NOAA Office of Response and Restoration

A simple model of the temperature‐dependent biological decay of dissolved oil is embedded in an ocean‐climate model and used to simulate underwater plumes of dissolved and suspended oil originating from a point source in the northern Gulf of Mexico, with an upper‐bound supply rate estimated from the contemporary analysis of the Deepwater Horizon blowout. The behavior of plumes at different depths is found to be determined by the combination of sheared current strength and the vertical profile of decay rate. For all plume scenarios, toxic levels of dissolved oil remain confined to the northern Gulf of Mexico, and abate within weeks after the spill stops. An estimate of oxygen consumption due to microbial oxidation of hydrocarbons suggests that a deep plume of hydrocarbons could lead to localized regions of prolonged hypoxia near the source, but only when oxidation of methane is included.

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies.

(DWH) oil spill, a number of government agencies, academic institutions, consultants, and nonprofit organizations conducted lab- and field-based research to understand the toxic effects of the oil. Lab testing was performed with a variety of fish, birds, turtles, and vertebrate cell lines (as well as invertebrates); field biologists conducted observations on fish, birds, turtles, and marine mammals; and epidemiologists carried out observational studies in humans. Eight years after the spill, scientists and resource managers held a workshop to summarize the similarities and differences in the effects of DWH oil on vertebrate taxa and to identify remaining gaps in our understanding of oil toxicity in wildlife and humans, building upon the cross-taxonomic synthesis initiated during the Natural Resource Damage Assessment. Across the studies, consistency was found in the types of toxic response observed in the different organisms. Impairment of stress responses and adrenal gland function, cardiotoxicity, immune system dysfunction, disruption of blood cells and their function, effects on locomotion, and oxidative damage were observed across taxa. This consistency suggests conservation in the mechanisms of action and disease pathogenesis. From a toxicological perspective, a logical progression of impacts was noted: from molecular and cellular effects that manifest as organ dysfunction, to systemic effects that compromise fitness, growth, reproductive potential, and survival. From a clinical perspective, adverse health effects from DWH oil spill exposure formed a suite of signs/symptomatic responses that at the highest doses/concentrations resulted in multi-organ system failure.

This paper reviews the tissue residue approach (TRA) for toxicity assessment as it applies to organic chemicals and some organometallic compounds (Sn, Hg, and Pb) in aquatic organisms. Specific emphasis was placed on evaluating key factors that influence interpretation of critical body residue (CBR) toxicity metrics including data quality issues, lipid dynamics, choice of endpoints, processes that alter toxicokinetics and toxicodynamics, phototoxicity, species- and life stage-specific sensitivities, and biotransformation. The vast majority of data available on TRA is derived from laboratory studies of acute lethal responses to organic toxicants exhibiting baseline toxicity. Application of the TRA to various baseline toxicants as well as substances with specific modes of action via receptor-mediated processes, such as chlorinated aromatic hydrocarbons, pesticides, and organometallics is discussed, as is application of TRA concepts in field assessments of tissue residues. In contrast to media-based toxicity relationships, CBR values tend to be less variable and less influenced by factors that control bioavailability and bioaccumulation, and TRA can be used to infer mechanisms of toxic action, evaluate the toxicity of mixtures, and interpret field data on bioaccumulated toxicants. If residue-effects data are not available, body residues can be estimated, as has been done using the target lipid model for baseline toxicants, to derive critical values for risk assessment. One of the primary unresolved issues complicating TRA for organic chemicals is biotransformation. Further work on the influence of biotransformation, a better understanding of contaminant lipid interactions, and an explicit understanding of the time dependency of CBRs and receptor-mediated toxicity are all required to advance this field. Additional residue-effects data on sublethal endpoints, early life stages, and a wider range of legacy and emergent contaminants will be needed to improve the ability to use TRA for organic and organometallic compounds.

Hazardous site management in the United States includes remediation of contaminated environmental media and restoration of injured natural resources. Site remediation decisions are informed by ecological risk assessment (ERA), whereas restoration and compensation decisions are informed by the natural resource damage assessment (NRDA) process. Despite similarities in many of their data needs and the advantages of more closely linking their analyses, ERA and NRDA have been conducted largely independently of one another. This is the 4th in a series of papers reporting the results of a recent workshop that explored how ERA and NRDA data needs and assessment processes could be more closely linked. Our objective is to evaluate the technical underpinnings of recentmethods used to translate natural resource injuries into ecological service losses and to propose ways to enhance the usefulness of data obtained in ERAs to the NRDA process. Three aspects are addressed: 1) improving the linkage among ERA assessment endpoints and ecological services evaluated in the NRDA process, 2) enhancing ERA data collection and interpretation approaches to improve translation of ERA measurements in damage assessments, and 3) highlighting methods that can be used to aggregate service losses across contaminants and across natural resources. We propose that ERA and NRDA both would benefit by focusing ecological assessment endpoints on the ecosystem services that correspond most directly to restoration and damage compensation decisions, and we encourage development of generic ecosystem service assessment endpoints for application in hazardous site investigations. To facilitate their use in NRDA, ERA measurements should focus on natural resource species that affect the flow of ecosystem services most directly, should encompass levels of biological organization above organisms, and should be made with the use of experimental designs that support description of responses to contaminants as continuous (as opposed to discrete) variables. Application of a data quality objective process, involving input from ERA and NRDA practitioners and site decision makers alike, can facilitate identification of data collection and analysis approaches that will benefit both assessment processes. Because of their demonstrated relationships to a number of important ecosystem services, we recommend that measures of biodiversity be targeted as key measurement endpoints in ERA to support the translation between risk and service losses. Building from case studies of recent successes, suggestions are offered for aggregating service losses at sites involving combinations of chemicals and multiple natural resource groups. Recognizing that ERA and NRDA are conducted for different purposes, we conclude that their values to environmental decision making can be enhanced by more closely linking their data collection and analysis activities.

The removal of fish biomass by extensive commercial and recreational fishing has been hypothesized to drastically alter the strength of trophic linkages among adjacent habitats. We evaluated the effects of removing predatory fishes on trophic transfers between coral reefs and adjacent seagrass meadows by comparing fish community structure, grazing intensity, and invertebrate predation potential in predator-rich no-take sites and nearby predator-poor fished sites in the Florida Keys (USA). Exploited fishes were more abundant at the no-take sites than at the fished sites. Most of the exploited fishes were either omnivores or invertivores. More piscivores were recorded at no-take sites, but most (approximately 95%) were moderately fished and unexploited species (barracuda and bar jacks, respectively). Impacts of these consumers on lower trophic levels were modest. Herbivorous and smaller prey fish (< 10 cm total length) densities and seagrass grazing diminished with distance from reefs and were not negatively impacted by the elevated densities of exploited fishes at no-take sites. Predation by reef fishes on most tethered invertebrates was high, but exploited species impacts varied with prey type. The results of the study show that, even though abundances of reef-associated fishes have been reduced at fished sites, there is little evidence that this has produced cascading trophic effects or interrupted cross-habitat energy exchanges between coral reefs and seagrasses.

The National Oceanic and Atmospheric Administration Office of Response and Restoration (OR&R) provides scientific support for oil and chemical spills. During the unprecedented Deepwater Horizon oil spill response in the Gulf of Mexico, the Emergency Response Division (OR&R/Emergency Response Division) provided daily 72 h tactical forecasts for movement of the surface oil. Surface oil distribution was initialized daily from analysis of satellite imagery and incorporation of visual overflight observations. Computation of oil trajectories utilized currents from a number of hydrodynamic models allowing an ensemble forecasting approach. Results from the suite of trajectories were combined to produce a final forecast product for distribution to the Incident Command Posts. These forecasts were utilized during the Deepwater Horizon response for planning, allocation of resources, and direction of response assets.

Marine fish movement plays a critical role in ecosystem functioning and is increasingly studied with acoustic telemetry. Traditionally, this research has focused on single species and small spatial scales. However, integrated tracking networks, such as the Integrated Tracking of Aquatic Animals in the Gulf of Mexico (iTAG) network, are building the capacity to monitor multiple species over larger spatial scales. We conducted a synthesis of passive acoustic monitoring data for 29 species (889 transmitters), ranging from large top predators to small consumers, monitored along the west coast of Florida, USA, over 3 yr (2016-2018). Space use was highly variable, with some groups using all monitored areas and others using only the area where they were tagged. The most extensive space use was found for Atlantic tarpon Megalops atlanticus and bull sharks Carcharhinus leucas . Individual detection patterns clustered into 4 groups, ranging from occasionally detected long-distance movers to frequently detected juvenile or adult residents. Synchronized, alongshore, long-distance movements were found for Atlantic tarpon, cobia Rachycentron canadum , and several elasmobranch species. These movements were predominantly northbound in spring and southbound in fall. Detections of top predators were highest in summer, except for nearshore Tampa Bay where the most detections occurred in fall, coinciding with large red drum Sciaenops ocellatus spawning aggregations. We discuss the future of collaborative telemetry research, including current limitations and potential solutions to maximize its impact for understanding movement ecology, conducting ecosystem monitoring, and supporting fisheries management.

Increased organized monitoring is key to improving our understanding of marine debris on shorelines. Shorelines are demonstrated sinks for marine debris but efforts to quantify debris often fail to capture and report core variables and survey design techniques necessary to ensure study repeatability, comparability and to provide meaningful results. Here, we systematically review the available literature regarding marine debris distribution and abundance on shorelines of countries bordering the North Pacific Ocean (NPO), which are demonstrated to have unusually high marine debris abundance and diversity both at the ocean surface and stranded on shorelines. The majority of the 81 papers documenting shoreline debris in the NPO were studies that took place for less than one year (76.5%). Additionally, most sampling sites were visited only once (57.3%). Precise site locations (GPS coordinates) were provided in only 44.4% of the evaluated studies. Debris quantities were reported using nine different measurement units, with item counts per area and item counts per mass being most commonly reported for macro- and microplastics, respectively. Taken together, most of the reviewed studies could not be repeated by others given the information provided. We propose a series of guidelines with regard to marine debris shoreline sampling metrics, indicators, methods, and target goals in the NPO in order to improve comparability and repeatability. These follow the basic tenets of environmental survey design, which when not accounted for, can limit the applicability and value of large-scale shoreline monitoring efforts.

The Deepwater Horizon (DWH) oil spill was unprecedented in extent and duration, and affected marine natural resources, including sea turtles, throughout the northern Gulf of Mexico. Consequently, US federal and state Trustees documented and quantified oil exposure and resulting injuries to sea turtles under the DWH Natural Resource Damage Assessment. At-sea rescue operations focused on surface-pelagic juvenile sea turtles, which were especially at risk to oil exposure within oceanic convergence zones, and provided direct observations of the degree that turtles in this young life stage were exposed to DWH oil. In contrast, locations of larger neritic juvenile and adult turtles were documented during aerial surveys, but because these turtles were not captured, their oiling status could not be directly evaluated. Both the rescue operations and aerial surveys were able to observe only a small fraction of sea turtles within the vast spill footprint. We developed a spatio-temporally explicit approach that used direct observations of oiled surface-pelagic juvenile sea turtles and satellite-derived surface oil distributions to statistically estimate the probabilities of oil exposure for all sea turtles that were present within the area of the DWH spill, but whose oiling status was unknown. Our results enabled an expansion of exposure and injury quantification across the entire DWH spill area and period. This approach was conceptually straightforward and used common geospatial and statistical techniques, making it applicable to other situations in which the full extent of oil exposure for marine natural resources must be estimated from an incomplete sample.

Marine debris is a threat to our ocean that can be more effectively addressed through monitoring and assessment of items stranded on shorelines. This study engaged citizen scientists to conduct shoreline marine debris surveys according to a published NOAA protocol within the Greater Farallones and Olympic Coast National Marine Sanctuaries on the west coast of the United States. Here, we use the results of these multi-year monitoring data to estimate marine debris abundance and temporal trends, and identify drivers of debris loads. Changes in debris counts and composition are shown to reflect seasonal patterns of coastal upwelling and downwelling, but longer temporal trends in overall debris loads depend on the sampling window. Identifying drivers of stranded debris is challenging given the observational nature of the data. A linear increase in total expected debris counts was observed when up to five participants are conducting a survey, suggesting a need to standardize the number of participants and their search pattern for debris in shoreline monitoring efforts. Lastly, we discuss the application of shoreline marine debris data to evaluate the impact of management decisions and identify new targets for mitigation.

ABSTRACT The Coastal Response Research Center (CRRC), a partnership between the University of New Hampshire (UNH) and NOAA'S Office of Response and Restoration (ORR), is leading an effort to develop a data platform capable of intefacing both static and real-time data sets accessible simultaneously to a command post and assets in the field with an open source internet mapping server. The Environmental Response Management Application (ERMA™) is designed to give responders and decision makers ready access to geographically specific data useful during spill planning/drills, incident response, damage assessment and site restoration. In addition to oil spill and chemical release response, this website can be relevant to other environmental incidents and natural disasters, responses and regional planning efforts. The platform is easy to operate, without the assistance of Information Technology or Geographic Information Systems (GIS) specialists. It allows users to access individual data layer values, overlay relevant data sets, and zoom into segments of interest. The platform prototype is being developed specifically for Portsmouth Harbor and the Great Bay Estuary, NH. The prototype demonstrates the capabilities of an integrated data management platform and serves as the pilot for web-based GIS platforms in other regions.

When oil spills occur in the marine environment, many species of wildlife in that ecosystem may be either directly or indirectly impacted. The impacts of spilled oil on birds are well known In comparison, marine mammals (and, in particular, cetaceans and sirenians) have only infrequently been documented

Derelict fishing gear (DFG) is abundant across the remote North Pacific Ocean, accumulating in convergence zones that coincide with the fishing grounds of the Hawai'i-based pelagic longline fishery. Longlines are prone to snagging DFG, providing an opportunistic, yet regular, reporting mechanism by longline fishery observers (fishery-dependent data). We apply a zero-inflated negative binomial model previously used to standardize catch per unit effort (CPUE) for bycatch and incidentally caught species in this fishery to estimate DFG relative abundance and qualitative trends within the longline fishing grounds. During 2008-2016, observers reported 1326 marine debris items intercepted by longlines, dominated by DFG at nearly 90%. Modeling results suggest that the relative abundance of DFG has declined ~66% from 2008-2016. DFG standardized CPUE was higher for longlines fished inside the North Pacific Subtropical Convergence Zone (versus outside) and increased moving eastward and northward toward the Great Pacific Garbage Patch. Despite substantially less effort in the shallow-set sector of the fishery (∼60 m depth), DFG standardized CPUE was four-fold greater than that of the deep-set sector (∼250 m) suggesting that marine debris observer reporting focused in this sector may be most effective. Some fishermen voluntarily stow snagged debris; incentivizing at-sea removal may elicit further cooperation.

Shoreline surveys are a common approach for documenting loads of marine macrodebris (≥ 2.5 cm). When surveys are conducted repeatedly over time and space, patterns in source, abundance, geographic distribution, and composition can be detected. Yet to realize their full potential, monitoring programs that rely on surveys must grapple with high variability in debris abundance, and appropriately manage uncertainty when reporting estimates of debris quantity. A potentially important source of bias in estimating debris loads from shoreline monitoring datasets is variability in debris detection rates. With this in mind, we conducted field experiments using common strip-transect marine debris survey protocols, designed to test detection of macrodebris. We quantified how protocol, shoreline, and debris characteristics influence the detectability of marine macrodebris. Detection rates varied according to debris distance from observer (0–5 m), number of observers, debris characteristics (size, color), and shoreline substrate. Our results highlight considerations for monitoring program design. Comparisons across datasets should be approached cautiously given differences in survey protocols and sources of bias that may affect debris density estimates should be quantified and addressed. We hope these results will inform marine debris monitoring efforts that are optimized for intended data use and impact. • Debris size, color, and distance from observer influence macrodebris detection • Detection is also affected by substrate and number of observers performing surveys • Counts are minimums especially for small (2.5 - 5 cm) and dull colored items • Datasets from different survey methods may be biased in different ways • Adjustments to minimize or account for error will depend on study goals

The rise in oil trade and transportation has led to a continuous increase in the risk of oil spills, posing a serious worldwide concern. However, there is a lack of numerical models for predicting oil spill transport in freshwater, especially under icy conditions. To tackle this challenge, we developed a prediction system for oil with ice modeling by coupling the General NOAA Operational Modeling Environment (GNOME) model with the Great Lakes Operational Forecast System (GLOFS) model. Taking Lake Erie as a pilot study, we used observed drifter data to evaluate the performance of the coupled model. Additionally, we developed six hypothetical oil spill cases in Lake Erie, considering both with and without ice conditions during the freezing, stable, and melting seasons spanning from 2018 to 2022, to investigate the impacts of ice cover on oil spill processes. The results showed the effective performance of the coupled model system in capturing the movements of a deployed drifter. Through ensemble simulations, it was observed that the stable season with high-concentration ice had the most significant impact on limiting oil transport compared to the freezing and melting seasons, resulting in an oil-affected open water area of 49 km2 on day 5 with ice cover, while without ice cover it reached 183 km2. The stable season with high-concentration ice showed a notable reduction in the probability of oil presence in the risk map, whereas this reduction effect was less prominent during the freezing and melting seasons. Moreover, negative correlations between initial ice concentration and oil-affected open water area were consistent, especially on day 1 with a linear regression R-squared value of 0.94, potentially enabling rapid prediction. Overall, the coupled model system serves as a useful tool for simulating oil spills in the world's largest freshwater system, particularly under icy conditions, thus enhancing the formulation of effective emergency response strategies.

The Marine Pollution Program of NOAA/NESDIS's Satellite Analysis Branch (SAB) consists of manual detection and mapping of oil slicks through the use of available moderate to high resolution visible imagery such as MODIS (NASA), Landsat-7 (USGS) and SPOT-5 (CNES). Prior to 2012, synthetic aperture radar (SAR) imagery from ENVISAT (ESA) was acquired in addition to visible imagery for satellite-based oil spill detection. Frequently oil spills are small in size and short in duration, but there have been times when events have continued to persist for weeks, months and even years. Located approximately 10 miles southeast of the Mississippi River Delta in the Gulf of Mexico resides the former location of the now destroyed Taylor Energy oil rig. This platform was damaged in 2004 during the passage of Hurricane Ivan and since then small surface oil slicks and sheens have been observed in satellite imagery originated from the site. Surface slicks or sheens associated with this source are frequently detected in satellite imagery analysis (&amp;gt;110 images since August 2010). Slicks are typically aligned along the isobaths (southwest to northeast) with typical dimensions of 0.5–2 km by 10–30 km varying with wind conditions (i.e. longer slicks tend to be more visible in satellite under winds generally &amp;lt;10 kts). The distribution of slick detection has two peaks, one in May with secondary maxima in September. This is primarily due to the advantage of having sun-glint, which enhances the ability for surface slick detection during the months from April to October in the Gulf of Mexico. On several occasions overflight reports have confirmed the presence of oil sheens at this location, matching very well with satellite analyzed maps. Geographic Information System (GIS) shapefiles and Keyhole Markup Language (KML) files depicting the location of the observed oil from satellites are disseminated to NOAA's National Ocean Service (NOS) Emergency Response Division (ERD), U.S. Coast Guard, Department of Homeland Security, Bureau of Ocean Energy Management and several local and state agencies. NOS/ERD uses these analyses in their surface oil trajectory models in an effort to improve the model's performance.

ABSTRACT During the height of historic flooding from Hurricane Harvey's rainfall, a rupture occurred in a 16-inch, 80 psia (65 psig) natural gas pipeline crossing the Neches River east of Beaumont, Texas. Over the preceding five days, Hurricane Harvey stalled over the area, generating rainfall totals between 35 and 60 inches. The storm broke the record for rainfall totals in the U.S., with 60.58 inches reported in Nederland, Texas and 60.54 inches near Groves, Texas. The Neches River was in extreme flood conditions, cresting the day after the pipeline rupture at a historic high of 19.59 feet (nearly 10 feet above major flood stage and nearly 7 feet above the former historic record from 1994). At the request of the U.S. Coast Guard Marine Safety Unit (MSU) Port Arthur, NOAA's Emergency Response Division provided scientific support for the incident including on-scene support from the NOAA Scientific Support Coordinator (pre-deployed in Port Arthur, Texas for disaster response) as well as technical assistance from the NOAA Scientific Support Team in Seattle and Baton Rouge. Products and support provided by NOAA included air hazard modeling using ALOHA (Areal Locations of Hazardous Atmospheres) as well as the overall hazards assessment. ALOHA modeling indicated that several significant ignition sources were located within the specific threat zone identified. However, no ignition occurred and no injury or further damage resulted from the release. This incident highlights the advantages and limitations of using ALOHA to model a subsurface natural gas release from a large underwater pipeline provided in the context of an ongoing response to historic flooding and high intensity search and rescue and emergency port operations resulting from a natural disaster.

ABSTRACT In this paper, we demonstrate the use of a new operational, unstructured-grid hydrodynamic model within the oil spill trajectory model GNOME (the General NOAA Operational Modeling Environment) to examine the transport of surface oil from a known source approximately 10 miles offshore of the Mississippi River Delta. At this location, a cluster of wells and/or contaminated sediments have been persistently leaking small amounts of oil since they were damaged in 2004. Slicks associated with this source are frequently detected in satellite imagery analysis, which indicates they are often oriented in the along isobath direction with typical dimensions of 0.5–2 km by 10–30 km varying with wind conditions. The Northern Gulf of Mexico Operation Forecast System (NGOFS) has recently been deployed by NOAA and includes this region. The underlying hydrodynamic model is an unstructured grid finite-volume model which allows variable grid resolution ranging from 10 km offshore to ~600 m near the coastline. Unstructured grid models are ideally suited for coastal areas as they allow flexible resolution to resolve complex bathymetry and coastlines. However, large model domains combined with high grid resolution can provide a challenge for operational trajectory models as sub-setting the model grid is not as straightforward as in the structured grid case. The utility of any hydrodynamic model for emergency response depends not only on its accuracy, but on the trajectory modeler's ability to access and use the information in a timely manner. As part of this study, we have developed tools to allow the NGOFS results (in addition to other unstructured grid models) to be readily available to GNOME users. Using output from the NGOFS in GNOME, a one year modeled simulation was run in which surface particles were released continuously from the location of the damaged wells. Predicted trajectories of modeled particles less than ~24-hours in age compare qualitatively well with the satellite observations.

A recent focus of marine debris research is to identify and target pollution sources so that solutions to the problem can be developed through policy and education. This project hopes to expand upon this focus by also examining public attitudes toward marine debris and using this information with cleanup data to systematically implement and test community mitigation techniques. One objective of this research was to examine current community marine debris cleanup and reduction efforts in New Hampshire (as a baseline) by analyzing beach cleanup data. Marine debris monitoring data has been collected by the Blue Ocean Society for Marine Conservation over the past four years. Cleanups have been conducted by the organization at fourteen different New Hampshire sites during this time. A data summary was composed for each which included a compilation of data from 2002 through 2006. Additionally, marine debris composition (e.g., land-based, ocean-based, etc.) was mapped in Geographic Information Systems (GIS) along with significant influencing factors. Besides mapping the marine debris quantity and composition per collection site, the powerful component to GIS is that any potential influencing data available can be tied to all of these locations. The full integration of all available data will allow the evaluation of trends and correlations in marine debris data with myriad potential influences. Additionally, because the amount of ocean-based debris found on the NH Seacoast is greater than land-based debris for the majority of beaches, a new outreach program targeting commercial and recreation fisherman is being implemented. Finally, new technologies for monitoring, specifically, using personal digital assistants (PDAs) with integrated GPS systems to collect marine debris or oiled shoreline data have been evaluated. This technology could be transferred to other applications for monitoring marine pollution.