Signals of selection in the mitogenome provide insights into adaptation mechanisms in heterogeneous habitats in a widely distributed pelagic fish

Oceans are vast, dynamic, and complex ecosystems characterized by fluctuations in environmental parameters like sea surface temperature (SST), salinity, oxygen availability, and productivity. Environmental variability acts as the driver of organismal evolution and speciation as organisms strive to cope with the challenges. We investigated the evolutionary consequences of heterogeneous environmental conditions on the mitogenome of a widely distributed small pelagic fish of Indian ocean, Indian oil sardine, Sardinella longiceps. Sardines were collected from different eco-regions of the Indian Ocean and selection patterns analyzed in coding and non-coding regions. Signals of diversifying selection were observed in key functional regions involved in OXPHOS indicating OXPHOS gene regulation as the critical factor to meet enhanced energetic demands. A characteristic control region with 38–40 bp tandem repeat units under strong selective pressure as evidenced by sequence conservation and low free energy values was also observed. These changes were prevalent in fishes from the South Eastern Arabian Sea (SEAS) followed by the Northern Arabian Sea (NAS) and rare in Bay of Bengal (BoB) populations. Fishes belonging to SEAS exhibited accelerated substitution rate mainly due to the selective pressures to survive in a highly variable oceanic environment characterized by seasonal hypoxia, variable SST, and food availability

Seasonal Prediction of Arabian Sea Marine Heatwaves

Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps)

A future for intelligent autonomous ocean observing systems

Ocean scientists have dreamed of and recently started to realize an ocean observing revolution with autonomous observing platforms and sensors. Critical questions to be answered by such autonomous systems are where, when, and what to sample for optimal information, and how to optimally reach the sampling locations. Definitions, concepts, and progress towards answering these questions using quantitative predictions and fundamental principles are presented. Results in reachability and path planning, adaptive sampling, machine learning, and teaming machines with scientists are overviewed. The integrated use of differential equations and theory from varied disciplines is emphasized. The results provide an inference engine and knowledge base for expert autonomous observing systems. They are showcased using a set of recent at-sea campaigns and realistic simulations. Real-time experiments with identical autonomous underwater vehicles (AUVs) in the Buzzards Bay and Vineyard Sound region first show that our predicted time-optimal paths were faster than shortest distance paths. Deterministic and probabilistic reachability and path forecasts issued and validated for gliders and floats in the northern Arabian Sea are then presented. Novel Bayesian adaptive sampling for hypothesis testing and optimal learning are finally shown to forecast the observations most informative to estimate the accuracy of model formulations, the values of ecosystem parameters and dynamic fields, and the presence of Lagrangian Coherent Structures

Climate change impacts : Implications on marine resources and resource users

The warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global mean sea level. The Earth’s average surface temperature has risen by 0.76° C since 1850. Most of the warming that has occurred over the last 50 years is very likely to have been caused by human activities. In its Fourth Assessment Report projects that, without further action to reduce greenhouse gas emissions, the global average surface temperature is likely to rise by a further 1.8-4.0°C this century, and by up to 6.4°C in the worst case scenario. Even the lower end of this range would take the temperature increase since pre-industrial times above 2°C – the threshold beyond which irreversible and possibly catastrophic changes become far more likely

Estimation of mixed-layer depth from surface parameters

Author Posting. © Sears Foundation for Marine Research, 2006. This article is posted here by permission of Sears Foundation for Marine Research for personal use, not for redistribution. The definitive version was published in Journal of Marine Research 64 (2006): 745-758, doi:10.1357/002224006779367285.Mixed layer depth (MLD) is an important oceanographic parameter. However, the lack of direct observations of MLD hampers both specification and investigation of its spatial and temporal variability. An important alternative to direct observation would be the ability to estimate MLD from surface parameters easily available from satellites. In this study, we demonstrate estimation of MLD using Artificial Neural Network methods and surface meteorology from a surface mooring in the Arabian Sea. The estimated MLD had a root mean square error of 7.36 m and a coefficient of determination (R2) of 0.94. About 67% (91%) of the estimates lie within ± 5 m (± 10 m) of the MLD determined from temperature sensors on the mooring

A relocatable ocean model in support of environmental emergencies

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio

A southeastern Mediterranean PV streamer and its role in December 2001 case with torrential rains in Israel

A precipitation event of unprecedented intensity took place over northern part of Israel during 4 December 2001–5 December 2001. The case was associated with formation of a Cyprus Low cyclone over the Asia Minor. In the current study the synoptic developments over the eastern part of the Mediterranean region are simulated with the MM5 nonhydrostatic model and analyzed based on dynamic tropopause patterns calculated from the simulation results. According to the results, a powerful potential vorticity (PV) streamer system played a major role in the process over the southeastern Mediterranean region. The PV streamer created conditions for seclusion of moist air masses from the equatorial East Africa and Atlantics during the cyclone development. Condensation of the moisture, associated with the latent heat release processes have contributed to the intense thunderstorm activity and heavy precipitation of the event

A road map to IndOOS-2 better observations of the rapidly warming Indian Ocean

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(11), (2020): E1891-E1913, https://doi.org/10.1175/BAMS-D-19-0209.1The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.We thank the World Climate Research Programme (WCRP) and its core project on Climate and Ocean: Variability, Predictability and Change (CLIVAR), the Indian Ocean Global Ocean Observing System (IOGOOS), the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), the Integrated Marine Biosphere Research (IMBeR) project, the U.S. National Oceanic and Atmospheric Administration (NOAA), and the International Union of Geodesy and Geophysics (IUGG) for providing the financial support to bring international scientists together to conduct this review. We thank the members of the independent review board that provided detailed feedbacks on the review report that is summarized in this article: P. E. Dexter, M. Krug, J. McCreary, R. Matear, C. Moloney, and S. Wijffels. PMEL Contribution 5041. C. Ummenhofer acknowledges support from The Andrew W. Mellon Foundation Award for Innovative Research.2021-05-0

The role of potential vorticity anomalies in the Somali Jet on Indian summer monsoon intraseasonal variability

The climate of the Indian subcontinent is dominated by rainfall arising from the Indian summer monsoon (ISM) during the summer season (June to September). Intraseasonal variability during the monsoon is characterized by periods of heavy rainfall interspersed by drier periods, known as active and break events respectively. Understanding and predicting such events is of vital importance for forecasting human impacts such as water resources. The Somali Jet is a key regional feature of this circulation. In the present study, we find that the spatial structure of Somali Jet potential vorticity (PV) anomalies varies considerably during active and break periods. Analysis of these anomalies shows a mechanism whereby sea surface temperature (SST) anomalies propagate north/northwestwards through the Arabian Sea, caused by a positive feedback loop joining anomalies in SST, convection, modification of PV by diabatic heating and mixing in the atmospheric boundary layer, wind stress curl, and upwelling processes. The feedback mechanism is consistent with observed coupled ocean-atmosphere system variability timescales of approximately 20 days. This research suggests that better understanding and prediction of monsoon subseasonal variability in the South Asian monsoon may be gained by analysis of the day-to-day dynamical evolution of PV in the Somali Jet