Drought is among the most damaging climate extremes, potentially causing significant decline in ecosystem functioning and services at the regional to global scale, thus monitoring of drought events is critically important. Solar‐induced chlorophyll fluorescence (SIF) has been found to strongly correlate with gross primary production on the global scale. Recent advances in the remote sensing of SIF allow for large‐scale, real‐time estimation of photosynthesis using this relationship. However, several studies have used SIF to quantify the impact of drought with mixed results, and the leaf‐level mechanisms linking SIF and photosynthesis are unclear, particularly how the relationship may change under drought. We conducted a drought experiment with 2‐yr old
- Award ID(s):
- 1724433
- NSF-PAR ID:
- 10346096
- Date Published:
- Journal Name:
- Frontiers in Forests and Global Change
- Volume:
- 4
- ISSN:
- 2624-893X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Populus deltoides . We measured leaf‐level gas exchange, SIF, and pulse amplitude modulated (PAM) fluorescence before and during the 1‐month drought. We found clear responses of net photosynthesis and stomatal conductance to water stress, however, SIF showed a smaller response to drought. Net photosynthesis (A net) and conductance dropped 94% and 95% on average over the drought, while SIF values only decreased slightly (21%). Electron transport rate dropped 64% when compared to the control over the last week of drought, but the electron transport chain did not completely shut down asA netapproached zero. Additionally, SIF yield (SIFy) was positively correlated with steady‐state fluorescence (F s) and negatively correlated with non‐photochemical quenching (NPQ;R 2 = 0.77). BothF sand SIFy, after normalization by the minimum fluorescence from a dark‐adapted sample (F o), showed a more pronounced drought response, although the results suggest the response is complicated by several factors. Leaf‐level experiments can elucidate mechanisms behind large‐scale remote sensing observations of ecosystem functioning. The value of SIF as an accurate estimator of photosynthesis may decrease during mild stress events of short duration, especially when the response is primarily stomatal and not fully coupled with the light reactions of photosynthesis. We discuss potential factors affecting the weak SIF response to drought, including upregulation of NPQ, change in internal leaf structure and chlorophyll concentration, and photorespiration. The results suggest that SIF is mainly controlled by the light reactions of photosynthesis, which operate on different timescales than the stomatal response. -
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Abstract Accurate estimation of terrestrial gross primary productivity (
GPP ) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF ) in a temperate deciduous forest at Harvard Forest, Massachusetts,USA . Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R 2 = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively;P < 0.0001). We developed a model to estimateGPP from the tower‐based measurement ofSIF and leaf‐level ChlF parameters. The estimation ofGPP from this model agreed well with flux tower observations ofGPP (R 2 = 0.68;P < 0.0001), demonstrating the potential ofSIF for modelingGPP . At the leaf scale, we found that leafF q ’ /F m ’ , the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopySIF yield (SIF /APAR ,R 2 = 0.79;P < 0.0001). We also found that canopySIF andSIF ‐derivedGPP (GPPSIF ) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R 2 = 0.65 for canopyGPPSIF and chlorophyll content;P < 0.0001), leaf area index (LAI ) (R 2 = 0.35 for canopyGPPSIF andLAI ;P < 0.0001), and normalized difference vegetation index (NDVI ) (R 2 = 0.36 for canopyGPPSIF andNDVI ;P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales. -
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Abstract Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (
R 2 = 0.72,p < 0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R 2 = 0.57–0.79,p < 0.0001) except evergreen broadleaf forests (R 2 = 0.16,p < 0.05) at the daily timescale. A higher slope was found for C4grasslands and croplands than for C3ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies. -
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Abstract Recent advances in satellite observations of solar‐induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf‐level to canopy‐level is usually not well‐represented. Here, we incorporate the simulation of far‐red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf‐level fluorescence yield was simulated by a parametric simplification of the Soil Canopy‐Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf‐level to top‐of‐canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (
R 2 > 0.91, root‐mean‐square error <0.19 W⋅m−2⋅sr−1⋅μm−1), and captured the day‐to‐day variation of tower‐measured SIF at temperate forest sites (R 2 > 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite‐observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations. -
null (Ed.)Abstract. At the leaf level, stomata control the exchange of water and carbon across the air–leaf interface. Stomatal conductance is typically modeledempirically, based on environmental conditions at the leaf surface. Recently developed stomatal optimization models show great skills at predictingcarbon and water fluxes at both the leaf and tree levels. However, how well the optimization models perform atlarger scales has not been extensively evaluated. Furthermore, stomatal models are often used with simple single-leaf representations of canopy radiative transfer (RT), such asbig-leaf models. Nevertheless, the single-leaf canopy RT schemes do not have the capability to model optical properties of the leaves nor the entirecanopy. As a result, they are unable to directly link canopy optical properties with light distribution within the canopy to remote sensing dataobserved from afar. Here, we incorporated one optimization-based and two empirical stomatal models with a comprehensive RT model in the landcomponent of a new Earth system model within CliMA, the Climate Modelling Alliance. The model allowed us to simultaneously simulate carbon and waterfluxes as well as leaf and canopy reflectance and fluorescence spectra. We tested our model by comparing our modeled carbon and water fluxes andsolar-induced chlorophyll fluorescence (SIF) to two flux tower observations (a gymnosperm forest and an angiosperm forest) and satellite SIFretrievals, respectively. All three stomatal models quantitatively predicted the carbon and water fluxes for both forests. The optimization model,in particular, showed increased skill in predicting the water flux given the lower error (ca. 14.2 % and 21.8 % improvement for thegymnosperm and angiosperm forests, respectively) and better 1:1 comparison (slope increases from ca. 0.34 to 0.91 for the gymnosperm forest andfrom ca. 0.38 to 0.62 for the angiosperm forest). Our model also predicted the SIF yield, quantitatively reproducing seasonal cycles for bothforests. We found that using stomatal optimization with a comprehensive RT model showed high accuracy in simulating land surface processes. Theever-increasing number of regional and global datasets of terrestrial plants, such as leaf area index and chlorophyll contents, will helpparameterize the land model and improve future Earth system modeling in general.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/ffgc.2021.695269
