Evidence and attribution of the enhanced land carbon sink

Nature Reviews Earth & Environment, Journal Year: 2023, Volume and Issue: 4(8), P. 518 - 534

Published: July 25, 2023

Language: Английский

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Global datasets of leaf photosynthetic capacity for ecological and earth system research

Earth system science data, Journal Year: 2022, Volume and Issue: 14(9), P. 4077 - 4093

Published: Sept. 7, 2022

Abstract. The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information lacking, hindering global ecological research. Here, we convert chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants' optimal distribution nitrogen between light harvesting pathways. We also derive Vcmax (GOME-2) observations sun-induced fluorescence (SIF) as proxy photosynthesis using assimilation technique. These two independent products agree well (r2=0.79,RMSE=15.46µmol m−2 s−1, P<0.001) compare with 3672 ground-based measurements (r2=0.69,RMSE=13.8µmol s−1 P<0.001 SIF; r2=0.55,RMSE=18.28µmol LCC). LCC-derived product used constrain retrieval TROPical Ozone Mission (TROPOMI) SIF produce an optimized both LCC information. distributions these are compatible computed optimality theory meteorological variables, importantly reveal additional influence land cover, irrigation, soil pH, capacity. satellite-based approaches primed play major role in ecosystem three remote sensing SIF, LCC, SIF+LCC available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2022), code implementing https://github.com/SmithEcophysLab/optimal_vcmax_R https://doi.org/10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith 2022).

Language: Английский

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Global photosynthetic capacity of C3 biomes retrieved from solar-induced chlorophyll fluorescence and leaf chlorophyll content

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 287, P. 113457 - 113457

Published: Jan. 19, 2023

Language: Английский

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Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods

GIScience & Remote Sensing, Journal Year: 2024, Volume and Issue: 61(1)

Published: Feb. 20, 2024

Accurately estimating gross primary productivity (GPP), the largest carbon flux in terrestrial ecosystems, is crucial for advancing our understanding of global cycle and predicting climate feedbacks. The advancements remote sensing (RS) have facilitated development GPP estimation models at regional scales recent decades. This article systemically reviews RS-based three main aspects: theoretical foundation, key parameters methods. Regarding RS generally excels representing characteristics during light transmission process photosynthesis. However, it exhibits a relatively weaker ability to describe reaction process, severely limiting in-depth mechanisms estimation. Concerning parameters, definition traditional such as leaf area index (LAI), photosynthetically active radiation (PAR), fraction absorbing PAR, has been detailed (e.g. LAI divided into sunlit shaded LAI). their accuracy still needs improvement. Additionally, researchers developed effective photochemical reflectance index, sun-induced chlorophyll fluorescence, maximum carboxylation rate) that possess increased capability represent interpret methods, although four categories (statistical model, use efficiency model machine learning-based model) made significant progress parameter optimization, mechanism innovation remain less than satisfactory. Finally, we summarize current issues related performance accuracy, capabilities, well scale connotation mismatch. Integrating more adequate situ comprehensive observations would enhance interpretability models, providing reliable insights future studies. contributes photosynthetic estimation, potentially aiding optimization (improving existing developing new ones) design (introducing exploring mechanistic models).

Language: Английский

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Chlorophyll a fluorescence as a tool to monitor physiological status in the leaves of Artemisia ordosica under root cutting conditions

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 14

Published: Jan. 15, 2024

Background Root cutting caused by underground coal mining subsidence is among the leading causes of plant damage in western China. Detection root stress great importance evaluating degree and changes physiological conditions disturbance conditions. Methods The present study assessed use chlorophyll fluorescence OJIP transient data to evaluate characteristics on leaf photosynthetic mechanisms typical shrub Artemisia ordosica Krasch. Different ratios (10%, 20%, 30%, 50%, 75%, 100%) were established roots A. field, JIP parameters leaves measured. Results overall curves each step decreased as ratio increased, but impact was relatively small for less than 30%. Through analysis energy pipeline model, it found that capture efficiency electron transfer photosystem II increased. Therefore, we also inferred threshold at which begin change 30–50%. Conclusion These results indicate can serve a non-destructive, rapid technique detecting areas, value non-destructive monitoring damage.

Language: Английский

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A SIF-based approach for quantifying canopy photosynthesis by simulating the fraction of open PSII reaction centers (qL)

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 305, P. 114111 - 114111

Published: March 16, 2024

Advances in retrieval of solar-induced chlorophyll fluorescence (SIF) provide a promising and independent approach for quantifying gross primary production (GPP) across spatial scales. Recent studies have highlighted the prominent role qL, fraction open Photosystem II (PSII) reaction centers, mechanistically modeling GPP from remote sensing SIF. However, due to limited availability simulated experimental data, comprehensive understanding qL responses environmental physiological variations has yet emerge, as consequence, prediction leaf canopy scales is still an early stage. Based on global sensitivity analysis recently developed mechanical model photosynthesis, we find that broadband total SIF emitted PSII (SIFTOT_FULL_PSII) temperature (TLeaf) are two major predictors qL. A leaf-level instrument designed obtain concurrent measurements SIFTOT_FULL_PSII, TLeaf over wide range conditions. From these measurements, show can be modelled hyperbolic function SIFTOT_FULL_PSII with only one temperature-related parameter m which increases temperature, but decreases rapidly temperatures exceed optimum temperature. It suggested mathematically by peaked function. The results experiments winter wheat demonstrate proposed predicts high accuracy (R2 ≥ 0.91, rRMSE ≤ 8.46%) under diverse light essential steps necessary apply it at scale, including estimating escape fraction, removing I, reconstructing top-of-canopy (TOC) narrowband SIF, also presented. Our confirm estimated using SIF-informed agrees well measured site = 0.81, 12.03%). key benefit provides critical information collective influence sub-canopy environment avoiding requirement explicitly estimate different depths, potentially promoting ability quantify photosynthetic CO2 assimilation large

Language: Английский

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Comparing the quantum use efficiency of red and far-red sun-induced fluorescence at leaf and canopy under heat-drought stress

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 311, P. 114294 - 114294

Published: June 27, 2024

Sun-Induced chlorophyll Fluorescence (SIF) is the most promising remote sensing signal to monitor photosynthesis in space and time. However, under stress conditions its interpretation often complicated by factors such as light absorption plant morphological physiological adaptations. To ultimately derive quantum yield of fluorescence (ΦF) at photosystem from canopy measurements, so-called escape probability (fesc) needs be accounted for. In this study, we aim compare ΦF measured leaf- canopy-scale evaluate influence responses on two signals based a potato mesocosm heat-drought experiment. First, compared performance recently proposed reflectance-based approaches estimate leaf red fesc using data-supported simulations radiative transfer model SCOPE. While showed strong correlation (r2 ≥ 0.76), exhibited no relationship with SCOPE retrieved our We therefore propose modifications address limitation. then used modified models fesc, along an existing for far-red analyse dynamics increasing drought heat conditions. By incorporating obtained closer agreement between measurements. Specifically, r2 variables increased 0.3 0.50, 0.36 0.48. When comparing (ΦF,687 ΦF,760) stress, observed statistically significant decrease both ΦF,687 well ΦF,760, intensified. Canopy contrary, did not exhibit same trend, since measurements low wider spread lower median than high Finally, analysed sensitivity ΦF,760 changing solar incidence angle, variability without rotation. Our results suggest that variation strongly angle. These findings highlight need further research understand causes discrepancies scale ΦF,760. On underutilised understudied great potential assessing stress.

Language: Английский

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Global modeling diurnal gross primary production from OCO-3 solar-induced chlorophyll fluorescence

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 285, P. 113383 - 113383

Published: Dec. 5, 2022

Language: Английский

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Combining Solar-Induced Chlorophyll Fluorescence and Optical Vegetation Indices to Better Understand Plant Phenological Responses to Global Change

Journal of Remote Sensing, Journal Year: 2023, Volume and Issue: 3

Published: Jan. 1, 2023

Recent advances in the satellite retrieval of solar-induced chlorophyll fluorescence (SIF) provide new opportunities for understanding phenological responses ecosystems to global climate change. Because strong link between SIF and plant gross photosynthesis, events derived from represent seasonal variation ecosystem functioning (photosynthetic phenology) differ phenologies traditional vegetation indices. We an overview recent remotely sensed photosynthetic phenologies, with a focus on their driving factors, impact carbon cycle, relationships index-derived land surface phenology metrics. also discuss future research directions how better use various metrics understand plants

Language: Английский

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Vegetation Index‐Based Models Without Meteorological Constraints Underestimate the Impact of Drought on Gross Primary Productivity

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(1)

Published: Jan. 1, 2024

Abstract Recently developed solar‐induced chlorophyll fluorescence‐related vegetation indices (e.g., near infrared reflectance of (NIRv) and kernel normalized difference index (kNDVI)) have been reported to be appropriate proxies for photosynthesis. These can used estimate gross primary productivity (GPP) without considering meteorological constraints. However, it is not clear whether such a statement holds true under various environmental conditions. In this study, we explored these require constraints better characterize GPP extreme drought conditions using three cases in Europe 2003, 2010, 2018. According the long‐term series observations, (NIRv kNDVI) alone explained 60% 57%, respectively, weekly variation across 66 flux sites. The increased 69% 64%, models that take into account radiative effects kNDVI multiplied by radiation). constraints, index‐based estimations severely underestimated negative anomalies stress, especially incorporate effects. After incorporating vapor pressure deficit (VPD)‐based exhibited more pronounced during periods while maintaining model accuracy (at 70% 65%, respectively). addition, based on site observations were applied at regional scale (Europe). Our results indicated again impact GPP. This study emphasizes importance estimation GPP,

Language: Английский

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