Research article
26 Jul 2017
Research article
| 26 Jul 2017
Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments
R. Quinn Thomas et al.
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Total article views: 2,499 (including HTML, PDF, and XML)
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Total article views: 1,961 (including HTML, PDF, and XML)
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Total article views: 538 (including HTML, PDF, and XML)
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Cited
24 citations as recorded by crossref.
- Fertilization increased leaf water use efficiency and growth of Pinus taeda subjected to five years of throughfall reduction L. Samuelson et al. 10.1139/cjfr-2017-0357
- Calibration of the process-based model 3-PG for major central European tree species D. Forrester et al. 10.1007/s10342-021-01370-3
- Effects of climate on the growth of Swiss uneven-aged forests: Combining >100 years of observations with the 3-PG model D. Forrester et al. 10.1016/j.foreco.2021.119271
- Predicting Adaptive Genetic Variation of Loblolly Pine (Pinus taeda L.) Populations Under Projected Future Climates Based on Multivariate Models M. Lu et al. 10.1093/jhered/esz065
- Ecological forecasting of tree growth: Regional fusion of tree‐ring and forest inventory data to quantify drivers and characterize uncertainty K. Heilman et al. 10.1111/gcb.16038
- Creating Landscape-Scale Site Index Maps for the Southeastern US Is Possible with Airborne LiDAR and Landsat Imagery R. Gopalakrishnan et al. 10.3390/f10030234
- Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation I. Fer et al. 10.5194/bg-15-5801-2018
- A mid‐century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity R. Thomas et al. 10.1002/eap.1761
- Macrosystems EDDIE Teaching Modules Increase Students’ Ability to Define, Interpret, and Apply Concepts in Macrosystems Ecology A. Hounshell et al. 10.3390/educsci11080382
- Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model Y. Xie et al. 10.1016/j.jenvman.2020.110249
- The effect of climate variability factors on potential net primary productivity uncertainty: An analysis with a stochastic spatial 3-PG model H. Restrepo et al. 10.1016/j.agrformet.2022.108812
- r3PG – An r package for simulating forest growth using the 3‐PG process‐based model V. Trotsiuk et al. 10.1111/2041-210X.13474
- Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory F. Minunno et al. 10.1016/j.foreco.2019.02.041
- Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models Y. Huang et al. 10.5194/gmd-12-1119-2019
- Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion V. Trotsiuk et al. 10.1111/gcb.15011
- Targeting Extreme Events: Complementing Near-Term Ecological Forecasting With Rapid Experiments and Regional Surveys M. Redmond et al. 10.3389/fenvs.2019.00183
- Bayesian hybrid analytics for uncertainty analysis and real‐time crop management E. Meenken et al. 10.1002/agj2.20659
- Introducing 3-PG2Py, an open-source forest growth model in Python X. Song & Y. Song 10.1016/j.envsoft.2022.105358
- Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model Y. Xie et al. 10.1016/j.ecolmodel.2020.109267
- Biological and market responses of pine forests in the US Southeast to carbon fertilization J. Henderson et al. 10.1016/j.ecolecon.2019.106491
- Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis H. Restrepo et al. 10.1016/j.foreco.2018.12.007
- Perspective: Advancing the research agenda for improving understanding of cyanobacteria in a future of global change M. Burford et al. 10.1016/j.hal.2019.04.004
- Species interactions under climate change in mixed stands of Scots pine and pedunculate oak M. Bouwman et al. 10.1016/j.foreco.2020.118615
- Evapotranspiration and water yield of a pine‐broadleaf forest are not altered by long‐term atmospheric [CO 2 ] enrichment under native or enhanced soil fertility E. Ward et al. 10.1111/gcb.14363
23 citations as recorded by crossref.
- Fertilization increased leaf water use efficiency and growth of Pinus taeda subjected to five years of throughfall reduction L. Samuelson et al. 10.1139/cjfr-2017-0357
- Calibration of the process-based model 3-PG for major central European tree species D. Forrester et al. 10.1007/s10342-021-01370-3
- Effects of climate on the growth of Swiss uneven-aged forests: Combining >100 years of observations with the 3-PG model D. Forrester et al. 10.1016/j.foreco.2021.119271
- Predicting Adaptive Genetic Variation of Loblolly Pine (Pinus taeda L.) Populations Under Projected Future Climates Based on Multivariate Models M. Lu et al. 10.1093/jhered/esz065
- Ecological forecasting of tree growth: Regional fusion of tree‐ring and forest inventory data to quantify drivers and characterize uncertainty K. Heilman et al. 10.1111/gcb.16038
- Creating Landscape-Scale Site Index Maps for the Southeastern US Is Possible with Airborne LiDAR and Landsat Imagery R. Gopalakrishnan et al. 10.3390/f10030234
- Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation I. Fer et al. 10.5194/bg-15-5801-2018
- A mid‐century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity R. Thomas et al. 10.1002/eap.1761
- Macrosystems EDDIE Teaching Modules Increase Students’ Ability to Define, Interpret, and Apply Concepts in Macrosystems Ecology A. Hounshell et al. 10.3390/educsci11080382
- Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model Y. Xie et al. 10.1016/j.jenvman.2020.110249
- The effect of climate variability factors on potential net primary productivity uncertainty: An analysis with a stochastic spatial 3-PG model H. Restrepo et al. 10.1016/j.agrformet.2022.108812
- r3PG – An r package for simulating forest growth using the 3‐PG process‐based model V. Trotsiuk et al. 10.1111/2041-210X.13474
- Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory F. Minunno et al. 10.1016/j.foreco.2019.02.041
- Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models Y. Huang et al. 10.5194/gmd-12-1119-2019
- Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion V. Trotsiuk et al. 10.1111/gcb.15011
- Targeting Extreme Events: Complementing Near-Term Ecological Forecasting With Rapid Experiments and Regional Surveys M. Redmond et al. 10.3389/fenvs.2019.00183
- Bayesian hybrid analytics for uncertainty analysis and real‐time crop management E. Meenken et al. 10.1002/agj2.20659
- Introducing 3-PG2Py, an open-source forest growth model in Python X. Song & Y. Song 10.1016/j.envsoft.2022.105358
- Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model Y. Xie et al. 10.1016/j.ecolmodel.2020.109267
- Biological and market responses of pine forests in the US Southeast to carbon fertilization J. Henderson et al. 10.1016/j.ecolecon.2019.106491
- Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis H. Restrepo et al. 10.1016/j.foreco.2018.12.007
- Perspective: Advancing the research agenda for improving understanding of cyanobacteria in a future of global change M. Burford et al. 10.1016/j.hal.2019.04.004
- Species interactions under climate change in mixed stands of Scots pine and pedunculate oak M. Bouwman et al. 10.1016/j.foreco.2020.118615
Discussed (final revised paper)
Latest update: 31 Jan 2023
Short summary
To improve predictions of future forest productivity, we introduce an analytical approach that uses data from numerous research experiments that have occurred across the southeastern US to calibrate a mathematical forest model and estimate uncertainty in predictions. As a result, predictions using the model are consistent with a rich history of forest research in a region that supplies a large fraction of wood products to the world.
To improve predictions of future forest productivity, we introduce an analytical approach that...
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