Abstract
Vegetation annual gross primary production (AGPP), the total yearly carbon assimilation via photosynthesis, serves as a key indicator of ecosystem carbon uptake. While AGPP variations are jointly influenced by both vegetation phenology and physiology, the effectiveness of satellite-derived indicators in capturing these variations has not been fully evaluated. This study develops and evaluates the satellite-derived phenology and physiology indicators for modeling AGPP variability. We assessed the performance of satellite-derived metrics, including solar-induced chlorophyll fluorescence (SIF), leaf area index (LAI), and enhanced vegetation index (EVI), in capturing AGPP variations. Among these, SIF-based indicators exhibited the highest accuracy (Pearson's r = 0.79; root mean square error = 414.7 gC·m −2 ·year −1 ), outperforming LAI- and EVI-based indicators. To further investigate the mechanisms driving AGPP variability, we used a structural equation model based on in situ observations to quantify the direct and indirect effects of climate on AGPP through phenology and physiology. Our results reveal that vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology. Furthermore, we found that globally, SIF-derived phenology indicators tend to be lower than those from LAI and EVI, whereas SIF-derived physiology indicators are elevated in tropical regions and the Southern Hemisphere. These findings highlight the potential of satellite-derived indicators in advancing AGPP modeling and emphasize the predominant role of vegetation physiology in regulating ecosystem carbon uptake. This study contributes to a refined understanding of global carbon cycle dynamics and provides insights for improving large-scale carbon assessments in the context of climate change.
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Claims 5
Claim · model-written summary
SIF indicators had the highest AGPP prediction accuracy, with Pearson r of 0.79.
Verbatim
e0“SIF-based indicators exhibited the highest accuracy (Pearson's r = 0.79; root mean square error = 414.7 gC·m −2 ·year −1 ), outperforming LAI- and EVI-based indicators”
t0“phenology and physiology”
e1“vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology”
Claim · model-written summary
SIF indicators had an AGPP prediction root mean square error of 414.7 gC·m −2 ·year −1.
Verbatim
e0“SIF-based indicators exhibited the highest accuracy (Pearson's r = 0.79; root mean square error = 414.7 gC·m −2 ·year −1 ), outperforming LAI- and EVI-based indicators”
t0“phenology and physiology”
e1“vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology”
Claim · model-written summary
Vegetation physiology, especially seasonal maximum gross primary production, had a more dominant role than phenology in AGPP variability.
Not reportedOrgan / stage
Verbatim
e0“vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology”
Claim · model-written summary
Globally, SIF-derived phenology indicators were lower than LAI and EVI indicators.
Verbatim
e0“globally, SIF-derived phenology indicators tend to be lower than those from LAI and EVI”
t0“phenology and physiology”
e1“vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology”
Claim · model-written summary
SIF-derived physiology indicators were elevated in tropical regions and the Southern Hemisphere.
- Taxon
- vegetatione1
- Outcome
- physiology indicatorse0
- Direction
- elevatede0
- Setting
- tropical regions and the Southern Hemispheree0
Not reportedComparatorValue
Verbatim
e0“SIF-derived physiology indicators are elevated in tropical regions and the Southern Hemisphere”
t0“phenology and physiology”
e1“vegetation physiology, particularly the seasonal maximum gross primary production, plays a more dominant role in regulating AGPP than phenology”