Seagrass distribution changes in Swan Lake of Shandong Peninsula from 1979 to 2009 inferred from satellite remote sensing data

Seagrass and associated bio-resources are very important for swan’s overwintering in Swan Lake in Rongcheng of Shandong Peninsula of China. The seagrass distribution changes, which are usually affected by the regional human activities, can indirectly affect swan’s habitat. In this study the satellite remote sensing data in years 1979–2009 together with in-situ observations in recent years were used to examine the seagrass distribution changes in Swan Lake. The band ratio of band 1 to band 2, Lyzenga’s methods and band synthesize of band 1, band 2 and band 3 were used for seagrass retrieval. The band ratio of band 1 to band 2 with ranges greater than 4.5 was used for estimating the seagrass coverage greater than 50%. Results showed that in years 1979–1990 seagrass coverage greater than 50% occupied more than half of the surface area of Swan Lake. In years 2000–2005, the total area with seagrass distributions reduced greatly, only about one sixth to one fourth of Swan Lake’s surface area. After 2005, the seagrass area in Swan Lake increased gradually and occasionally was greater than one third of the total surface area of the Lake. It was shown that human activities such as the dam and fish pond establishment and the awareness of seagrass importance and protected actively result in the seagrass distributions changes in Swan Lake which decreased first and then increased afterwards

Detection of Seagrass Distribution Changes from 1991 to 2006 in Xincun Bay, Hainan, with Satellite Remote Sensing

Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes

Rapid Detection of Three Common Bacteria Based on Fluorescence Spectroscopy

As an important part of environmental water quality monitoring, efficient bacterial detection has attracted widespread attention. Among them, LIF (laser-induced fluorescence) technology has the characteristics of high efficiency and sensitivity for bacterial detection. To simplify the experimental process of bacterial detection, fluorescence emission spectra of E. coli (Escherichia coli) and its deactivated controls, K. pneumoniae (Klebsiella pneumoniae) and S. aureus (Staphylococcus aureus), were analyzed with fluorescence excitation by a 266 nm laser. By analyzing the results, it was found that the dominant fluorescence peaks of bacterial solutions at 335~350 nm were contributed by tryptophan, and the subfluorescence peaks at 515.9 nm were contributed by flavin; besides, K. pneumoniae and S. aureus had their own fluoresces characteristics, such as tyrosine contributing to sub-fluorescence peaks at 300 nm. The three species of bacteria can be differentiated with whole fluorescence spectrum by statistically analysis (p E. coli. The indexes of fluorescence intensity and FIR (fluorescence intensity ratio, I335~350/I515.9) can be used to retrieve the bacteria concentration as well as for bacteria differentiation using the index of slopes. The detection limit of bacteria is less than ~105 cell/mL using laser induced fluorescence methods in the paper. The study demonstrated the rapid detection capability of the LIF bacterial detection system and its great potential for rapid quantitative analysis of bacteria. This may bring new insight into the detection of common bacteria in water in situ

Predator-Prey Interactions between Nonnative Juvenile Largemouth Bass (Micropterus salmoides) and Local Candidate Prey Species in the Pearl River Delta: Predation Capacity, Preference and Growth Performance

An ontogenetic dietary shift is crucial for the survival and growth of piscivorous largemouth bass (LB). However, there is much to learn about the predator-prey interaction during the switching process. We carried out a series of indoor experiments to examine the predation capacity, predation preference, and growth performance of exotic juvenile LB feeding on candidate prey species in the Pearl River Delta. The widely distributed oriental river prawn (Macrobranchium nipponense), barcheek goby (Ctenogobius giurinus), western mosquitofish (Gambusia affinis), silver carp (Hypophthalmichthys molitrix), and mud carp (Cirrhinus molitorella), with relatively similar total lengths, were selected as potential prey based on their availability and habitat use. Our results show that predation capacity and preference varied quantitatively and qualitatively among prey species. The number of oriental river prawns killed was significantly less than that of fish species, comparing the 1st hour with the 24th hour (p < 0.01). The feeding rhythm of LB varied significantly from crayfish to fish. Numerically, Jacobs’ selection index reinforced LB’s special preference for predating G. affinis. Although there were obvious variations in predation capacity and feed selection, no statistically significant growth differences were detected among LB groups feeding on live M. nipponense, G. affinis, H. molitrix, and C. molitorella (p < 0.05). These findings suggest that the successful ontogenetic dietary shift of juvenile LB may depend on the availability and vulnerability of local fish species. Further study on the reproductive phenology of potential fish prey may help to predict LB’s establishment

Fishery Resource Evaluation in Shantou Seas Based on Remote Sensing and Hydroacoustics

The Shantou-Taiwan shoal fishing ground in southeastern China supports a significant population of pelagic fish, which play a key role in the marine ecosystem. An acoustic survey was carried out using a digital scientific echosounder in June 2019. In this paper, the spatial distribution of pelagic fish is analyzed based on acoustic data using geostatistical analysis tools. Meanwhile, the relationship between fish density from acoustic data and sea surface environment factors were evaluated by using generalized additive models (GAMs) based on the satellite-based oceanographic data of sea surface temperature, sea surface chlorophyll-a concentration, sea surface height and sea surface wind. The results showed the following: (1) Fish density and acoustic biomass have strong spatial correlation; the optimal model for acoustic biomass is exponential and the optimal model for fish density is gaussian; based on optimal model, spatial interpolation analysis of fish density and acoustic biomass was performed using the ordinary kriging method, and the higher values of density and acoustic biomass were located in the central and eastern parts of the study area. The total fish density and acoustic biomass is 2.56 × 1010 ind. and 1908.99 m2/m, respectively. (2) In vertical distribution, fish gradually move to the middle and lower layers of water during daytime, and gather in the middle and upper layers of water at night. (3) The variance explanation rate of GAM was 88.2% which indicates that the model has an excellent fitting degree, and the results of GAM showed that longitude, sea surface temperature (SST), sea surface wind (SSW), and sea surface height (SSH) had significant effects on fish density. Results of this study were meaningful for understanding the distribution of fishery resources, and as a guide for fish management in the Shantou offshore water

Fishery Resource Evaluation in Shantou Seas Based on Remote Sensing and Hydroacoustics

The Shantou-Taiwan shoal fishing ground in southeastern China supports a significant population of pelagic fish, which play a key role in the marine ecosystem. An acoustic survey was carried out using a digital scientific echosounder in June 2019. In this paper, the spatial distribution of pelagic fish is analyzed based on acoustic data using geostatistical analysis tools. Meanwhile, the relationship between fish density from acoustic data and sea surface environment factors were evaluated by using generalized additive models (GAMs) based on the satellite-based oceanographic data of sea surface temperature, sea surface chlorophyll-a concentration, sea surface height and sea surface wind. The results showed the following: (1) Fish density and acoustic biomass have strong spatial correlation; the optimal model for acoustic biomass is exponential and the optimal model for fish density is gaussian; based on optimal model, spatial interpolation analysis of fish density and acoustic biomass was performed using the ordinary kriging method, and the higher values of density and acoustic biomass were located in the central and eastern parts of the study area. The total fish density and acoustic biomass is 2.56 × 1010 ind. and 1908.99 m2/m, respectively. (2) In vertical distribution, fish gradually move to the middle and lower layers of water during daytime, and gather in the middle and upper layers of water at night. (3) The variance explanation rate of GAM was 88.2% which indicates that the model has an excellent fitting degree, and the results of GAM showed that longitude, sea surface temperature (SST), sea surface wind (SSW), and sea surface height (SSH) had significant effects on fish density. Results of this study were meaningful for understanding the distribution of fishery resources, and as a guide for fish management in the Shantou offshore water

Interannual, Seasonal, and Monthly Variability of Sea Surface Temperature Fronts in Offshore China from 1982–2021

The offshore China (OC) region is a significant sea area in the Western Pacific and many researchers have been interested in the distribution of sea surface temperature (SST) fronts in this area. In this study, the Cayula and Cornillon single image edge detection algorithm was used to detect SST fronts using the Daily Optimum Interpolation Sea Surface Temperature data from 1982 to 2021. The results revealed that there are eighteen SST fronts in OC— three in the Bohai Sea, seven in the Yellow Sea, two in the East China Sea, five in the South China Sea, one in the Pacific Ocean east of Taiwan province, China—and among them a new front was detected in the Yellow Sea and named the Yellow Sea Ring Front. The frequency of most fronts showed a tendency of initially increasing and then decreasing from January to September, followed by a trend of growing steadily from October to December. The frequency of a few fronts showed a decreasing tendency from January to September and an increasing tendency from October to December. The frequency of most fronts is highest in winter and lowest in summer. In spring and autumn, the frequency of most fronts is lower than that in winter and higher than that in summer. The annual average frontal probability of five-ninths of the fronts showed an upward trend, and the annual average frontal probability value of one-third of the fronts showed a downward trend. The rest of the fronts showed a stable trend. The results of this paper also showed that the Liaodong Bay Front and the Bohai-Laizhou Bay Front did not form a complete front, as previously reported. In addition, the frontal probability of the Bohai Front to the north of 39° N was in the tendency of decreasing

Interannual, Seasonal, and Monthly Variability of Sea Surface Temperature Fronts in Offshore China from 1982–2021

The offshore China (OC) region is a significant sea area in the Western Pacific and many researchers have been interested in the distribution of sea surface temperature (SST) fronts in this area. In this study, the Cayula and Cornillon single image edge detection algorithm was used to detect SST fronts using the Daily Optimum Interpolation Sea Surface Temperature data from 1982 to 2021. The results revealed that there are eighteen SST fronts in OC— three in the Bohai Sea, seven in the Yellow Sea, two in the East China Sea, five in the South China Sea, one in the Pacific Ocean east of Taiwan province, China—and among them a new front was detected in the Yellow Sea and named the Yellow Sea Ring Front. The frequency of most fronts showed a tendency of initially increasing and then decreasing from January to September, followed by a trend of growing steadily from October to December. The frequency of a few fronts showed a decreasing tendency from January to September and an increasing tendency from October to December. The frequency of most fronts is highest in winter and lowest in summer. In spring and autumn, the frequency of most fronts is lower than that in winter and higher than that in summer. The annual average frontal probability of five-ninths of the fronts showed an upward trend, and the annual average frontal probability value of one-third of the fronts showed a downward trend. The rest of the fronts showed a stable trend. The results of this paper also showed that the Liaodong Bay Front and the Bohai-Laizhou Bay Front did not form a complete front, as previously reported. In addition, the frontal probability of the Bohai Front to the north of 39° N was in the tendency of decreasing