Evaluation of Polycyclic Aromatic Hydrocarbon Pollution From the HMS Royal Oak Shipwreck and Effects on Sediment Microbial Community Structure

Despite many shipwrecks containing oil there is a paucity of studies investigating their impact on surrounding environments. This study evaluates any potential effect the World War II shipwreck HMS Royal Oak is having on surrounding benthic sediments in Scapa Flow, Scotland. HMS (Her Majesty’s Ship) Royal Oak sank in 1939, subsequently leaked oil in the 1960s and 1990s, and is estimated to still hold 697 tonnes of fuel oil. In this study, sediments were analysed, over a 17.5 cm depth profile, along a 50–950 m cruciform transect away from the shipwreck. Analysis of polycyclic aromatic hydrocarbons (PAHs) revealed low concentrations (205.91 ± 50.15 μg kg‾¹ of dry sediment), which did not significantly differ with either distance from the shipwreck or sediment depth. PAH concentrations were well below the effects-range low (ERL) for the OSPAR (Oslo/Paris convention for the Protection of the Marine Environment of the North-East Atlantic) maritime area. The average Pyrogenic Index, in sediments around HMS Royal Oak, was 1.06 (±0.34), indicating PAHs were pyrogenic rather than petrogenic. Moreover, analysis of sediment microbiomes revealed no significant differences in bacterial community structure with distance from the shipwreck, with extremely low levels of obligate hydrocarbonoclastic bacteria (OHCB; 0.21% ± 0.54%). Both lines of evidence suggest that sampled sediments are not currently being impacted by petrogenic hydrocarbons and show no long-term impact by previous oil-spills from HMS Royal Oa

A spatially resolved pressure-based approach to evaluate combined effects of human activities and management in marine ecosystems

Our oceans are heavily utilized by a wide variety of human activities that exert pressures which negatively impact marine ecosystems, occasionally leading to unsustainable rates of exploitation. A linkage framework approach can be used to make independent associations between sectors, activities, and the pressures they introduce. However, in reality, many different sectors and their associated activities overlap in time and space, potentially changing the severity of their impact as pressures combine, and undermine the efforts of environmental managers to mitigate the harmful effects of those activities. Here, we present a spatially resolved approach to assess the potential for combined effects using a linkage framework assessment. Using illustrative examples from the Northeast Atlantic, we show the likelihood of changes in pressure severity as a result of multiple overlapping activities.Management options to limit pressure introduction are explored and their benefit—measured as a reduction in the area of seabed impacted—assessed. In its simplest form, the approach can be used to develop potential precautionary management options in areas where data availability is poor and more comprehensive management measures where data are more widely available

Ticking ecological time bombs:Risk characterisation and management of oil polluting World War II shipwrecks in the Pacific Ocean

The Second World War in the Pacific has left a legacy of over 3800 wrecks on the ocean floor. These wrecks contain thousands of tons of oil and pose a risk to the marine environment. Estimates of current corrosion rates show many wrecks are at risk of structural collapse. However, the scale of threat posed by potentially polluting wrecks (PPW) to coastal ecosystems in the Pacific is largely unknown, due to the lack of data to inform risk. This paper presents a strategy aimed to prioritise, manage, and mitigate negative effects of oil spills posed by PPW in the Pacific, using an example in Chuuk Lagoon. Wrecks are assessed and prioritised by means of risk characterisation. Wrecks are surveyed using photogrammetry to assess hull integrity. Finally, recommendations are made for the production of bespoke management plans and risk reduction strategies that work towards safeguarding marine ecosystems and the livelihoods of coastal communities

Population genetics provides new insights into biomarker prevalence in dab ( Limanda limanda L.): a key marine biomonitoring species

Bioindicators are species for which some quantifiable aspect of its biology, a biomarker, is assumed to be sensitive to ecosystem health. However, there is frequently a lack of information on the underlying genetic and environmental drivers shaping the spatiotemporal variance in prevalence of the biomarkers employed. Here, we explore the relative role of potential variables influencing the spatiotemporal prevalence of biomarkers in dab, Limanda limanda, a species used as a bioindicator of marine contaminants. Firstly, the spatiotemporal genetic structure of dab around UK waters (39 samples across 15 sites for four years: 2005–2008) is evaluated with 16 microsatellites. Two temporally stable groups are identified corresponding to the North and Irish Seas (average between basin inline image = 0.007; inline image = 0.022). Secondly, we examine the association between biomarker prevalence and several variables, including genetic structuring, age and contaminant exposure. Genetic structure had significant interactive effects, together with age and some contaminants, in the prevalence of some of the biomarkers considered, namely hyperpigmentation and liver lesions. The integration of these data sets enhanced our understanding of the relationship between biomarker prevalence, exposure to contaminants and population-specific response, thereby yielding more informative predictive models of response and prospects for environmental remediation

Data from: Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species

Bioindicators are species for which some quantifiable aspect of its biology, a biomarker, is assumed to be sensitive to ecosystem health. However, there is frequently a lack of information on the underlying genetic and environmental drivers shaping the spatiotemporal variance in prevalence of the biomarkers employed. Here, we explore the relative role of potential variables influencing the spatiotemporal prevalence of biomarkers in dab, Limanda limanda, a species used as a bioindicator of marine contaminants. Firstly, the spatiotemporal genetic structure of dab around UK waters (39 samples across 15 sites for four years: 2005-2008) is evaluated with 16 microsatellites. Two temporally stable groups are identified corresponding to the North and Irish Seas (average between basin G’ST =0.007; G’’ST=0.022). Secondly, we examine the association among biomarker prevalence and several variables, including genetic structuring, age, and contaminant exposure. Genetic structure had significant interactive effects, together with age and some contaminants, in the prevalence of some of the biomarkers considered, namely hyperpigmentation and liver lesions. The integration of these datasets enhanced our understanding of the relationship between biomarker prevalence, exposure to contaminants, and population-specific response, thereby yielding more informative predictive models of response and prospects for environmental remediation

Dab population genetics raw data and biomarker modelling infiles

This is a file containing raw information on dab, Limanda limanda, population genetic structure, contaminant exposure, age and biomarker prevalence around the British Isles (dab.popgen.biomonitoring.xlsx). Dab.genotypes: microsatellite allele size data in GenAlex format. Further information on sex, age, weight, length, inbreeding coefficients (IR and hL values) and latitude and longitude is also included where available. Pop.models: Information of sample-average age, contaminant exposure (liver concentration), prevalence (%) of external biomarkers (HYP, LY, U, EP), proxies of populations structure (ca.axis1 and ca.axis3) and sample level genetic diversity (Ho) and inbreeding coefficient (Fis). Ind.models: Individual information for 451 individuals on population membership (ca.axis1, ca.axis3), inbreeding coefficients (IR, hL), length, weight, age, sex, age-site average estimated exposure to contaminant, presence or absence of external biomarkers, presence or absence of 32 internal biomarkers classified by categories (CAT 1: healthy to CAT 5:malignant neoplasms) and liver status (lv.sts: highest category of liver damage present in an individual). For any questions in the data please contact Niklas Tysklind ([email protected])