Long-term and longitudinal nutrient stoichiometry changes in oligotrophic cascade reservoirs with trout cage aquaculture

Hydrodynamics Regulate Longitudinal Plankton Community Structure in an Alpine Cascade Reservoir System

Previous studies report significant changes on biotic communities caused by cascade reservoir construction. However, factors regulating the spatial–temporal plankton patterns in alpine cascade reservoir systems have not been fully explored. The current study explored effects of environmental factors on the longitudinal plankton patterns, through a 5-year-long study on the environmental factors and communities of phytoplankton and zooplankton in an alpine cascade reservoir system located upstream of Yellow River region. The findings showed that phytoplankton and zooplankton species numbers in the studied cascade reservoir system were mainly regulated by the hydrological regime, whereas nutrient conditions did not significantly affect the number of species. Abundance and biovolume of phytoplankton in cascade reservoirs were modulated by the hydrological regime and nutrient conditions. The drainage rate, N:P ratio, and sediment content in cascade reservoirs were negatively correlated with abundance and biovolume of phytoplankton. Abundance and biovolume of zooplankton were not significantly correlated with the hydrological regime but showed a strong positive correlation with nutrient conditions in cascade reservoirs. Shannon–Wiener index (H’) and the Pielou index (J) of phytoplankton were mainly regulated by the hydrological regime factors, such as drainage rate and sediment content in cascade reservoirs. However, temperature and nutrient conditions were the main factors that regulated the Shannon–Wiener index (H’) and the Pielou index (J) of zooplankton. Species number, abundance, and biovolume of phytoplankton showed a significant positive correlation with those of zooplankton. Hydrodynamics and nutrient conditions contributed differently in regulating community structure of phytoplankton or zooplankton. These findings provide an understanding of factors that modulate longitudinal plankton community patterns in cascade reservoir systems.

Gaussian Distribution Model for Detecting Dangerous Operating Conditions in Industrial Fish Farming

The development of better monitoring technologies, the early combat of outbreaks, massive mortality, and promoting sustainability are challenges that the aquaculture industry still faces, and the development of solutions for this is an open problem. In this paper, focusing our attention on monitoring technologies as a promising solution to these issues, we report a Gaussian distribution model for detecting dangerous operating conditions in industrial fish farming. This approach allows us to indicate through a 2D image visualization when fish production is under normal, warning, or dangerous operating conditions. Furthermore, our proposed method has promising possibilities for application in the most varied fields of science, given that the mathematical procedure described allows us to discover the fundamental statistical structure of physical, chemical, and biological systems governed by laws of a probabilistic nature.