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Titel |
Interpreting canopy development and physiology using a European phenology camera network at flux sites |
VerfasserIn |
L. Wingate, J. Ogée, E. Cremonese, G. Filippa, T. Mizunuma, M. Migliavacca, C. Moisy, M. Wilkinson, C. Moureaux, G. Wohlfahrt, A. Hammerle, L. Hörtnagl, C. Gimeno, A. Porcar-Castell, M. Galvagno, T. Nakaji, J. Morison, O. Kolle, A. Knohl, W. Kutsch, P. Kolari, E. Nikinmaa, A. Ibrom, B. Gielen, W. Eugster, M. Balzarolo, D. Papale, K. Klumpp, B. Köstner, T. Grünwald, R. Joffre, J.-M. Ourcival, M. Hellström, A. Lindroth, C. George, B. Longdoz, B. Genty, J. Levula, B. Heinesch, M. Sprintsin, D. Yakir, T. Manise, D. Guyon, H. Ahrends, A. Plaza-Aguilar, J. H. Guan, J. Grace |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1726-4170
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Digitales Dokument |
URL |
Erschienen |
In: Biogeosciences ; 12, no. 20 ; Nr. 12, no. 20 (2015-10-21), S.5995-6015 |
Datensatznummer |
250118133
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Publikation (Nr.) |
copernicus.org/bg-12-5995-2015.pdf |
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Zusammenfassung |
Plant phenological development is orchestrated through subtle changes in
photoperiod, temperature, soil moisture and nutrient availability.
Presently, the exact timing of plant development stages and their response
to climate and management practices are crudely represented in land surface
models. As visual observations of phenology are laborious, there is a need
to supplement long-term observations with automated techniques such as those
provided by digital repeat photography at high temporal and spatial
resolution. We present the first synthesis from a growing observational
network of digital cameras installed on towers across Europe above deciduous
and evergreen forests, grasslands and croplands, where vegetation and
atmosphere CO2 fluxes are measured continuously. Using colour indices
from digital images and using piecewise regression analysis of time series,
we explored whether key changes in canopy phenology could be detected
automatically across different land use types in the network. The piecewise
regression approach could capture the start and end of the growing season,
in addition to identifying striking changes in colour signals caused by
flowering and management practices such as mowing. Exploring the dates of
green-up and senescence of deciduous forests extracted by the piecewise
regression approach against dates estimated from visual observations, we
found that these phenological events could be detected adequately (RMSE < 8 and 11 days for leaf out and leaf fall, respectively). We also
investigated whether the seasonal patterns of red, green and blue colour
fractions derived from digital images could be modelled mechanistically
using the PROSAIL model parameterised with information of seasonal changes
in canopy leaf area and leaf chlorophyll and carotenoid concentrations. From
a model sensitivity analysis we found that variations in colour fractions,
and in particular the late spring `green hump' observed repeatedly in
deciduous broadleaf canopies across the network, are essentially dominated
by changes in the respective pigment concentrations. Using the model we were
able to explain why this spring maximum in green signal is often observed
out of phase with the maximum period of canopy photosynthesis in ecosystems
across Europe. Coupling such quasi-continuous digital records of canopy
colours with co-located CO2 flux measurements will improve our
understanding of how changes in growing season length are likely to shape
the capacity of European ecosystems to sequester CO2 in the future. |
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