Details

Autor(en) / Beteiligte

• Magney, Troy S.
• Bowling, David R.
• Logan, Barry A.
• Grossmann, Katja
• Stutz, Jochen
• Blanken, Peter D.
• Burns, Sean P.
• Cheng, Rui
• Garcia, Maria A.
• Kӧhler, Philipp
• Lopez, Sophia
• Parazoo, Nicholas C.
• Raczka, Brett
• Schimel, David
• Frankenberg, Christian

Titel

Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence

Ist Teil von

• Proceedings of the National Academy of Sciences - PNAS, 2019-06, Vol.116 (24), p.11640-11645

Ort / Verlag

United States: National Academy of Sciences

Erscheinungsjahr

2019

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO₂ but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated (R² = 0.62–0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution.