Imprint of monsoonal patterns on the fish assemblage in coastal waters of south‐east India: a case study

Biswas, Sudeepta; Hussain, K. Jahir; Das, Nilamadhab Prasad Indradyumna; Russell, Barry C.; Satpathy, K.K.; Mishra, Subhrendu Sekhar

doi:10.1111/jfb.12461

Cited by 18 publications

(6 citation statements)

References 34 publications

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“…CCA creates orthogonal components and a set of scores for each item. Therefore, it has been widely used to predict interactions between community structure and environmental variables (Godoy et al, 2002;Martino and Able, 2003;Mansor et al, 2012;Barrella et al, 2014;Biswas et al, 2014).…”

Section: Key Habitat Factors Determinationmentioning

confidence: 99%

Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city

Zhao¹,

Yang²,

Dou

et al. 2015

Journal of Hydrology

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Section: Key Habitat Factors Determinationmentioning

confidence: 99%

Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city

Zhao¹,

Yang²,

Dou

et al. 2015

Journal of Hydrology

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“…CCA is a multivariate gradient analysis method designed to elucidate relationships between biological assemblages of species and environmental factors and has been widely used to predict interactions between community structure and environmental variables (Biswas et al, 2015). It requires two data matrices that were the food web structure index data matrix and the environmental data matrix in this study (Barrella, Martins, Petrere, & Ramires, 2014).…”

Section: Methodsmentioning

confidence: 99%

Effects and prediction of nonpoint source pollution on the structure of aquatic food webs

et al. 2020

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Nonpoint source pollution entering rivers will pollute water quality, degrading the health of aquatic ecosystems. However, owing to the lack of quantitative research on the effects of nonpoint source pollution on the structure of aquatic food webs, there is a lack of quantitative basis for river management. Nonpoint source pollution is not only difficult to control effectively, but also the success rate of water ecological restoration projects is low. With the increasing proportion of nonpoint source pollution in water environmental problems, it is urgent to quantitatively assess and predict the impact of nonpoint source pollution on the structure of food webs. Therefore, this thesis presents a method for quantitatively assessing and predicting the impact of nonpoint source pollution on the structure of food webs through using fuzzy clustering to screen the typical points of the impact of nonpoint source pollution, then using canonical correspondence analysis (CCA) and partial least squares regression analysis to comprehensively filtrate the driving factors affect food web that results in nonpoint source pollution, and then determining the impact of each driving factor on the structure of food webs. Finally, the change trend of food web structure is predicted. The results show that (1) the driving factors that the nonpoint source pollution that affects the food web structure is NH3‐N and chemical oxygen demand (COD). The increase in NH3‐N and COD promotes the growth of phytoplankton, causing the change of the primary productivity of the ecosystem, and ultimately changes the entire food web structure; (2) NH3‐N and COD affect the stability, maturity, connectivity and complexity of the aquatic food web structure. The increase of NH3‐N increases the connectivity and maturity of the food web structure but reduces complexity and stability; the increase of COD increases the connection of the food web structure, while reducing the other three indicators; (3) in some areas with good water quality, aquatic species diversity is high, the relationship of interspecies dietary is complex, food web structure level index is high and the structure of food web is stable. The food web structure in the rainy season will be better than that in the dry season. In some areas with severe water pollution and poor food web structure, the ability of the food web to resist external interference is weak. The food web structure in the rainy season will be worse than that in the dry season owing to rainfall into the river. The methods and conclusions in this treatise can provide a reliable and quantitative scientific basis for river ecosystem management and ecosystem restoration and can improve the success rate of ecological restoration projects.

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“…CCA creates orthogonal components and a set of scores for each item. Therefore, it has been widely used to predict interactions between community structure and environmental variables (Barrella, Martins, Petrere, & Ramires, 2014; Biswas et al, 2014; Godoy, Almeida, & Zalmon, 2002; Mansor, Mohammad‐Zafrizal, Nur‐Fadhilah, Khairun, & Wan‐Maznah, 2012; Martino & Able, 2003).…”

Section: Sampling and Data Analysis Methodsmentioning

confidence: 99%

Principal hydrology and water quality factors driving the development of plankton communities in a pilot city of China

et al. 2020

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Healthy plankton communities form the basis of healthy aquatic ecosystems. By elucidating the mechanisms of mutual feedback between plankton and habitat processes and identifying key driving factors can enhance the success rate of ecosystem restoration. However, previous studies suffered from a lack of consideration for temporal and spatial variation in aquatic biome. In this study, three sets of samples were collected in May, September and October 2015 from 59 sampling sites in Jinan, a pilot city for water ecological civilization project, China. Canonical correspondence analysis was performed on the vast amount of data obtained from the samples to analyse the driving effects of various hydrological and water quality factors on plankton. The analysis results indicated that the development of plankton communities in Jinan were primarily driven by (1) hydrological factors of water depth, river width and flow velocity; (2) water quality physical factors of water temperature and conductivity and (3) water quality chemical factors of pH, chemical oxygen demand, biochemical oxygen demand, carbonate and sulphate contents. These results will provide in-depth theoretical and technical direction for the restoration of aquatic ecosystems in the first pilot city in China and other regions worldwide. K E Y W O R D S aquatic ecosystem, canonical correspondence analysis, hydrological and water quality factors, Jinan City

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Imprint of monsoonal patterns on the fish assemblage in coastal waters of south‐east India: a case study

Cited by 18 publications

References 34 publications

Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city

Linking hydrologic, physical and chemical habitat environments for the potential assessment of fish community rehabilitation in a developing city

Effects and prediction of nonpoint source pollution on the structure of aquatic food webs

Principal hydrology and water quality factors driving the development of plankton communities in a pilot city of China

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