Sun Y.G.,National Marine Environmental Monitoring Center |
Zhao D.Z.,National Marine Environmental Monitoring Center |
Guo W.Y.,University of Aarhus |
Gao Y.,South China Sea Environmental Monitoring Center |
And 2 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2013
Mangrove trees form a community of woody plants in intertidal areas periodically immersed by sea water, and are located in tropical and sub-tropical zones. Mangrove forests are complicated ecological systems with characteristics of both land and sea, and form coastal ecologically critical areas (ECA). Monitoring ecological parameters of mangrove ecological systems has gained increased attention from governments and scholars. Ground-based investigation can lead to comprehensive understanding of the structure and functions of the mangrove ecosystem. However, because of spatial and temporal limitations, information on ecological changes of mangrove trees over long periods and large regions cannot be obtained in this way. Advancements in modern remote sensing technology, modeling and simulation, and landscape pattern analysis have provided important technological means for discerning spatiotemporal ecological ecosystem changes. In particular, remote sensing has become an important tool for obtaining temporal and spatial dimensions of ecological parameters of the mangrove forest ecological system. Statistics show that by May 2012, a total of 233 academic papers had been published outside China on remote sensing for monitoring mangrove forests, a number which is increasing yearly. This research mainly focuses on dynamic monitoring, inter-species classification, and structural monitoring of those forests. Especially since 2000, structural monitoring of mangrove communities and investigation of their driving forces and other aspects (sea level changes and comprehensive investigations) have become primary research topics. The application of remote sensing to mangrove forest ecosystem monitoring in China began in the 1990s and has been increasing remarkably in recent years, particularly during the period 2008-2011. This paper summarizes the status of such application and current problems. Specifically, the work expounds on the following aspects: 1) Theories and methods of dynamic monitoring of mangrove-covered wetlands. 2) Theories and methods of inter-species classification technology, as well as requirements of image data. In particular, classification of mangrove trees does not rely only on spectral characteristics, but also requires consideration of structural information that helps enhance classification precision. 3) Theories and methods of remote monitoring of structural parameters of mangrove communities (LAI, crown diameter, tree height and others). In addition, investigations of the relationship between the radar backscattering coefficient and crown diameter and vertical structure of mangrove trees, through establishing a model of their quantitative relationships; this facilitates remote monitoring of mangrove forest growth by applying C-band, L-band, P-band, C-VV and C-HH bands of NASA/JPL. 4) Theories and methods of remote monitoring and inversion of primary production of mangrove forests. Comparative analysis shows that the radar backscattering coefficient is more precise than the NDVI model in estimating vegetation biomass. 5) The status of disasters affecting mangrove forests (diseases, insect infestation and storm surges) and of monitoring theories. 6) Remote dynamic monitoring of and comments on the mangrove-covered region and inter-species landscape patterns. 7) Remote sensing of and comments on driving mechanisms of dynamic evolution of mangrove-covered wetlands. 7) Status and methods of application of remote sensing technology in protection and management of mangrove-covered wetlands. This paper points out existing deficiencies and challenges in remote monitoring of elements of the mangrove forest ecosystem, and emphasizes the need for more research into standardization of classification systems and enhancement of classification precision. Also needed is research into parameters of the ecological characteristics of mangrove forests (diversity and species dominance), spatial evolution of the ecological system, and dimensional effects of remote monitoring. Remote monitoring of the mangrove forest ecosystem lags behind in China, so more such studies should be undertaken in the country.
Jiang A.,CAS Guangzhou Institute of Geochemistry |
Jiang A.,University of Chinese Academy of Sciences |
Zhou P.,CAS Guangzhou Institute of Geochemistry |
Zhou P.,South China Sea Environmental Monitoring Center |
And 3 more authors.
Organic Geochemistry | Year: 2013
A rapid, small scale method for separating alkylnaphthalenes from aromatic fractions in sedimentary organic matter, named two-step column chromatography, is described using alumina as the stationary phase. The entire process operates using minimal amounts of solvents and alumina, with sample sizes of as little as 1. mg and a duration of 30. min. The results monitored by gas chromatography-mass spectrometry showed that clean alkylnaphthalenes and biphenyls can be obtained that are free of unresolved complex mixture (UCM), monoaromatics and triaromatics, which allows accurate measurement of compound specific stable isotope data. This method provides rapid sample processing suitable for routine analysis in organic geochemistry to better extract the geological and geochemical information carried by alkylnaphthalenes in sedimentary organic matter. © 2013 Elsevier Ltd.
Chen W.,Guangzhou University |
Chen W.,South China Sea Environmental Monitoring Center |
Zhang H.,Guangzhou University |
Chen Y.,Guangzhou University |
And 2 more authors.
Chinese Journal of Environmental Engineering | Year: 2014
Environmental factors play important roles in the removal of thallium by sulfate-reducing bacteria (SRB).In present study, three SRBs were isolated from an up-flow anaerobic sludge bed (UASB) used for treatment of acid mine drainage and effect of pH, temperatures and initial concentration on thallium removal by the three SRBs were investigated. The results showed that the highest thallium removal efficiencies of 96.71%,97% and 96.23% for the three SRBs were achieved at pH 6.0 while 93.11%,91.84% and 92.83% were obtained at 28~32℃.Low initial thallium concentration had little effect on thallium removal, and more than 99.4% of thallium could be removed by the three SRBs. Our study demonstrated that enhanced removal of thallium can be achieved by using SRBs and adjusting pH, temperatures and the initial thallium concentration of thallium.
Xu Z.,South China Sea Environmental Monitoring Center |
Zhu A.,South China Sea Environmental Monitoring Center |
Zhu A.,University of Chinese Academy of Sciences |
Cai W.,South China Sea Environmental Monitoring Center |
And 2 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2011
Seagrass beds are valuable coastal ecosystems and are also of economic importance. For the first time, we measured the levels of heavy metals (copper, lead, cadmium, and zinc) in the environment and in the bodies of benthic biota within a seagrass bed in Liusha Bay, Guangdong Province. The results revealed that concentrations of heavy metals in the water column and sediment were relatively low and of little potential threat to the ecosystem. The average concentrations of copper, lead, and zinc in the water column were (2. 2 ± 0. 1) μg/L, (0. 8 ± 0. 2) μg/L, and (7. 0 ± 0. 3) μg/L, respectively. Cadmium was not detected in the water column. The average concentrations of copper, lead, cadmium, and zinc in the surface of the sediment were (8. 2±0. 3) μg/L, (17. 3 ±1. 2) μg/L, (0. 10 ±0. 2) μg/L, and (11. 9 ±0. 2) μg/L, respectively. The ratios of metal concentration in water compared with sediment were 3 791, 21 625, 2 900, and 1681 for copper, lead, cadmium, and zinc, respectively. In contrast the levels of metals, especially cadmium, were markedly high in the bodies of macro-benthos such as the green algae, seagrasses, mollusca, and gastropods. The average concentrations of copper, lead, cadmium, and zinc in the green algae were 320, 21. 0, 0. 59 μg/L, and 142 μg/L, respectively. The average concentrations of copper, lead, cadmium, and zinc in the seagrasses were 13. 2, 10. 6, 1. 00 μg/L, and 72. 2 μg/L, respectively. The average concentrations of copper, lead, cadmium, and zinc in the bodies of mollusca were 1. 9, 0. 6, 1. 0 μg/L, and 13. 3 μg/L, respectively. The average concentrations of copper, lead, cadmium, and zinc in the bodies of gastropods were 5. 3, 1. 5, 0. 15 μg/L, and 21. 4 μg/L, respectively. The biological concentrating factors of benthic flora were generally greater than those of benthic fauna. The average biological concentrating factors for copper, lead, cadmium, and zinc in the green algae were 145. 45, 26. 25, 11. 80, and 20. 29, respectively. The average biological concentrating factors for copper, lead, cadmium, and zinc in the seagrasses were 6. 00, 13. 25, 20. 00, and 10. 31, respectively. The average biological concentrating factors for copper, lead, cadmium, and zinc in the bodies of mollusca were 0. 86, 0. 75, 20. 00, and 1. 90, respectively. The average biological concentrating factors for copper, lead, cadmium, and zinc in the bodies of gastropods were 2. 41, 1. 88, 3. 00, and 3. 06, respectively. The maximum biological concentrating factor was found for copper, in the alga Cladophora glomerata. Higher levels of copper, lead, and zinc were found in the green algae than in the seagrass. Lower levels of copper, lead, and zinc were concentrated in the bodies of mollusca than in the gastropods. For cadmium, the patterns of enrichment were reversed. This indicated that the dynamics of enrichment for cadmium might be very different from those of copper, lead, and zinc. Meanwhile, of these four metals, the biological concentrating factor of cadmium was the highest in seagrasses and mollusca. It was also the second highest in gastropods. In contrast, the biological concentrating factor of cadmium was the lowest of the four metals in the green algae. This indicated that the dynamics of enrichment for cadmium in the green algae might be very different from those in seagrasses, mollusca, and gastropods. The concentrations of lead and cadmium in the bodies of mollusca greatly exceeded the first levels of Marine Biological Quality (GB18421-2001, lead: 0. 1mg/kg; cadmium: 0. 2mg/kg). The greatest quality index (16. 2) was found for cadmium in the bodies of Barbatia fusca, indicating that there was cadmium discharging near the seagrass meadow.
Zhang J.-H.,South China Sea Environmental Monitoring Center |
Gao Y.,South China Sea Environmental Monitoring Center |
Fang H.-D.,South China Sea Environmental Monitoring Center
Chinese Journal of Applied Ecology | Year: 2011
An investigation was conducted on the meiobenthic abundance and biomass in the Lingdingyang Bay of Pearl River Estuary in July-August 2006(summer), April 2007(spring), and October 2007(autumn). A total of 15 meiobenthic groups were recorded, including Nematoda, Copepoda, Polychaeta, Ostracoda, Kinorhyncha, Amphipoda, Cumacea, Tanaidacea, Gnathosto-mulida, Nemertea, Gastropoda, Bivalvia, Sipuncula, Echiura, and other unidentified taxa. The average abundance of the meiobenthos in spring, summer, and autumn was 272.1 ±281.9, 165.1±147.1 and 246.4 ±369.3 ind · 10 cm-2, and Nematoda was the most dominant group in abundance, accounting for 86.8%, 83.5%, and 93.4% of the total, respectively, followed by Polychaeta, and benthic Copepoda. The meiobenthic abundance had an uneven vertical distribution. 54.1% of the meibenthos were in 0-2 cm sediments, 35.2% were in 2-5 cm sediments, and 10.8% were in 5-10 cm sediments. 87.4% of nematodes were distributed in 0-5 cm sediments. The average biomass of the meiobenthos in spring, summer, and autumn was 374.6 ± 346.9, 274.1 ±352.2, and 270.8 ±396.0 μg · 10 cm-2, and Polychaeta was the most dominant group in biomass, accounting for 30.1%, 46.7% and 46.0%, respectively, followed by Nematoda(25.2%, 20.1%, and 34.0%), and Ostracoda(20.6%, 15.3%, and 14.8%). The horizontal distribution of the meiobenthos had a trend of increasing from north to south, and being higher at east than at west. The meiobenthic abundance and biomass had significant positive correlations with water depth.