Causal Approach to Determining the Environmental Risks of Seabed Mining.

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.

Cost-efficiency assessments of marine monitoring methods lack rigor-a systematic mapping of literature and an end-user view on optimal cost-efficiency analysis.

Global deterioration of marine ecosystems, together with increasing pressure to use them, has created a demand for new, more efficient and cost-efficient monitoring tools that enable assessing changes in the status of marine ecosystems. However, demonstrating the cost-efficiency of a monitoring method is not straightforward as there are no generally applicable guidelines. Our study provides a systematic literature mapping of methods and criteria that have been proposed or used since the year 2000 to evaluate the cost-efficiency of marine monitoring methods. We aimed to investigate these methods but discovered that examples of actual cost-efficiency assessments in literature were rare, contradicting the prevalent use of the term "cost-efficiency." We identified five different ways to compare the cost-efficiency of a marine monitoring method: (1) the cost-benefit ratio, (2) comparative studies based on an experiment, (3) comparative studies based on a literature review, (4) comparisons with other methods based on literature, and (5) subjective comparisons with other methods based on experience or intuition. Because of the observed high frequency of insufficient cost-benefit assessments, we strongly advise that more attention is paid to the coverage of both cost and efficiency parameters when evaluating the actual cost-efficiency of novel methods. Our results emphasize the need to improve the reliability and comparability of cost-efficiency assessments. We provide guidelines for future initiatives to develop a cost-efficiency assessment framework and suggestions for more unified cost-efficiency criteria.

Quantitative criteria for choosing targets and indicators for sustainable use of ecosystems.

Wide-ranging, indicator-based assessments of large, complex ecosystems are playing an increasing role in guiding environmental policy and management. An example is the EU's Marine Strategy Framework Directive, which requires Member States to take measures to reach "good environmental status" (GES) in European marine waters. However, formulation of indicator targets consistent with the Directive's high-level policy goal of sustainable use has proven challenging. We develop a specific, quantitative interpretation of the concepts of GES and sustainable use in terms of indicators and associated targets, by sharply distinguishing between current uses to satisfy current societal needs and preferences, and unknown future uses. We argue that consistent targets to safeguard future uses derive from a requirement that any environmental state indicator should recover within a defined time (e.g. 30 years) to its pressure-free range of variation when all pressures are hypothetically removed. Within these constraints, specific targets for current uses should be set. Routes to implementation of this proposal for indicators of fish-community size structure, population size of selected species, eutrophication, impacts of non-indigenous species, and genetic diversity are discussed. Important policy implications are that (a) indicator target ranges, which may be wider than natural ranges, systematically and rationally derive from our proposal; (b) because relevant state indicators tend to respond slowly, corresponding pressures should also be monitored and assessed;

Modelling framework to evaluate societal effects of ecosystem management.

The ecosystem effects of different management options can be predicted through models that simulate the ecosystem functioning under different management scenarios. Optimal management strategies are searched by simulating different management (and other, such as climate) scenarios and finding the management measures that produce desirable results. The desirability of results is often defined through the attainment of policy objectives such as good environmental/ecological status. However, this often does not account for societal consequences of the environmental status even though the consequences can be different for different stakeholder groups. In this work we introduce a method to evaluate management alternatives in the light of the experiential value of stakeholder groups, using a case study in the Baltic Sea. We use an Ecopath with Ecosim model to simulate the ecosystem responses to management and climate scenarios, and the results are judged based on objectives defined based on a stakeholder questionnaire on what aspects of the ecosystem they value or detest. The ecosystem responses and the stakeholder values are combined in a Bayesian decision support model to illustrate which management options bring the highest benefits to stakeholders, and whether different stakeholder groups benefit from different management choices. In the case study, the more moderate climate scenario and strict fisheries and nutrient loading management brought the highest benefits to all stakeholders. The method can be used to evaluate and compare the effects of different management alternatives to various stakeholder groups, if their preferences are known.

Evaluation of reaching the targets of the water framework directive in the Gulf of Finland.

This paper describes the development of the EU Water Framework Directive central water quality elements from 1970 to 2010 in the Gulf of Finland, a eutrophied sub-basin of the Baltic Sea. The likelihood of accomplishing the management objectives simultaneously is assessed using Bayesian networks. The objectives of good ecological status in winter-time total nitrogen and phosphorus, summer-time chlorophyll-a and summer-time Secchi depth have not been met yet. In addition, the results indicate that it is unlikely for them to be achieved in the near future, despite the decreasing trend in nutrient concentrations over the past few years. It was demonstrated that neither phosphorus nor nitrogen alone controls summertime plankton growth. Reaching good ecological status in nutrients does not necessarily lead to good ecological status of chlorophyll-a, even though a dependency between the parameters does exist. In addition, secchi-depth status is strongly related to chlorophyll-a status in three of the four study-areas.

Food web assessments in the Baltic Sea: Models bridging the gap between indicators and policy needs.

Ecosystem-based management requires understanding of food webs. Consequently, assessment of food web status is mandatory according to the European Union's Marine Strategy Framework Directive (MSFD) for EU Member States. However, how to best monitor and assess food webs in practise has proven a challenging question. Here, we review and assess the current status of food web indicators and food web models, and discuss whether the models can help addressing current shortcomings of indicator-based food web assessments, using the Baltic Sea as an example region. We show that although the MSFD food web assessment was designed to use food web indicators alone, they are currently poorly fit for the purpose, because they lack interconnectivity of trophic guilds. We then argue that the multiple food web models published for this region have a high potential to provide additional coherence to the definition of good environmental status, the evaluation of uncertainties, and estimates for unsampled indicator values, but we also identify current limitations that stand in the way of more formal implementation of this approach. We close with a discussion of which current models have the best capacity for this purpose in the Baltic Sea, and of the way forward towards the combination of measurable indicators and modelling approaches in food web assessments.

Integrating diverse model results into decision support for good environmental status and blue growth.

Sustainable environmental management needs to consider multiple ecological and societal objectives simultaneously while accounting for the many uncertainties arising from natural variability, insufficient knowledge about the system's behaviour leading to diverging model projections, and changing ecosystem. In this paper we demonstrate how a Bayesian network- based decision support model can be used to summarize a large body of research and model projections about potential management alternatives and climate scenarios for the Baltic Sea. We demonstrate how this type of a model can act as an emulator and ensemble, integrating disciplines such as climatology, biogeochemistry, marine and fisheries ecology as well as economics. Further, Bayesian network models include and present the uncertainty related to the predictions, allowing evaluation of the uncertainties, precautionary management, and the explicit consideration of acceptable risk levels. The Baltic Sea example also shows that the two biogeochemical models frequently used in future projections give considerably different predictions. Further, inclusion of parameter uncertainty of the food web model increased uncertainty in the outcomes and reduced the predicted manageability of the system. The model allows simultaneous evaluation of environmental and economic goals, while illustrating the uncertainty of predictions, providing a more holistic view of the management problem.

Bayesian Networks in Environmental Risk Assessment: A Review.

Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer-reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors' experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62-78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Gaps in current Baltic Sea environmental monitoring - Science versus management perspectives.

Legislations and commitments regulate Baltic Sea status assessments and monitoring. These assessments suffer from monitoring gaps that need prioritization. We used three sources of information; scientific articles, project reports and a stakeholder survey to identify gaps in relation to requirements set by the HELCOM's Baltic Sea Action Plan, the Marine Strategy Framework Directive and the Water Framework Directive. The most frequently mentioned gap was that key requirements are not sufficiently monitored in space and time. Biodiversity monitoring was the category containing most gaps. However, whereas more than half of the gaps in reports related to biodiversity, scientific articles pointed out many gaps in the monitoring of pollution and water quality. An important finding was that the three sources differed notably with respect to which gaps were mentioned most often. Thus, conclusions about gap prioritization for management should be drawn after carefully considering the different viewpoints of scientists and stakeholders.

Indicator Properties of Baltic Zooplankton for Classification of Environmental Status within Marine Strategy Framework Directive.

The European Marine Strategy Framework Directive requires the EU Member States to estimate the level of anthropogenic impacts on their marine systems using 11 Descriptors. Assessing food web response to altered habitats is addressed by Descriptor 4 and its indicators, which are being developed for regional seas. However, the development of simple foodweb indicators able to assess the health of ecologically diverse, spatially variable and complex interactions is challenging. Zooplankton is a key element in marine foodwebs and thus comprise an important part of overall ecosystem health. Here, we review work on zooplankton indicator development using long-term data sets across the Baltic Sea and report the main findings. A suite of zooplankton community metrics were evaluated as putative ecological indicators that track community state in relation to Good Environmental Status (GES) criteria with regard to eutrophication and fish feeding conditions in the Baltic Sea. On the basis of an operational definition of GES, we propose mean body mass of zooplankton in the community in combination with zooplankton stock measured as either abundance or biomass to be applicable as an integrated indicator that could be used within the Descriptor 4 in the Baltic Sea. These metrics performed best in predicting zooplankton being in-GES when considering all datasets evaluated. However, some other metrics, such as copepod biomass, the contribution of copepods to the total zooplankton biomass or biomass-based Cladocera: Copepoda ratio, were equally reliable or even superior in certain basin-specific assessments. Our evaluation suggests that in several basins of the Baltic Sea, zooplankton communities currently appear to be out-of-GES, being comprised by smaller zooplankters and having lower total abundance or biomass compared to the communities during the reference conditions; however, the changes in the taxonomic structure underlying these trends vary widely across the sea basins due to the estuarine character of the Baltic Sea.

The Marine Strategy Framework Directive and the ecosystem-based approach ­ pitfalls and solutions.

The European Marine Strategy Framework Directive aims at good environmental status (GES) in marine waters, following an ecosystem-based approach, focused on 11 descriptors related to ecosystem features, human drivers and pressures. Furthermore, 29 subordinate criteria and 56 attributes are detailed in an EU Commission Decision. The analysis of the Decision and the associated operational indicators revealed ambiguity in the use of terms, such as indicator, impact and habitat and considerable overlap of indicators assigned to various descriptors and criteria. We suggest re-arrangement and elimination of redundant criteria and attributes avoiding double counting in the subsequent indicator synthesis, a clear distinction between pressure and state descriptors and addition of criteria on ecosystem services and functioning. Moreover, we suggest the precautionary principle should be followed for the management of pressures and an evidence-based approach for monitoring state as well as reaching and maintaining GES.

Good Environmental Status of marine ecosystems: what is it and how do we know when we have attained it?

The European Marine Strategy Framework Directive (MSFD) requires EU Member States (MS) to achieve Good Environmental Status (GEnS) of their seas by 2020. We address the question of what GEnS entails especially with regard to the level at which targets are set (descriptors, criteria, indicators), to scales for assessments (regional, sub-divisions, site-specific), and to difficulties in putting into practice the GEnS concept. We propose a refined and operational definition of GEnS, indicating the data and information needed to all parts of that definition. We indicate the options for determining when GEnS has been met, acknowledge the data and information needs for each option, and recommend a combination of existing quantitative targets and expert judgement. We think that the MSFD implementation needs to be less complex than shown for other similar directives, can be based largely on existing data and can be centred on the activities of the Regional Seas Conventions.

Assessing the roles of environmental factors in coastal fish production in the northern Baltic Sea: a Bayesian network application.

Environmental conditions play a crucial role in the distribution and abundance of fish species in any area. Much research has been attributed to the requirements and tolerance limits of commercially exploited fish species. It is rare, however, that studies have been able to address the relative importance of potentially restrictive environmental factors; extensive enough to allow for estimation of the effect of several environmental factors through the fishes' life span. The coastline of Finland in the northern Baltic Sea offers a unique natural experimental setting that can be used to assess the relative importance of various environmental factors for the species occupying it. The area includes major variations in several crucial environmental factors: salinity, temperature regime, represented by winter ice duration, coastline characteristics, and eutrophic status. Furthermore, Finland has collected extensive and spatially representative data of water quality and environmental factors, as well as a long and extraordinarily spatially detailed data set of commercial catches of several fish species. In this article, we make an attempt to correlate the environmental data to the commercial catches of fish species, assuming that the commercial catches reflect, to some reasonable degree, the productivity of that species in that area (compared to other areas and combinations of environmental factors, not to other species). We use a Bayesian network approach to examine the sensitivity of the species to the environmental factors.

Bayesian networks in environmental and resource management.

This overview article for the special series, "Bayesian Networks in Environmental and Resource Management," reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.