Group items tagged

The aim of this study was to document the composition and distribution of deep-water fishes associated with a submarine canyon-valley feature. A work-class Remotely Operated Vehicle (ROV) fitted with stereo-video cameras was used to record fish abundance and assemblage composition along transects at water depths between 300 and 900 metres. Three areas (A, B, C) were sampled along a submarine canyon-valley feature on the continental slope of tropical north-western Australia. Water conductivity/salinity, temperature, and depth were also collected using an ROV mounted Conductivity Temperature and Depth (CTD) instrument. Multivariate analyses were used to investigate fish assemblage composition, and species distribution models were fitted using boosted regression trees. These models were used to generate predictive maps of the occurrence of four abundant taxa over the survey areas. CTD data identified three water masses, tropical surface water, South Indian Central Water (centred ∼200 m depth), and a lower salinity Antarctic Intermediate Water (AAIW) ∼550 m depth. Distinct fish assemblages were found among areas and between canyon-valley and non-canyon habitats. The canyon-valley habitats supported more fish and taxa than non-canyon habitats. The fish assemblages of the deeper location (∼700-900 m, Area A) were different to that of the shallower locations (∼400-700 m, Areas B and C). Deep-water habitats were characterised by a Paraliparis (snail fish) species, while shallower habitats were characterised by the family Macrouridae (rat tails). Species distribution models highlighted the fine-scale environmental niche associations of the four most abundant taxa. The survey area had a high diversity of fish taxa and was dominated by the family Macrouridae. The deepest habitat had a different fish fauna to the shallower areas. This faunal break can be attributed to the influence of AAIW. ROVs provide a platform on which multiple instruments can be mounted and com

Accurately estimating the ocean's subsurface thermohaline structure is essential for advancing our understanding of regional and global ocean dynamics. In this study, we propose a novel neural network model based on Convolutional Block Attention Module-Convolutional Neural Network (CBAM-CNN) to simultaneously estimate the ocean subsurface thermal structure (OSTS) and ocean subsurface salinity structure (OSSS) in the tropical Indian Ocean using satellite observations. The input variables include sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly (SSHA), eastward component of sea surface wind (ESSW), northward component of sea surface wind (NSSW), longitude (LON), and latitude (LAT). We train and validate the model using Argo data, and compare its accuracy with that of the original Convolutional Neural Network (CNN) model using root mean square error (RMSE), normalized root mean square error (NRMSE), and determination coefficient (R²). Our results show that the CBAM-CNN model outperforms the CNN model, exhibiting superior performance in estimating thermohaline structures in the tropical Indian Ocean. Furthermore, we evaluate the model's accuracy by comparing its estimated OSTS and OSSS at different depths with Argo-derived data, demonstrating that the model effectively captures most observed features using sea surface data. Additionally, the CBAM-CNN model demonstrates good seasonal applicability for OSTS and OSSS estimation. Our study highlights the benefits of using CBAM-CNN for estimating thermohaline structure and offers an efficient and effective method for estimating thermohaline structure in the tropical Indian Ocean.

Stable isotope analysis of dermis was used to examine foraging behavior of whale sharks at Ningaloo Reef in Western Australia. Values of δ13C and δ15N in dermis were compared to those obtained from likely species of local prey. The δ13C values of zooplankton and nektonic taxa at Ningaloo ranged from −18.9‰ to −16.5‰ reflecting the different carbon sources (from pelagic to more inshore and benthic) entering the food web. Isotopic values also varied depending on the diet-to-tissue discrimination factor applied in the analysis. When data was corrected using factors derived from slow turnover, structural cartilage in fins, whale sharks showed a greater reliance on pelagic food webs, whereas analyses using raw data suggested a greater dietary component from benthic and inshore habitats. Variability in δ15N values (6.9‰ to 10.8‰) implied different patterns of foraging among whale sharks, likely indicating movement among foraging localities that occur at Ningaloo Reef and along the Western Australian coast. There was evidence of enrichment in 15N occurring with increasing size in males and females, a pattern that could have been due to changes in growth rate and trophic level with age and/or an ontogenetic shift in feeding grounds. Given the variability potentially induced in stable isotope values by differences in rates of turnover of tissues and the use of diet-to-tissue discrimination factors, future studies would benefit from a multi-technique approach using different tissues to identify the diet of whale sharks.

Highly mobile marine megafauna species, while widely distributed and frequently threatened, often aggregate in distinct localized habitats. Implementation of local management initiatives within these hotspots is more achievable than developing effective conservation strategies that encompass their entire distributions. Such measures have the potential for disproportionate population-level benefits but rely on a detailed understanding of spatiotemporal habitat use. To that end, we examined the residency and small-scale habitat use of 51 whale sharks (Rhincodon typus) over 5 years at an aggregation site in Tanzania using passive acoustic telemetry. Whale sharks were highly resident within and across years, with a combined maximum residency index of 0.39. Although fewer sharks were detected from March to September, residency was high throughout the year. Ancillary photographic-identification data showed that individual residency persisted before and after tag attachment. Kernel utilization distributions (KUD) and movement networks both revealed the same spatiotemporal pattern of habitat use, with a small core habitat (50% KUD area for all sharks combined = 12.99 km2) that predictably changed on a seasonal basis. Activity spaces did not differ with time of day, sex, or size of the sharks, indicating a population-level pattern driven by prey availability. The small and predictable core habitat area at this site means that site-based management options to reduce shark injuries and mortality from boat strike and fishing gear entanglement can be spatially targeted for maximum effectiveness and compliance by human users.

In recent years, shoreline determination has become an issue of increasing importance and concern, especially at the local level, as sea level continues to rise. This study identifies the rates of absolute and net erosion, accretion, and shoreline stabilization along the coast of Kuakata, a vulnerable coastal region in south-central Bangladesh. Shoreline change was detected by applying remote sensing and geographic information system (RS-GIS)-based techniques by using Landsat Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) satellite images at 30-m resolution from 1989, 2003, 2010, and 2020. The band combination (BC) method was used to extract the shoreline (i.e., land-water boundary) due to its improved accuracy over other methods for matching with the existing shoreline position. This study also used participatory rural appraisal (PRA) tools which revealed the societal impacts caused by the shoreline changes. Coupling RS-GIS and PRA techniques provides an enhanced understanding of shoreline change and its impacts because PRA enriches the RS-GIS outcomes by contextualizing the findings. Results show that from 1989 to 2020, a total of 13.59 km2 of coastal land was eroded, and 3.27 km2 of land was accreted, suggesting that land is retreating at about 0.32 km2 yr-1. Results from the PRA tools support this finding and demonstrate that fisheries and tourism are affected by the shoreline change. These results are important in Kuakata, a major tourist spot in Bangladesh, because of the impacts on fisheries, recreation, resource extraction, land use planning, and coastal risk management.

Coastal upwelling is an oceanographic process that brings cold, nutrient-rich waters to the ocean surface from depth. These nutrient-rich waters help drive primary productivity which forms the foundation of ecological systems and the fisheries dependent on them. Although coastal upwelling systems of the Western Indian Ocean (WIO) are seasonal (i.e., only present for part of the year) with large variability driving strong fluctuations in fish catch, they sustain food security and livelihoods for millions of people via small-scale (subsistence and artisanal) fisheries. Due to the socio-economic importance of these systems, an "Upwelling Watch" analysis is proposed, for producing updates/alerts on upwelling presence and extremes. We propose a methodology for the detection of coastal upwelling using remotely-sensed daily chlorophyll-a and Sea Surface Temperature (SST) data. An unsupervised machine learning approach, K-means clustering, is used to detect upwelling areas off the Somali coast (WIO), where the Somali upwelling - regarded as the largest in the WIO and the fifth most important upwelling system globally - takes place. This automatic detection approach successfully delineates the upwelling core and surrounds, as well as non-upwelling ocean regions. The technique is shown to be robust with accurate classification of out-of-sample data (i.e., data not used for training the detection model). Once upwelling regions have been identified, the classification of extreme upwelling events was performed using confidence intervals derived from the full remote sensing record. This work has shown promise within the Somali upwelling system with aims to expand it to the rest of the WIO upwellings. This upwelling detection and classification method can aid fisheries management and also provide broader scientific insights into the functioning of these important oceanographic features.

Mangroves, intertidal forests, are increasingly considered a high-priority ecosystem for international conservation efforts. Setting targets for future mangrove conservation and restoration requires understanding of the health of the ecosystem. However, the way 'ecosystem health' is defined varies across locations, users, and indices due to differences in knowledge of the ecosystem, scales of the ecosystem being assessed, perceptions of what is 'healthy', or because of differences in the way people use or benefit from ecosystems. This can result in misunderstandings which can undermine effective actions to protect and restore functioning ecosystems. Here, we use a case study of a mangrove fishing community in coastal Thailand to examine how local people assess and define mangrove ecosystem health. Through participatory workshops, we show that local people use at least 27 indicators to define mangrove ecosystem health, including biological, physical, and human indices. Mangrove ecosystem health is defined by both direct material benefits derived from the ecosystem, non-material aspects, and the relational value experienced through 'bundles' of benefits linked to people's livelihood activities. Our findings suggest that ecosystem health frameworks would be more useful if they incorporated social components and metrics, recognising both the interdependencies between ecosystems and human societies, and that ecosystems possess intrinsic value. Local communities that interact most closely with ecosystems can contribute to improving and operationalising frameworks for ecosystem health.

What happened to MH370? Prediction markets might give us the answer.

What happened to MH370? Prediction markets might give us the answer.

US Court in Virginia Hears 2 Somali Pirates' Appeals.

US Court in Virginia Hears 2 Somali Pirates' Appeals.

Every one of India's 1.3 billion people uses an average 11kg of plastic each year. After being used, much of this plastic finds its way to the Arabian Sea and Indian Ocean, where it can maim and kill fish, birds and other marine wildlife.

Detailed ocean currents in the southeastern tropical Indian Ocean adjacent to southern Sumatran and Javan coasts have not been fully explained because of limited observations. In this study, zonal current characteristics in the region have been studied using simulation results of a 1/8∘ global hybrid coordinate ocean model from 1950 to 2013. The simulated zonal currents across three meridional sections were then investigated using an empirical orthogonal function (EOF), where the first three modes account for 75 %-98 % of the total variance. The first temporal mode of EOF is then investigated using ensemble empirical mode decomposition (EEMD) to distinguish the signals. This study has revealed distinctive features of currents in the South Java Current (SJC) region, the Indonesian Throughflow (ITF)-South Equatorial Current (SEC) region, and the transition zone between these regions. The vertical structures of zonal currents in southern Java and offshore Sumatra are characterized by a one-layer flow. Conversely, a two-layer flow is observed in the nearshore and transition regions of Sumatra. Current variation in the SJC region has peak energies that are sequentially dominated by semiannual, intraseasonal, and annual timescales. Meanwhile, the transition zone is characterized by semiannual and intraseasonal periods with pronounced interannual variations. In contrast, interannual variability associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) modulates the prominent intraseasonal variability of current in the ITF-SEC region. ENSO has the strongest influence at the outflow ITF, while the IOD's strongest influence is in southwestern Sumatra, with the ENSO (IOD) leading the current by 4 months (1 month). Moreover, the contributions (largest to smallest) of each EEMD mode at the nearshore of Java and offshore Sumatra are intraseasonal, semiannual, annual, interannual, and long-term fluctuations. The contribution of long-term

Ethnobiological knowledge is an important part of people's capacity to manage, conserve, and improve the governance of mangrove ecosystems. This paper assesses the ethnobiological importance of mangroves to coastal communities adjacent to seven mangrove forests in Southern and North-western Sri Lanka. 197 households were interviewed, and respondents identified various mangrove ecosystem goods and services. Fruit juice produced from Sonneratia spp. and salads made with Acrostichum aureum L. young leaves constitutes valuable edible products in both regions. Rhizophora mucronata Lamk. and Lumnitzera racemosa Willd., were employed as alternative sources of fuel. Other uses of mangroves include wood for construction, chemical, and medicinal products. However, the usage extent was significantly higher in the Southern province (87.6%) compared to the North-western province (51%). Five indices were developed to understand the ethnobiological knowledge of respondents (Mangrove Use Index, Perception Index, Regulation Awareness Index, and Knowledge Index, Mangrove Dynamics Index). Except for the Mangrove Use Index, the rest of the indices were significantly different between the provinces. Communities with higher mangrove knowledge showed lesser usage. Respondents had negative attitudes towards the regulations that limit/did not allow the community to enter mangrove forests. Community participation, ethnobiological importance, and perspectives regarding how the community wants to manage mangrove forests should be taken into account to avoid conflicts in the future. Considering local perceptions and translating them into mangrove management regulations can be effective in guiding sustainable mangrove management in Sri Lanka as well as in other countries in the world.

The values used for natural mortality (M) are very influential in stock assessment models, affecting model outcomes and management advice. Natural mortality is one of the most difficult demographic parameters to estimate, and there is often limited information about the true levels. Here, we summarise the evidence used to estimate natural mortality at age for the four main stocks of yellowfin tuna (Indian, Western and Central Pacific, Eastern Pacific, and Atlantic Oceans), including catch curves, tagging experiments, and maximum observed age. We identify important issues for estimating M such as variation with age linked to size, maturity state or senescence, and highlight information gaps. We describe the history of natural mortality values used in stock assessments by the tuna Regional Fisheries Management Organisations responsible for managing each stock and assess the evidence supporting these values. In June 2021, an online meeting was held by the Center for the Advancement of Population Assessment Methodology (CAPAM), to provide advice and guidance on practices for modelling natural mortality in fishery assessments. Based on approaches presented and discussed at the meeting, we develop a range of yellowfin tuna natural mortality estimates for each stock. We also recommend future research to improve these estimates of natural mortality.

Coastal waters are inherently dynamic due to river discharge, industrial effluents, shipping, dredging, waste dumping, and sewage disposal. Population growth in urban cities, climate change and variability, and changes in land-use practices all contribute to pressure on coastal water quality (SKOVSKI et al., 2012; MILLER and HUTCHINS, 2017; KUMAR et al., 2020; Vijay PRAKASH et al., 2021). Anthropogenic activity is evident around these estuaries and coastal and open ocean environments. Hence, it is important to assess the water quality on a regular basis and provide mitigation measures for coastal pollution (YUVARAJ et al., 2018). Improving water quality and variability in coastal waters is necessary and should be prioritized. Observational programs, which are more expensive and time-consuming, aid in understanding the status of water quality and its trends. Many countries have coastal programs that use predictive systems to inform the public and stakeholders about coastal health. Hydrodynamic processes are an integral part of complex surface water systems. The main factor that determines the concentration of pollutants is hydrodynamic transport, which includes advection, dispersion, vertical mixing, and convection (James, 2002). The flow and circulation patterns have a great influence not only on the distribution of temperature, nutrients, and dissolved oxygen (DO) but also on the aggregation and distribution of sediments and pollutants. When a load of pollutants is discharged into coastal waters, it is affected by the fate and transportation processes that change its concentration. Several studies have been conducted to evaluate the coastal water quality spatiotemporally along the east coast of Indian coastal waters using site-specific data and model configuration (PANDA et al., 2006; BHARAHTI et al., 2017; NAIK et al., 2020; MOHANTY et al., 2021). Through numerical modeling and remote sensing, estimation is user-friendly and low-cost in evaluating any water quali

Gaining insight into the interannual variability of the Indian Ocean Subtropical Mode Water (IOSTMW) is essential for understanding ocean dynamics in the Southwest Indian Ocean, since it carries the signal of winter mixing and transports it into the ocean interior. As the number of Argo profiles in the Southwest Indian Ocean increases, it has become possible to study temporal variations in IOSTMW using observation data. We used Argo products to examine the interannual variability of the IOSTMW from 2005 to 2020. We examined various definitions to determine the most suitable definition for IOSTMW in this study, choosing to define the IOSTMW as a layer with a vertical temperature gradient of less than 1°C per 100 meters (dT/dz< 1°C/100 m) and a temperature range of 16°C-18°C because this correlates strongly with winter heat loss in the same year. This method is particularly useful for investigating how mode water captures anomalous winter mixing signals and advects them to the ocean interior via subduction. Furthermore, we found that summer stratification can play a role in either facilitating or hindering the formation of thick IOSTMW layers. Our study indicates that thin IOSTMW layers are primarily caused by extremely weak winter heat loss associated with anomalously weak latent heat, whereas thick IOSTMW formation is aided by weak summer stratification.

Oceanic whitetip shark (Carcharhinus longimanus) is an important top predator in pelagic ecosystems currently classified as globally Critically Endangered by the International Union for the Conservation of Nature. This species is incidentally caught by fisheries targeting highly migratory tunas and billfishes throughout the Indian Ocean. Understanding the temporal, spatial and environmental factors influencing the capture of this species is essential to reduce incidental catches. In this study, we used generalized additive models to analyze the spatio-temporal distributions of the juvenile oceanic whitetip shark catches and the environmental conditions in the western Indian Ocean using observer data from 2010 to 2020 of the European Union and associated flags purse seine fishery. We found sea surface temperature and nitrate concentration to be the most important environmental variables predicting the probability of catching an oceanic whitetip shark. A higher probability of capture was predicted in areas where sea surface temperature was below 24°C and with low nitrate concentrations close to zero and intermediate values (1.5-2.5 mmol.m-3). We also found a higher probability of capture in sets on fish aggregating devices than in sets on free schools of tuna. The Kenya and Somalia basin was identified to have higher probabilities of capture during the summer monsoon (June to September) when upwelling of deep cold waters occurs. We provide the first prediction maps of capture probabilities and insights into the environmental preferences of oceanic whitetip shark in the western Indian Ocean. However, the causal mechanisms behind these insights should be explored in future studies before they can be used to design spatial management and conservation strategies, such as time-area closures, for bycatch avoidance.

A microplastics (MPs) emergence study in pelagic and mesopelagic species was carried out to delineate coastal degradation and ecosystem status around the Karachi metropolis. Species of high commercial and ecological worth were sampled using a gillnet of 1.5 cm knot-to-knot mesh size in November and December 2021. In total twenty-six individuals including Liza subviridis (15), Thryssa dussumieri (3), Rastrelliger kanagurta (2), and Portunus sanguinolentus (6) were used to perceive MPs. A strong linearity between body length and MPs (R2 = 0.937, SE 0.071 and R2 = 0.928, SE 0.104) were calculated for L. subviridis and P. sangiuilatus, respectively. However, the data of T. dussummeiri and R. Kanagurta showed minimization failure. The MPs in GIT were extracted using direct observation under a sophisticated binuclear microscope and chemical digestion (KOH) together with wet peroxide oxidation (H2O2+FeSO4) methods. The MP materials were categorized as foam, film, fiber, fragment, and beads of three different sizes 170, 120, 100 μm in the stomach, intestine, and esophagus. Film-type MPs appeared frequently, whereas beads were rarely seen. It is hoped that this baseline research would help to minimize industrial release, recognize critical knowledge gaps, and demonstrate MP flux being released into the aquatic environment. The results will support mitigation of this emerging threat to the living resources around the Karachi coastal area.

The Southern Indian Ocean is a major reservoir for rapid carbon exchange with the atmosphere, plays a key role in the world's carbon cycle. To understand the importance of anthropogenic CO2 uptake in the Southern Indian Ocean, a variety of methods have been used to quantify the magnitude of the CO2 flux between air and sea. The basic approach is based on the bulk formula-the air-sea CO2 flux is commonly calculated by the difference in the CO2 partial pressure between the ocean and the atmosphere, the gas transfer velocity, the surface wind speed, and the CO2 solubility in seawater. However, relying solely on wind speed to measure the gas transfer velocity at the sea surface increases the uncertainty of CO2 flux estimation. Recent studies have shown that the generation and breaking of ocean waves also significantly affect the gas transfer process at the air-sea interface. In this study, we highlight the impact of windseas on the process of air-sea CO2 exchange and address its important role in CO2 uptake in the Southern Indian Ocean. We run the WAVEWATCH III model to simulate surface waves in this region over the period from January 1st 2002 to December 31st 2021. Then, we use the spectral partitioning method to isolate windseas and swells from total wave fields. Finally, we calculate the CO2 flux based on the new semiempirical equation for gas transfer velocity considering only windseas. We found that after considering windseas' impact, the seasonal mean zonal flux (mmol/m2·d) increased approximately 10%-20% compared with that calculated solely on wind speed in all seasons. Evolution of air-sea net carbon flux (PgC) increased around 5.87%-32.12% in the latest 5 years with the most significant seasonal improvement appeared in summer. Long-term trend analysis also indicated that the CO2 absorption capacity of the whole Southern Indian Ocean gradually increased during the past 20 years. These findings extend the understanding of the roles of the Southern Indian Ocea

Oceans across the globe are warming rapidly and marine ecosystems are changing as a result. However, there is a lack of information regarding how blue whales are responding to these changing environments, especially in the Southern Hemisphere. This is because long term data are needed to determine whether blue whales respond to variability in environmental conditions. Using over 16 years of passive acoustic data recorded at Cape Leeuwin, we investigated whether oceanic environmental drivers are correlated with the migration patterns of eastern Indian Ocean (EIO) pygmy blue whales off Western Australia. To determine which environmental variables may influence migration patterns, we modelled the number of acoustic call detections of EIO pygmy blue whale calls with broad and fine scale environmental variables. We found a positive correlation between total annual whale call detections and El Niño Southern Oscillation (ENSO) cycles and the Indian Ocean Dipole (IOD), with more whale calls detected during La Niña years. We also found that monthly whale call detections correlated with sea surface height around the hydrophone and chlorophyll-a concentration at a prominent blue whale feeding aggregation area (Bonney Upwelling) where whales feed during the summer before migrating up the west Australian coast. At the interannual scale, ENSO had a stronger relationship with call detections than IOD. During La Niña years, up to ten times more EIO pygmy blue whale calls were detected than in neutral or El Niño years. This is likely linked to changes in productivity in the feeding areas of the Great Australian Bight and Indian Ocean. We propose that in lower productivity years whales either skipped migration or altered their habitat use and moved further offshore from the hydrophones and therefore were not detected. The frequency and intensity of ENSO events are predicted to increase with climate change, which is likely to impact the productivity of the areas used by blue whale