Evaluating the spatiotemporal patterns of GPP and tree growth for their response to CO 2 fertilization effects in mid-latitude forests of China DOI Creative Commons
Bin Wang,

Xiangqi Kong,

Shaojie Bian

et al.

Geo-spatial Information Science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: Jan. 17, 2025

The investigation of the spatiotemporal variation trend atmospheric CO2 fertilization effect (𝛽) has emerged as a prominent topic interest on global scale in recent times. Nevertheless, patterns 𝛽 remain unclear. Herein, we selected mid-latitude forests China designated study region. Accordingly, remote sensing Gross Primary Productivity (GPP) products were used along with model-based GPP simulation results and tree-ring data this study. This was combined random forest algorithm moving window approach to assess vegetation productivity tree growth responses variations between 1982 2015. Our findings suggest that from 2015, estimated derived two demonstrated declining trend. In particular, EC-LUE exhibited decrease rate βˆ’0.46%.100 ppmβˆ’1yrβˆ’1, while NIRv showed βˆ’0.04%.100ppmβˆ’1yrβˆ’1. Similarly, estimation based models also indicated decline Ξ², an average βˆ’0.08%.100 ppmβˆ’1yrβˆ’1 across total 18 models. Based analysis rings 16 sites, it observed radial response βˆ’0.81%.100 ppmβˆ’1yrβˆ’1. We speculated Ξ² is primarily driven by LAI age.

Language: Английский

Artificial intelligence for geoscience: Progress, challenges and perspectives DOI Creative Commons
Tianjie Zhao, Sheng Wang,

Chaojun Ouyang

et al.

The Innovation, Journal Year: 2024, Volume and Issue: 5(5), P. 100691 - 100691

Published: Aug. 23, 2024

Public summaryβ€’What does AI bring to geoscience? has been accelerating and deepening our understanding of Earth Systems in an unprecedented way, including the atmosphere, lithosphere, hydrosphere, cryosphere, biosphere, anthroposphere interactions between spheres.β€’What are noteworthy challenges As we embrace huge potential geoscience, several arise reliability interpretability, ethical issues, data security, high demand cost.β€’What is future The synergy traditional principles modern AI-driven techniques holds immense promise will shape trajectory geoscience upcoming years.AbstractThis paper explores evolution geoscientific inquiry, tracing progression from physics-based models data-driven approaches facilitated by significant advancements artificial intelligence (AI) collection techniques. Traditional models, which grounded physical numerical frameworks, provide robust explanations explicitly reconstructing underlying processes. However, their limitations comprehensively capturing Earth's complexities uncertainties pose optimization real-world applicability. In contrast, contemporary particularly those utilizing machine learning (ML) deep (DL), leverage extensive glean insights without requiring exhaustive theoretical knowledge. ML have shown addressing science-related questions. Nevertheless, such as scarcity, computational demands, privacy concerns, "black-box" nature hinder seamless integration into geoscience. methodologies hybrid presents alternative paradigm. These incorporate domain knowledge guide methodologies, demonstrate enhanced efficiency performance with reduced training requirements. This review provides a comprehensive overview research paradigms, emphasizing untapped opportunities at intersection advanced It examines major showcases advances large-scale discusses prospects that landscape outlines dynamic field ripe possibilities, poised unlock new understandings further advance exploration.Graphical abstract

Language: Английский

Citations

57
Maximizing carbon sequestration potential in Chinese forests through optimal management DOI Creative Commons
Zhen Yu, Shirong Liu, Haikui Li

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: April 11, 2024

Abstract Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion biomass stock 13.6 Β± 1.5 Pg C from 2020 2100, with additional sink through augmentation wood product pool (0.6-2.0 C) spatiotemporal optimization management (2.3 0.03 C). We find that statistical might cause large bias long-term projection underrepresentation or neglect changes. Remarkably, disregarding the repercussions harvesting on age can result premature shift timing peak 1–3 decades. Our findings emphasize pressing necessity for swift implementation optimal strategies enhancement.

Language: Английский

Citations

36
Unveiling China’s natural and planted forest spatial–temporal dynamics from 1990 to 2020 DOI
Kai Cheng, Haitao Yang, Hongcan Guan

et al.

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 209, P. 37 - 50

Published: Feb. 5, 2024

Language: Английский

Citations

33
Carbon sequestration potential of tree planting in China DOI Creative Commons
Ling Yao, Tang Liu, Jun Qin

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 27, 2024

Language: Английский

Citations

22
Forest aging limits future carbon sink in China DOI
Yi Leng, Wei Li, Philippe Ciais

et al.

One Earth, Journal Year: 2024, Volume and Issue: 7(5), P. 822 - 834

Published: May 1, 2024

Language: Английский

Citations

19
A daily gap-free normalized difference vegetation index dataset from 1981 to 2023 in China DOI Creative Commons
Huiwen Li, Yue Cao, Jingfeng Xiao

et al.

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: May 22, 2024

Long-term, daily, and gap-free Normalized Difference Vegetation Index (NDVI) is of great significance for a better Earth system observation. However, gaps contamination are quite severe in current daily NDVI datasets. This study developed 0.05Β° dataset from 1981-2023 China by combining valid data identification spatiotemporal sequence gap-filling techniques based on the National Oceanic Atmospheric Administration dataset. The generated more than 99.91% area showed an absolute percent bias (|PB|) smaller 1% compared with original data, overall R2 root mean square error (RMSE) 0.79 0.05, respectively. PB RMSE between our MODIS gap-filled (MCD19A3CMG) during 2000 to 2023 7.54% 0.1, three monthly datasets (i.e., GIMMS3g, MOD13C2, SPOT/PROBA) only -5.79%, 4.82%, 2.66%, To best knowledge, this first long-term far.

Language: Английский

Citations

11
Changes in soil microbial community and function across stand age of Cryptomeria japonica var. sinensis plantations in subtropical China DOI
Li Zhang,

Shichen Xiong,

Ya Shen

et al.

Applied Soil Ecology, Journal Year: 2024, Volume and Issue: 203, P. 105645 - 105645

Published: Sept. 20, 2024

Language: Английский

Citations

9
Exploring the role of the rhizosphere in soil carbon cycling: impacts on pools and components of SOC along a chronosequence of Cryptomeria japonica plantations in subtropical China DOI

Dengjie Zhou,

Yaling Yuan,

Jing Li

et al.

Plant and Soil, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Language: Английский

Citations

1
Incorporating site suitability and carbon sequestration of tree species into China’s climate-adaptive forestation DOI Creative Commons
Meinan Zhang, Shirong Liu, Xiangzhong Luo

et al.

Science Bulletin, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Strategic selection and precise matching of climate-resilient tree species are crucial for maximizing the mitigation adaptation potential Climate-Smart Forestry. However, current forestation plans often overlook species-specific environmental shifts, leading to suboptimal long-term carbon sequestration. Here we developed a climate-adaptive optimization framework guide planting in China, based on projected habitat suitability range shifts under future climate scenarios. Utilizing over 200,000 records from China's National Forest Inventory (1999-2018), quantified declines 12.1%-42.9% currently dominant plantation by 2060 due change. By optimizing species-site strategically harvesting timber at peak uptake, identified 43.2 million hectares suitable between 2025 2060, enabling approximately 46 billion climate-adapted trees with total sequestration 3822.6 Tg carbon-a 28.7% increase compared unmanaged Our study highlights importance adaptive strategies enhance conditions, providing technical guidance forest management support net-zero commitment.

Language: Английский

Citations

1
Accumulation of soil microbial extracellular and cellular residues during forest rewilding: Implications for soil carbon stabilization in older plantations DOI
Ke Shi, Jiahui Liao, Xiaoming Zou

et al.

Soil Biology and Biochemistry, Journal Year: 2023, Volume and Issue: 188, P. 109250 - 109250

Published: Nov. 17, 2023

Language: Английский

Citations

19