Impacts of Oil Spills on Arctic Marine Ecosystems: A Quantitative and Probabilistic Risk Assessment Perspective

Helle, Inari; Mäkinen, Jussi; Nevalainen, Maisa Katariina; Afenyo, Mawuli; Vanhatalo, Jarno

doi:10.1021/acs.est.9b07086

Cited by 57 publications

(26 citation statements)

References 44 publications

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“…Given their modular structure, BNs can be used to support integrative modeling and can accommodate inputs from multiple sources, including simulations, empirical data, and expert knowledge. 28 , 29 These properties make BNs well-suited for data-poor cases. 28 …”

Section: Introductionmentioning

confidence: 99%

Causal Approach to Determining the Environmental Risks of Seabed Mining

Kaikkonen

Helle

Kostamo

et al. 2021

Environ. Sci. Technol.

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Mineral deposits containing commercially exploitable metals are of interest for seabed mineral extraction in both the deep sea and shallow sea areas. However, the development of seafloor mining is underpinned by high uncertainties on the implementation of the activities and their consequences for the environment. To avoid unbridled expansion of maritime activities, the environmental risks of new types of activities should be carefully evaluated prior to permitting them, yet observational data on the impacts is mostly missing. Here, we examine the environmental risks of seabed mining using a causal, probabilistic network approach. Drawing on a series of expert interviews, we outline the cause-effect pathways related to seabed mining activities to inform quantitative risk assessments. The approach consists of (1) iterative model building with experts to identify the causal connections between seabed mining activities and the affected ecosystem components and (2) quantitative probabilistic modeling. We demonstrate the approach in the Baltic Sea, where seabed mining been has tested and the ecosystem is well studied. The model is used to provide estimates of mortality of benthic fauna under alternative mining scenarios, offering a quantitative means to highlight the uncertainties around the impacts of mining. We further outline requirements for operationalizing quantitative risk assessments in data-poor cases, highlighting the importance of a predictive approach to risk identification. The model can be used to support permitting processes by providing a more comprehensive description of the potential environmental impacts of seabed resource use, allowing iterative updating of the model as new information becomes available.

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Section: Introductionmentioning

confidence: 99%

Causal Approach to Determining the Environmental Risks of Seabed Mining

Kaikkonen

Helle

Kostamo

et al. 2021

Environ. Sci. Technol.

Self Cite

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“…Oil spills in the Arctic will affect the entire food web. Model studies suggest, for example, that oil spills can expose large fractions of populations of polar bears to released oil in the Chukchi Sea (Wilson et al 2018) and causes different risks to other animals, like ringed seals and walrus, based on an oil spill risk assessment for the Kara Sea (Helle et al 2020). Arctic sea birds are also sensitive to oil pollution as demonstrated in the high mortality of guillemots and little auks off Newfoundland caused by ship-source oil pollution (Frederiksen et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Crude oil exposure reduces ice algal growth in a sea-ice mesocosm experiment

et al. 2021

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Oil production in Arctic ice-covered areas poses a risk for pollution of the ecosystem including that within the brine channel network of sea ice. Sea-ice autotrophs contribute substantially to Arctic primary production, but are inherently difficult to test for oil exposure responses in situ. This study had two objectives, first, we developed a suitable lab-based mesocosm system, second, we tested oil effects on sea-ice algae. Specifically, we investigated if Alaska North Slope crude oil exposure reduces ice algal abundance, biomass and concentration of extracellular polymeric substances (EPS) using indoor ice tanks over a 10-day exposure period. Six tanks in one cold room were used in pairs for the following treatments: (1) control, (2) oil release as a layer under ice and (3) release of dispersed oil. All tanks were inoculated with sea-ice microbial communities collected from Utqiaġvik, Alaska. After 10 days of exposure, the abundance of algae, dominated by the pennate diatom genus Nitzschia, and the concentrations of EPS and chlorophyll a were significantly lower in the oiled treatments compared to the control. We suggest light attenuation by the oil, reduced algal mobility, and oil toxicity as causes for this reduction. Observed changes in cell fluorescence characteristics based on DNA staining could be linked to the oil exposure and could provide a new tool for assessment of toxicity in microalgae.

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“…Spilled oil in the Arctic environment can have negative economic, cultural, and ecological impacts, including disturbances to sensitive species, damage to sensitive coastal and marine habitats, and it can impose stressors on coastal communities, by threatening their subsistence-based food supplies and culture. These impacts may be long lasting because oil is more persistent in extremely cold environments due to the decreased rate of natural weathering (e.g., evaporation, biodegradation) [6]. Some components of spilled oil, such as polycyclic aromatic hydrocarbons, may also contribute to persistent pollution that negatively impacts marine organisms [7].…”

Section: Introductionmentioning

confidence: 99%

Responder Needs Addressed by Arctic Maritime Oil Spill Modeling

Manning

Verfaillie

Barker

et al. 2021

JMSE

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There is a greater probability of more frequent and/or larger oil spills in the Arctic region due to increased maritime shipping and natural resource development. Accordingly, there is an increasing need for effective spilled-oil computer modeling to help emergency oil spill response decision makers, especially in waters where sea ice is present. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the U.S. Coast Guard Federal On-Scene Coordinator (FOSC) during oil spill response. OR&R’s modeling products must provide adequate spill trajectory predictions so that response efforts minimize economic, cultural, and ecologic impacts, including those to species, habitats, and food supplies. The Coastal Response Research Center is conducting a project entitled Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward, in conjunction with modelers, responders, and researchers. A goal of the project is to prioritize new investments in model and tool development to improve response effectiveness in the Arctic. The project delineated FOSC needs during Arctic maritime spill response and provided a solution communicating sources of uncertainty in model outputs using a Confidence Estimates of Oil Model Inputs and Outputs (CEOMIO) table. The table shows the level of confidence (high, medium, low) in a model’s trajectory prediction over scenario-specific time intervals and the contribution of different component inputs (e.g., temperature, wind, ice) to that result.

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Impacts of Oil Spills on Arctic Marine Ecosystems: A Quantitative and Probabilistic Risk Assessment Perspective

Cited by 57 publications

References 44 publications

Causal Approach to Determining the Environmental Risks of Seabed Mining

Causal Approach to Determining the Environmental Risks of Seabed Mining

Crude oil exposure reduces ice algal growth in a sea-ice mesocosm experiment

Responder Needs Addressed by Arctic Maritime Oil Spill Modeling

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