Small Oil Spill Research Articles

Combined use of SAR images and numerical simulations to identify the source and trajectories of oil spills in coastal environments

Remote sensing data and numerical simulation are important tools to rebuild any oil spill accident letting to identify its source and trajectory. Through these tools was identified an oil spill that affected Oaxacan coast in October 2022. The SAR images were processed with a standard method included in SNAP software, and the numerical simulation was made using Lagrangian transport model included in GNOME software. With the combining of these tools was possible to discriminate the look-alikes from true oil slicks; which are the main issue when satellite images are used. Obtained results showed that 4.3m3 of crude oil were released into the ocean from a punctual point of oil pollution. This oil spill was classified such as a small oil spill. The marine currents and weathering processes were the main drivers that controlled the crude oil displacement and its dispersion. It was estimated in GNOME that 1.6 m3 of crude oil was floating on the sea (37.2 %), 2.4 m3 was evaporated into the atmosphere (55.8 %) and 0.3 m3 reached the coast of Oaxaca (7 %). This event affected 82 km of coastline, but the most important touristic areas as well as turtle nesting zones were not affected by this small crude oil spill. Results indicated that the marine-gas-pump number 3 in Salina Cruz, Oaxaca, is a punctual point of oil pollution in the Southern Mexican Pacific Ocean. Further work is needed to assess the economic and ecological damage to Oaxacan coast caused by this small oil spill.

Detection of oil spills based on gray level co-occurrence matrix and support vector machine

Accurate reconnaissance of Marine oil spill is very important for emergency management of Marine oil spill accidents. Unmanned aerial vehicles (UAV) is a suitable carrier for offshore oil spill reconnaissance because of its fast deployment speed and low cost. Aiming at the identification accuracy of small oil spill accident in offshore port area and the problem of day and night reconnaissance, this study takes thermal infrared remote sensing images of oil leakage captured by UAV as the research object and proposes an oil spill detection method based on a Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM) method. Firstly, the extraction steps of image GLCM feature and the basic principle of SVM classification are studied. Then, the thermal infrared image data collected by UAV is preprocessed, including image filtering, clipping and rotation, and the sample database is generated. Subsequently, GLCM features of the samples were extracted, and the energy and correlation in GLCM were selected as classification features and sent to the SVM classifier to complete the oil spill detection of real-time thermal infrared images. The experimental results show that, compared with Classification and Regression Tree algorithm (CART) and Random Forests of Decision Trees (RF) algorithm, the detection accuracy of the method proposed in this paper reaches 95%, which were 10 and 2 percentage points higher than them respectively. The proposed method in this paper has fast recognition speed and high accuracy, and can provide all-weather recognition of oil spills for the detection of small oil spills in the offshore port area.

Potential changes in the recreational use value for Coastal Bay of Plenty, New Zealand due to oil spills: A combined approach of the travel cost and contingent behaviour methods

New Zealand is an island nation with an extensive coastline. Subsequently, marine water-based recreational activities are important to New Zealanders and bring income to coastal communities. Pollution events, such as marine oil spills, are incidents that can negatively impact the water quality and the recreational use of the New Zealand coastline. To improve the information base for informing maritime policies, and estimate the likely impacts of an oil spill to coastal areas of New Zealand, this study examined the potential impacts on recreational value with three oil spill scenarios at a stretch of beach in the Bay of Plenty, New Zealand. Using a combined approach of travel cost and contingent behaviour methods revealed that the consumer surplus of a visit to the beach by domestic visitors was approximately NZD 121 per person. The approach allowed assessment of the likely use of the beach under differing potential oil spill impacts restricting various marine-based recreational activities. A small oil spill with occasional traces of oil but no restrictions on recreational activities decreased the value to NZD 29.74. A moderate oil spill restricting only fishing, surfing, and swimming decreased the value to NZD 9.83. A severe oil spill stopping all recreational use decreased the value to NZD 4.30. When these recreational losses are combined with known clean-up costs and direct use losses in fisheries and tourism, the total direct use loss to a coastal area like this stretch of beach in the Bay of Plenty, where the MV Rena spill occurred in 2011, could be over NZD (2011) 111 million, of which NZD (2011) 66.14 million is recreational visitor use alone. This estimate allows consideration for the entire direct use values lost that an oil spill could have to a coastal community and to New Zealand as a whole.

Evaluation of machine learning techniques to select marine oil spill response methods under small-sized dataset conditions

Oil spill incidents can significantly impact marine ecosystems in Arctic/subarctic areas. Low biodegradation rate, harsh environments, remoteness, and lack of sufficient response infrastructure make those cold waters more susceptible to the impacts of oil spills. A major challenge in Arctic/subarctic areas is to timely select suitable oil spill response methods (OSRMs), concerning the process complexity and insufficient data for decision analysis. In this study, we used various regression-based machine learning techniques, including artificial neural networks (ANNs), Gaussian process regression (GPR), and support vector regression, to develop decision-support models for OSRM selection. Using a small hypothetical oil spill dataset, the modelling performance was thoroughly compared to find techniques working well under data constraints. The regression-based machine learning models were also compared with integrated and optimized fuzzy decision trees models (OFDTs) previously developed by the authors. OFDTs and GPR outperformed other techniques considering prediction power (> 30 % accuracy enhancement). Also, the use of the Bayesian regularization algorithm enhanced the performance of ANNs by reducing their sensitivity to the size of the training dataset (e.g., 29 % accuracy enhancement compared to an unregularized ANN).

MAPPING OIL SPILLS ON SEA SURFACE FROM SENTINEL 2 IMAGES USING PRINCIPAL COMPONENTS AND CATEGORICAL BOOSTING

Abstract. A large oil spill in Iloilo Straight that occurred on July 3, 2020, as well as a possible deliberate, small but frequent oil spill and surfactant contamination in Manila Bay, were mapped. The method employs the Sentinel 2-1C image, which is transformed into principal components to reveal the presence of oil spills and possibly surfactants. Additionally, a gradient boosting algorithm was trained to discriminate between pixels that were contaminated with oil and those that were not. The multi-band image with three principal components with a 99% cumulative explained variance ratio highlights the occurrence of an oil spill in Iloilo Straight. Further, the classified image produced by pixel-based classification clearly distinguishes between water and oil pixels in the said area. The methodology was applied to a Sentinel 2-1C image of Manila Bay, with pixels observed/identified as oil and classified as well. The highest density of supposedly oil-contaminated pixels (large or small but frequent) was observed on the eastern side of Manila Bay (Bataan). While there were no documented oil spills concurrent to the satellite image used, historical reports on the area indicate that the likelihood of an oil spill is extremely high due to the massive amount of shipping activity. Pixels supposedly contaminated by oil spills also occur in areas near ports where oil spills could occur as a result of ship operations. Pixels with the same properties as oil contamination are also visible in areas adjacent to fishponds and aquaculture, where phytoplankton and fish contribute to surfactant contamination.

Terrestrial oil spill mapping using satellite earth observation and machine learning: A case study in South Sudan

Terrestrial oil spills are a major threat to environmental and human well-being. Rapid, accurate, and remote spatial assessment of oil contamination is critical to implementing countermeasures that prevent potentially lasting ecological damage and irreversible harm to local communities. Satellite remote sensing has been used to support such assessments in inaccessible regions, although mapping small terrestrial oil spills is challenging – partly due to the pixel size of remote sensing systems, but also due to the distinguishability of small oil spill areas from other land cover types. We assessed the usability of freely available Sentinel satellite images to map terrestrial oil spills with machine learning algorithms. Using two test sites in South Sudan, we demonstrated that information from the Sentinel-1 and -2 instruments can be used to map oil spills with more than 90 % classification accuracy. Classification accuracy was significantly increased (>95 %) with the addition of multi-temporal information and spatial predictor variables that quantify proximity to oil production infrastructure such as pipelines and oil pads. The mapping of terrestrial oil spills with freely available Sentinel satellite images may thus represent an accurate and efficient means for the regular monitoring of oil-impacted areas.

Oil Spill Detection with Multiscale Conditional Adversarial Networks with Small-Data Training

We investigate the problem of training an oil spill detection model with small data. Most existing machine-learning-based oil spill detection models rely heavily on big training data. However, big amounts of oil spill observation data are difficult to access in practice. To address this limitation, we developed a multiscale conditional adversarial network (MCAN) consisting of a series of adversarial networks at multiple scales. The adversarial network at each scale consists of a generator and a discriminator. The generator aims at producing an oil spill detection map as authentically as possible. The discriminator tries its best to distinguish the generated detection map from the reference data. The training procedure of MCAN commences at the coarsest scale and operates in a coarse-to-fine fashion. The multiscale architecture comprehensively captures both global and local oil spill characteristics, and the adversarial training enhances the model’s representational power via the generated data. These properties empower the MCAN with the capability of learning with small oil spill observation data. Empirical evaluations validate that our MCAN trained with four oil spill observation images accurately detects oil spills in new images.

Modelling the Dynamics of a Facility for Understanding Critical Resource Use in Oiled Seabird Rehabilitation

Abstract The rehabilitation of oiled birds in a large scale event can be a challenging undertaking, especially because of emergency dynamics which make it difficult to predict when, and how many animals will be arriving at a facility from day to day. Scenarios from past spill events demonstrate that even a small oil spill in a vulnerable area or season can produce hundreds of live oiled birds washing ashore, every day, for many days or weeks in a row. Any facility (permanent or temporary) or a network of facilities near the incident site would have difficulty to admit and process streams of hundreds of birds per day while continuing to try and guarantee mimumum care standards in every stage of the rehabilitation process. Guaranteeing these minimum standards during the whole of the response needs a thorough understanding of the many functional relationships between available resources (people, equipment, consumables, foods etc), the quality and size of the facility set-up, and the maximum number of animals that each department in the facility can treat per time unit, according to these standards. The mathematical model “Birds in Rehab (BiR version 1.0)” was developed between 2012 and 2015 as a simulation tool for facility managers to understand the dynamics of animals of one species (guillemot/murre) flowing through a facility according to realistic decision making of experts on the work floor. Recently, thanks to funds from the Netherlands authorities, the tool was updated (current version: BiR 2.2) in order to be able to simulate multiple species that are admitted to a facility. Different species need different resources, which have been included in the updated model. A new functionality is a calculator, which runs a given scenario in a few seconds, and allow the user to compare the results (survival, release of species) of alternative treatment strategies. This paper will describe the BiR 2.2 model and its applications. One of the useful features is that it provides quantitative overviews of how many animals are in care at any time, and in which phase of treatment they are. This allows a useful assessment of the feasibility of such numbers in relation to available resources, space, and other natural limits of the facility that is simulated. The model can help to explore the capacity limits of a given facility setup and see where bottlenecks may appear. The new version will be used for training and planning purposes, and is guaranteed to assist experts who are interested in deepening their insights in dynamic processes on the work floor of a facility that are impossible to exercise and in reality hard to unravel.

Diagnosing Insensitivity to Scope in Contingent Valuation

Sensitivity to scope is considered a desirable property of contingent valuation studies and often treated as a necessary condition for validity. We first provide an overview of scope insensitivity explanations put forth in the environmental valuation literature. Then we analyze data from a contingent valuation survey eliciting willingness-to-pay to prevent oil spills of four different magnitudes in Arctic Norway. In the baseline analysis, the scope inference is ambiguous. There is only statistical difference in willingness to pay to avoid a very large versus small oil spill (NOK 1869 and NOK 1086, respectively). However, further explorations show that several confounding factors suggested in the literature influence the scope inference. The scope sensitivity improves when we control for subjective probabilities of amenity provision, exclude respondents based on the debriefing questions, take into consideration the sample sizes, and impose diminishing marginal utility. Overall, the analysis supports an emerging view in the contingent valuation literature suggesting that statistical scope insensitivity is not a sufficient reason for deeming a study invalid.

Natural attenuation of spilled crude oil by cold-adapted soil bacterial communities at a decommissioned High Arctic oil well site

Romulus C-42 is a decommissioned oil well on Ellesmere Island in the Canadian High Arctic, and is the northernmost well to have produced oil and gas anywhere in the world. The remote site has been untouched since a crude oil spill in 1972, offering a rare opportunity to examine natural attenuation in Arctic soils >40 years after a pollution event. Bacterial community composition in crude oil contaminated soils was significantly different from adjacent background soils. Two members of the genus Rhodanobacter (Alphaproteobacteria) were found consistently in contaminated soils, whereas two members of the genus Sphingomonas (Gammaproteobacteria) appeared opposite to each other, one consistently within the oil contaminated soil and the other consistently in non-oil contaminated soils. GC of soil hydrocarbon extracts revealed moderate levels of biodegradation relative to the original oil produced in 1972. Despite conditions permissive for bacterial activity (>0 °C) being limited to only a few months each year, natural attenuation by cold adapted soil microbial communities has taken place since the oil spill over 40 years ago. Rhodanobacter and Sphingomonas lineages are associated with contaminated and baseline conditions in this extreme environment, revealing the utility of bacterial diversity measurements for assessing long-term responses of Arctic soils to pollution. Originality-significance statementRomulus C-42, the northernmost onshore drilling well in the world, was decommissioned following a small crude oil spill in 1972. Soil bacterial diversity profiles obtained >40 years later revealed significant differences in oil contaminated soils relative to adjacent non-oil contaminated background soils, consistent with evidence for moderate biodegradation of spilled crude oil having taken place since 1972. The results indicate that microbial diversity profiling is an effective tool for assessing natural attenuation in remote High Arctic soils with a history of oil pollution.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

Oil Pollution in the Marine Environment I: Inputs, Big Spills, Small Spills, and Dribbles

The BP Deepwater Horizon Macondo Oil Well spill in the Gulf of Mexico three years ago renewed and reinforced concerns about oil pollution in the marine environment. This article is intended to prov...

Integrated assessment of estuarine sediment quality based on a multi-biomarker approach in the bivalve Scrobicularia plana

The bivalve Scrobicularia plana has been proposed as a sentinel species for the assessment of estuarine sediment quality. The aim of this study was to test the responsiveness of a set of biomarkers in bivalves originating from a moderately contaminated site (Loire estuary, France) and a comparatively cleaner site (Bay of Bourgneuf, France) used as reference. Temporal fluctuations were examined in animals collected on eight occasions from March 2008 to October 2009 for the determination of biochemical (MTs, GST, AChE), physiological (energy reserves as glycogen and lipids, condition, hepato-somatic and gonado-somatic indices), and behavioural biomarkers (burrowing). Metals in clams were examined with the aim of understanding the variations in MT concentrations. The current findings indicate that among biochemical markers MTs must be used in a precautionary fashion, and comparison with a reference site remains indispensable together with an appreciation of any salinity effects. Clearer responses were obtained for GST activity which contributes to defence against organic compounds. However, any such defence was not sufficient to ensure total protection since a number of impairments were observed at the individual level (burrowing behaviour, condition index, gonado-somatic index). The integrated biomarker response (IBR) illustrated higher levels of stress in clams collected from the Loire estuary compared to those gathered from the reference site at most of the sampling periods. The interpretation of responses involved in the cascade of energetic events (from available food, digestive enzyme activities, energy reserves to condition and reproductive status) is complex but did reveal disturbances in the Loire estuary which is far from being the most contaminated estuary in France and over the world. However, no links can be established between effects at individual and supra-individual levels in organisms in the Loire estuary, even in the case of a small oil spill which occurred at the beginning of this study.

Intersite variations of a battery of biomarkers at different levels of biological organisation in the estuarine endobenthic worm Nereis diversicolor (Polychaeta, Nereididae)

The ragworm Nereis diversicolor has been proposed as a sentinel species for the assessment of estuarine sediment quality. The aim of this study was to test the responsiveness of the worms using a battery of biomarkers in specimens from a moderately contaminated site (Loire estuary, Fr.) and a comparatively cleaner site (Bay of Bourgneuf, Fr.) as a reference site. Ragworms were collected on 7 occasions from April 2008 to October 2009 for the determination of biochemical (GST, AChE, digestive enzymes), physiological (energy reserves (glycogen, lipids and proteins), relationship between length and weight), and behavioural (feeding and burrowing) biomarkers. The biomarker responses were tentatively interpreted in terms of the concept of cascading events potentially responsible for local depletion/extinction of populations submitted to chemical stress. Impairments of AChE and amylase activities, feeding rate, energy reserve concentrations (glycogen and lipids), and the relationship between length and weight showed up differences between the reference site and the Loire estuary despite the latter being far from the most contaminated estuary in France or internationally. However, no links could be established in the Loire estuary ragworms between effects at infra-individual and individual levels, nor with worm population density, even though a small oil spill had occurred in the Loire estuary only one month before the beginning of sampling.

Biochemical, physiological and behavioural markers in the endobenthic bivalve Scrobicularia plana as tools for the assessment of estuarine sediment quality

The aim of this study was to link the responses at different levels of biological organisation of the endobenthic bivalve Scrobicularia plana differentially exposed to anthropogenic pressure. Clams were collected in April 2008 from three estuaries along a pollution gradient (Goyen<Loire<Seine). Biomarkers of defence (metallothionein concentration and glutathione- S-transferase activity) were activated in the Loire and the Seine. Biomarkers of damage revealed neurotoxicity (decreased AChE activity) and impairment of digestive enzyme activities (cellulase or amylase) in these estuaries. The highest lactate dehydrogenase activity was registered in the Loire estuary, in parallel with enhanced levels of vanadium (a metal present in petroleum), likely as a consequence of a small oil spill that occurred one month before the sampling collection. Physiological biomarkers (energy reserves as glycogen, lipids and proteins, condition and gonado-somatic indices) showed a few intersite differences. However, the median size was significantly lower in clams exposed to direct (chemicals) or indirect (available food) effects in the most contaminated site. Burrowing behaviour was disturbed in clams from both of the Loire and Seine estuaries, a response probably due to physiological impairment rather than to avoidance of contaminated sediment. The activation of defence mechanisms towards metals (metallothionein) and other classes of contaminants (the biotransformation enzyme glutathione- S-transferase) do not ensure a total protection since a number of impairments were observed at the infra-organismal (AChE and digestive enzyme activities) and individual (burrowing behaviour) levels in relation to the degree of anthropogenic pressure. However, even in the most contaminated estuary (Seine), historical records do not show a consistent decrease of S. plana populations.

Assessment of the health status of populations of the ragworm Nereis diversicolor using biomarkers at different levels of biological organisation

We compared behavioural (burrowing speed), biochemical (acetylcholinesterase (AChE) inhibition, activities of digestive enzymes) and physiological (feeding and egestion rates, condition) responses in Nereis diversicolor originating from a multipolluted estuary (Loire estuary) and a relatively clean site (Bay of Bourgneuf) on 3 occasions during spring 2008. Significant inhibi- tion of AChE and digestive enzymes (amylase and carboxymethylcellulase) activities were recorded in individuals from the Loire estuary compared to the reference site. At the individual level no signif- icant intersite differences in burrowing speed were observed when ragworms were exposed to their sediment of origin. No link between AChE activity and burrowing behaviour was found in worms from either site. Cross-tests revealed that behavioural disturbances in locomotion were not due to neurological dysfunction but to avoidance of contaminated sediments. Feeding and egestion rates were depressed significantly in worms originating from the Loire estuary compared to the reference site. These behavioural impairments were accompanied by changes in digestive enzyme activities, which can explain the generally poorer condition of ragworms from the Loire estuary. Temporal changes in responses reported in the present study underline the importance of the fluctuation of environmental factors and thus the need for more than one sampling series to assess the health sta- tus of a given site. Disturbances at the different levels of biological organisation are likely explained by environmental contamination either chronic in the Loire estuary or the result of a small oil spill.

TIER-2 IN EAST ASIA1: CHALLENGES AND ANSWERS

ABSTRACT On numerous occasions, East Asia has been affected by marine oil spills incidents, originating from tankers and other types of ships. Important spills incidents that involved the IOPC Funds in the last decade (e.g. Nakhodka, Evoikos, Natuna Sea and Solar 1 …) indicate an average occurrence of one spill per year. This figure remains significantly high when considering that some States in the region are still not parties to international compensation regimes. In addition, numerous incidents do not benefit of international media coverage, thus making them often unnoticed. Lower scale incidents (within the range of hundreds of tonnes) occur on a more frequent basis and may appear trivial to respond to. Nevertheless, they represent the same range of difficulties experienced during larger scale incidents (logistics, suitable means to apply dispersants promptly and effectively, availability of temporary storage, lack of plan and training …) In terms of response, the ultimate authority in the coordination of spill response activities is in the hands of Government Agencies. However, the equipment and manpower available belong in various proportions to both Government Agencies and the Oil Industry. The latter operates numerous oil terminals and offshore facilities and is responsible to respond to minor spills defined as Tier 1. In the case of a large spill that exceeds the on-site capability, Tier 3 Cooperatives funded by the vast majority of major companies were created to assist and complement the local response, by offering access to a large range of special supplementary resources and services, such as the Airborne Dispersant Delivery System. Whilst Tiers 1 and 3 are well defined and are respectively synonyms of small and huge oil spill incidents, there is a lack of clarity and consistency in-between, thus making the Tier 2 response difficult to define. This gap that is often underestimated and may result in a preparedness weakness leading to unfortunate consequences. The aim of this paper is to analyse the Tier-2 response requirements and to discuss on the challenges of implementing effective measures in a region where the only imports of crude oil of China have more than doubled in the past five years.

Weathering of a subarctic oil spill over 25 years: the Caribou-Poker Creeks Research Watershed experiment

A small experimental oil spill conducted in an open black spruce forest within the Caribou-Poker Creeks Research Watershed (CPCRW), 48 km north of Fairbanks, AK, in the winter of 1976 was designed to examine the effects of crude oil spills in permafrost terrain. No clean-up was attempted, and the site now provides an opportunity to follow the natural weathering of spilled oil under these conditions. In summer 2001, more than 25 years after the spill, we sampled soils from the spill plot and a nearby reference plot to determine how the oil had weathered, and to assess microbial populations and activity. All samples collected from the oiled plot contained substantial amounts of methylene chloride extractable oil, between 4% and 66% by weight. Using 17α(H)21β(H)hopane as a conserved internal marker within the oil, we determined that while some heavily oiled samples were almost unchanged since the spill, others had lost more than 80% of their initial hydrocarbon. Evaporation, biodegradation and photooxidation all seem to have played important roles in this process, but to varying degrees in different samples. Assays of culturable populations of total heterotrophs and crude oil emulsifiers, and mineralization potentials for hexadecane and phenanthrene, indicate that the microbial population in the oiled soils has remained acclimated to degrade hydrocarbons. We conclude that natural weathering processes will eventually lead to the removal of much of the hydrocarbon from these heavily oiled subarctic soils; however, the combination of low rates of nutrient turnover, a short thaw season, and high hydrocarbon concentrations will result in the persistence of oil residue for many more decades. Finding an environmentally appropriate cleanup technology for sites like this remains an important challenge for future research.

Weathering of an Arctic oil spill over 20 years: the BIOS experiment revisited

A small experimental oil spill was conducted on the northern tip of Baffin Island Nunavut, Canada (72°31 ′ N, 79°50 ′ W) in August 1981, and the natural weathering of the oil has been followed by periodic visits. This paper reports on the chemical composition of oil collected in August 2001. The vast majority of the initial oil has gone, but small patches remain. Some samples remain essentially unaltered despite their 20 years of exposure to the elements, while others show that biodegradation and photooxidation can play important roles in removing the majority of the components of the oil. Using 17α(H)21β(H)hopane as a conserved marker within the oil, we show that the most biodegraded sample has lost more than 87% of the hydrocarbons initially present, while another has lost a substantial proportion of its initial chrysene and alkylated congeners. Potential explanations for the different weathering patterns seen in samples collected from this small site are briefly discussed.

Recovery of benthic communities at Macquarie Island (sub-Antarctic) following a small oil spill

Intertidal communities at Macquarie Island (sub-Antarctic) were re-evaluated seven years after a small oil spill resulting from the grounding of the “Nella Dan”, and six years after the first assessment of biological impact. Sampling was conducted to evaluate community structure in three zones of the exposed rocky shore (upper red, kelp, and lower red) and in samples of Durvillaea antarctica holdfasts. There were no significant differences between the community structure in oiled and control locations in any of the three shore zones, but holdfast macrofaunal communities at oiled sites still showed evidence of impact. Holdfast community-structure in samples from heavily oiled sites showed moderate levels of recovery, with increased abundances of species which were considered sensitive to the oiling in the first post-impact studies and decreased abundances of opportunistic polychaete and oligochaete worms. In contrast, samples collected from the moderately oiled location at Secluded Bay showed little evidence of recovery. Holdfasts at this site were filled with sediment containing traces of diesel oil, and the macrofaunal community was dominated by opportunistic worms. This study clearly indicates that even small incidents of anthropogenic perturbation can have long-lasting consequences for marine communities at Macquarie Island.