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Predicting yields of short-rotation hybrid poplar (Populus spp.) for the United States through model–data synthesis
Corresponding Author
Dan Wang
Department of Plant Biology and Energy Bioscience Institute, University of Illinois, Urbana, Illinois 61801 USA
E-mail: [email protected]Search for more papers by this authorDavid LeBauer
Department of Plant Biology and Energy Bioscience Institute, University of Illinois, Urbana, Illinois 61801 USA
Search for more papers by this authorMichael Dietze
Department of Earth and Environment, Boston University, Boston, Massachusetts 02215 USA
Search for more papers by this authorCorresponding Author
Dan Wang
Department of Plant Biology and Energy Bioscience Institute, University of Illinois, Urbana, Illinois 61801 USA
E-mail: [email protected]Search for more papers by this authorDavid LeBauer
Department of Plant Biology and Energy Bioscience Institute, University of Illinois, Urbana, Illinois 61801 USA
Search for more papers by this authorMichael Dietze
Department of Earth and Environment, Boston University, Boston, Massachusetts 02215 USA
Search for more papers by this authorCorresponding Editor: D. S. Schimel.
Abstract
Hybrid poplar (Populus spp.) is an important biomass crop being evaluated for cellulosic ethanol production. Predictions of poplar growth, rotation period, and soil carbon sequestration under various growing conditions, soils, and climates are critical for farmers and managers planning to establish short-rotation forestry (SRF) plantations. In this study, we used an ecoinformatics workflow, the Predictive Ecosystem Analyzer (PEcAn), to integrate literature data and field measurements into the Ecosystem Demography 2 (ED2) model to estimate yield potential of poplar plantations. Within PEcAn 164 records of seven different traits from the literature were assimilated using a Bayesian meta-analysis. Next, variance decomposition identified seven variables for further constraint that contributed >80% to the uncertainty in modeled yields: growth respiration, dark respiration, quantum efficiency, mortality coefficient, water conductance, fine-root allocation, and root turnover rate. Assimilation of observed yields further constrained uncertainty in model parameters (especially dark respiration and root turnover rate) and biomass estimates. Additional measurements of growth respiration, mortality, water conductance, and quantum efficiency would provide the most efficient path toward further constraint of modeled yields.
Modeled validation demonstrated that ED2 successfully captured the interannual and spatial variability of poplar yield observed at nine independent sites. Site-level analyses were conducted to estimate the effect of land use change to SRF poplar on soil C sequestration compared to alternate land uses. These suggest that poplar plantations became a C sink within 18 years of conversion from corn production or existing forest. Finally, poplar yields were estimated for the contiguous United States at a half degree resolution in order to determine potential productivity, estimate the optimal rotation period, and compare poplar to perennial grass yields. This regional projection suggests that poplar yield varies considerably with differences in soil and climate, reaching as much as 18 Mg·ha−1·yr−1 in eastern, southern, and northwest regions. In New England, the upper Midwest, and northern California, yields are predicted to exceed those of the highly productive C4 perennial grass, Miscanthus. In these poplar-productive regions, 4–11 year rotations give the highest potential yields. In conclusion, poplar plantations are predicted to have a high yield potential across a wide range of climates and soils and could be sustainable in soil C sequestration.
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