Radia 59951/3/2024 Understanding the relationship between leaf phenology and physiological properties has important implications for improving ecosystem models of biogeochemical cycling. However, it is difficult to clarify the cause of these discrepancies from ecosystem-level studies because the observed patterns and relationships between flux and leaf phenology integrate the responses of multiple species, age classes, and canopy layers within the ecosystem thus, biological interpretation of these relationships is far from trivial. Many possible explanations for the dissimilarity have been inferred, for example, earlier saturation of green signal at relatively low LAI, slower development of leaf physiological properties than leaf area, spring increase in leaf carotenoid content and subsequent decrease in the fraction of green signal from the canopy, and earlier decrease in leaf physiological properties than the onset of leaf fall, e.g. Although mid-growing season phenology has received less attention than phenology at the beginning and end of the growing season, it determines the attainment of full photosynthetic capacity and its period, thus affecting the annual sums of GPP. Therefore, phenocams have been installed in many flux sites in various ecosystems, such as temperate and boreal forests, savannas, and grasslands, and time-series data of canopy greenness or redness have been used to analyze seasonal changes in ecosystem gas flux, especially for CO 2, e.g. Because canopy color derived from phenocam imagery depends on both the leaf amount and the color of individual leaves, it reflects both physiological and structural characteristics of the canopy, such as leaf area index (LAI), leaf chlorophyll and carotenoid concentrations, which are key components of canopy photosynthesis and transpiration. Especially, a tower-mounted digital camera called a "phenocam", which is categorized as a near-surface remote sensing approach, can provide ecosystem-level leaf phenology at a higher temporal frequency and finer spatial resolution than satellite remote sensing without being obscured by clouds, enabling detailed comparison of leaf phenology with ecosystem carbon and water flux obtained by the eddy covariance method. The capacity of European ecosystems to sequester CO2 in the future. Understanding of how changes in growing season length are likely to shape Coupling such quasi-continuous digital records of canopyĬolours with co-located CO2 flux measurements will improve our Out of phase with the maximum period of canopy photosynthesis in ecosystemsĪcross Europe. Using the model we wereĪble to explain why this spring maximum in green signal is often observed FromĪ model sensitivity analysis we found that variations in colour fractions,Īnd in particular the late spring `green hump' observed repeatedly inĭeciduous broadleaf canopies across the network, are essentially dominatedīy changes in the respective pigment concentrations. In canopy leaf area and leaf chlorophyll and carotenoid concentrations. Using the PROSAIL model parameterised with information of seasonal changes Investigated whether the seasonal patterns of red, green and blue colourįractions derived from digital images could be modelled mechanistically Regression approach against dates estimated from visual observations, weįound that these phenological events could be detected adequately (RMSE < 8 and 11 days for leaf out and leaf fall, respectively). Green-up and senescence of deciduous forests extracted by the piecewise In addition to identifying striking changes in colour signals caused byįlowering and management practices such as mowing. Regression approach could capture the start and end of the growing season, We explored whether key changes in canopy phenology could be detectedĪutomatically across different land use types in the network. Using colour indicesįrom digital images and using piecewise regression analysis of time series, Network of digital cameras installed on towers across Europe above deciduousĪnd evergreen forests, grasslands and croplands, where vegetation andĪtmosphere CO2 fluxes are measured continuously. We present the first synthesis from a growing observational Provided by digital repeat photography at high temporal and spatial To supplement long-term observations with automated techniques such as those As visual observations of phenology are laborious, there is a need ![]() To climate and management practices are crudely represented in land surface Presently, the exact timing of plant development stages and their response ![]() Photoperiod, temperature, soil moisture and nutrient availability. Plant phenological development is orchestrated through subtle changes in
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