Quantifying the human disturbance intensity of ecosystems and its natural and socioeconomic driving factors in urban agglomeration in South China.

Autor: Wang X; School of Geography Sciences, South China Normal University, Guangzhou, 510631, China. gwangxj@163.com., Liu G; School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China. lg760411@126.com., Xiang A; School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China., Qureshi S; Institute of Geography, Humboldt University of Berlin, Rudower Chaussee 16, 12489, Berlin, Germany., Li T; School of Geography Sciences, South China Normal University, Guangzhou, 510631, China., Song D; School of Geography Sciences, South China Normal University, Guangzhou, 510631, China., Zhang C; School of Geography Sciences, South China Normal University, Guangzhou, 510631, China.
Jazyk: angličtina
Zdroj: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2022 Feb; Vol. 29 (8), pp. 11493-11509. Date of Electronic Publication: 2021 Sep 18.
DOI: 10.1007/s11356-021-16349-1
Abstrakt: The impact of human activities on terrestrial ecosystems is becoming more intense than ever in history. Human disturbance analyses play important roles in appropriately managing the human-environment relationship. In this study, a human disturbance index (HDI) that uses land use and land cover data from 1980, 2000, 2010, and 2018 is proposed to assess the human disturbance of ecosystems in the Guangdong-Hong Kong-Macao Greater Bay Area. The HDI is first calculated by classifying the human disturbance intensity into seven levels and 13 categories from weak to strong in ecosystems. Then the driving factors of the HDI spatial pattern change are explored using a geographically weighted regression (GWR) model. The results showed that the spatial pattern of the HDI was high in the middle and low in the surrounding areas. The intensity of human disturbance increased, and the medium and high disturbance areas expanded during 1980-2018, especially in Guangzhou, Foshan, Shenzhen, and Dongguan. Human disturbance displayed an obvious spatial heterogeneity. The GWR model had a better explanation effect of the analysis of the HDI change drivers. The driving effect of the socioeconomic conditions was significantly stronger than that of the natural environmental. This study assists in understanding the distribution and change characteristics of the ecological environment in areas with strong human activities and provides a reference for related studies.
(© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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