Inari Helle

Modeling the effectiveness of oil combating from an ecological perspective--a Bayesian network for the Gulf of Finland; the Baltic Sea.

Maritime traffic poses a major threat to marine ecosystems in the form of oil spills. The Gulf of Finland, the easternmost part of the Baltic Sea, has witnessed a rapid increase in oil transportation during the last 15 years. Should a spill occur, the negative ecological impacts may be reduced by oil combating, the effectiveness of which is, however, strongly dependent on prevailing environmental conditions and available technical resources. This poses increased uncertainty related to ecological consequences of future spills. We developed a probabilistic Bayesian network model that can be used to assess the effectiveness of different oil combating strategies in minimizing the negative effects of oil on six species living in the Gulf of Finland. The model can be used for creating different accident scenarios and assessing the performance of various oil combating actions under uncertainty, which enables its use as a supportive tool in decision-making. While the model is confined to the western Gulf of Finland, the methodology is adaptable to other marine areas facing similar risks and challenges related to oil spills.

Combining Conservation Value, Vulnerability, and Effectiveness of Mitigation Actions in Spatial Conservation Decisions: An Application to Coastal Oil Spill Combating

Increasing oil transportation and severe oil accidents in the past have led to the development of various sensitivity maps in different countries all over the world. Often, however, the areas presented on the maps are far too large to be safeguarded with the available oil combating equipment and prioritization is required to decide which areas must be safeguarded. While oil booms can be applied to safeguard populations from a drifting oil slick, decision making on the spatial allocation of oil combating capacity is extremely difficult due to the lack of time, resources and knowledge. Since the operational decision makers usually are not ecologists, a useful decision support tool including ecological knowledge must be readily comprehensible and easy to use. We present an index-based method that can be used to make decisions concerning which populations of natural organisms should primarily be safeguarded from a floating oil slick with oil booms. The indices take into account the relative exposure, mortality and recovery potential of populations, the conservation value of species and populations, and the effectiveness of oil booms to safeguard different species. The method has been implemented in a mapping software that can be used in the Gulf of Finland (Baltic Sea) for operational oil combating. It could also be utilized in other similar conservation decisions where species with varying vulnerability, conservational value, and benefits received from the management actions need to be prioritized.

Toward integrative management advice of water quality, oil spills, and fishery in the Gulf of Finland: a Bayesian approach.

Understanding and managing ecosystems affected by several anthropogenic stressors require methods that enable analyzing the joint effects of different factors in one framework. Further, as scientific knowledge about natural systems is loaded with uncertainty, it is essential that analyses are based on a probabilistic approach. We describe in this article about building a Bayesian decision model, which includes three stressors present in the Gulf of Finland. The outcome of the integrative model is a set of probability distributions for future nutrient concentrations, herring stock biomass, and achieving the water quality targets set by HELCOM Baltic Sea Action Plan. These distributions can then be used to derive the probability of reaching the management targets for each alternative combination of management actions.

Preparing for the unprecedented - Towards quantitative oil risk assessment in the Arctic marine areas.

The probability of major oil accidents in Arctic seas is increasing alongside with increasing maritime traffic. Hence, there is a growing need to understand the risks posed by oil spills to these unique and sensitive areas. So far these risks have mainly been acknowledged in terms of qualitative descriptions. We introduce a probabilistic framework, based on a general food web approach, to analyze ecological impacts of oil spills. We argue that the food web approach based on key functional groups is more appropriate for providing holistic view of the involved risks than assessments based on single species. We discuss the issues characteristic to the Arctic that need a special attention in risk assessment, and provide examples how to proceed towards quantitative risk estimates. The conceptual model presented in the paper helps to identify the most important risk factors and can be used as a template for more detailed risk assessments.

A probabilistic approach for a cost-benefit analysis of oil spill management under uncertainty: A Bayesian network model for the Gulf of Finland

Large-scale oil accidents can inflict substantial costs to the society, as they typically result in expensive oil combating and waste treatment operations and have negative impacts on recreational and environmental values. Cost-benefit analysis (CBA) offers a way to assess the economic efficiency of management measures capable of mitigating the adverse effects. However, the irregular occurrence of spills combined with uncertainties related to the possible effects makes the analysis a challenging task. We develop a probabilistic modeling approach for a CBA of oil spill management and apply it in the Gulf of Finland, the Baltic Sea. The model has a causal structure, and it covers a large number of factors relevant to the realistic description of oil spills, as well as the costs of oil combating operations at open sea, shoreline clean-up, and waste treatment activities. Further, to describe the effects on environmental benefits, we use data from a contingent valuation survey. The results encourage seeking for cost-effective preventive measures, and emphasize the importance of the inclusion of the costs related to waste treatment and environmental values in the analysis. Although the model is developed for a specific area, the methodology is applicable also to other areas facing the risk of oil spills as well as to other fields that need to cope with the challenging combination of low probabilities, high losses and major uncertainties.

A software system for assessing the spatially distributed ecological risk posed by oil shipping

A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team. We develop a system for assessing spatially distributed ecological risk.We link geospatial scenarios with a Bayesian network to obtain an expected scenario.Assessment of ecological risk of oil spill requires an extensive data collection.Foreign function interfaces are effective in linking heterogeneous software.

The role of stream ecosystems in urban planning: a case study from the stream Rekolanoja in Finland.

Purpose – Urban stream ecosystems have often been seen as channels of water flow rather than as the valuable parts of an urban green space system providing ecosystem services. The study seeks to address the importance of urban stream ecosystems from the perspective of urban ecology, human health and social well‐being in the context of urban planning.Design/methodology/approach – The case study area is the Rekolanoja stream ecosystem in the City of Vantaa, southern Finland. The data from the case study area were gathered from existing ecological studies and by conducting semi‐structured interviews, a resident inquiry and a writing contest.Findings – The results from the Rekolanoja case show that intense management of the streamside vegetation and treatment of the stream channel in construction projects have decreased species richness and diminished valuable streamside biotopes. However, the stream corridor can function as an important recreational and educational element within the local green space networ...

Evaluating the impact of nutrient abatement measures on the ecological status of coastal waters: a Bayesian network for decision analysis

Environmental managers must make decisions about complex problems that have a high degree of uncertainty such as, which nutrient abatement measure optimally improves the condition of an ecosystem. Although data and models that provide information on this subject exist, their knowledge may be fragmentary and difficult to interpret. We present a user-friendly modelling tool that integrates results of different models and data-analyses. It can be used by decision-makers for assessing the probabilities of different nutrient abatement scenarios for achieving specific targets set by the Water Framework Directive for Finnish coastal waters in the Gulf of Finland. The results suggest that significant reductions in nutrient loads are required to achieve good ecological status in Finnish coastal waters, and in the event of increased precipitation these targets may be less likely to be attained. Moreover, different approaches to the status classification lead to very different conclusions.

Species and habitats in danger: estimating the relative risk posed by oil spills in the northern Baltic Sea

Largescale oil spills can have adverse eff ects on biodiversity in coastal areas where maritime oil transportation is intense. In this article we conducted a spatial risk assessment to study the risk that potential tanker accidents pose to threatened habitat types and species living in the northern Baltic Sea, which has witnessed a rapid increase in maritime oil transportation within the past two decades. We applied a probabilistic method, which combines three components: a Bayesian network describing tanker accidents and uncertainties related to them, probabilistic maps showing the movement of oil, and a database of threatened species and habitats in the area. The results suggest that spatial risk posed by oil spills varies across the area, and does not correspond, for example, to the frequency of accidents in a given area. The relative risk is highest for seashore meadows, which is important to take into account when managing these habitats. Our analysis underlines the importance of a thorough risk assessment, which is not only based solely on one or two specifi c factors such as accident probabilities or the trajectories of spilled oil but also contains as broad a view of the consequences as possible. We believe that the probabilistic methodology applied in the study will be of high interest to people who have to cope with uncertainties typical for environmental risk assessment and management.

Geospatial Web Services for Responding to Ecological Risks Posed by Oil Spills

The increased maritime oil transportation raises the risk of marine oil spill accidents. An oil spill accident can cause severe harm to the ecosystem. Adequate contingency planning for oil spill and efficient combating operations require ecological data and knowledge to be integrated in tools that facilitate the decision making. A great deal of the decisions required during these operations is of spatial nature, such as defining areas with high priority for safeguarding. Also, real time decision making is required in the operations. All of this calls for spatial and on-sit accessible tools. The authors analyze and discuss geospatial Web services and an application develop[ed for responding to the ecological risk posed by oil spills. The case study presented in this paper concerns the Gulf of Finland and the Finnish Archipelago Sea. The results indicate that geospatial services are an efficient method to deliver ecological knowledge and information for oil spill combating.