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Wang X, Liu G, Xiang A, Qureshi S, Li T, Song D, Zhang C. Quantifying the human disturbance intensity of ecosystems and its natural and socioeconomic driving factors in urban agglomeration in South China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:11493-11509. [PMID: 34535865 DOI: 10.1007/s11356-021-16349-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/31/2021] [Indexed: 05/04/2023]
Abstract
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.
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Affiliation(s)
- Xiaojun Wang
- School of Geography Sciences, South China Normal University, Guangzhou, 510631, China.
| | - Guangxu Liu
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China.
| | - Aicun Xiang
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Salman Qureshi
- Institute of Geography, Humboldt University of Berlin, Rudower Chaussee 16, 12489, Berlin, Germany
| | - Tianhang Li
- School of Geography Sciences, South China Normal University, Guangzhou, 510631, China
| | - Dezhuo Song
- School of Geography Sciences, South China Normal University, Guangzhou, 510631, China
| | - Churan Zhang
- School of Geography Sciences, South China Normal University, Guangzhou, 510631, China
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Diamantopoulou C, Christoforou E, Dominoni DM, Kaiserli E, Czyzewski J, Mirzai N, Spatharis S. Wavelength-dependent effects of artificial light at night on phytoplankton growth and community structure. Proc Biol Sci 2021; 288:20210525. [PMID: 34157871 DOI: 10.1098/rspb.2021.0525] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Artificial light at night (ALAN) is a disruptive form of pollution, impacting physiological and behavioural processes that may scale up to population and community levels. Evidence from terrestrial habitats show that the severity and type of impact depend on the wavelength and intensity of ALAN; however, research on marine organisms is still limited. Here, we experimentally investigated the effect of different ALAN colours on marine primary producers. We tested the effect of green (525 nm), red (624 nm) and broad-spectrum white LED ALAN, compared to a dark control, on the green microalgae Tetraselmis suesica and a diatom assemblage. We show that green ALAN boosted chlorophyll production and abundance in T. suesica. All ALAN wavelengths affected assemblage biomass and diversity, with red and green ALAN having the strongest effects, leading to higher overall abundance and selective dominance of specific diatom species, some known to cause harmful algal blooms. Our findings show that green and red ALAN should be used with caution as alternative LED colours in coastal areas, where there might be a need to strike a balance between the effects of green and red light on marine primary producers with the benefit they appear to bring to other organisms.
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Affiliation(s)
- Christina Diamantopoulou
- Department of Biological Applications and Technology, University of Ioannina, 45110 Ioannina, Greece.,School of Life Sciences, University of Glasgow, Glasgow G128QQ, UK
| | - Eleni Christoforou
- School of Life Sciences, University of Glasgow, Glasgow G128QQ, UK.,Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G128QQ, UK
| | - Davide M Dominoni
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G128QQ, UK
| | - Eirini Kaiserli
- Molecular Cell and Systems Biology, University of Glasgow, Glasgow G128QQ, UK
| | - Jakub Czyzewski
- College of Medical, Veterinary and Life Sciences (MVLS), Bioelectronics Unit, University of Glasgow, Glasgow G128QQ, UK
| | - Nosrat Mirzai
- College of Medical, Veterinary and Life Sciences (MVLS), Bioelectronics Unit, University of Glasgow, Glasgow G128QQ, UK
| | - Sofie Spatharis
- School of Life Sciences, University of Glasgow, Glasgow G128QQ, UK.,Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G128QQ, UK
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Shi H, Lu J, Zheng W, Sun J, Li J, Guo Z, Huang J, Yu S, Yin L, Wang Y, Ma Y, Ding D. Evaluation system of coastal wetland ecological vulnerability under the synergetic influence of land and sea: A case study in the Yellow River Delta, China. MARINE POLLUTION BULLETIN 2020; 161:111735. [PMID: 33080385 DOI: 10.1016/j.marpolbul.2020.111735] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 09/30/2020] [Accepted: 09/30/2020] [Indexed: 06/11/2023]
Abstract
A comprehensive evaluation system and model of Coastal Wetland Ecological Vulnerability (CWEV) was constructed and applied to reveal spatial heterogeneity of the ecological vulnerability of the Yellow River Delta Wetland (YRDW). The results showed that the score of the ecological vulnerability (EVS) of the YRDW was 0.49, which was generally at a medium vulnerability level. The wetland area of high vulnerability was up to 943km2, accounting for 35.2% of the total area, followed by the medium vulnerable area with an area of 750km2, accounting for 28.1% of the total area. From the coastline perpendicularly to the land, the "seaward" gradient effect gradually decreased, the vulnerability-increasing "hydrologic connectivity" effect increased with the distance from the river channel, and the "land source influence" effect gradually decayed along with the vulnerability of population and economy gathering areas.
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Affiliation(s)
- Honghua Shi
- The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China.
| | - Jingfang Lu
- Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
| | - Wei Zheng
- The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
| | - Jingkuan Sun
- Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta, Binzhou University, Binzhou, Shandong Province 256603, China
| | - Jie Li
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266033, China
| | - Zhen Guo
- The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
| | - Jiantao Huang
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266033, China
| | - Shuting Yu
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266033, China
| | - Liting Yin
- Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
| | - Yongzhi Wang
- The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
| | - Yuxian Ma
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Dewen Ding
- The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
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