Tracking vegetation phenology of pristine northern boreal peatlands by combining digital photography with CO 2 flux and remote sensing data
Vegetation phenology, which refers to the seasonal changes in plant physiology, biomass and plant cover, is affected by many abiotic factors, such as precipitation, temperature and water availability. Phenology is also associated with the carbon dioxide (CO2) exchange between ecosystems and the atmo...
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Veröffentlicht in: | Biogeosciences 2022-10, Vol.19 (19), p.4747-4765 |
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Sprache: | eng |
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Zusammenfassung: | Vegetation phenology, which refers to the seasonal changes in
plant physiology, biomass and plant cover, is affected by many abiotic
factors, such as precipitation, temperature and water availability.
Phenology is also associated with the carbon dioxide (CO2) exchange
between ecosystems and the atmosphere. We employed digital cameras to
monitor the vegetation phenology of three northern boreal peatlands during
five growing seasons. We derived a greenness index (green chromatic
coordinate, GCC) from the images and combined the results with measurements
of CO2 flux, air temperature and high-resolution satellite data
(Sentinel-2). From the digital camera images it was possible to extract
greenness dynamics on the vegetation community and even species level. The
highest GCC and daily maximum gross photosynthetic production (GPPmax)
were observed at the site with the highest nutrient availability and richest
vegetation. The short-term temperature response of GCC depended on
temperature and varied among the sites and months. Although the seasonal
development and year-to-year variation in GCC and GPPmax showed
consistent patterns, the short-term variation in GPPmax was explained
by GCC only during limited periods. GCC clearly indicated the main phases of
the growing season, and peatland vegetation showed capability to fully
compensate for the impaired growth resulting from a late growing season
start. The GCC data derived from Sentinel-2 and digital cameras showed
similar seasonal courses, but a reliable timing of different phenological
phases depended upon the temporal coverage of satellite data. |
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ISSN: | 1726-4189 1726-4189 |
DOI: | 10.5194/bg-19-4747-2022 |