Spatio-temporal variations of ecosystem services and their drivers in the Pearl River Delta, China

被引:99
作者
Liu, Wei [1 ]
Zhan, Jinyan [2 ]
Zhao, Fen [3 ]
Wang, Chao [2 ]
Zhang, Fan [4 ]
Teng, Yanmin [5 ]
Chu, Xi [2 ]
Kumi, Michael Asiedu [2 ]
机构
[1] Shandong Normal Univ, Coll Geog & Environm, Jinan 250358, Peoples R China
[2] Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing 100875, Peoples R China
[3] Ludong Univ, Sch Resources & Environm Engn, Yantai 264025, Peoples R China
[4] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[5] Dongguan Univ Technol, Res Ctr Ecoenvironm Engn, Dongguan 523808, Peoples R China
基金
中国国家自然科学基金;
关键词
Ecosystem services; Driving factors analysis; Spatial heterogeneity; Land use change; Pearl River Delta; LAND-USE; REGION; URBANIZATION; IMPACTS; CLIMATE; AREAS; MODEL;
D O I
10.1016/j.jclepro.2022.130466
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent decades, ecosystems have been continuously deteriorating as a result of global climate change and human interference. Addressing changes in ecosystem services (ESs) and analyzing the drivers are critical for improving human wellbeing. Here, we evaluate the changes in five key ESs (grain production (GP), water yield (WY), soil conservation (SC), carbon sequestration (CS) and habitat quality (HQ)) in the Pearl River Delta (PRD) between 2000 and 2015 using an ecological process model. Furthermore, we analyze the spatial heterogeneity of the drivers behind ES change from the perspectives of nature, society, and economy. During the study period, the GP, CS, and HQ decreased by 2.05 x 10(6) tons, 2.9 x 10(6) tons and 0.043, respectively, while WY and SC increased by 0.51 x 10(10) m(3) and 0.3 x 10(10) tons, respectively. Across the PRD, the spatial distribution of ESs varied greatly. In general, ESs were lower in the plain areas and higher in the mountain areas. This was largely driven by natural, economic, and social factors; however, the driving factors for different ESs were diverse. GP and HQ were more affected by social and economic factors than natural factors, including urbanization level, the per-centage of construction land; whereas SC, WY, and CS were more affected by natural factors, including pre-cipitation, NDVI and DEM. Furthermore, the driving factors were spatially heterogeneous. The results of this study indicate that attention should be focused on key driving factors to generate targeted land use policies that improve ES values in the PRD.
引用
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页数:11
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