Show simple item record

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorTHOMAS, R. Quinn
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorBROOKS, Evan B.
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorJERSILD, Annika L.
hal.structure.identifierClimate Change Science Institute [Oak Ridge] [CCSI]
dc.contributor.authorWARD, Eric J.
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorWYNNE, Randolph H.
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorALBAUGH, Timothy J.
hal.structure.identifierState Climate Office of North Carolina
dc.contributor.authorDINON-ALDRIDGE, Heather
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorBURKHART, Harold E.
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierNicholas School of the Environment
dc.contributor.authorDOMEC, Jean-Christophe
hal.structure.identifierDepartment of Forest Resources and Environmental Conservation [Blacksburg]
dc.contributor.authorFOX, Thomas R.
hal.structure.identifierDepartment of Forest Engineering, Resources and Management
dc.contributor.authorGONZALEZ-BENECKE, Carlos A.
hal.structure.identifierSchool of Forest Resources and Conservation
dc.contributor.authorMARTIN, Timothy A.
hal.structure.identifierDepartment of Forestry and Environmental Resources [North Carolina State University]
dc.contributor.authorNOORMETS, Asko
hal.structure.identifierDecision Center for a Desert City
dc.contributor.authorSAMPSON, David A.
hal.structure.identifierWarnell School of Forestry and Natural Resources
dc.contributor.authorTESKEY, Robert O.
dc.date.accessioned2024-04-08T12:03:34Z
dc.date.available2024-04-08T12:03:34Z
dc.date.issued2017
dc.identifier.issn1726-4170
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196275
dc.description.abstractEnPredicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6  ×  105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
dc.language.isoen
dc.publisherEuropean Geosciences Union
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectpinus taeda
dc.subjectassimilation de données
dc.subjectcycle du carbone
dc.subjectécosystème forestier
dc.subjectchangement climatique
dc.subject.enloblolly pine
dc.subject.encarbon cycle
dc.subject.enforest ecosystem
dc.subject.englobal change
dc.title.enLeveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments
dc.typeArticle de revue
dc.identifier.doi10.5194/bg-14-3525-2017
dc.subject.halSciences du Vivant [q-bio]
bordeaux.journalBiogeosciences
bordeaux.page3525-3547
bordeaux.volume14
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue14
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-01600941
hal.version1
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01600941v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Biogeosciences&rft.date=2017&rft.volume=14&rft.issue=14&rft.spage=3525-3547&rft.epage=3525-3547&rft.eissn=1726-4170&rft.issn=1726-4170&rft.au=THOMAS,%20R.%20Quinn&BROOKS,%20Evan%20B.&JERSILD,%20Annika%20L.&WARD,%20Eric%20J.&WYNNE,%20Randolph%20H.&rft.genre=article


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record