The Relationship of Upwelling to Mussel Production in the Rias on the Western Coast of Spain

We have calculated an upwelling index for each month over a 17-year period (1969-1985) for a point off the western coast of Spain. We interpret April through September values of the index to indicate the flux of nitrate-rich water in the Spanish Rias. The index representing the 6-month upwelling series has been correlated with an index representing the conditions of mussels grown during that season on rafts in Ria de Arosa. Two seasons represent extreme upwelling conditions over the 17-year sampling period: 1977 when the upwelling index was the highest, and 1983 when it was the lowest. A comparison of the condition of mussels during these years showed that meat content was double in 1977. We suggest, by this study, that long range forecasts of synoptic scale weather patterns could be used to predict the potential nutritional value of mussels harvested in the rias of Spain

Vulnerability and resilience of living marine resources to the Deepwater Horizon oil spill : an overview

Funding for the project was primarily provided by the Gulf of Mexico Research Initiative through several of its research centers.The 2010 Deepwater Horizon (DWH) oil well blowout in the Gulf of Mexico (GoM) was the largest and perhaps most consequential accidental marine oil spill in global history. This paper provides an overview of a Research Topic consisting of four additional papers that: (1) assemble time series data for ecosystem components in regions impacted by the spill, and (2) interpret temporal changes related to the vulnerability of species and ecosystems to DWH and the ensuing resilience to perturbation. Time series abundance data for many taxa pre-date DWH, often by decades, thus allowing an assessment of population- and community-level impacts. We divided the north central GoM into four interconnected “eco-types”: the coastal/nearshore, continental shelf, open-ocean pelagic and deep benthic. Key taxa in each eco-type were evaluated for their vulnerability to the circumstances of the DWH spill based on population overlap with oil, susceptibility to oil contamination, and other factors, as well their imputed resilience to population-level impacts, based on life history metrics, ecology and post-spill trajectories. Each taxon was scored as low, medium, or high for 13 vulnerability attributes and 11 resilience attributes to produce overall vulnerability and resilience scores, which themselves were also categorical (i.e., low, medium, or high). The resulting taxon-specific V-R scores provide important guidance on key species to consider and monitor in the event of future spills similar to DWH. Similar analyses may also guide resource allocation to collect baseline data on highly vulnerable taxa or those with low resilience potential in other ecosystems. For some species, even a decade of observation has been insufficient to document recovery given chronic, long-term exposure to DWH oil remaining in all eco-types and because of impacts to the reproductive output of long-lived species. Due to the ongoing threats of deep-water blowouts, continued surveillance of populations affected by DWH is warranted to document long-term recovery or change in system state. The level of population monitoring in the open-ocean and deep benthic eco-types has historically been low and is inconsistent with the continued migration of the oil industry to the ultra-deep (≥1,500 m) where the majority of leasing, exploration, and production now occurs.Publisher PDFPeer reviewe

Variability of coastal and ocean water temperature in the upper 700 m along the western Iberian Peninsula from 1975 to 2006

Temperature is observed to have different trends at coastal and ocean locations along the western Iberian Peninsula from 1975 to 2006, which corresponds to the last warming period in the area under study. The analysis was carried out by means of the Simple Ocean Data Assimilation (SODA). Reanalysis data are available at monthly scale with a horizontal resolution of 0.5° × 0.5° and a vertical resolution of 40 levels, which allows obtaining information beneath the sea surface. Only the first 21 vertical levels (from 5.0 m to 729.35 m) were considered here, since the most important changes in heat content observed for the world ocean during the last decades, correspond to the upper 700 m. Warming was observed to be considerably higher at ocean locations than at coastal ones. Ocean warming ranged from values on the order of 0.3 °C dec(-1) near surface to less than 0.1 °C dec(-1) at 500 m, while coastal warming showed values close to 0.2 °C dec(-1) near surface, decreasing rapidly below 0.1 °C dec(-1) for depths on the order of 50 m. The heat content anomaly for the upper 700 m, showed a sharp increase from coast (0.46 Wm(-2)) to ocean (1.59 Wm(-2)). The difference between coastal and ocean values was related to the presence of coastal upwelling, which partially inhibits the warming from surface of near shore water.publishe

Anthropogenic disturbance in a changing environment : modelling lifetime reproductive success to predict the consequences of multiple stressors on a migratory population

This study was supported by Office of Naval Research grant N00014‐16‐1‐2858: ‘PCoD+: Developing widely‐applicable models of the population consequences of disturbance’. DPC, MM, EAM and LKS were supported by the E&P Sound and Marine Life Joint Industry Project of the International Association of Oil and Gas Producers. JAG was supported by funding from the Young Investigator Program at the Office of Naval Research (award no. N00014‐16‐1‐2477). VH was funded by European Research Council Grant No. 322814 awarded to A.M. de Roos.Animals make behavioural and reproductive decisions that maximise their lifetime reproductive success, and thus their fitness, in light of periodic and stochastic variability of the environment. Modelling the variation of an individual's energy levels formalises this tradeoff and helps to quantify the population‐level consequences of stressors (e.g. disturbance from human activities and environmental change) that can affect behaviour or physiology. In this study, we develop a dynamic state variable model for the spatially explicit behaviour, physiology and reproduction of a female, long‐lived, migratory marine vertebrate. The model can be used to investigate the spatio‐temporal patterns of behaviour and reproduction that allow an individual to maximise its overall reproductive output. We parametrised the model for eastern North Pacific blue whales Balaenoptera musculus, and used it to predict the effects of changing environmental conditions and increasing human disturbance on the population's vital rates. In baseline conditions, the model output had high fidelity to observed energy dynamics, movement patterns and reproductive strategies. Simulated scenarios suggested that environmental changes could have severe consequences on the population's vital rates, but that individuals could tolerate high levels of anthropogenic disturbance. However, this ability depended on where, when and how often disturbance occurred. In scenarios with both environmental change and anthropogenic disturbance, synergistic interactions caused stronger effects than in isolation. In general, larger body size offered a buffer against stochasticity and disturbance, and, consequently, we predicted juveniles to be more susceptible to disturbance. We also predicted that females prioritise their own survival at the expense of the current reproductive attempt, presumably the result of their long lifespan. Our approach provides a general framework to make predictions of the cumulative and synergistic effects of human disturbance and climate change on migratory populations, which can inform effective management and conservation efforts.Publisher PDFPeer reviewe

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd