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

被引:36
作者
He, Ning [1 ]
Guo, Wenxian [1 ]
Wang, Hongxiang [1 ]
Yu, Long [1 ]
Cheng, Siyuan [1 ]
Huang, Lintong [1 ]
Jiao, Xuyang [1 ]
Chen, Wenxiong [1 ]
Zhou, Haotong [1 ]
机构
[1] North China Univ Water Resources & Elect Power, Coll Water Resources, Zhengzhou 450045, Peoples R China
基金
中国国家自然科学基金;
关键词
PLUS model; In-VEST model; landscape pattern; habitat quality; driving factors; AREA;
D O I
10.3390/land12071338
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 and environmental factors that drive landscape transformations. Hence, this study concentrates on the YRB as the focal area, with the aim of utilizing the Patch Landscape Upscaling Simulation model (PLUS) and the habitat quality model to scrutinize the spatial distribution of landscape patterns and the evolution of HQ under four scenarios: the natural development scenario (NDS), farmland protection scenario (CPS), urban development scenario (UDS), and ecological protection scenario (EPS), spanning from the past to 2030. Our results show that (1) from 2000 to 2020, the construction land in the YRB expanded at a high dynamic rate of 47.86% per year, leading to a decrease of 32,776 km(2) in the cultivated land area; (2) the UDS had the most significant expansion of construction land, followed by the NDS, CPS, and EPS, which had higher proportions of ecologically used land such as forests and grasslands; (3) from 2000 to 2020, the HQ index ranged from 0.211 to 0.215 (low level), showing a slight upward trend, with the most drastic changes occurring in the low-level areas (-0.49%); (4) the EPS had the highest HQ (0.231), followed by the CPS (0.215), with the CPS increasing the HQ proportion of the lower-level areas by 2.64%; (5) and in addition to government policies, NDVI, DEM, GDP, and population were also significant factors affecting landscape pattern and changes in habitat quality.
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页数:19
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共 52 条
[1]   Multi-temporal analysis of past and future land cover change in the highly urbanized state of Selangor, Malaysia [J].
Azari, Majid ;
Billa, Lawal ;
Chan, Andy .
ECOLOGICAL PROCESSES, 2022, 11 (01)
[2]   WORLD WILDLIFE FUND [J].
BARCLAYSMITH, P .
NATURE, 1962, 193 (4810) :12-&
[3]   Forces driving changes in cultivated land and management countermeasures in the Three Gorges Reservoir Area, China [J].
Cao Yin-gui ;
Bai Zhong-ke ;
Zhou Wei ;
Wang Jing .
JOURNAL OF MOUNTAIN SCIENCE, 2013, 10 (01) :149-162
[4]   Effects of long-term and large-scale ecology projects on forest dynamics in Yangtze River Basin, China [J].
Chen, Shanshan ;
Wen, Zhaofei ;
Zhang, Songlin ;
Huang, Ping ;
Ma, Maohua ;
Zhou, Xu ;
Liao, Tao ;
Wu, Shengjun .
FOREST ECOLOGY AND MANAGEMENT, 2021, 496
[5]   Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil [J].
da Cunha, Elias Rodrigues ;
Guimaraes Santos, Celso Augusto ;
da Silva, Richarde Marques ;
Bacani, Vitor Matheus ;
Pott, Arnildo .
LAND USE POLICY, 2021, 101
[6]   Intensity Characteristics and Multi-Scenario Projection of Land Use and Land Cover Change in Hengyang, China [J].
Deng, Zhiwei ;
Quan, Bin .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (14)
[7]   Pervasive human-driven decline of life on Earth points to the need for transformative change [J].
Diaz, Sandra ;
Settele, Josef ;
Brondizio, Eduardo S. ;
Ngo, Hien T. ;
Agard, John ;
Arneth, Almut ;
Balvanera, Patricia ;
Brauman, Kate A. ;
Butchart, Stuart H. M. ;
Chan, Kai M. A. ;
Garibaldi, Lucas A. ;
Ichii, Kazuhito ;
Liu, Jianguo ;
Subramanian, Suneetha M. ;
Midgley, Guy F. ;
Miloslavich, Patricia ;
Molnar, Zsolt ;
Obura, David ;
Pfaff, Alexander ;
Polasky, Stephen ;
Purvis, Andy ;
Razzaque, Jona ;
Reyers, Belinda ;
Chowdhury, Rinku Roy ;
Shin, Yunne-Jai ;
Visseren-Hamakers, Ingrid ;
Willis, Katherine J. ;
Zayas, Cynthia N. .
SCIENCE, 2019, 366 (6471) :1327-+
[8]   Spatiotemporal variations and driving factors of habitat quality in the loess hilly area of the Yellow River Basin: A case study of Lanzhou City, China [J].
Dong, Jianhong ;
Zhang, Zhibin ;
Liu, Benteng ;
Zhang, Xinhong ;
Zhang, Wenbin ;
Chen, Long .
JOURNAL OF ARID LAND, 2022, 14 (06) :637-652
[9]   Improving land-use change modeling by integrating ANN with Cellular Automata-Markov Chain model [J].
Gharaibeh, Anne ;
Shaamala, Abdulrazzaq ;
Obeidat, Rasha ;
Al-Kofahi, Salman .
HELIYON, 2020, 6 (09)
[10]   Multi-scale variability of hydrothermal regime based on wavelet analysis-The middle reaches of the Yangtze River, China [J].
Guo, Wenxian ;
He, Ning ;
Ban, Xuan ;
Wang, Hongxiang .
SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 841