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.

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.

The role of marinas in the establishment and spread of non-indigenous species in Baltic Sea fouling communities.

The study included the sampling of 12 marinas across six areas of the Baltic Sea with settlement plates and scraping of submerged structures to assess the role of marinas in the spread of non-indigenous species (NIS) via biofouling. 15 NIS were detected in the marinas and secondary spread of previously introduced NIS was detected in five out of six sea areas. Salinity and sea area significantly affected the composition of the fouling assemblages. Settlement plates appeared as the more efficient sampling method over scraping, while the seasonal analyses revealed that the monitoring effort should span over the summer and early autumn in the south-eastern, central, and northern Baltic Sea. The present findings indicate that marinas contribute to the spread of non-indigenous fouling organisms, and there is an increasing demand for the monitoring of marinas and stricter regulations regarding the biofouling management of leisure boats in the Baltic Sea.

Citizen science provides added value in the monitoring for coastal non-indigenous species.

Continuous and comprehensive monitoring is one of the most important practices to trace changes in the state of the environment and target management efforts. Yet, governmental resources are often insufficient for monitoring all required environmental parameters, and therefore authorities have started to utilize citizen observations to supplement and increase the scale of monitoring. The aims of the present study were to show the potential of citizen science in environmental monitoring by utilising citizen observations of the non-indigenous Harris mud crab Rhithropanopeus harrisii in Finnish waters, where coastal monitoring is insufficient to estimate the distribution and spread of non-indigenous species. Harris mud crab has shown measurable impact locally and is considered invasive. For reporting the status of invasions to national and European authorities and planning for potential eradication efforts, up to date knowledge on NIS ranges are needed. Citizen observations on the species were collected from the first observation onwards between 2009 and 2018, at first via email and later through an active citizen observation web portal (Invasive Alien Species Portal). The outcomes of the study indicate that species-specific citizen observations can be a beneficial addition to supplement national monitoring programs to fulfil legislative reporting requirements and to target potential management. Recognizable species and geographical areas with low biodiversity provide a good opportunity to utilize citizen observations. Moreover, citizen observations may enable distribution assessments for certain species that would otherwise require excessive resources and sampling efforts.

Knowledge to decision in dynamic seas: Methods to incorporate non-indigenous species into cumulative impact assessments for maritime spatial planning.

Incorporating ecosystem changes from non-indigenous species (NIS) is an important task of maritime spatial planning. Maritime spatial planning requires a framework that emphasises ecological functioning in a state of dynamic change, including changes to ecosystem services from functions introduced by new NIS. Adaptable modelling toolsets should be developed that can readily incorporate knowledge of new NIS. In the Baltic Sea, recent NIS examples are the North American mud crab Rhithropanopeus harrisii and the Ponto-Caspian round goby Neogobius melanostomus. We performed environmental niche modelling that predicted N. melanostomus will spread across large areas of the Baltic Sea coast while R. harrisii will be limited to regions with high temperature and low salinity conditions. We then performed a meta-analysis on literature showing effects in the Baltic Sea from these NIS and calculated the standardised effect-sizes on relevant ecosystem services. Half the impacts identified for N. melanostomus were considered to increase ecosystem service outcomes, while all R. harrisii impacts caused apparent decreases. Effect coefficients were incorporated into an online impact assessment tool developed by the Estonian Marine Institute. Users with or without science training can use the portal to estimate areas impacted and changes to natural assets (km2) caused by these NIS and cumulative effects from other pressure-types. Impact estimates are based on best available knowledge from manipulative and correlative experiments and thus form a link between science and management. Dynamic modelling techniques informed from varied ecological and methodological perspectives will effectively advise spatial planners about rapid maritime changes and mitigation actions to reduce NIS impacts especially in the focus areas.