From remotely sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Sun, Ying; Gu, Lianhong; Wen, Jiaming; Tol, Christiaan van der; Porcar‐Castell, Albert; Joiner, Joanna; Chang, C. Y.; Magney, Troy S.; Wang, Lixin; Hu, Leiqiu; Rascher, Uwe; Zarco‐Tejada, Pablo J.; Barrett, Christopher B.; Lai, Jiameng; Han, Jimei; Luo, Zhenqi

doi:10.1111/gcb.16634

Cited by 37 publications

(84 citation statements)

References 171 publications

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“…This can be explained by

\frac{{normalΦ}_{PSII}}{{normalΦ}_{F}} = \frac{q_{L II} Φ_{PSIIm} ()(, 1 + k_{DF})}{1 - Φ_{PSIIm}}

(derived as the ratio of equations 16 and 14 in Gu, Han, et al, 2019), which reveals the impact of redox states

q_{L II}

on the ratio of quantum yields of GPP over SIF. Further complications include the sensitivity of

q_{L II}

to temperature and water stress (stated above, and detailed discussion in Sun et al, 2023).…”

Section: Applicationsmentioning

confidence: 99%

“…Moreover, SIF (and/or its quantum yield) has been employed to infer

V_{c \max}

(and/or

J_{\max}

) across cultivars, indicating the potential of SIF in rapidly screening cultivars with different traits (Camino et al, 2019; Fu, Meacham‐Hensold, et al, 2021). In the future, such efforts can be guided by the toy model developed in Sun et al (2023). For example, any trait variations among cultivars (related to genetic variations) may drive differences in variables (e.g., LAI, leaf angle, pigment content) and parameters (e.g.,

k_{λ_{F}}

k_{PAR}

\overset{β}{true}

, and that affecting the redox state) in equations 8–9 of Sun et al (2023), assuming other conditions are equal.…”

Section: Applicationsmentioning

confidence: 99%

“…So far, the consensus is that, under severe and/or persistent stress, concurrent decline of

f PAR

and the apparent quantum yield of SIF (without correction of

f_{normalΩ ↑}^{esc}

) are likely to happen, but their relative contribution can be biome‐dependent and stress‐severity dependent (Sun et al, 2015; Yoshida et al, 2015). Mechanistic explanation of such patterns and causal inference can be guided by equation 8 in Sun et al (2023) in the future. For example, the contribution of

f PAR

(previously based on the LUE model) can be broken into light harvesting and canopy vertical extinction of PAR and SIF driven by the 3D leaf/canopy structure; the contribution of quantum yield of SIF can be studied separately from the contribution of PSII/PSI stoichiometry and state transition (if such ancillary information is available).…”

Section: Applicationsmentioning

confidence: 99%

“…The practical benefits of SIF relative to hyperspectral reflectance remain to be explored, especially considering that SIF, as a flux variable, is not only affected by plant structural and functional traits (state variables) but also rapid environmental fluctuations, which need to be teased out. On the other hand, SIF may still carry greater scalability in inferring GPP (and other associated functions and traits) across biomes than NIRv, given its mechanistic linkage with ETR and GPP (equations 9 and 10 in Sun et al, 2023), despite the biome‐specific or universal debate on the SIF‐GPP scaling. Moreover, the practical advantage of SIF over NIRv may be more apparent under stress conditions (Damm et al, 2022; Martini et al, 2022), and when the growing season progresses towards senescence especially for conifers (Raczka et al, 2019).…”

Section: Applicationsmentioning

confidence: 99%

“…The at‐sensor SIF signal that is directly measured does not equal to the total Chl a F emission that is directly related to ecophysiological processes. Even when SIF is retrieved accurately at specific wavelengths, it is not certain whether they are equally informative as the total Chl a F emission (which is a broadband quantity, that is, integrated over the full spectra of fluorescence emission) that is directly related to photosynthetic electron transport and CO 2 assimilation (Gu, Wood, et al, 2019; Zhang et al, 2019), equations 6–7 in Sun et al, 2023). Furthermore, a substantial portion of the total Chl a F emission is reabsorbed/scattered within a canopy and only a fraction escapes from the canopy to be detected by a sensor (section 3.1 in Sun et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

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From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

Sun

Wen

et al. 2023

Global Change Biology

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This paper aims to (1) synthesize the variety, scale, and uncertainty of existing solar-induced chlorophyll fluorescence datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities may impact process interpretation of various applications and contribute to inconsistent findings. We offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change.

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“…This can be explained by

\frac{{normalΦ}_{PSII}}{{normalΦ}_{F}} = \frac{q_{L II} Φ_{PSIIm} ()(, 1 + k_{DF})}{1 - Φ_{PSIIm}}

(derived as the ratio of equations 16 and 14 in Gu, Han, et al, 2019), which reveals the impact of redox states

q_{L II}

on the ratio of quantum yields of GPP over SIF. Further complications include the sensitivity of

q_{L II}

to temperature and water stress (stated above, and detailed discussion in Sun et al, 2023).…”

Section: Applicationsmentioning

confidence: 99%

“…Moreover, SIF (and/or its quantum yield) has been employed to infer

V_{c \max}

(and/or

J_{\max}

k_{λ_{F}}

k_{PAR}

\overset{β}{true}

, and that affecting the redox state) in equations 8–9 of Sun et al (2023), assuming other conditions are equal.…”

Section: Applicationsmentioning

confidence: 99%

“…So far, the consensus is that, under severe and/or persistent stress, concurrent decline of

f PAR

and the apparent quantum yield of SIF (without correction of

f_{normalΩ ↑}^{esc}

f PAR

Section: Applicationsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

Sun

Wen

et al. 2023

Global Change Biology

Self Cite

View full text Add to dashboard Cite

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Extreme Events Contributing to Tipping Elements and Tipping Points

Romanou,

Hegerl,

Seneviratne

et al. 2024

Surv Geophys

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This review article provides a synthesis and perspective on how weather and climate extreme events can play a role in influencing tipping elements and triggering tipping points in the Earth System. An example of a potential critical global tipping point, induced by climate extremes in an increasingly warmer climate, is Amazon rainforest dieback that could be driven by regional increases in droughts and exacerbated by fires, in addition to deforestation. A tipping element associated with the boreal forest might also be vulnerable to heat, drought and fire. An oceanic example is the potential collapse of the Atlantic meridional overturning circulation due to extreme variability in freshwater inputs, while marine heatwaves and high acidity extremes can lead to coral reef collapse. Extreme heat events may furthermore play an important role in ice sheet, glacier and permafrost stability. Regional severe extreme events could also lead to tipping in ecosystems, as well as in human systems, in response to climate drivers. However, substantial scientific uncertainty remains on mechanistic links between extreme events and tipping points. Earth observations are of high relevance to evaluate and constrain those links between extreme events and tipping elements, by determining conditions leading to delayed recovery with a potential for tipping in the atmosphere, on land, in vegetation, and in the ocean. In the subsurface ocean, there is a lack of consistent, synoptic and high frequency observations of changes in both ocean physics and biogeochemistry. This review article shows the importance of considering the interface between extreme events and tipping points, two topics usually addressed in isolation, and the need for continued monitoring to observe early warning signs and to evaluate Earth system response to extreme events as well as improving model skill in simulating extremes, compound extremes and tipping elements.

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Improving the ability of solar-induced chlorophyll fluorescence to track gross primary production through differentiating sunlit and shaded leaves

Zhang,

Chen,

Zhang

et al. 2023

Agricultural and Forest Meteorology

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From remotely sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Cited by 37 publications

References 171 publications

From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

Extreme Events Contributing to Tipping Elements and Tipping Points

Improving the ability of solar-induced chlorophyll fluorescence to track gross primary production through differentiating sunlit and shaded leaves

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