AntonucciRossiDeslauriersEtAl2017

Reference

Antonucci, S., Rossi, S., Deslauriers, A., Morin, H., Lombardi, F., Marchetti, M., Tognetti, R. (2017) Large-scale estimation of xylem phenology in black spruce through remote sensing. Agricultural and Forest Meteorology, 233:92-100. (Scopus )

Abstract

There is a growing need for understanding the timing of wood formation in relation to the dynamics of bud phenology at wide geographical scale. This study analysed the relationships between long-term chronologies of xylem growth and the timing of plant phenology detected by Normalized Difference Vegetation Index (NDVI) in five permanent stands across the latitudinal distribution of black spruce [Picea mariana (Mill.) BPS] in the boreal forest of Quebec, Canada. Xylogenesis was studied weekly from April to October for thirteen years (2002–2014) on anatomical sections derived by wood microcores. The timing of the growing season detected by remote sensing was extracted from MODerate resolution Imaging Spectroradiometer (MODIS) 250 m 16-days NDVI data. The NDVI time-series were fitted using a double-logistic curve. Phenological chronologies from remote sensing and xylem phenology showed a latitudinal trend. The models correlating the data inferred from satellite sensors and the spring observations of xylem phenology were significant (p < 0.0001). The length of NDVI growing season and the duration of xylogenesis showed a close correlation. This study demonstrated that the timing of xylem formation could be suitably estimated at wide geographical scale using remote sensing data. However, the inter-annual phenological variability remained unexplained, which might limit the application of the models only to the years considered by our chronologies. © 2016 Elsevier B.V.

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@ARTICLE { AntonucciRossiDeslauriersEtAl2017,
    AUTHOR = { Antonucci, S. and Rossi, S. and Deslauriers, A. and Morin, H. and Lombardi, F. and Marchetti, M. and Tognetti, R. },
    TITLE = { Large-scale estimation of xylem phenology in black spruce through remote sensing },
    JOURNAL = { Agricultural and Forest Meteorology },
    YEAR = { 2017 },
    VOLUME = { 233 },
    PAGES = { 92-100 },
    NOTE = { cited By 0 },
    ABSTRACT = { There is a growing need for understanding the timing of wood formation in relation to the dynamics of bud phenology at wide geographical scale. This study analysed the relationships between long-term chronologies of xylem growth and the timing of plant phenology detected by Normalized Difference Vegetation Index (NDVI) in five permanent stands across the latitudinal distribution of black spruce [Picea mariana (Mill.) BPS] in the boreal forest of Quebec, Canada. Xylogenesis was studied weekly from April to October for thirteen years (2002–2014) on anatomical sections derived by wood microcores. The timing of the growing season detected by remote sensing was extracted from MODerate resolution Imaging Spectroradiometer (MODIS) 250 m 16-days NDVI data. The NDVI time-series were fitted using a double-logistic curve. Phenological chronologies from remote sensing and xylem phenology showed a latitudinal trend. The models correlating the data inferred from satellite sensors and the spring observations of xylem phenology were significant (p < 0.0001). The length of NDVI growing season and the duration of xylogenesis showed a close correlation. This study demonstrated that the timing of xylem formation could be suitably estimated at wide geographical scale using remote sensing data. However, the inter-annual phenological variability remained unexplained, which might limit the application of the models only to the years considered by our chronologies. © 2016 Elsevier B.V. },
    AUTHOR_KEYWORDS = { Black spruce; Cell differentiation; Phenology; Remote sensing; Vegetation index; Xylogenesis },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1016/j.agrformet.2016.11.011 },
    KEYWORDS = { Picea mariana },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84997294914&doi=10.1016%2fj.agrformet.2016.11.011&partnerID=40&md5=c5d546e6143bd8a3b15b3aa3b9c33f5f },
}

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