techniques for deriving these quantities will both inform
sampling design and equip up-and-coming ecologists with critical skills. This half-day workshop will highlight the underlying mathematical approaches to uncertainty quantification and trend detection and relate these methods to the nationally/internationally accepted standards. Emphasis will be placed on unified approaches to spatio-temporal scaling and the
detection/attribution of long-term trending. The format will consist of 2-3 overview talks, followed by several breakout sessions, and end with a unified synthesis session. Attendees are encouraged to provide feedback and suggest alternative approaches based on their own experience. Lunch will not be provided, but afternoon snacks and refreshments (alcoholic/non-
alcoholic) will be available. NEON will sponsor all costs and the workshop will be free of charge for participants.

Uncertainty in precipitation inputs to ecosystems

Measuring the amount and chemistry of rainfall at a precipitation station is relatively straightforward.  However, estimating the input of rain water and solutes to ecosystems requires interpolation between the precipitation stations.  Various methods of interpolation are used in precipitation and atmospheric deposition studies (Garcia et al. 2008, Weathers et al. 2006), but the uncertainty in the interpolation is rarely reported or used in estimating uncertainty in deposition estimates.  

John Campbell conducted a preliminary analysis of spatial uncertainty in rainfall amounts using data from the Hubbard Brook Experimental Forest in New Hampshire. Hubbard Brook uses eleven precipitation gauges to estimate annual precipitation for six adjacent experimental watersheds. Thiessen polygons (Viessman and Lewis 1996) are used to define the area characterized by each of these eleven precipitation estimates, and precipitation to each watershed is calculated as the sum of the areas contributed by each polygon.  He compared this to several other interpolation methods (spline, inverse distance weighting, kriging, and regression modeling) and found differences of less than 1% across the methods for annual precipitation of the nine watersheds at Hubbard Brook (Figure 1).  The error associated with model selection is thus likely to be small.  The error within the models describing precipitation amounts (e.g. model or parameter error in the regression) has yet to be estimated.  Accounting for uncertainty in solute deposition is further complicated by the spatial and temporal mismatch between volume and chemistry samples, with fewer samples typically collected for solute chemistry than for rainfall volume.  Additional challenges to be addressed in estimates of atmospheric inputs are associated with the difficulty of monitoring dry deposition and cloud deposition and their interaction with vegetation structure.

Shannon LaDeau will develop a hierarchical regression model that can accommodate the spatial and temporal mismatches in precipitation volume and chemistry observations, using weekly data sampled from five watersheds at Hubbard Brook.  The regression will estimate monthly and annual wet deposition of solutes for each watershed and probability distributions for inference on predictive covariates. The model will also partition uncertainty due to measurement error, missing data, and poor model fit and will provide estimates of environmental stochasticity.  Methods for spatial interpolation of regressions will be explored and impacts on annual budgets compared, including spatial analyses packages in ArcView, R (e.g, ModelMap package) and Bayesian kriging methods in OpenBUGS (i.e., geoBugs). 

We also have support from the LTER Network Office for a Synthesis Working Group to further develop approaches to estimating uncertainty in precipitation fluxes.  We will extend our model protocol and results to similar data from other LTER sites.

Summer Course: Assimilating Long-Term Data into Ecosystem Models

Offered by: PaleoEcological Observatory Network (PalEON)

Dates: August 12-18, 2012

Course description: Estimating the impact of global change processes like land-use and climate on terrestrial ecosystems requires an integration of long-term data and ecosystem models. This course will provide 20 graduate students and postdocs with intensive training in the emerging tools that allow us to:

-estimate the signal and uncertainty in historical and paleoecological data
-assimilate both signal and uncertainty into the current suite of terrestrial ecosystem models

The course has a hands-on, integrated curriculum emphasizing the data/model process from design through data collection, analysis and back to design. We will collect tree-rings, historical survey data and sedimentary data (e.g., pollen, charcoal, and macrofossils). Analysis of these data will take place in a Bayesian mode of inference addressing uncertainty in age-models, calibration of proxy data, and integration of diverse historical data. After an introduction to inference from ecosystem models in traditional "forward" mode, participants will integrate ecological parameters estimated from their data sets into these ecosystem models using formal Bayesian data assimilation.

Participating faculty: Mike Dietze (University of Illinois); Steve Jackson (University of Wyoming); Jason McLachlan (University of Notre Dame); Chris Paciorek (University of California Berkeley); Jack Williams (University of Wisconsin)

Location: University of Notre Dame Environmental Research Center, Land O'Lakes, WI, USA.

Fees: This workshop is funded by a grant from the National Science Foundation and is free to participants. You must provide your own means of transportation to Chicago, Illinois, or Madison, Wisconsin.
There are a limited number of travel grants available to applicants from NEON, Inc., member institutions (see www.neoninc.org/content/paleon-data-assimilation-course).

Application: We are seeking students with interests and backgrounds in paleoecology, terrestrial ecosystem modeling, and/or statistics.  Send a CV, a statement detailing why you want to take the course and how you anticipate it helping your research, and arrange to have a letter sent from your major advisor supporting your application.

Apply to: Jason McLachlan at jmclachl@nd.edu

Deadline: March 30, 2012. Selections announced by April 15, 2012

QUEST presentation at the Northeast Soil Monitoring Cooperative annual meeting

Carrie Rose Levine gave a presentation on QUEST and sources of uncertainty in soils at the annual meeting of the Northeast Soil Monitoring Cooperative on March 13, 2012.

Uncertainty in soils is difficult to quantify due to the natural spatial and temporal variability of soils. Soil depth, rock content, bulk density, and nutrient concentration are all highly variable in soils. We may also expect high temporal variation of nutrient concentration and mass of the forest floor depending on changes in litterfall inputs over time.

Along with natural variation in soils, researchers have difficulty quantifying the uncertainty in soils as a result of what we call "knowledge uncertainty." In soils, knowledge uncertainty includes rejection criteria (obstructions), problems with excavation, representative subsampling, and uncertainty in analytical methods.

A link to the full presentation will be available shortly through the NESMC website:
http://www.uvm.edu/~nesmc/ 

LTER Working Group Funded: Uncertainty in Atmospheric Deposition

The estimation of wet atmospheric deposition requires the interpolation between point measurements of precipitation and solute chemisty across a landscape.  There are many approaches to interpolation, resulting in different estimates, usually reported without uncertainty.  QUEST has received funding from the LTER Network Office to conduct a Synthesis Working Group to quantify the uncertainties in these interpolations.
A workshop will be held May 21-22, 2012, at HJ Andrews Experimental Forest, involving representatives from four LTER sites: Hubbard Brook, Sevilleta, HJ Andrews, and Coweeta.  Sites were selected for their long-term precipitation records and multiple locations for precipitation solute chemistry.  On the first day, attendees will compare the various models for scaling up point measurements to the landscape, by applying all the models to all the sites.  The second day will be devoted to a more general discussion of uncertainty in deposition estimates, and will include a presentation by Chris Daly of the PRISM group.

QUEST Workshop at LTER All Scientists Meeting

Members of QUEST held a two hour workshop entitled “Quantifying Uncertainty in Ecosystem Studies” at the 2012 LTER All Scientists Meeting.  The two hour discussion-based workshop started with a round of introductions in which the 40 participants identified their system of study, and the biggest source of uncertainty they face.  The rest of the time was devoted by ten “lightening round” presentations on uncertainty in different ecosystem components (see presenters below).  Each five minute talk was followed up by a group discussion.   We received positive feedback from many of the workshop participants, and a proposal has been submitted for an organized oral session at next years ESA conference in Minneapolis. Full meeting notes are available for download below

List of presenters:

John Campbell:  Intro to QUEST, Participant introductions (what's your biggest uncertainty?)
Harmon:  Intro to sources of uncertainty
Adam Skibbe: Precipitation Uncertainty

Xuesong Zhang: Precipitation Uncertainty
John Battles: Biomass Uncertainty
Mark Green: Streamflow Uncertainty
Ruth Yanai: Uncertainty in Soils
Jeff Taylor: NEON products and their uncertainty
Craig See: Uncertainty in Data Gaps
Carrie Rose Levine: Monitoring Uncertainty

FILLED: Graduate Student Opportunities with QUEST!

Ruth Yanai at the State University of New York College of Environmental Science and Forestry (SUNY-ESF) is recruiting students to start in Fall 2012 or Spring 2013.  We have made progress quantifying uncertainty in estimates of forest biomass and stream loads and are also working on wet deposition and changes in soil storage.  There are currently research opportunities associated with each of these areas. 
In addition to the primary research with QUEST, there are opportunities for involvement in other projects associated with MELNHE (Multi-Element Limitation in Northern Hardwood Ecosystems) in the White Mountains.  MELNHE sites are located at Bartlett Experimental Forest, Hubbard Brook Experimental Forest, and Jeffers Brook (USFS).  http://www.esf.edu/melnhe
Background in ecology, statistics, and programming would be valuable assets.  Funding will consist of a combination of research and teaching assistantships.  Please contact Heather Engelman at forestecology@esf.edu if you are interested in applying.  Preference will be given to students available to start with the 2012 summer field season in the White Mountains of New Hampshire.