Search Results (3)

Macroalgae are an integral part of estuarine primary production; however, their excessive growth may have severe negative impacts on the ecosystem. Although it is generally believed that algal blooms may be caused by a combination of excessive nutrients and temperature, their occurrences are hard to predict, and quantitative monitoring is a logistical challenge which requires the development of reliable and inexpensive techniques. This can be achieved by implementation of processing algorithms and indices on multi-spectral satellite images. Tuggerah Lakes estuary on the Central Coast of NSW was studied because of the regular occurrences of blooms, primarily of green filamentous algae. The detection of algal blooms based on the red-edge effect of the chlorophyll provided consistent results supported by direct observations. The Floating Algae Index (FAI) was identified as the most accurate index for detecting algal blooms in shallow areas, following a comparative analysis of six commonly used algae detection indices. Logistic regression was implemented where FAI was used as a predictor of two clusters, “bloom” and “non-bloom”. FAI was calculated for multi-spectral satellite images based on pixels of 20 × 20 m, covering the entire area of the Tuggerah Lakes. Seven sample points (pixels) were chosen, and the optimal threshold was found for each pixel to assign it to one of the two clusters. The logistic regression model was trained for each pixel; then the optimal parameters for its coefficients and the optimal classification threshold were obtained by cross-validation based on bootstrapping. Probabilities for classifying clusters as either “bloom” or “non-bloom” were predicted with respect to the optimal threshold. The resulting model can be used to estimate probability of macroalgal blooms in coastal estuaries, allowing quantitative monitoring through time and space. Full article

Oculatellaceae is a family of cyanobacteria with orange spots in the apical cells and has a wide distribution in various living environments. The species of this family are widely distributed but relatively few in number. In order to enrich our knowledge of the species diversity of cyanobacteria in China, and further achieve the monophyletic development of modern cyanobacteria classification systems, we studied two algal strains, designated as SXACC0114 and SXACC0117, isolated from China and subjected to taxonomic studies using a multiphase approach. The colony of the strain SXACC0114 is bright blue-green in color and does not form a biofilm. The trichomes are yellow-green to bright blue-green. For the strain SXACC0117, no false branching is observed. It has wider filaments and more distinct sheaths, and lacks swollen cells. Based on 16S rRNA gene phylogenetic analysis, the results showed that these two algal strains clustered in Albertania and Tildeniella evolutionary branches, respectively, with high bootstrap support. In addition, the secondary structures, which are constructed based on the internal transcription spacer (ITS) of 16S-23S rRNA, exhibit differences, and the algal strain has unique D1-D1ʹ, Box-B, and V3 helix structures. These results support the establishment of two new species, described as Albertania yunnanense sp. nov. and Tildeniella yunnanense sp. nov. The discovery of these new species provides a scientific basis for the development and utilization of algae. Full article

The Middle Route of the South-to-North Water Diversion Project (MRP) is an important water supply for 20 large cities and 100 counties in Northern China. However, since 2016, the growth of large filamentous algae clusters has threatened the safety of the main canal water supply and water quality. In this study, a field investigation, monitoring, and hydrodynamic simulation were performed to analyze the hydrodynamic habitat conditions in areas with vigorous algae growth and establish a relationship between the hydrodynamic habitat conditions of the main canal and the growth, distribution, and correlation of macrobenthic algae in the main canal. The results showed that: (1) algae zones in the main canal are more likely to appear along curves, and the largest algal zone was at the front of the large curved section; (2) the length of the algae growth zone is related to the flow rate; and (3) a lower flow velocity in the main canal facilitates faster growth of an algae zone. This study provides specific and effective suggestions for the key prevention and control positions, which has important guidance on improving the efficiency of algae control in the main canal. Full article