Unraveling the impact of urban expansion on vegetation carbon sequestration capacity: A case study of the Yangtze River Economic Belt

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106157 - 106157

Published: Jan. 1, 2025

Language: Английский

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Time-lag effects of NEP and NPP to meteorological factors in the source regions of the Yangtze and Yellow Rivers

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 15

Published: Jan. 10, 2025

Vegetation productivity and ecosystem carbon sink capacity are significantly influenced by seasonal weather patterns. The time lags between changes in these patterns (including vegetation) responses is a critical aspect vegetation-climate ecosystem-climate interactions. These can vary considerably due to the spatial heterogeneity of vegetation ecosystems. In this study focused on source regions Yangtze Yellow Rivers (SCRYR), we utilized long-term datasets Net Primary Productivity (NPP) model-estimated Ecosystem (NEP) from2015 2020, combined with reconstructed 8-day scale climate sequences, conduct partial correlation regression analysis (isolating influence individual meteorological factors lag effects). found that length effects varies depending regional topography, types, sensitivity their ecological environments factors. region River (SCR), times for NPP NEP response temperature (Tem) longer, compared (SYR), where generally less than 10 days. long precipitation (Pre), ranging from 50 60 days, were primarily concentrated northwestern part SCR, while precipitation, 34 48 covered broad western area. exhibits least solar radiation (SR), exceeding 54 days 99.30% region. contrast, showed varying respect SR: short (ranging 0 15 days) observed areas, 55 64 evident areas. highest SVL, followed C3A, PW, BDS, C3 descending order. This examined spatiotemporal impacts climatic drivers both perspectives. findings crucial enhancing sequestration at important water sources China.

Language: Английский

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Assessing eco-physiological patterns of Ailanthus altissima (Mill.) Swingle and differences with native vegetation using Copernicus satellite data on a Mediterranean Island

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103080 - 103080

Published: Feb. 1, 2025

Language: Английский

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Analysis of Driving Factors of Cropland Productivity in Northeast China Using OPGD-SHAP Framework

Land, Journal Year: 2025, Volume and Issue: 14(5), P. 1010 - 1010

Published: May 7, 2025

In the context of climate change and ecological degradation, enhancing cropland productivity in Northeast China is essential for ensuring national food security. This study adopted an integrated framework combining optimal parameter-based geographical detector (OPGD) SHapley Additive exPlanations (SHAP) to identify key drivers average total at county level from 2001 2020. Growing-season-based Net Primary Productivity (NPP) was estimated using CASA model represent productivity. Results indicated that natural factors significantly dominated spatial variation productivity, with their interactions amplified through dual-factor or nonlinear enhancements. Various machine learning models were fine-tuned compared, selected subsequent SHAP analysis. The findings revealed erosion intensity exhibited most significant impact on whereas effect precipitation shifted negative positive, a clear threshold around 400 mm—matching boundary between China’s semi-arid semi-humid regions. Low-elevation plains (<300 m) gentle slopes (<0.5°) predominately promoted Interactions fertilizer highlighted need moderate fertilization prevent degradation severely eroded counties. These provide scientific support targeted management aimed achieving sustainable agriculture China.

Language: Английский

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Dynamic Response of Vegetation Net Primary Productivity to Climate and Human Impacts in Mining-Dominated Basin in Inner Mongolia, China

Atmosphere, Journal Year: 2024, Volume and Issue: 15(12), P. 1457 - 1457

Published: Dec. 5, 2024

The net primary productivity (NPP) of vegetation is the key indicator for assessing ecosystem and carbon cycling. Ulan Mulun River Basin (UMRB) in Northwest China a typical coal mining area, including open-pit (OPM) underground (UGM). There are limited studies utilizing long-term, high-resolution data to investigate spatiotemporal driving mechanisms NPP different types non-coal (NCM) areas. In this study, was estimated using Landsat (30 m) an improved CASA model period 1987–2022. variations across basin were systematically investigated Theil–Sen–MK trend analysis, partial derivatives, multivariate regression residual explore quantify impacts climate variability (CV) human activities (HAs) on NCM research results show that overall fluctuating upward cover country 64.84% during from 1987 2022. However, there decreasing Precipitation major factor influencing change (21.835 gC/m2/a), while HAs had lesser effect (4.667 gC/m2/a). addition, UGM more positively affected by than OPM, OPM CV NCM. These findings can guide scientific ecological restoration strategies, assess balance impacts, optimize land management planning areas achieve between resource development environmental protection.

Language: Английский

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Assessment of the conservation effectiveness of nature reserves on the Qinghai-Tibet plateau using human activity and habitat quality indicators

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102872 - 102872

Published: Oct. 1, 2024

Language: Английский

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Spatiotemporal analysis of ocean primary productivity in Bohai Sea estimated using improved DINEOF reconstructed MODIS data

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102920 - 102920

Published: Nov. 1, 2024

Language: Английский

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