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hal.structure.identifierDepartment of Organismic and Evolutionary Biology
dc.contributor.authorKLOSTERMAN, Stephen
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierFaculty of Bioscience Engineering
hal.structure.identifierDepartment of Organismic and Evolutionary Biology
dc.contributor.authorHUFKENS, Koen
hal.structure.identifierDepartment of Organismic and Evolutionary Biology
hal.structure.identifierSchool of Informatics, Computing, and Cyber Systems [SICCS]
hal.structure.identifierNorthern Arizona University [Flagstaff]
dc.contributor.authorRICHARDSON, Andrew D.
dc.date.accessioned2024-04-08T12:05:40Z
dc.date.available2024-04-08T12:05:40Z
dc.date.issued2018
dc.identifier.issn0020-7128
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196368
dc.description.abstractEnIn deciduous forests, spring leaf phenology controls the onset of numerous ecosystem functions. While most studies have focused on a single annual spring event, such as budburst, ecosystem functions like photosynthesis and transpiration increase gradually after budburst, as leaves grow to their mature size. Here, we examine the "velocity of green-up," or duration between budburst and leaf maturity, in deciduous forest ecosystems of eastern North America. We use a diverse data set that includes 301 site-years of phenocam data across a range of sites, as well as 22 years of direct ground observations of individual trees and 3 years of fine-scale high-frequency aerial photography, both from Harvard Forest. We find a significant association between later start of spring and faster green-up: - 0.47 ± 0.04 (slope ± 1 SE) days change in length of green-up for every day later start of spring within phenocam sites, - 0.31 ± 0.06 days/day for trees under direct observation, and - 1.61 ± 0.08 days/day spatially across fine-scale landscape units. To explore the climatic drivers of spring leaf development, we fit degree-day models to the observational data from Harvard Forest. We find that the default phenology parameters of the ecosystem model PnET make biased predictions of leaf initiation (39 days early) and maturity (13 days late) for red oak, while the optimized model has biases of 1 day or less. Springtime productivity predictions using optimized parameters are closer to results driven by observational data (within 1%) than those of the default parameterization (17% difference). Our study advances empirical understanding of the link between early and late spring phenophases and demonstrates that accurately modeling these transitions is important for simulating seasonal variation in ecosystem productivity.
dc.language.isoen
dc.publisherSpringer Verlag
dc.subjectphenology
dc.subject.enecosystem model
dc.subject.enforest productivity
dc.subject.engreen-up
dc.subject.ennorth america
dc.title.enLater springs green-up faster: the relation between onset and completion of green-up in deciduous forests of North America
dc.typeArticle de revue
dc.identifier.doi10.1007/s00484-018-1564-9
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.journalInternational Journal of Biometeorology
bordeaux.page1645-1655
bordeaux.volume62
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue9
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02622148
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02622148v1
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