The localized scale of most fisheries management does not account for potential regional connectivity, particularly for fish species with prolonged planktonic larval durations (PLD). Although bonefish (Albula vulpes) inhabits shallow coastal habitats from juvenile through adult life stages, it is a strong candidate for population connectivity via larval dispersal with a PLD of 41–71 days. To address this knowledge gap, surface trajectories of particles (“virtual larvae”) released from 26 known and predicted spawning sites of bonefish around the Caribbean Sea, Florida, and Bahamas were simulated for 2009–2015 using a realistic ocean circulation hindcast model coupled with an online particle tracking simulator to study larval transport variations. At each site, 100 surface particles were released twice per month (at full and new moons) from October to April in each year and tracked for 53 days. We then estimated the likelihood that management regions would rely upon larval retention versus larval dispersal from other management zones. Overall, separately managed areas are likely to be connected via larval dispersal rather than entirely self-recruiting. Significant temporal differences in particle dispersal found for new and full moon phases, and between winter and spring, highlight that it is vital to resolve multiscale temporal and spatial variability in circulation transport when studying larval transport and connectivity. Results underscore the need to include the likelihood of population connectivity in fisheries management and conservation strategies, and to ensure that the ontogenetic habitat requirements of bonefish are properly managed at a regional scale.

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

We organized environmental observations (Sea Surface Temperature, chlorophyll concentration, and primary productivity) and biological diversity indices based on reconstructed fisheries landings obtained from the Sea Around Us project to address two objectives: 1) to understand whether adjacent Large Marine Ecosystems (LMEs) of the Americas form megaregions for assemblages of commercially-valuable fish; and 2) to assess changes in the diversity of fisheries landings in LMEs of the Americas over time (1982 to 2010). To test for similarities between LMEs, we used the seascape approach of unsupervised clustering of annual mean environmental observations and fisheries-derived diversity indices. Beta-diversity estimates based on fisheries landings were used to evaluate the degree to which species spanned LMEs. Temporal trends were computed for each dataset by linear least-squares. Three megaregions emerged when considering similarities in species composition of fisheries landings, fisheries-derived diversity indices, and characteristic environmental conditions among LMEs. These include (A) the South Brazil Shelf, East Brazil Shelf, and North Brazil Shelf LMEs, (B) the Gulf of Mexico and Southeast U.S. Continental Shelf LMEs, and (C) the Northeast U.S. Continental Shelf, Scotian Shelf, and Newfoundland-Labrador Shelf LMEs. No megaregions emerged for the Pacific Ocean. While there were some shared species assemblages between the California Current and the Gulf of Alaska, the Gulf of California, and the Pacific Central-American Coastal LMEs, these showed different average environmental conditions and fishery-derived diversity indices, so they did not cluster as a megaregion. In the Pacific Ocean, the high dissimilarity in the fisheries is in part related to different top-down pressures and strong regional differences in oceanographic properties, including upwelling and impacts of El-Niño Southern Oscillation events. Overall, between 1982 and 2010, seven LMEs diversified their fisheries (Pacific Central-America Coastal, Patagonian Shelf, South Brazil Shelf, East Brazil Shelf, North Brazil Shelf, Southeast U.S. Continental Shelf, and Newfoundland-Labrador Shelf). This may be due to a number of reasons including decreasing fishing pressure but expansion of target stocks due to management quotas, changes in regional markets, competition, effort, or a decrease in particular target stocks. Three LMEs showed increasingly less diversified fisheries, namely the California Current, the Northeast U.S. Continental Shelf, and the Caribbean Sea LMEs. While in some cases this may be related to historical overfishing, such as in the Northeast U.S. Continental Shelf LME, the California Current LME has been subjected to strong and conservative management practices. The Caribbean Sea LME was likely subjected to heavy fishing at a time of rapid environmental change.

Climate change is likely to drive complex shifts in the distribution and ecology of marine species. Projections of future changes may vary, however, depending on the biological impact model used. In this study, we compared a correlative species distribution model and a simple mechanistic oxygen balance model for Atlantic bluefin tuna (Thunnus thynnus: ABFT) in the North Atlantic Ocean. Both models gave similar results for the recent historical time period, and suggested that ABFT generally occupy favourable metabolic habitats. Projections from an earth system model showed largely temperature-induced reductions in ABFT habitat in the tropical and sub-tropical Atlantic by 2100. However, the oxygen balance model showed more optimistic results in parts of the subpolar North Atlantic. This was partially due to an inherent ability to extrapolate beyond conditions currently encountered by pelagic longline fishing fleets. Projections included considerable uncertainty due to the simplicity of the biological models, and the coarse spatiotemporal resolution of the analyses. Despite these limitations, our results suggest that climate change is likely to increase metabolic stress on ABFT in sub-tropical habitats, but may improve habitat suitability in subpolar habitats, with implications for spawning and migratory behaviours, and availability to fishing fleets.

Increasing water temperatures due to climate change will likely have significant impacts on distributions and life histories of Atlantic tunas. In this study, we combined predictive habitat models with a downscaled climate model to examine potential impacts on adults and larvae of Atlantic bluefin tuna (Thunnus thynnus) and skipjack tuna (Katsuwonus pelamis) in the Intra-Americas Sea (IAS). An additional downscaled model covering the 20th century was used to compare habitat fluctuations from natural variability to predicted future changes under two climate change scenarios: Representative Concentration Pathway (RCP) 4.5 (medium–low) and RCP 8.5 (high). Results showed marked temperature-induced habitat losses for both adult and larval bluefin tuna on their northern Gulf of Mexico spawning grounds. In contrast, habitat suitability for skipjack tuna increased as temperatures warmed. Model error was highest for the two skipjack tuna models, particularly at higher temperatures. This work suggests that influences of climate change on highly migratory Atlantic tuna species are likely to be substantial, but strongly species-specific. While impacts on fish populations remain uncertain, these changes in habitat suitability will likely alter the spatial and temporal availability of species to fishing fleets, and challenge equilibrium assumptions of environmental stability, upon which fisheries management benchmarks are based.

This study examines the potential impact of anthropogenic greenhouse warming on the Intra-Americas Sea (IAS, Caribbean Sea and Gulf of Mexico) by downscaling the Coupled Model Intercomparison Project phase-5 (CMIP5) model simulations under historical and two future emission scenarios using an eddy-resolving resolution regional ocean model. The simulated volume transport by the western boundary current system in the IAS, including the Caribbean Current, Yucatan Current and Loop Current (LC), is reduced by 20-25% during the 21st century, consistent with a similar rate of reduction in the Atlantic Meridional Overturning Circulation (AMOC). The effect of the LC in the present climate is to warm the Gulf of Mexico (GoM). Therefore, the reduced LC and the associated weakening of the warm transient LC eddies have a cooling impact in the GoM, particularly during boreal spring in the northern deep basin, in agreement with an earlier dynamic downscaling study. In contrast to the reduced warming in the northern deep GoM, the downscaled model predicts an intense warming in the shallow (≤200m) northeastern shelf of the GoM especially during boreal summer since there is no effective mechanism to dissipate the increased surface heating. Potential implications of the regionally distinctive warming trend pattern in the GoM on the marine ecosystems and hurricane intensifications during landfall are discussed. This study also explores the effects of 20th century warming and climate variability in the IAS using the regional ocean model forced with observed surface flux fields. The main modes of sea surface temperature variability in the IAS are linked to the Atlantic Multidecadal Oscillation and a meridional dipole pattern between the GoM and Caribbean Sea. It is also shown that variability of the IAS western boundary current system in the 20th century is largely driven by wind stress curl in the Sverdrup interior and the AMOC.

Satellite observations and their derived products played a key role during the Deepwater Horizon oil spill monitoring efforts in the Gulf of Mexico in April–July 2010. These observations were sometimes the only source of synoptic information available to monitor and analyse several critical parameters on a daily basis. These products also complemented in situ observations and provided data to assimilate into or validate model. The ocean surface dynamics in the Gulf of Mexico are dominated by strong seasonal cycles in surface temperature and mixing due to convective and storm energy, and by major currents that include the Loop Current and its associated rings. Shelf processes are also strongly influenced by seasonal river discharge, winds, and storms. Satellite observations were used to determine that the Loop Current exhibited a very northern excursion (to approximately 28 $$^{\circ }$$ N) during the month of May, placing the core of this current and of the ring that it later shed at approximately 150 km south of the oil spill site. Knowledge gained about the Gulf of Mexico since the 1980s using a wide range of satellite observations helped understand the timing and process of separation of an anticyclonic ring from the Loop Current during this time. The surface extent of the oil spill varied largely based upon several factors, such as the rate of oil flowing from the well, clean up and recovery efforts, and biological, chemical, and physical processes. Satellite observations from active and passive radars, as well as from visible and infrared sensors were used to determine the surface extent of the oil spill. Results indicate that the maximum and total cumulative areal extent were approximately 45 $$\times $$ 10 $$^3$$ km $$^2$$ and 130 $$\times $$ 10 $$^3$$ km $$^2$$ , respectively. The largest increase of surface oil occurred between April 22 and May 22, at an average rate of 1.3 $$\times $$ 10 $$^3$$ km $$^2$$ per day. The largest decrease in the extent of surface oil started on June 26, at an average rate of 4.4 $$\times $$ 10 $$^3$$ km $$^2$$ per day. Surface oil areas larger than approximately 40 $$\times $$ 10 $$^3$$ km $$^2$$ occurred during several periods between late May and the end of June. The southernmost surface oil extent reached approximately 85 $$^{\circ }$$ W 27 $$^{\circ }$$ N during the beginning of June. Results obtained indicate that surface currents may have partly controlled the southern and eastern extent of the surface oil during May and June, while intense southeast winds associated with Hurricane Alex caused a reduction of the surface oil extent at the end of June and beginning of July, as oil was driven onshore and mixed underwater. Given the suite of factors determining the variability of the oil spill extent at ocean surface, work presented here shows the importance of data analyses to compare against assessments made to evaluate numerical models.

Climate change is likely to impact migration, spawning and recruitment of Atlantic tunas and billfishes, however potential responses and mechanisms remain largely unknown. A multidisciplinary, multi-agency research group has been using a combination of historical environmental and biological data, ecological experiments and climate modeling work to begin to address this knowledge gap. A summary of research activities over the past ~4 years is presented here. Results to date suggest that responses of highly migratory tunas and billfishes are likely to be species-specific. Temperate species such as Atlantic bluefin tuna are potentially most vulnerable. In order to estimate future trends in recruitment, an understanding of the basic ecology of early life history stages is vital, but has frequently been neglected in previous research. Collaborations across disciplines between ecologists, modelers and other researchers have allowed us to link smaller-scale laboratory studies with regional-scale models of environmental change, and to move towards development of species-specific impact models.

This work characterizes patterns of temporal variability in surface waters of the central Gulf of Mexico. We examine remote-sensing based observations of sea surface temperature (SST), wind speed, sea surface height anomaly (SSHA), chlorophyll-a concentration (Chl-a) and Net Primary Production (NPP), along with model predictions of mixed layer depth (MLD), to determine seasonal changes and long-term trends in the central Gulf of Mexico between the early 1980s and 2012. Specifically, we examine variability in four quadrants of the Gulf of Mexico (water depth >1000 m). All variables show strong seasonality. Chl-a and NPP show positive anomalies in response to short-term increases in wind speed and to cold temperature events. The depth of the mixed layer (MLD) directly and significantly affects primary productivity throughout the region. This relationship is sufficiently robust to enable real-time estimates of MLD based on satellite-based estimates of NPP. Over the past 15-20 years, SST, wind speed, and SSHA show a statistically significant, gradual increase. However, Chl-a and NPP show no significant trends over this period. There has also been no trend in the MLD in the Gulf of Mexico interior. The positive long-term trend in wind speed and SST anomalies is consistent with the warming phase of the Atlantic Multidecadal Oscillation (AMO) that started in the mid-90s. This also coincides with a negative trend in the El Nino/ Southern Oscillation Multivariate ENSO Index (MEI) related to an increase in the frequency of cooler ENSO events since 1999-2000. The results suggest that over decadal scales, increasing temperature, wind speed, and mesoscale ocean activity have offsetting effects on the MLD. The lack of a trend in MLD anomalies over the past 20 years explains the lack of long-term changes in chlorophyll concentration and productivity over this period in the Gulf. Understanding the background of seasonal and long-term variability in these ocean characteristics is important to interpret changes in ocean health due to episodic natural and anthropogenic events and long term climate changes or development activities. With this analysis we provide a baseline against which such changes can be measured. (C) 2014 The Authors. Published by Elsevier Ltd. All rights reserved.

Annual ichthyoplankton surveys have been conducted in the Gulf of Mexico during spring since 1982 by the National Oceanic and Atmospheric Administration (NOAA) National Marine Fisheries Service (NMFS) Southeast Area Monitoring and Assessment Program (SEAMAP). Historically, ichthyoplankton has been assessed using bongo and surface neuston nets. A new sampling gear, the S‐10 net, was tested between 2009 and 2011. This is a 1 × 2 m frame fitted with a 0.505 mm mesh net, towed in a yo‐yo fashion between the surface and 10 m. Sampling effectiveness of the three gears was compared by examining the abundance and length of larvae of bluefin tuna (Thunnus thynnus) and seven co‐occurring pelagic taxa (Auxis spp., Euthynnus alleteratus, Coryphaena spp., Katsuwonus pelamis, other Thunnus spp., family Istiophoridae, and Xiphias gladius) and vertical distributions of scombrid taxa were examined using MOCNESS samples. Permutational multivariate analysis of variance (PERMANOVA) of net type and time of sampling (day/night) indicated that net type was a significant factor in assessing abundance and length for all taxa. Highest abundances for seven of eight taxa were in S‐10 samples, and MOCNESS samples confirm highest scombrid abundance between the surface and 20 m. Our results show sampling effectiveness strongly depends on the depth fished by the net and that the S‐10 net was more effective than standard SEAMAP bongo and neuston nets. Thus, future sampling with the S‐10 net may improve the annual index of larval abundance for the western population of Atlantic bluefin tuna, traditionally based on abundance from bongo samples.

Despite being well adapted for feeding in cold water on their North Atlantic feeding grounds, Atlantic bluefin tuna undertake long migrations to reach warm, low productivity spawn - ing grounds in the Gulf of Mexico and Mediterranean Sea. Environmental conditions within spawning areas have been presumed to benefit larval survival, through appropriate feeding conditions, and enhanced larval retention and growth rates. However, field collections and studies to explore the potential mechanisms are rare. In this study, a comparison of the environmental characteristics of both spawning sites was completed using standardized environmental data and modeling methods. Predictive models of larval occurrence were constructed using historical larval collections, and environmental variables from both in situ and remotely sensed sources. Results showed that larvae on both spawning grounds were most likely to be found in warm (23 to 28°C), low chlorophyll areas with moderate current velocities and favorable regional retention condi- tions. In the Gulf of Mexico, larvae were located in offshore waters outside of the Loop Current and warm eddies, while in the western Mediterranean, larval occurrences were associated with the confluence of inflowing Atlantic waters and saltier resident surface waters. Although our results suggested common themes within preferred spawning grounds on both sides of the Atlantic Ocean, the ecological processes governing larval survival and eventual recruitment are yet to be fully understood.

Earth observing satellites represent some of the most valued components of the international Global Ocean Observing System (GOOS) and of the Global Climate Observing System (GCOS), both part of the Global Earth Observation System of Systems (GEOSS). In the United States, such satellites are a cornerstone of the Integrated Ocean Observing System (IOOS), required to carry out advanced coastal and ocean research, and to implement and sustain sensible resource management policies based on science. Satellite imagery and satellite-derived data are required for mapping vital coastal and marine resources, improving maritime domain awareness, and to better understand the complexities of land, ocean, atmosphere, ice, biological, and social interactions. These data are critical to the strategic planning of in situ observing components and are critical to improving forecasting and numerical modeling. Specifically, there are several stakeholder communities that require periodic, frequent, and sustained synoptic observations. Of particular importance are indicators of ecosystem structure (habitat and species inventories), ecosystem states (health and change) and observations about physical and biogeochemical variables to support the operational and research communities, and industry sectors including mining, fisheries, and transportation. IOOS requires a strategy to coordinate the human capacity, and fund, advance, and maintain the infrastructure that provides improved remote sensing observations and support for the nation and the globe. A partnership between the private, government, and education sectors will enhance remote sensing support and product development for critical coastal and deep-water regions based on infrared, ocean color, and microwave satellite sensors. These partnerships need to include international research, government, and industry sectors in order to facilitate open data access, understanding of calibration and algorithm strategies, and fill gaps in coverage. Such partnerships will define the types of observations required to sustain vibrant coastal economies and to improve the health of our marine and coastal ecosystems. They are required to plan, fund, launch and operate the types of satellite sensors needed in the very near future to maintain continuity of observations.

RÉSUMÉ George A. Maul a, Francis Williams b, Mitchell Roffer b, Fatima M. Sousa e a National Oceanic and Atmospheric Administration, Atlantic Oceanographie and Meteorological Laboratory, and Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, Florida, USA. b Division of Biology and Living Resources, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA. c Oceanography Group, Department of Physics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal. Received 16/8/83, in revised form 27/3/84, accepted 5/4/84. Data from the Japanese longline bluefin fishery in the Gulf of Mexico for 1979 and 1980 were combined with in situ oceanographie data from four research cruises and several ship-of-opportunity XBT transects, and with infrared and visible ssatellite imagery from GOES, TIROS-n, and NIMBUS-7. Catch per unit effort, CPUE, for Atlantic bluefin tuna (Thunnus thynnus thynnus) in 1979 was approximately one third that in 1980 and appears to be associated with the area fished. Using GOES infrared data, the boundary of the Gulf Loop Current was located and compared with the CPUE; the high 1980 catch was correlated with proximity to the surface thermal front of the current and appears to reflect a change in fishing strategy between years. Correlations with other environmental factors such as sea surface temperature, temperature differences, time (spectral estimates), and configuration of the Loop Current, were generally inconclusive. Polar orbiting satellite data, with at most twice-per-day observations, provided very few useful current boundary locations whereas GOES, with its hourly imagery schedule for oceanographie features, allowed comparisons almost every day during the fishing season. Operational application of satellite data to fisheries oceanography in the tropics and sub-tropics requires the high imaging frequency of geostationary vehicles because of cloud abundance, separation, and advection rates. Oceanol. Acta, 1984, 7, 4, 469-479. Télédétectiop de structures océanographiques et variabilité de la capture du thon rouge dans le Golfe du Mexique Les données de la pêcherie japonaise de thon rouge dans le Golfe du Mexique pendant 1979 et 1980 ont été combinées avec les données in situ de quatre campagnes océanographiques et de plusieurs sections XBT de navires volontaires, et avec des images des satellites GOES, TIROS-n et NIMBUS-7 dans le visible et l'infrarouge. La capture par unité d'effort (CPUE) du thon rouge de l'Atlantique (Thunnus thynnus thynnus) a été, en 1979, d'un tiers de celle de 1980, et semble associée à l'étendue de la région de pêche. En utilisant la bande infrarouge du satellite GOES, la frontière du courant «Gulf Loop »a été localisée et comparée avec le CPUE; corrélées avec la proximité du front thermique superficiel du courant, les grandes captures de 1980 semblent indiquer une modification dans la stratégie de pêche d'une année à l'autre. Des corrélations avec d'autres paramètres environnementaux comme la température superficielle de la mer, les gradients thermiques et de l'évolution temporelle (spectres) de la configuration du courant« Gulf Loop »,n'ont généralement pas été concluantes. Les données du satellite d'orbite polaire, avec ses deux passages par jour au maximum, ont fourni très peu d'information sur la localisation des limites du « Gulf Loop »; O.A. 0399-1784/84/04 469 11/S 3.1 0/(èl Gauthier-Villars 469

The 2010 Deepwater Horizon oil spill impacted the northern Gulf of Mexico (GOM) during the spring spawning season of Atlantic bluefin tuna (BFT). Overlap between BFT spawning habitat and surface oil in the northern GOM was examined using satellite-derived estimates of oil coverage, and spawning habitat models. Results suggested that although eggs and larvae were likely impacted by oil-contaminated waters in the eastern GOM, high abundances of larvae were located elsewhere, especially in the western GOM. Overall, less than 10% of BFT spawning habitat was predicted to have been covered by surface oil, and less than 12% of larval BFT were predicted to have been located within contaminated waters in the northern GOM, on a weekly basis. Our results provide preliminary but important initial estimates of the effects of the spill on larval BFT mortality, as concern continues over the appropriate management responses to impacts of the spill.

Atlantic bluefin tuna, Thunnus thynnus (Linnaeus, 1758), are highly migratory and capable of traversing large distances throughout the North Atlantic Ocean. However, the majority of spawning activity has only been reported from the Mediterranean Sea and Gulf of Mexico. In early April 2009, low numbers of very small larval bluefin tuna were collected within and south of the Yucatan Channel, and along the western boundary of the Loop Current, northeast of Campeche Bank. In situ current velocity measurements showed that these larvae were collected in moderate to strong northward flow regimes, suggesting that they were spawned outside of the Gulf of Mexico. Here we describe the location and oceanographic environment of these larval bluefin tuna collections, and compare the 2009 data with some historical collections in the area.

Two oil particle trajectory forecasting systems were developed and applied to the 2010 Deepwater Horizon Oil Spill in the Gulf of Mexico. Both systems use ocean current fields from high-resolution numerical ocean circulation model simulations, Lagrangian stochastic models to represent unresolved sub-grid scale variability to advect oil particles, and Monte Carlo-based schemes for representing uncertain biochemical and physical processes. The first system assumes two-dimensional particle motion at the ocean surface, the oil is in one state, and the particle removal is modeled as a Monte Carlo process parameterized by a one number removal rate. Oil particles are seeded using both initial conditions based on observations and particles released at the location of the Maconda well. The initial conditions (ICs) of oil particle location for the two-dimensional surface oil trajectory forecasts are based on a fusing of all available information including satellite-based analyses. The resulting oil map is digitized into a shape file within which a polygon filling software generates longitude and latitude with variable particle density depending on the amount of oil present in the observations for the IC. The more complex system assumes three (light, medium, heavy) states for the oil, each state has a different removal rate in the Monte Carlo process, three-dimensional particle motion, and a particle size-dependent oil mixing model.Simulations from the two-dimensional forecast system produced results that qualitatively agreed with the uncertain "truth" fields. These simulations validated the use of our Monte Carlo scheme for representing oil removal by evaporation and other weathering processes. Eulerian velocity fields for predicting particle motion from data-assimilative models produced better particle trajectory distributions than a free running model with no data assimilation. Monte Carlo simulations of the three-dimensional oil particle trajectory, whose ensembles were generated by perturbing the size of the oil particles and the fraction in a given size range that are released at depth, the two largest unknowns in this problem. 36 realizations of the model were run with only subsurface oil releases. An average of these results yields that after three months, about 25% of the oil remains in the water column and that most of the oil is below 800 m. (C) 2011 Elsevier B.V. All rights reserved.