Climate Regulates the Effects of Abrupt Vegetation Shifts on Soil Moisture in the Loess Plateau, China DOI Open Access
Xiao Guo-an, Liangjie Xin, Xue Wang

и другие.

Land Degradation and Development, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 7, 2024

ABSTRACT Abrupt vegetation shifts, defined as an abrupt and irreversible level shift in the intercept (rather than slope) productivity, indicate transitions of unstable ecosystems to alternative states. Understanding these shifts is critical when monitoring ecosystem productivity because they may reveal drivers environmental impacts that differ from gradual changes vegetation. In China's Loess Plateau where sustainable water resource limits are being approached due revegetation, it unclear whether large‐scale have occurred how various affected soil content (SMC). this study, we found approximately 27.9% grasslands 24.8% forests on experienced positive 2000 2020. The results climate zone method multi‐period difference‐in‐differences (MDID) model showed effects SMC vary geographically. Approximately 55.9% 33.9% can wet (0–289 cm) during greening, while 35.7% 37.6% cause drying such events. Positive hydrological responses greening were concentrated with precipitation below 340 mm 520 mm, could be related limitation lower evapotranspiration. Similar also strong evaporative environments temperature, solar radiation, wind speed higher, vapor pressure deficit was lower, which been associated constraints evaporation through greening. This study reveals existence spatial heterogeneity response soils explores possible climate‐regulating mechanisms. used inform development targeted conservation restoration measures areas similar conditions.

Язык: Английский

Spatiotemporal changes of vegetation in the northern foothills of Qinling Mountains based on kNDVI considering climate time-lag effects and human activities DOI
Lili Chen,

Zhenhong Li,

Chenglong Zhang

и другие.

Environmental Research, Год журнала: 2025, Номер unknown, С. 120959 - 120959

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2

Analysis of Vegetation Restoration Potential and Its Influencing Factors on the Loess Plateau: Based on the Potential Realization Model and Spatial Dubin Model DOI Creative Commons
Chao Wang, Li‐Li Han, Youjun He

и другие.

Land, Год журнала: 2025, Номер 14(1), С. 138 - 138

Опубликована: Янв. 10, 2025

Improvements in vegetation coverage are driven by both resource endowment conditions and policy behaviors. To accurately reflect the restoration effect after ecological policies, this study used potential realization model to calculate degree of on Loess Plateau assess Grain for Green Program from 2000 2020. Then, influencing factors were explored using spatial Dubin model. The results reveal that (1) EVI value northern Shaanxi increased below 0.25 at beginning approximately 0.35 end, indicating green territory gradually expanded northwest over period, east west key areas cover further improvement; (2) compared traditional indicator, can more evaluate policies; (3) intensity is positively correlated with growth rate 0.183 significant 1% level, making it primary factor restoration. Additionally, annual average precipitation sunshine percentage have positive contributions improvement Plateau. study’s findings expected contribute development a scientific basis adjusting enhancing efforts.

Язык: Английский

Процитировано

1

Analysis of vegetation dynamics from 2001 to 2020 in China's Ganzhou rare earth mining area using time series remote sensing and SHAP-enhanced machine learning DOI Creative Commons
Ming Lei, Yuandong Wang, Guangxu Liu

и другие.

Ecological Informatics, Год журнала: 2024, Номер 84, С. 102887 - 102887

Опубликована: Ноя. 9, 2024

Язык: Английский

Процитировано

8

Dynamic monitoring and drivers of ecological environmental quality in the Three-North region, China: Insights based on remote sensing ecological index DOI Creative Commons

Leyi Zhang,

Li Xia, Xiuhua Liu

и другие.

Ecological Informatics, Год журнала: 2024, Номер unknown, С. 102936 - 102936

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

8

Determining Dominant Factors of Vegetation Change with Machine Learning and Multisource Data in the Ganjiang River Basin, China DOI Creative Commons
Zhiming Xia, Kaitao Liao, Liping Guo

и другие.

Land, Год журнала: 2025, Номер 14(1), С. 76 - 76

Опубликована: Янв. 3, 2025

Vegetation is a fundamental component of terrestrial ecosystems, and accurately assessing the effects seasonal climate variations, extreme weather events, land use changes on vegetation dynamics crucial. The Ganjiang River Basin (GRB), key region for water conservation recharge in southeastern China, has experienced significant variable past. However, comprehensive evaluations how these have impacted remain limited. To address this gap, we used machine learning models (random forest XGBoost) to assess impact variables, cover, topography, soil properties, atmospheric CO2, night-time light intensity dynamics. We found that annual mean NDVI showed slight increase from 1990 1999 but decreased significantly over last 8 years. XGBoost was better than RF model simulating when using all five types data source (R2 = 0.85; RMSE 0.04). most critical factors influencing were cropland ratio, followed by organic carbon content, elevation, cation exchange capacity, intensity, CO2 concentration. Spring minimum temperature important variable. Both linear nonlinear relationships identified between variables NDVI, with exhibiting threshold effects. These findings underscore need develop implement effective management strategies enhance health promote ecological balance region.

Язык: Английский

Процитировано

1

Multiscale analysis of ecosystem service interactions and driving factors in the Loess Plateau: Implications for ecological management DOI

Tao Xu,

Guangjin Tian, Tong Lin

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145074 - 145074

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Spatiotemporal evolution of ecological environmental quality and its dynamic relationships with landscape pattern in the Zhengzhou Metropolitan Area: A perspective based on nonlinear effects and spatiotemporal heterogeneity DOI
Qi Liu, Jiajun Qiao, Mengjuan Li

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер unknown, С. 144102 - 144102

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

5

Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index DOI
Tao Qi, Qiang Ren, Chunyang He

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 928, С. 172481 - 172481

Опубликована: Апрель 16, 2024

Язык: Английский

Процитировано

4

Unraveling supply-demand relationship of urban agglomeration's ecosystem services for spatial management zoning: Insights from threshold effects DOI

Mutian Xu,

Chao Bao

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106239 - 106239

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Social–Ecological Factors and Ecosystem Service Trade-Offs/Synergies in Vegetation Change Zones of Qilian Mountain National Park During 2000–2020 DOI Creative Commons
Xiaoyuan Yang, Zhonghua Zhang, Huakun Zhou

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(8), С. 1402 - 1402

Опубликована: Апрель 15, 2025

An ecological restoration assessment aims to evaluate whether projects (ERPs) have achieved predefined objectives, such as improving fractional vegetation cover (FVC) and enhancing ecosystem services (ESs), well optimize strategies based on outcomes. Despite recent advancements, current studies still fall short of fully capturing the trade-offs among ESs identifying underlying drivers different trends. To address these challenges, we applied Theil–Sen method delineate change zones in Qilian Mountain National Park (QLMNP) between 2000 2020, employed bivariate Moran’s I statistics analyze synergies four within zones, including carbon sequestration (CS), soil conservation (SC), water (WC), biodiversity maintenance (BIO), utilized a spatial random forest (SRF) model explore main socio-ecological driving factors trends their distribution. Our results revealed significant recovery QLMNP particularly regions with initially low FVC. Positive CS, SC, BIO highlighted success efforts, primarily driven by land conversion forests increased precipitation. However, 8.82% exhibited stagnation or degradation due rising temperatures overgrazing, leading declines SC BIO. Notably, introduced ESs, especially high FVC areas, where strong trade-off emerged WC. These findings highlight need for refining balance resource allocation. Finally, integrated trends, ES relationships, propose grid-based zonal governance plans QLMNP, prioritizing WC enhancement critical components future planning. This study serves foundation optimizing maintaining while offering actionable insights fine-grained evaluation sustainable development planning other regions.

Язык: Английский

Процитировано

0