Solar-Induced Chlorophyll Fluorescence-Based GPP Estimation and Analysis of Influencing Factors for Xinjiang Vegetation DOI Open Access
Cong Xue, Mei Zan, Yanlian Zhou

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(12), P. 2100 - 2100

Published: Nov. 27, 2024

With climate change and the intensification of human activity, drought event frequency has increased, affecting Gross Primary Production (GPP) terrestrial ecosystems. Accurate estimation GPP in-depth exploration its response mechanisms to are essential for understanding ecosystem stability developing strategies adaptation. Combining remote sensing technology machine learning is currently mainstream method estimating in ecosystems, which can eliminate uncertainty model parameters errors input data. This study employed extreme gradient boosting, random forest (RF), light use efficiency models. Additionally, we integrated solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance vegetation, leaf area index (LAI) construct various The standardised precipitation evapotranspiration (SPEI) was utilised at timescales analyse relationship between SPEI during dry years. Moreover, potential pathways coefficients environmental factors that influence were explored using structural equation modelling. Our key findings include following: (1) combining SIF RF algorithms exhibits higher accuracy applicability vegetation arid zone Xinjiang, with an overall (MODIS R2) 0.775; (2) Xinjiang had different characteristics drought, optimal timescale respond 9 months, a mean correlation coefficient 0.244 grass land SPEI09, indicating high sensitivity; (3) modelling, found temperature affect both directly indirectly through LAI. provides reliable tool methodology conclusions important references similar environments. In addition, this bridges research gap timescales, mechanism natural on scientific basis early warning management. Further validation longer time series required confirm robustness model.

Language: Английский

Identification and Evaluation of Key Environmental Drivers Based on the Ten-Year Evolutionary Characteristics of Global Grassland Gpp DOI
Zhe Meng, Yuanyuan Hao, Xuexia Liu

et al.

Published: Jan. 1, 2025

As the largest terrestrial ecosystem globally, grasslands and their Gross Primary Productivity (GPP) play a critical role in global carbon cycle, influenced by environmental changes human activities. This study classifies into multiple types, uses trend analysis to investigate temporal spatial of GPP for various grassland types from 2010 2020, extracts approximately 940,000 pixel data identify evaluate factors using best prediction model PLS-PM structural equation model. The results indicate that shows an increasing trend, concentrated mid- low-latitude regions, with differences between hemispheres. Woody Savannas have highest mean GPP, while Grasslands lowest. At low altitudes, peaks, reaching maximum elevations at 4580 m 4950 m, respectively, persist higher altitudes lowest GPP. Climate soil hydrology contributed most significantly accounting 62.11%-77.95%, showing contribution (71.63%). Within climate factors, actual evapotranspiration, volumetric water layer, fraction photosynthetically active radiation, temperature had significant positive impacts on CO2 concentration activities smaller direct contributions, primarily influencing indirectly. Topographic least. These findings reveal dominant highlight differing growth trends among providing insights responses change

Language: Английский

Citations

0
Role of Micrometeorological Memory in Modulating Sub‐Daily Scale Variability of Net Ecosystem Exchange DOI
Akash Verma, Leena Khadke,

Elizabeth Eldhose

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2025, Volume and Issue: 130(1)

Published: Jan. 1, 2025

Abstract Net Ecosystem Exchange (NEE) is crucial for understanding the carbon balance in ecosystems, indicating whether they act as sinks or sources. While impact of hydrometeorological factors on NEE at daily and monthly scales has been well‐researched, significance sub‐daily variability influence memory micrometeorological variables remain understudied. This study addresses this gap by analyzing temporal dynamics using half‐hourly data from 29 FLUXNET sites over least 6 years. We found that contributes 10%–55% 13‐day variability, depending seasonal cycles biome characteristics. Using an information theory based transfer entropy (TE) approach, we identified causal drivers within a 6‐hr memory. Our results show significantly impacts NEE, surpassing their instantaneous effects. Temperature (TA), vapor pressure deficit (VPD), soil water content (SWC Mean ) consistently affect memory, whereas sensible heat (H) incoming shortwave radiation (SW IN diminishes higher lags. magnitude average TE to exhibits notable variations, structure how transferred does not differ across seasons, reflected shape values various time SWC , VPD, TA jointly, while H SW have overlapping Additionally, precipitation influences indirectly through . findings highlight importance accounting high‐frequency its underlying when investigating ecohydrological interactions, shedding light role carbon‐water interactions.

Language: Английский

Citations

0
Improvement of FAPAR Estimation Under the Presence of Non-Green Vegetation Considering Fractional Vegetation Coverage DOI Creative Commons
Rui Li, Baolin Li, Yecheng Yuan

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(4), P. 603 - 603

Published: Feb. 10, 2025

The homogeneous turbid medium assumption inherent to the Beer-Lambert’s law can lead a reduction in shading effect between leaves when non-green vegetation canopies are present, resulting an overestimation of fraction absorbed photosynthetically active radiation (FAPAR). This paper proposed method improve FAPAR estimation (FAPARFVC) based on by incorporating fractional coverage (FVC). Initially, canopy-scale leaf area index (LAI) green canopy distribution within pixel (sample site) was determined FVC. Subsequently, calculated area, adhering law. Finally, average across conducted case study using measured data from BigFoot Project and grass savanna Senegal, West Africa, as well Moderate Resolution Imaging Spectroradiometer (MODIS) LAI/FPAR products. results indicated that FAPARFVC approach demonstrated superior accuracy compared MODIS LAI, according (FAPARLAI) FPAR products (FAPARMOD). mean absolute percentage error 48.2%, which is 25.6% 52.1% lower than FAPARLAI FAPARMOD, respectively. 16.8%, 71.6% 73.4% improvements decrease for became more pronounced with increasing FVC FAPARLAI. findings suggested enhanced under presence canopies. be extended regional scale gross primary production (GPP) estimations, thereby providing accurate inputs understanding its tempo-spatial patterns drivers.

Language: Английский

Citations

0
Quantifying the impact of single-tree morphological characteristics on the vertical gradient cooling effect and human thermal comfort during summer DOI
Yue Cai, Chong Li, Chunyu Pan

et al.

Urban forestry & urban greening, Journal Year: 2025, Volume and Issue: unknown, P. 128789 - 128789

Published: March 1, 2025

Language: Английский

Citations

0
Divergent vegetation greening's direct impacts on land-atmosphere water and carbon exchanges in the northeastern Tibetan Plateau DOI
Yiwen Luo, Ning Ma, Yongqiang Zhang

et al.

Global and Planetary Change, Journal Year: 2025, Volume and Issue: unknown, P. 104825 - 104825

Published: April 1, 2025

Language: Английский

Citations

0
Responses of rainfall partitioning to water conditions in Chinese forests DOI
Qi Wu, Rui Yang, Hui Zeng

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 637, P. 131410 - 131410

Published: May 24, 2024

Language: Английский

Citations

1
CMIP6 ESMs overestimate greening and the photosynthesis trends in Dryland East Asia DOI

Yin-Miao Xiao,

Tiexi Chen, Xin Chen

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 937, P. 173432 - 173432

Published: May 24, 2024

Language: Английский

Citations

1
Acid deposition and meteorological factors together drive changes in vegetation cover in acid rain areas DOI Creative Commons

Zhongyuan Su,

Yunqi Wang,

Yonglin Zheng

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 167, P. 112720 - 112720

Published: Oct. 1, 2024

Language: Английский

Citations

1
Vegetation Phenology Rather than Climate Factors Dominate Productivity Growth Across Climate Zones and Vegetation Types DOI
Xinwei Wang, Jianhao Li,

Jianghua Zheng

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Warming and Rising CO2 Concentrations Drive Global Woody Encroachment from 2001 to 2020 DOI Creative Commons
Mengchen Yu, Yaoyao Zheng, Zaichun Zhu

et al.

Ecosystem Health and Sustainability, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

Woody plant encroachment (WPE) has been widely studied, yet the spatiotemporal pattern of global WPE and its drivers remain unclear. Here, based on long-term remote sensing observations, we investigated dynamics from 2001 to 2020 assessed contributions changes in main environmental factors. We found a significantly increasing trend (0.25% −1 , P < 0.01), resulting pronounced gain slight loss woody vegetation (0.29% 0.04% 0.01, respectively). The trends was characterized by large spatial heterogeneity, with 82.95% areas experiencing an expansion plants. then used random forest model incorporating key factors investigate complicated driving mechanisms WPE. Our results identified warming elevated CO 2 concentrations as primary dynamics, given their substantial (0.66% 0.32% Changing precipitation regime crucial, but showed great heterogeneity offset each other, ultimately leading smaller contribution (0.09% 0.05). In contrast, varying radiation burned had minimal effects (−0.04% > 0.05 −0.03% 0.01). also that local factors, such human activities natural disturbances, were non-negligible (0.07% study provides comprehensive picture WPE, enhancing our understanding biome transitions response changes.

Language: Английский

Citations

0