Analysis of changes and driving forces of landscape pattern vulnerability at Qianping Reservoir in Central China DOI

Enkai Xu,

Hua Wang, Ying Li

и другие.

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 196(10)

Опубликована: Сен. 26, 2024

Язык: Английский

Temporal and Spatial Variations in Landscape Habitat Quality under Multiple Land-Use/Land-Cover Scenarios Based on the PLUS-InVEST Model in the Yangtze River Basin, China DOI Creative Commons

Ning He,

Wenxian Guo,

Hongxiang Wang

и другие.

Land, Год журнала: 2023, Номер 12(7), С. 1338 - 1338

Опубликована: Июль 4, 2023

Despite the Yangtze River Basin (YRB)’s abundant land and forestry resources, there is still a dearth of research on forecasting habitat quality changes resulting from various geographic environmental factors that drive landscape transformations. Hence, this study concentrates YRB as focal area, with aim utilizing Patch Landscape Upscaling Simulation model (PLUS) to scrutinize spatial distribution patterns evolution HQ under four scenarios: natural development scenario (NDS), farmland protection (CPS), urban (UDS), ecological (EPS), spanning past 2030. Our results show (1) 2000 2020, construction in expanded at high dynamic rate 47.86% per year, leading decrease 32,776 km2 cultivated area; (2) UDS had most significant expansion land, followed by NDS, CPS, EPS, which higher proportions ecologically used such forests grasslands; (3) index ranged 0.211 0.215 (low level), showing slight upward trend, drastic occurring low-level areas (−0.49%); (4) EPS highest (0.231), CPS (0.215), increasing proportion lower-level 2.64%; (5) addition government policies, NDVI, DEM, GDP, population were also affecting pattern quality.

Язык: Английский

Процитировано

36

Influence of Human Activity Intensity on Habitat Quality in Hainan Tropical Rainforest National Park, China DOI
Nianlong HAN, Miao Yu, Peihong Jia

и другие.

Chinese Geographical Science, Год журнала: 2024, Номер 34(3), С. 519 - 532

Опубликована: Март 18, 2024

Язык: Английский

Процитировано

10

Understanding relationships between landscape multifunctionality and land-use change across spatiotemporal characteristics: Implications for supporting landscape management decisions DOI

Quan Wang,

Haijun Wang, Haoran Zeng

и другие.

Journal of Cleaner Production, Год журнала: 2022, Номер 377, С. 134474 - 134474

Опубликована: Окт. 4, 2022

Язык: Английский

Процитировано

20

Analysis of landscape pattern vulnerability in Dasi river basin at the optimal scale DOI Creative Commons
Haocheng Wang, Lin Wang, Xia Liu

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Май 10, 2024

Abstract Since the reform and opening up in 1978, Dasi River Basin within Jinan’s startup area from replacing old growth drivers with new ones (startup area) has experienced rapid urbanization industrialization, landscape pattern changed significantly, resulting a series of eco-environmental problems. In order to more accurately identify vulnerable areas pattern, understand their cause mechanism changing laws, provide theoretical basis for implementation sustainable planning management region. Four Landsat images 2002, 2009, 2015 2020 were taken as data sources, optimal granularity analysis was determined perspective level class by using coefficient variation method, effect curve information loss model, amplitude grid method semi-variance function. Then, vulnerability assessment model constructed based on scale, its spatiotemporal evolution characteristics spatial autocorrelation analyzed. The result showed that: (1) this study 80 m, 350 × m. (2) During 2002–2020, overall southern part an increasing trend, while that middle northern parts decreasing trend. (3) mean values index 0.1479, 0.1483, 0.1562 0.1625, respectively, showing trend year year. terms land use, during average indices forestland built increased 23.18% 21.43%, followed water body bare land, 12.18% 9.52%, changes cropland grassland relatively small, 5.36% 5.65%, respectively. (4) significant positive correlation distribution. Low-Low generally transferred southeastern midwestern northern, High–High mainly southern. Overall, degree agglomeration

Язык: Английский

Процитировано

4

Spatiotemporal analysis of habitat quality and driving factors in the middle reaches of the Yellow River Basin DOI
Luyao Wang,

Dong Jia

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(4)

Опубликована: Март 12, 2025

Язык: Английский

Процитировано

0

Spatiotemporal patterns of pesticide residues in intensive agricultural soil and water bodies in Shaheed Benazirabad, Pakistan DOI

Najeeba Parre Pakar,

Kelly Redeker,

Muhammad Farooq Husain Munis

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(4)

Опубликована: Март 19, 2025

Язык: Английский

Процитировано

0

Change Patterns of Ecological Vulnerability and Its Dominant Factors in Mongolia During 2000–2022 DOI Creative Commons
Jing Han, Bing Guo,

Liang Pan

и другие.

Remote Sensing, Год журнала: 2025, Номер 17(7), С. 1248 - 1248

Опубликована: Апрель 1, 2025

Under global climate change, the ecological vulnerability issue in Mongolia has become increasingly severe. However, change process of environment and dominant driving factors different periods sub-regions are not clear. In this paper, we propose a new index for using MODIS data, combined with Geographical Detector gravity center model, to reveal spatiotemporal changes mechanisms from 2000 2022. The results show following: (1) newly proposed remote sensing high applicability ecosystems mainly Mongolia, an accuracy rate 89.39%; (2) belongs category moderate vulnerability, average 1.57, is shifting toward southwest direction; (3) Tmax leading factor especially at altitudes arid regions, where it directly affects vegetation growth, desertification, water availability. interactive have shifted ∩ Tmin PRE, PRE being eastern, central, southern regions western region, northwestern region. This study provides system constructing offers scientific references regional protection Mongolia.

Язык: Английский

Процитировано

0

Effects of the Loess Plateau on Habitat Quality of the West Qinling Mountains, China DOI Creative Commons
Caihong Hui, Xuelu Liu, Miaomiao Zhang

и другие.

Ecology and Evolution, Год журнала: 2025, Номер 15(5)

Опубликована: Май 1, 2025

ABSTRACT The West Qinling Mountains is the western extension of Mountains, geographic demarcation line between north and south China. Under control Loess Plateau, northern part has obvious transitional features in terms topography, climate, soil, vegetation. In order to explore effects Plateau on habitat quality (HQ) we selected five typical counties with different percentages area based geomorphic types, water system, vegetation zone, elevation, analyzed spatial temporal differentiation characteristics HQ their influence mechanisms help InVEST model geographical detector (GD) model. results showed that: (1) From 2000 2020, cultivated land continued decrease, while constructed increase. three regions a decreasing trend an increasing forest as within region decreases. Transition Zone increase construction county (2) changes bipolar sharpening phenomenon. moderately low grade high (3) mean first then decreasing. Zone, three‐level gradient low, medium, high. generally distribution south, was mainly distributed north. formation this verified that ecological environment had influenced Mountains. (4) Land use intensity (LUI) population density were dominant factors causing regions, NDVI NPP have always played key role variation synergistic enhancement effect various promotes change regional HQ.

Язык: Английский

Процитировано

0

Are the Main Drivers of Ecological Vulnerability in Typical Arid Zones Natural or Anthropogenic? An Analysis From an Evolutionary Process Framework DOI
Kexin Yang, Kang Hou,

Lixia Ma

и другие.

Land Degradation and Development, Год журнала: 2025, Номер unknown

Опубликована: Май 12, 2025

ABSTRACT As a key indicator of regional sustainable development, in‐depth study ecological vulnerability (EV) is conducive to the realization precise protection. However, complexity environment causes driving mechanism EV be difficult clarify, particularly for areas with special natural climates. This developed comprehensive natural‐social‐economic‐pollution‐environmental (NSEPE) index system and analytical framework typical arid areas, revealing EV's spatiotemporal heterogeneity factors. Based on structural equation modeling, spatial dominant factors was clarified. Finally, in 2035 under different scenarios predicted using CA‐Markov model. The results indicated that: (1) Ecological grades exhibited southeast‐northwest increasing trend (2000–2020), 9.6% transitioning from high low vulnerability. (2) three precipitation, farmers' income, Normalized Difference Vegetation Index (NDVI) were most important causing area. (3) Sustainable development better support protection human‐nature harmony by predicting 2035. can quantitatively identify law its influencing factors, also provides feasible idea evolution complex environments frequent human activities.

Язык: Английский

Процитировано

0

A new perspective on the whole process of ecological vulnerability analysis based on the EFP framework DOI

Lixia Ma,

Kang Hou,

Haojie Tang

и другие.

Journal of Cleaner Production, Год журнала: 2023, Номер 426, С. 139160 - 139160

Опубликована: Окт. 7, 2023

Язык: Английский

Процитировано

7