Dynamics of environmental variables during the incidence of algal bloom in the coastal waters of Gujarat along the northeastern Arabian Sea.

The dynamics of physico-chemical, nutrient, and chlorophyll-a variables were studied in the bloom and non-bloom locations along the off-Gujarat coastal waters to understand the variability in biogeochemistry using multivariate analytical tests. The dissolved oxygen was significantly lower in the bloom stations (3.89 ± 0.44 mgL-1) than in the non-bloom stations (5.50 ± 0.70 mg L-1), due to the biological degradation of organic matter in addition to anaerobic microbial respiration. Nutrients (PO4 and NO3) and Chl-a concentrations were recorded higher in the bloom locations at 0.83 ± 0.21 µmol L-1, 4.47 ± 0.69 µmol L-1, 4.14 ± 1.49 mg m-3, respectively. PO4 and NO3 have shown a significantly higher positive correlation of r = 0.73 and r = 0.69 with Chl-a for bloom data than the non-bloom data. The percentage variance contributed by PC1 and PC2 for both bloom and non-bloom locations were estimated at 52.33%. The variable PO4 explains the highest 24.19% variability in PC1, followed by Chl-a (19.89%). The PO4 triggers the bloom formation and also correlates to the higher concentrations of Chl-a in the bloom locations. The bloom concentration ranges from 9553 to 12,235 trichomes L-1. The bloom intensity has shown a significant positive correlation with Chl-a (r = 0.77), NO3 (r = 0.56), and PO4 (r = 0.30), but a negative correlation was noticed with DO (r = - 0.63) and pH (r = - 0.49). The study also initiates a way forward research investigation on ocean-color technologies to identify and monitor blooms and climate change-driven factors for bloom formation. The occurrence of bloom and its influence on fishery resources and other marine biotas will open many research windows in marine fisheries, oceanography, remote sensing, marine biology, and trophodynamics.

Exploring biophysical links of catch rate from mid-water trawl fishery in the north-west coast of India, Eastern Arabian Sea: A remote sensing approach.

Fish frequently shift their distribution ranges as a result of changes in preferred environmental factors. Knowledge on distribution of fish in relation to their environmental optima is crucial for improving the understanding of fishing grounds and planning sustainable exploitation. This study investigated the monthly variability in environmental factors impacting the catch rate and the spatio-temporal distribution patterns of fish along northwest coast of India (NWCI) from 2017 to 2019. The time series images of sea surface temperature (SST), sea surface height anomaly (SSHa), chlorophyll-a concentration (CHL), and euphotic depth (Zeu) indicate close coupling between bio-physical variables in the region. Generalized Additive Model (GAM) applied to the catch rate of mid-water trawlers found that CHL and Zeu were the most influential variables for ribbonfish distribution, while CHL and SST influence squid distribution and SST and SSHa influence cuttlefish distribution. The total deviation explained 37.70 %, 10.70 %, and 22.28 % in the final model for simulating the spatio-temporal distribution of ribbonfish, squid, and cuttlefish, respectively. Environmental factors were significant in the final GAM model (p < 0.05). Spatio-temporal distribution patterns of fishery resources from mid-water trawlers showed that they were related to biophysical changes in the northwest coast of India. The high catch rate was observed in the northern latitudes during the post-monsoon (October), the major fishing season in the region. However, it shrank and shifted to southern latitudes during the winter (January). This study could be adapted to nearby countries in the Arabian Sea region for an effective and useful tool to monitor and manage the fishery resources. Furthermore, it could aid in decision-making for policymakers and resource managers to formulate strategies for holistic marine fishery management and sustainable resource exploitation.

Spatio-temporal changes of winter and spring phytoplankton blooms in Arabian sea during the period 1997-2020.

Arabian Sea (AS) experiences Chlorophyll-a (Chl-a) blooms during winter and early spring (November-March) mainly due to the changes induced by seasonally reversing monsoon winds and associated processes. The seasonal blooms exhibit distinct regional patterns in their onset, duration, intensity and peak period. Recent changes in ocean dynamics and plankton composition have inflicted adverse effects in the distribution of Chl-a concentration in AS. Here, we analyse the long-term spatio-temporal changes in winter and early spring bloom events during the period 1997-2020, and evaluate the role of sea surface temperature (SST), mixed layer depth (MLD), sea surface salinity, winds, mesoscale eddies and surface currents on these bloom occurrences. We observe a significant reduction in these blooms, which started in the early 2000s and intensified in the last decade (2010-2020), with a notable drop in the adjacent gulfs (Gulf of Aden: 1.38 ± 0.7 × 10-5 mg m-3 yr-1, Gulf of Oman: 4.71 ± 1.35 × 10-6 mg m-3 yr-1) and West coast of India (-6.71 ± 2.85 × 10-6 mg m-3 yr-1). The MLD and ocean temperature are the major factors that govern bloom in Gulf of Oman and open waters. Conversely, the coastal upwelling and eddies drive blooms in Gulf of Aden. The winter cooling trigger the bloom in the northern Indian west coast, but the inter-basin exchange of surface waters through the West Indian Coastal Current inhibits its southward spread. This study, therefore, reveals unique processes that initiate and control the winter and early spring blooms in different regions of AS. The ongoing warming of AS could contribute to further decline in these seasonal blooms, which would be a great concern for regional marine productivity and associated regional food security.

Monitoring of Harmful Algal Bloom (HAB) of Noctiluca scintillans (Macartney) along the Gulf of Mannar, India using in-situ and satellite observations and its impact on wild and maricultured finfishes.

In the Gulf of Mannar, Noctiluca scintillans blooms have been observed three times in September 2019, September and October 2020, and October 2021. It was determined and measured how the bloom period affects ichthyo-diversity. Noctiluca cell density varied slightly from year to year, ranging from1.8433 × 103 cells/L to 1.3824 x 106cells/L. In surface and sea bottom waters, high ammonia levels and low dissolved oxygen levels were noted. During the bloom period a significant increase in chlorophyll concentration was found. The amount of chlorophyll in GOM was extremely high, according to remote sensing photos made using MODIS-Aqua 4 km data. Acute hypoxia caused the death of wild fish near coral reefs and also in fish reared in sea cages. The decay of the bloom resulted in significant ammonia production, a dramatic drop in the amount of dissolved oxygen in the water, and ultimately stress, shock, and mass mortality of fishes.

A regional algorithm to model mesozooplankton biomass along the southwestern Bay of Bengal.

A three-dimensional regression analysis attempted to model mesozooplankton (MSP) biomass using sea surface temperature (SST) and chlorophyll-a (Chl-a). The study was carried out from January 2014 to July 2015 in the southwestern Bay of Bengal (BoB) and sampling was carried out on board Sagar Manjusha and Sagar Purvi. SST ranged from 26.2 to 33.1 °C while Chl-a varied from 0.04 to 6.09 µg L-1. During the course of the study period, there was a weak correlation (r = 0.32) between SST and Chl-a statistically. MSP biomass varied from 0.42 to 9.63 mg C m-3 and inversely related with SST. Two kinds of approaches were adopted to develop the model by grouping seasonal datasets (four seasonal algorithms) and comprising all datasets (one annual algorithm). Among the four functions used (linear, paraboloid, the Lorentzian and the Gaussian functions), paraboloid model was best suited. The best seasonal and annual algorithms were applied in the synchronous MODIS-derived SST and Chl-a data to estimate the MSP biomass in the southwestern BoB. The modelled MSP biomass was validated with field MSP biomass and the result was statistically significant, showing maximum regression coefficient for the seasonal algorithms (R2 = 0.60; p = 0.627; α = 0.05), than the annual algorithm (R2 = 0.52; p = 0.015, α = 0.05).

Bio-optic characterization of Discosphaera tubifer bloom occurs in an overcrowded fishing harbour at Veraval, India.

Discosphaera tubifer, a coccolithophore has been first time reported as a bloom-forming organism from an over-crowded fishing harbour at Veraval, west coast of India. Physiochemical and optical parameters were measured following standard protocols. Average concentration of inorganic nutrients, such as NO2-N (17.26 ± 2.92 µM), NO3-N (643.80 ± 215.99 µM), PO4-P (74.10 ± 26.52 µM) and SiO3-Si (137.66 ± 25.83 µM) were recorded as very high at Veraval port as compared to other coastal stations i.e., 1.48 ± 0.66, 49.16 ± 13.73, 10.03 ± 5.31 and 96.23 ± 22.74 µM, respectively. The pH and salinity (‰) were observed to be low (7.80 ± 0.15 and 28.00 ± 4.54 ‰) as compared to coastal seawaters (8.34 ± 0.06 and 33.24 ± 2.32 ‰). Scanning electron microscopy (SEM) and spectral signature (absorbance and reflectance) study revealed that the bloom-forming organism was D. tubifer. High-performance liquid chromatography (HPLC) study detected that chlorophyllide-a represent nearly 47.53 % of total pigment composition followed by chlorophyll c2 (27.40 %) and chlorophyll c3 (14.25 %). Four prominent absorption peaks were observed within 350 to 700 nm. The first peak was very wide and ranged from 350 to 530 nm and the rest of the three peaks ranged from 550 to 590, 590 to 650 and 650 to 690 nm, respectively. In case of reflection, three peaks appeared between 550 and 590, 590 and 630 and 630 and 670 nm. Nearly 100 % reflection was observed after 720 nm. The eutrophic condition of the port water along with low salinity and low pH might be the reason for D. tubifer bloom formation. This species-specific spectral signature of the D. tubifer bloom may be helpful for developing algorithm of remote sensing data analysis.

Species identification of mixed algal bloom in the Northern Arabian Sea using remote sensing techniques.

Oceanic waters of the Northern Arabian Sea experience massive algal blooms during winter-spring (mid Feb-end Mar), which prevail for at least for 3 months covering the entire northern half of the basin from east to west. Ship cruises were conducted during winter-spring of 2001-2012 covering different stages of the bloom to study the biogeochemistry of the region. Phytoplankton analysis indicated the presence of green tides of dinoflagellate, Noctiluca scintillans (=N. miliaris), in the oceanic waters. Our observations indicated that diatoms are coupled and often co-exist with N. scintillans, making it a mixed-species ecosystem. In this paper, we describe an approach for detection of bloom-forming algae N. scintillans and its discrimination from diatoms using Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data in a mixed-species environment. In situ remote sensing reflectance spectra were generated using Satlantic™ hyperspectral radiometer for the bloom and non-bloom waters. Spectral shapes of the reflectance spectra for different water types were distinct, and the same were used for species identification. Scatter of points representing different phytoplankton classes on a derivative plot revealed four diverse clusters, viz. N. scintillans, diatoms, non-bloom oceanic, and non-bloom coastal waters. The criteria developed for species discrimination were implemented on MODIS data and validated using inputs from a recent ship cruise conducted in March 2013.