Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus

Wu, Guosheng; Guan, Kaiyu; Kimm, Hyungsuk; Miao, Guofang; Bernacchi, Carl J.; Moore, Caitlin E.; Ainsworth, Elizabeth A.; Yang, Xi; Frankenberg, Christian; Chen, Min

doi:10.1016/j.agrformet.2022.109046

Cited by 20 publications

(8 citation statements)

References 99 publications

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“…The above correlation values are based on the annually averaged data analysis from 2019 (see Table 2 ). It is noteworthy that the SIF-GPP relationship can become weak in certain environmental conditions such as drought (e.g., Shekhar et al [ 33 ]) and be variable within certain biomes based on leaf physiology (e.g., Wu et al [ 36 ]). However, a future study is needed to elucidate SIF-GPP relationships in India across different biomes in drought and wet conditions.…”

Section: Satellite-based Sif Observations Across Indian Biomesmentioning

confidence: 99%

Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes

Ravi,

Pillai,

Thilakan

et al. 2024

MethodsX

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Section: Satellite-based Sif Observations Across Indian Biomesmentioning

confidence: 99%

Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes

Ravi,

Pillai,

Thilakan

et al. 2024

MethodsX

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“…However, the variability of this relationship across various regions and growing seasons remains uncertain (Gu et al, 2019;, particularly in the context of agricultural ecosystems. Further, most previous studies (Guan et al, 2016;Sloat et al, 2021;Wu et al, 2022) investigating the connection between crop photosynthesis and SIF are limited to homogeneous crop areas worldwide by using satellite or ground-based SIF with flux tower GPP.…”

Section: 1029/2023jg007586mentioning

confidence: 99%

“…However, the variability of this relationship across various regions and growing seasons remains uncertain (Gu et al., 2019; X. Li, Xiao, et al., 2018), particularly in the context of agricultural ecosystems. Further, most previous studies (Guan et al., 2016; Sloat et al., 2021; S. Xu et al., 2021; Wu et al., 2022) investigating the connection between crop photosynthesis and SIF are limited to homogeneous crop areas worldwide by using satellite or ground‐based SIF with flux tower GPP. Earlier studies have also revealed that the variation in SIF signal at different spatial and temporal scales is largely attributable to the vegetation type, which has a direct correlation with the canopy structure (Turner et al., 2020; Wang et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Tracking Gross Primary Productivity Using Satellite Solar Induced Fluorescence: Insights Across Agricultural Ecosystems of India

Behera,

Dutta

2024

JGR Biogeosciences

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Accurately estimating gross primary productivity (GPP) in heterogeneous cropping systems from satellite data poses a challenge. In this study, for the first time, we examined how satellite solar‐induced chlorophyll fluorescence (SIF) tracks GPP in India's diverse cropping system. A significant correlation (r = 0.70–0.90, p ≤ 0.05) at 0.0833° spatial resolution is observed between 8daily and monthly FLUXCOM GPP and Global Ozone Monitoring Experiment‐2 (GOME‐2) SIF. Compared to GOME‐2 SIF the finer resolution, TROPOspheric Monitoring Instrument (TROPOMI) SIF showed greater potential (r = 0.80–0.95, p ≤ 0.05) in estimating GPP and crop productivity, except for Southern and Northeastern parts of India. These regions of India have heterogeneous cropland and low crop area fraction as identified from normalized difference vegetation index (NDVI), near‐infrared reflectance of vegetation and local moran's index map of NDVI. This heterogeneity leads to differences in the timing of growth stages across the annual cycle, such that the SIF signal is characterized by low seasonal variability across the cycle, leading to low correlation between GPP and SIF. Further, in addition to physiological control the intra‐annual variability of GPP‐SIF relationship (GPP/SIF ratio) is influenced by temperature, radiation, and moisture availability during peak/late growing seasons. However, in the early growing season, it primarily relies on soil moisture. Our findings should help improve GPP estimation using SIF across the agricultural ecosystems of India.

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“…SIF is a small amount of light energy that is reemitted from chlorophyll after the absorption of sunlight, and recent technological advances have allowed us to detect SIF from spaceborne platforms Guanter et al, 2007;Joiner et al, 2011). Although SIF, which is emitted during the light reactions of photosynthesis, is not a direct consequence of the fixation of CO 2 during the light-independent or dark reaction of photosynthesis (Chen et al, 2020;Porcar-Castell et al, 2021;G. Wu et al, 2022), SIF and photosynthesis can covary at larger spatial and temporal scales (Magney et al, 2020).…”

Section: Solar-induced Chlorophyll Fluorescencementioning

confidence: 99%

“…However, SIF is more related to APAR chl than GPP (G. Wu et al, 2022;, as the first-order determinant of SIF emission is the amount of sunlight that is absorbed by chlorophyll and changes in the amount of either directly and immediately impacts SIF. Leaf physiological processes also impact SIF by altering the proportion of the amount of APAR chl that is reemitted as fluorescence, or ΦF.…”

Section: Advantages Of Using Sif To Derive Apar Chlmentioning

confidence: 99%

A novel data-driven global model of photosynthesis using solar-induced chlorophyll fluorescence

Doughty

Wang

Johnson

et al. 2023

Preprint

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Space-based vegetation indices have been used to model global photosynthesis for more than two decades. However, vegetation indices are fundamentally linked to leaf optical properties rather than leaf physiology, which limits their utility in regions where changes in photosynthesis are driven by leaf development and demography. Contrary to vegetation indices, solar-induced chlorophyll fluorescence contains information on leaf physiology and has been shown to be synchronous with photosynthetic activity in the tropics. Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation (PAR) absorbed by chlorophyll (APAR chl ). ChloFluo is unique in that instead of estimating APAR chl as a function of a vegetation index and an ancillary PAR product, we model APAR chl using its empirical relationship with SIF and the proportion of APAR chl that is reemitted as SIF, or ΦF. This empirical, fluorescence-based approach to estimating the amount of sunlight absorbed by chlorophyll accounts for non-linearities between SIF and photosynthesis emerging from seasonality diverging efficiencies in light use. We compare and validate our model using FluxCom, FluxSat, and eddy covariance tower data and find that ChloFluo best matches the seasonality of tower photosynthesis in the Amazon. Thus, ChloFluo has potential for advancing our ability to accurately model photosynthesis in tropical evergreen broadleaf forests, which is responsible for one-third of terrestrial photosynthesis. Potential uses of our model are to investigate and advance our understanding of the timing and magnitude of the uptake of atmospheric carbon dioxide by vegetation, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.

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Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus

Cited by 20 publications

References 99 publications

Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes

Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes

Tracking Gross Primary Productivity Using Satellite Solar Induced Fluorescence: Insights Across Agricultural Ecosystems of India

A novel data-driven global model of photosynthesis using solar-induced chlorophyll fluorescence

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