Climate‐Induced Uncertainty in Modeling Gross Primary Productivity From the Light Use Efficiency Approach DOI
Jiyan Wang, Yong Wang, Xinyao Xie

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(10)

Published: Oct. 1, 2024

Abstract Light use efficiency (LUE) models, along with satellite‐based vegetation maps and climatic reanalysis products as drivers, are effective tools for estimating large‐scale gross primary productivity (GPP). However, the climate‐induced uncertainty in LUE‐based GPP remains poorly understood, particularly temporal scaling from ignored fluctuations. Here, two 1‐hourly products, site‐based observations, were employed to drive a two‐leaf LUE model at 194 eddy‐covariance (EC) sites. The observation‐driven reanalysis‐driven resolution evaluated against EC illustrate mean absolute deviation (MAD) Nash‐Sutcliffe (NSE) criterion. Moreover, was characterized by comparing distributed (modeled drivers) lumped 6‐hourly drivers). At resolution, results demonstrated that showed weaker relationship (MAD = 0.14 gC m −2 h −1 , NSE 0.48) than 0.12 0.60), confirming nonnegligible products. Additionally, arising gridded radiation found be significantly larger associated temperature vapor pressure deficit (VPD). both exhibited lower 0.63 6h 0.54) corresponding 0.57 0.59), demonstrating estimates apparent. This study emphasizes imperative refine more precise capture of short‐term fluctuations reduce uncertainties coarse estimates.

Language: Английский

A gradient-based 3D nonlinear spectral model for providing components optical properties of mixed pixels in shortwave urban images DOI Creative Commons
Zhijun Zhen, Shengbo Chen, Nicolas Lauret

et al.

Remote Sensing of Environment, Journal Year: 2025, Volume and Issue: 321, P. 114657 - 114657

Published: Feb. 28, 2025

Language: Английский

Citations

2
Trajectories of Terrestrial Vegetation Productivity and Its Driving Factors in China's Drylands DOI Creative Commons
Haixing Gong, Guoyin Wang, Xiaoyan Wang

et al.

Geophysical Research Letters, Journal Year: 2024, Volume and Issue: 51(20)

Published: Oct. 13, 2024

Abstract Climate change and large‐scale ecological restoration programs have profoundly influenced vegetation greening gross primary productivity (GPP) in China's drylands. However, the specific pathways through which climatic factors influence GPP remain poorly understood. This study examines spatiotemporal changes across drylands from 2001 to 2020 investigates direct indirect effects of leaf area index (LAI) on GPP. The results reveal that overall improvement cover has positively increased these regions. Although are minimal, they exert a substantial effect by regulating growth, highlighting LAI is key intermediary mediating Furthermore, complex interactions vary significantly along aridity gradient. emphasizes necessity comprehensively considering intricate among multiple climate factors.

Language: Английский

Citations

8
VPM v3.0 model: improved estimates of terrestrial gross primary production from individual eddy flux tower sites to the globe DOI Creative Commons
Li Pan, Xiangming Xiao,

Baihong Pan

et al.

Journal of Remote Sensing, Journal Year: 2025, Volume and Issue: 5

Published: Jan. 1, 2025

Accurate estimation of gross primary production (GPP) terrestrial vegetation is crucial for comprehending the carbon dynamics. To date, there still no consensus on magnitude and seasonality global GPP among major products, underscoring necessity to improve models higher accuracy estimates. Here, we introduce an improved Vegetation Photosynthesis Model (VPM v3.0), which incorporates site-specific apparent optimum temperature photosynthesis, leaf-trait-based light absorption (flat leaf vs. needle leaf), water stress estimation. The VPM simulation driven by Moderate Resolution Imaging Spectroradiometer images ERA5-Land climate dataset. We evaluate v3.0 using from 205 eddy flux tower sites across 11 land cover types (1,658 site-years) (GPP EC ), as well TROPOspheric monitoring instrument (TROPOMI) solar-induced fluorescence (SIF) product 2018 2021. slope, R 2 , root mean square error between VPM-v3 ) are 0.97, 0.78, 1.46 gC m −2 day −1 respectively. shows high temporal consistency with TROPOMI SIF. provides estimates at most evaluated than v2.0. Comparisons other products reveal both spatial–temporal discrepancies. These findings clearly indicate in estimating GPP, making it suitable generating datasets.

Language: Английский

Citations

0
Spatio-temporal simulation of net ecosystem productivity in the Tibetan Plateau region using multi-scale data assimilation for terrestrial ecosystem process model DOI
Changhui Ma, Si‐Bo Duan, Cong Xu

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 366, P. 110471 - 110471

Published: March 6, 2025

Language: Английский

Citations

0
Plant traits shape global spatiotemporal variations in photosynthetic efficiency DOI
Yulin Yan, Bolun Li, Benjamin Dechant

et al.

Nature Plants, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Language: Английский

Citations

0
Development of an ecohydrological model for coupled simulation of water and carbon fluxes, crop growth, and canopy spectra over croplands DOI
Cheng Yang, Huimin Lei, Xingyu Hu

et al.

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 235, P. 110336 - 110336

Published: April 6, 2025

Language: Английский

Citations

0
Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution DOI Creative Commons

Ruize Xu,

Jiahua Zhang, Meimei Zhang

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2024, Volume and Issue: 135, P. 104248 - 104248

Published: Nov. 6, 2024

Language: Английский

Citations

2
Field-scale evaluation of a satellite-based terrestrial biosphere model for estimating crop response to management practices and productivity DOI

Jingwen Wang,

J.L. Pancorbo, Miguel Quemada

et al.

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 219, P. 1 - 21

Published: Nov. 26, 2024

Language: Английский

Citations

2
Climate‐Induced Uncertainty in Modeling Gross Primary Productivity From the Light Use Efficiency Approach DOI
Jiyan Wang, Yong Wang, Xinyao Xie

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(10)

Published: Oct. 1, 2024

Abstract Light use efficiency (LUE) models, along with satellite‐based vegetation maps and climatic reanalysis products as drivers, are effective tools for estimating large‐scale gross primary productivity (GPP). However, the climate‐induced uncertainty in LUE‐based GPP remains poorly understood, particularly temporal scaling from ignored fluctuations. Here, two 1‐hourly products, site‐based observations, were employed to drive a two‐leaf LUE model at 194 eddy‐covariance (EC) sites. The observation‐driven reanalysis‐driven resolution evaluated against EC illustrate mean absolute deviation (MAD) Nash‐Sutcliffe (NSE) criterion. Moreover, was characterized by comparing distributed (modeled drivers) lumped 6‐hourly drivers). At resolution, results demonstrated that showed weaker relationship (MAD = 0.14 gC m −2 h −1 , NSE 0.48) than 0.12 0.60), confirming nonnegligible products. Additionally, arising gridded radiation found be significantly larger associated temperature vapor pressure deficit (VPD). both exhibited lower 0.63 6h 0.54) corresponding 0.57 0.59), demonstrating estimates apparent. This study emphasizes imperative refine more precise capture of short‐term fluctuations reduce uncertainties coarse estimates.

Language: Английский

Citations

0