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Interpreting canopy development and physiology using a European phenology camera network at flux sites

L. Wingate 1, * J. Ogée 1 E. Cremonese 2 G. Filippa 2 T. Mizunuma 3 M. Migliavacca 4 C. Moisy 1 M. Wilkinson 5 C. Moureaux 6 G. Wohlfahrt 7, 8 A. Hammerle 8 L. Hörtnagl 8, 9 C. Gimeno 10 A. Porcar-Castell 11 M. Galvagno 2 T. Nakaji 12 J. Morison 5 O. Kolle 4 A. Knohl 13 W. Kutsch 14 P. Kolari 11 E. Nikinmaa 11 A. Ibrom 15 B. Gielen 16 W. Eugster 9 M. Balzarolo 17, 16 D. Papale 17 K. Klumpp 18 B. Köstner 19 T. Grünwald 19 R. Joffre 20 J. Ourcival 20 M. Hellstrom 21 A. Lindroth 21 C. George 22 B. Longdoz 23 B. Genty 24 J. Levula 11 B. Heinesch 6 M. Sprintsin D. Yakir 25 T. Manise 6 D. Guyon 1 H. Ahrends 26, 9 A. Plaza-Aguilar 27 J. Guan 4 J. Grace 3 
Abstract : 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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L. Wingate, J. Ogée, E. Cremonese, G. Filippa, T. Mizunuma, et al.. Interpreting canopy development and physiology using a European phenology camera network at flux sites. Biogeosciences, 2015, 12 (20), pp.5995 - 6015. ⟨10.5194/bg-12-5995-2015⟩. ⟨hal-01557316⟩



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