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Li H, Zhang K, Liu Y, Qin Y, Wang W, Wang M, Liu Y, Li Y. Spatiotemporal evolution of land use and carbon storage in China: Multi-Scenario simulation and driving factor analysis based on the PLUS-InVEST model and SHAP. ENVIRONMENTAL RESEARCH 2025; 279:121860. [PMID: 40398701 DOI: 10.1016/j.envres.2025.121860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2025] [Revised: 05/13/2025] [Accepted: 05/14/2025] [Indexed: 05/23/2025]
Abstract
The spatiotemporal distribution of land use/cover changes (LUCCs) and carbon storage (CS), as well as their driving factors under global climate change, have become key issues in ecological and environmental sciences. As a major contributor to global CS, understanding China's CS changes and the driving forces is crucial for addressing climate change and achieving carbon neutrality. In the study, China is split into seven major ecological zones, and a combined model is suggested that uses the CMIP6 climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) along with the PLUS and InVEST models. The study systematically analyzes the spatiotemporal evolution of land use and CS from 1990 through 2020 and predicts the changes under three future scenarios for 2030 and 2050. Using Random Forest and SHAP methods, the study quantifies the impact weights of natural and anthropogenic factors on CS. The main findings are as follows: (1) From 1990 to 2020, China's CS showed a steadily increasing trend, but with significant regional differences. The Qinghai-Tibet Plateau is the largest CS area, accounting for 26.96 % of the national total CS in 2020, while the highly urbanized and densely populated South China region has the lowest CS share, only 4.39 %. (2) Under the SSP1-2.6 scenario, CS will be highest in 2030 and 2050, reaching 1.003 × 1011 t and 1.026 × 1011 t, respectively, with growth rates of 3.33 % and 5.79 % compared to 2020. Under the SSP5-8.5 scenario, CS shows a downward trend, with 9.31 × 1010 t and 9.32 × 1010 t in 2030 and 2050, respectively, corresponding to a decrease of 4.01 % and 3.91 % compared to 2020. The SSP2-4.5 scenario predicts relatively stable CS. (3) Natural and anthropogenic factors are the primary drivers of the spatiotemporal changes in CS. The importance of these factors varies across different regions. The study provides scientific insights for ecological protection and carbon neutrality policy formulation.
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Affiliation(s)
- Haojuan Li
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Kun Zhang
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Yongqiang Liu
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China.
| | - Yan Qin
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Weiping Wang
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Mingyu Wang
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Yongnan Liu
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
| | - Yaqian Li
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China; Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, 830017, China
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Liu L, Wang WJ, Wang L, Cong Y, Wu H. Impacts of Multi-Land Use Decisions on Temperate Forest Habitat Quality in the Changbai Mountain Region, Northeast China. Ecol Evol 2025; 15:e71123. [PMID: 40170829 PMCID: PMC11949574 DOI: 10.1002/ece3.71123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2024] [Revised: 02/11/2025] [Accepted: 02/28/2025] [Indexed: 04/03/2025] Open
Abstract
Human-driven land use changes significantly contribute to habitat loss and fragmentation in temperate forests, prompting the implementation of ecological conservation programs. However, these efforts may be undermined by the competing demands of ecological conservation and economic development. This study assessed changes in temperate forest habitat quality and the relative contribution of competing land use decisions (ecological programs, cropland expansion, and urbanization) to these changes in the Changbai Mountain region, Northeast China from 1990 to 2050. Our results revealed a region-wide decline (-20.77%) in habitat quality over the past 30 years, with projected improvements (+14.64%) under the future scenario, albeit with considerable regional variations. Ecological programs contributed to long-term habitat improvements by preserving and expanding forest cover. However, cropland expansion and urbanization through forest conversion were identified as the primary drivers of habitat quality degradation, leading to both direct habitat loss and indirect negative effects on the quality of the remaining habitat. Our findings offer valuable insights into the effectiveness of ecological programs and the trade-offs posed by economic pressures, highlighting the need for integrated land use strategies that balance ecological and socio-economic objectives in temperate forest management.
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Affiliation(s)
- Li Liu
- Northeast Institute of Geography and Agroecology, Chinese Academy of SciencesChangchunChina
- University of Chinese Academy of SciencesBeijingChina
| | - Wen J. Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of SciencesChangchunChina
| | - Lei Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of SciencesChangchunChina
| | - Yu Cong
- Northeast Institute of Geography and Agroecology, Chinese Academy of SciencesChangchunChina
| | - Haitao Wu
- Northeast Institute of Geography and Agroecology, Chinese Academy of SciencesChangchunChina
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Xi H, Li T. Unveiling the spatiotemporal dynamics and influencing factors of carbon stocks in the yangtze river basin over the past two decades. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176261. [PMID: 39277012 DOI: 10.1016/j.scitotenv.2024.176261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 09/09/2024] [Accepted: 09/11/2024] [Indexed: 09/17/2024]
Abstract
Terrestrial ecosystems are critical to the global carbon cycle and climate change mitigation. Over the past two decades, the Yangtze River Basin (YRB) has implemented various ecological restoration projects and active management measures, significantly impacting carbon stock patterns. This study employed random forest models to analyze the spatial and temporal patterns of carbon stocks in the YRB from 2001 to 2021. In 2021, carbon density in the YRB ranged from 8.5 to 177.4 MgC/ha, with a total carbon stock of 18.05 PgC. Over 20 years, the YRB sequestered 1.26 billion tons of carbon, accounting for 11.28 % of the region's fossil fuel carbon emissions. Notably, forests exhibited the highest carbon density, averaging 98.01 ± 25.01 MgC/ha (2021) with a carbon stock growth rate of 51.6 TgC/yr. Piecewise structural equation model was used to assess the effects of climate and human activities on carbon density, revealing regional variability, with unique patterns observed in the source region. Human activities primarily influence carbon density indirectly through vegetation alterations., while climate change directly impacts ecosystem biophysical processes. These findings offer critical insights for climate mitigation and adaptation strategies, enhancing the understanding of carbon dynamics for sustainable development and global carbon management.
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Affiliation(s)
- Haojun Xi
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China; State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Beijing 100871, China
| | - Tianhong Li
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China; State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Beijing 100871, China.
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Shahrour MH, Arouri M, Tran DV, Rao S. Carbon consciousness: The influence of CEO ownership. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 364:121455. [PMID: 38878577 DOI: 10.1016/j.jenvman.2024.121455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/28/2024] [Accepted: 06/09/2024] [Indexed: 06/24/2024]
Abstract
Building on prior research on managerial ownership and firm performance, this study is the first to link CEO ownership to carbon commitment. We examine if firms led by CEOs with substantial ownership are more or less inclined to prioritise reducing carbon emissions than those without such ownership. We find that higher CEO ownership is associated with a lower carbon commitment, indicating that CEOs with more significant ownership do not prioritise carbon emissions reduction. However, we notice an inverted U-shaped relationship. Particularly, moderate CEO ownership (between 5% and 10% of total shares) has the stronger impact. The results are robust to alternative measures and approaches. The study provides empirical evidence on how CEO ownership can influence corporate carbon commitment and contribute to the global fight against climate change.
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Affiliation(s)
- Mohamad H Shahrour
- College of Business, Accounting & Finance Department, University of Doha for Science and Technology, Doha, Qatar.
| | | | - Dung V Tran
- Banking Academy of Vietnam, State Bank of Vietnam, Ha Noi, Viet Nam
| | - Sandeep Rao
- DCU Business School, Dublin City University, Dublin, 09, Ireland
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