Small Scale Spatial and Temporal Patterns in Particles, Plankton, and Other Organisms

This study shows that the use of a submersible digital holographic camera as part of a multifunctional hardware and software complex allows carrying out in situ measurements of plankton, automating the process of obtaining data on plankton, as well as classifying plankton species up to an order within the specified taxonomic groups. Such automation ensures monitoring expeditionary or stationary research of species diversity and spatial and temporal organization of zooplankton in conjunction with the hydrophysical parameters of the medium. This paper presents the full-scale results of vertical profiles and daily measurements of plankton made with the use of the submersible digital holographic camera as well as the classification of plankton in laboratory and field conditions in the automatic mode. It is shown that, within the accomplished version, the classification algorithm using the morphological parameter makes it possible to solve the problem quickly (the time required to obtain the result is less than 1 s and depends on the number of plankton particles and the frame size of a restored image); however, the classification accuracy by orders varies within 50–60%.

Rushikulya Estuary is rich in biodiversity facing significant changes in recent periods due to pollution/anthropogenic impacts from the industries and growing urbanization along the banks of the river. This estuary caters mass nesting of Olive Ridley sea turtles and one of the world’s largest rookery in India. In view of the above, the present study examined the seasonal variability of water quality parameters [water temperature, pH, salinity, dissolved oxygen (DO), total suspended matter (TSM), inorganic nutrients (NO₂-N, NO₃-N, NH₄-N, PO₄-P, and SiO₄-Si), and the phytopigment, i.e., Chlorophyll-a (chl-a)] from the seawater samples of three different seasons pre-monsoon, monsoon, and post-monsoon. Time series observations were made at five locations off Rushikulya Estuary, Bay of Bengal, from March 2011 to February 2013. A wide range of nutrient concentrations except for NO₂-N, varied from 0.89–3.62 μmol/l in the NO₃-N, from 1.36–6.81 μmol/l in the NH₄-N, from 0.66–3.45 μmol/l in the PO₄-P and from 0.89–7.97 μmol/l in the SiO₄-Si. The highest chl-a (3.72 mg/m³) was recorded during pre-monsoon than monsoon and post-monsoon. Factor analysis (FA) showed that three underlying factors, each during pre-monsoon, monsoon, and post-monsoon, influenced the water quality to the extent of 75.02, 67.33, and 66.37%, respectively. The significant result from a statistical view of non-metric multidimensional scaling (nm-MDS) and cluster analysis (CA) revealed that the chl-a variability was due to the direct influence of nutrients than the physical parameters. Correlation analysis revealed that chl-a has positive correlation with DO, NO₂, NO₃, PO₄, and SiO₄, while negative with salinity in pre-monsoon and monsoon. The composite results indicated that the study area is well oxygenated and rich in nutrients, and chl-a distribution represents typical upper ocean dynamics and food chain linked to the pristine coastal and ecologically rich ecosystem.