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

Sun, Ying; Wen, Jiaming; Gu, Lianhong; Joiner, Joanna; Chang, C. Y.; Tol, Christiaan van der; Porcar‐Castell, Albert; 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.16646

Cited by 34 publications

(38 citation statements)

References 333 publications

(538 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the above description shows that a wide range of plant functional factors can affect

F_{↑}

, all is not lost in complexities. Photochemical and NPQ have a compensating effect on Chl a F emission and may facilitate the interpretation of SIF dynamics (but may complicate the interpretation of SIF‐GPP relationships, detailed discussion Sun et al, 2023). Under steady state in natural conditions,

NPQ

and

q_{L II}

tend to vary in opposite directions because more reduced PSII acceptors tend to be associated with higher proton gradients across the thylakoid membrane and therefore higher

NPQ

.…”

Section: The Forward Question: How Are the Dynamics Of Sif Affected B...mentioning

confidence: 99%

“…For example, two canopies with the same

\overset{p}{true}

can differ in

F_{↑} ()(, {normalλ}_{F})

if they differ in canopy/leaf structure or the mean quantum yield of Chl a F emission. This toy model is applicable for guiding process diagnosis and interpretation or knowledge inference on what structural and functional information can be inferred from

F_{↑} ()(, {normalλ}_{F})

(Sun et al, 2023). We note that Equation (8) can be applied to a leaf by setting

LAI = 1

and

r_{s} = 0

(derivation in Supporting Information 6).…”

Section: The Inference Question: What Aspects Of Terrestrial Ecosyste...mentioning

confidence: 99%

“…Existing theoretical and data gaps through the lens of applications (Sun et al, 2023), and potential solutions moving forward. This paper focuses on the theoretical side (the right columns highlighted in dark color) of this diagram.…”

Section: Innovations: What Innovations Are Needed To Realize the Full...mentioning

confidence: 99%

“…Filling this knowledge gap is crucial to enable SIF applications for inferring plant traits, selecting stress‐tolerant crop genotypes/phenotypes, precision agriculture management, as well as regional‐scale monitoring and early warning capacity for stress and food insecurity, etc. (Sun et al, 2023). A barrier is that SIF itself and its coupling with GPP is affected by a myriad of interactive processes and environmental variations (the forward issue, Equation 3), and thus the observed SIF

F_{↑} ()(, {normalλ}_{F})

reflects their collective and interactive effects (the inference issue, Equations 9 and 10).…”

Section: Innovations: What Innovations Are Needed To Realize the Full...mentioning

confidence: 99%

“…To advance, we must harness advances/innovations in theory and data (Figure 1), in order to shift from correlational analyses to causal quantification and reasoning. Toward this end, we offer our perspectives on critical research priorities moving forward, from the theoretical and observational aspects in two companion reviews (i.e., this paper, and Sun et al, 2023, respectively). Addressing these priorities will ultimately help improve predictive understanding and management of natural and agricultural ecosystems to enhance the services they offer to society (details in the companion review, Sun et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Sun

Wen

et al. 2023

Global Change Biology

Self Cite

View full text Add to dashboard Cite

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous | 2927 SUN et al.

show abstract

“…While the above description shows that a wide range of plant functional factors can affect

F_{↑}

NPQ

and

q_{L II}

tend to vary in opposite directions because more reduced PSII acceptors tend to be associated with higher proton gradients across the thylakoid membrane and therefore higher

NPQ

.…”

Section: The Forward Question: How Are the Dynamics Of Sif Affected B...mentioning

confidence: 99%

“…For example, two canopies with the same

\overset{p}{true}

can differ in

F_{↑} ()(, {normalλ}_{F})

F_{↑} ()(, {normalλ}_{F})

(Sun et al, 2023). We note that Equation (8) can be applied to a leaf by setting

LAI = 1

and

r_{s} = 0

(derivation in Supporting Information 6).…”

Section: The Inference Question: What Aspects Of Terrestrial Ecosyste...mentioning

confidence: 99%

Section: Innovations: What Innovations Are Needed To Realize the Full...mentioning

confidence: 99%

F_{↑} ()(, {normalλ}_{F})

reflects their collective and interactive effects (the inference issue, Equations 9 and 10).…”

Section: Innovations: What Innovations Are Needed To Realize the Full...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Sun

Wen

et al. 2023

Global Change Biology

Self Cite

View full text Add to dashboard Cite

show abstract

Seasonal timing of fluorescence and photosynthetic yields at needle and canopy scales in evergreen needleleaf forests

Pierrat,

Magney,

Maguire

et al. 2024

Ecology

View full text Add to dashboard Cite

The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive “greenness” of these systems. We combine continuous needle‐scale chlorophyll fluorescence measurements with tower‐based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar‐induced chlorophyll fluorescence (SIF) and solar intensity‐normalized SIF (SIFrelative) under snow‐covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near‐infrared vegetation index [NIRv] under 50% snow cover). Needle‐scale fluorescence and photochemistry strongly correlated (r2 = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower‐based estimates of LUEP and SIFrelative which were well correlated across all sites (r2 = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data‐driven and process‐based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems.

show abstract

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River, China

Liang,

Fang,

Lin

et al. 2024

Chin. Geogr. Sci.

View full text Add to dashboard Cite

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

Cited by 34 publications

References 333 publications

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

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

Seasonal timing of fluorescence and photosynthetic yields at needle and canopy scales in evergreen needleleaf forests

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River, China

Contact Info

Product

Resources

About