
NSF Org: |
DEB Division Of Environmental Biology |
Recipient: |
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Initial Amendment Date: | August 29, 2013 |
Latest Amendment Date: | August 29, 2013 |
Award Number: | 1241868 |
Award Instrument: | Standard Grant |
Program Manager: |
Elizabeth Blood
DEB Division Of Environmental Biology BIO Directorate for Biological Sciences |
Start Date: | September 1, 2013 |
End Date: | August 31, 2019 (Estimated) |
Total Intended Award Amount: | $793,161.00 |
Total Awarded Amount to Date: | $793,161.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
21 N PARK ST STE 6301 MADISON WI US 53715-1218 (608)262-3822 |
Sponsor Congressional District: |
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Primary Place of Performance: |
WI US 53706-1404 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | MacroSysBIO & NEON-Enabled Sci |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.074 |
ABSTRACT
Because of the slow pace of terrestrial ecosystem processes, including the slow generation time, growth rate, and decomposition rate of trees, the impact of changing climate and disturbance on forests plays out over hundreds of years. For this reason, terrestrial ecosystem models are used to anticipate the centennial scale projections of forest response to environmental change. Current terrestrial ecosystem model predictions vary widely and results have large statistical uncertainties. Furthermore, testing and calibration of these models relies on short term (sub-daily to decadal) data that fail to capture longer term trends and infrequent extreme events. The capacity of ecosystem models for scientific inference and long-term prediction would be greatly improved if uncertainties can be reduced through rigorous testing against observational data. PalEON is an interdisciplinary team of paleoecologists, statisticians, and modelers that have partnered to rigorously synthesize longer term paleoecological data and incorporate into ecosystem models to provide a deeper understanding of past dynamics and to use this knowledge to improve long-term forecasting capabilities.
Funds are provided to address four objectives and associated research questions: 1) Validation: How well do ecosystem models simulate decadal-to-centennial dynamics when confronted with past climate change, and what limits model accuracy? 2) Initialization: How sensitive are ecosystem models to initialization state and equilibrium assumptions? Do data-constrained simulations of centennial-scale dynamics improve 20thcentury simulations? 3) Inference: Was the terrestrial biosphere a carbon sink or source during the Little Ice Age and Medieval Climate Anomaly? and 4) Improvement: How can parameters and processes responsible for data-model divergences be improved? The data synthesis will include wide range of ecosystems, encompasses past climate variations that were large enough to affect tree growth rates, disturbance regimes, and forest demography, and leverages available paleodata. The synthesis will include 1) fossil pollen and Public Land Survey data to reconstruct forest composition, 2) sedimentary charcoal, stand-age and firescar indicators of past disturbance regimes, 3) tree-ring records of tree growth rates, and 4) multiple paleoclimatic proxies and paleoclimatic simulations. Bayesian hierarchical statistical models will be used to reconstruct key ecological variables and their associated uncertainty estimates. A standardized model intercomparison involving 13 ecosystem modeling groups will be used to evaluate the robustness of the modeling approach.
Three areas will be emphasized for PalEON's broader impacts. Community Building: The PalEON research community has doubled over the past 10 months, with more than 60 participants now. It is anticipated to nearly another doubling over the next five years, and the funds will allow the ongoing community-building via annual large meetings and task-oriented workshops. Interdisciplinary Training and Mentoring: A new generation of researchers will be trained to naturally conceptualize large spatial and temporal scales and to approach ecological forecasting as an integrative activity spanning data collection to model prediction. Eight postdocs and seven graduate students will be involved in proposed PalEON research, with multiple opportunities for cross-training. Additionally, the PalEON Summer Short Course provides an intensive cross-training experience for young scientists in all areas encompassed by PalEON. The 2012 course will be followed by courses in 2014 and 2016. Building Scientific Infrastructure: All PalEON datasets will be made publicly available upon publication, as will our new data-assimilation methods and model intercomparison protocols. Tools will be developed for optimal site selection (given the goal of reducing the integrated prediction uncertainty about past vegetation and climate over space and time) and will distribute a publicly available webtool version that will be linked directly to the Neotoma Paleoecology Database.
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
PalEON is a large collaborative project with PIs from a number of institutes. Notre Dame has requested No-Cost Extensions to finalize a number of analyses. Due to the integrative nature of PalEON the final project outcomes, including data and analyses provided by my portion of the award, will be provided with the final report and outcomes from the PalEON NSF lead award number 1241874, next year.
Wisconsin has co-led with Notre Dame the building of the historical and paleovegetation data products that have been the foundation of all subsequent PalEON analyses. Specific accomplishments include:
1) The assembly of historical tree survey data from across the north-central and northeastern US. These tree cover maps span 14 states (from Minnesota to Maine) and describe the composition and biomass of US forests at a critical moment in US history, just prior to widespread Euro-American land clearance and settlement. These maps have been used to document the disappearance of historic forest types and emergence of novel species associations (Goring et al. 2016 PLoS, Williams et al. Ecological Applications), show that tree-climate relationships have been altered by recent climate change and land use (Goring and Williams 2017 Ecology Letters), and have served as the foundational calibration dataset for the statistical models seeking to reconstruct past forest composition from fossil pollen datasets (Dawson et al. 2016 QSR).
2) The testing and deployment of the STEPPS pollen-vegetation model to reconstruct trajectories in tree species abundances and forest composition over the last 2000 years, in both the upper Midwest (MI, WI, MN) and New England states (Dawson et al. 2019 Ecology, Trachsel et al. in revision Quaternary Research). These reconstructions are important because many earth system models assume that terrestrial ecosystems were in steady state ca. 1800 AD, a common starting date for model simulations of the Anthropocene. Our results show that in contrast, forest composition was changing throughout the last 2,000 years, with notable changes including the ongoing expansion of hemlock populations in northern Wisconsin and spruce populations in northern New England. These changes may have been linked to gradually cooling temperatures between ca. 2000 years ago and 1800 AD.
These data products are unprecedented in their combination of spatial extent and attention to rigorous statistical modeling of past forest composition, tree density, and biomass, with uncertainty. They are the foundation of the statistical data-model assimilation efforts currently underway.
Last Modified: 12/02/2019
Modified by: John W Williams
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