Operationalising ODEMM risk assessment for Integrated Ecosystem Assessment scoping: Complexity vs. manageability

Integrated Ecosystem Assessments (IEA) require consideration of the full suite of pressures and impacts affecting ecosystems. However, capacity limitations often severely limit our ability to do everything that we want or ‘should’ do, outside of short-term fully-funded focused research projects. In order to make IEA a reality in many contexts, priority consideration has to be given to how to achieve such comprehensive assessments. Ecoregions and Large Marine Ecosystems (LMEs) have been identified as potential management units, however these large areas encompass diverse habitats, and multiple nations with diverse human communities and use of marine environments, and a multitude of different management strategies. In this context, how can we make IEA an operational tool that can be applied at such high-level in a comparable, yet regionally-relevant adaptable approach? This paper outlines the demonstration and adaptation of an established risk assessment approach (Options for Delivering Ecosystem-Based Marine Management: ODEMM) to a rapid risk scoping tool, and how this approach has been applied using open source common analytical tools to improve operationality in both the Mission Atlantic project and the International Council for the Exploration of the Seas (ICES) Integrated Ecosystem Assessment Working Groups. Furthermore, a hierarchical approach is detailed that allows the integration of different levels of detail into a common format. The resulting assessments are then ground-truthed with stakeholders to identify issues, omissions, potential conflicts, and key areas of interest for the next steps of the IEA process

Exploring methods for predicting multiple pressures on ecosystem recovery: A case study on marine eutrophication and fisheries

AbstractEfforts to attain good environmental status in the marine realm require decisions which cannot be done without knowledge of effects of different management measures. Given the wide diversity of marine ecosystems, multitude of pressures affecting it and the still poor understanding on linkages between those, there are likely no models available to give all the required answers. Hence, several separate approaches can be used in parallel to give support for management measures. We tested three completely different methods – a spatial impact index, a food web model and a Bayesian expert method. We found that a large uncertainty existed regarding the ecosystem response to the management scenarios, and that the three different modelling approaches complemented each other. The models indicated that in order to reach an improved overall state of the ecosystem nutrient reductions are the more effective of the two management variables explored, and that cumulative effects of the management of nutrient inputs and fishing mortality are likely to exist

Is Diversity the Missing Link in Coastal Fisheries Management?

Fisheries management has historically focused on the population elasticity of target fish based primarily on demographic modeling, with the key assumptions of stability in environmental conditions and static trophic relationships. The predictive capacity of this fisheries framework is poor, especially in closed systems where the benthic diversity and boundary effects are important and the stock levels are low. Here, we present a probabilistic model that couples key fish populations with a complex suite of trophic, environmental, and geomorphological factors. Using 41 years of observations we model the changes in eastern Baltic cod (Gadus morhua), herring (Clupea harengus), and Baltic sprat (Sprattus sprattus balticus) for the Baltic Sea within a Bayesian network. The model predictions are spatially explicit and show the changes of the central Baltic Sea from cod- to sprat-dominated ecology over the 41 years. This also highlights how the years 2004 to 2014 deviate in terms of the typical cod–environment relationship, with environmental factors such as salinity being less influential on cod population abundance than in previous periods. The role of macrozoobenthos abundance, biotopic rugosity, and flatfish biomass showed an increased influence in predicting cod biomass in the last decade of the study. Fisheries management that is able to accommodate shifting ecological and environmental conditions relevant to biotopic information will be more effective and realistic. Non-stationary modelling for all of the homogeneous biotope regions, while acknowledging that each has a specific ecology relevant to understanding the fish population dynamics, is essential for fisheries science and sustainable management of fish stocks

Editorial: Managing for the future: challenges and approaches for disentangling the relative roles of environmental change and fishing in marine ecosystems

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A participatory scenario method to explore the future of marine social‐ecological systems

Source at https://doi.org/10.1111/faf.12356.Anticipating future changes in marine social‐ecological systems (MSES) several decades into the future is essential in the context of accelerating global change. This is challenging in situations where actors do not share common understandings, practices, or visions about the future. We introduce a dedicated scenario method for the development of MSES scenarios in a participatory context. The objective is to allow different actors to jointly develop scenarios which contain their multiple visions of the future. The method starts from four perspectives: “fisheries management,” “ecosystem,” “ocean climate,” and “global context and governance” for which current status and recent trends are summarized. Contrasted scenarios about possible futures are elaborated for each of the four single perspectives before being integrated into multiple‐perspective scenarios. Selected scenarios are then developed into storylines. Focusing on individual perspectives until near the end allows actors with diverse cultures, interests and horizons to confront their own notions of the future. We illustrate the method with the exploration of the futures of the Barents Sea MSES by 2050. We emphasize the following lessons learned: first, many actors are not familiar with scenario building and attention must be paid to explaining the purpose, methodology, and benefits of scenarios exercises. Second, although the Barents Sea MSES is relatively well understood, uncertainties about its future are significant. Third, it is important to focus on unlikely events. Fourth, all perspectives should be treated equally. Fifth, as MSES are continuously changing, we can only be prepared for future changes if we collectively keep preparing

Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends

The Baltic Health Index (BHI) : Assessing the social–ecological status of the Baltic Sea

1. Improving the health of coastal and open sea marine ecosystems represents a substantial challenge for sustainable marine resource management, since it requires balancing human benefits and impacts on the ocean. This challenge is often exacerbated by incomplete knowledge and lack of tools that measure ocean and coastal ecosystem health in a way that allows consistent monitoring of progress towards predefined management targets. The lack of such tools often limits capabilities to enact and enforce effective governance. 2. We introduce the Baltic Health Index (BHI) as a transparent, collaborative and repeatable assessment tool. The Index complements existing, more ecological-oriented, approaches by including a human dimension on the status of the Baltic Sea, an ecosystem impacted by multiple anthropogenic pressures and governed by a multitude of comprehensive national and international policies. Using a large amount of social–ecological data available, we assessed the health of the Baltic Sea for nine goals that represent the status towards set targets, for example, clean waters, biodiversity, food provision, natural products extraction and tourism. 3. Our results indicate that the overall health of the Baltic Sea is suboptimal (a score of 76 out of 100), and a substantial effort is required to reach the management objectives and associated targets. Subregionally, the lowest BHI scores were measured for carbon storage, contaminants and lasting special places (i.e. marine protected areas), albeit with large spatial variation. 4. Overall, the likely future status of all goals in the BHI averaged for the entire Baltic Sea is better than the present status, indicating a positive trend towards a healthier Baltic Sea. However, in some Baltic Sea basins, the trend for specific goals was decreasing, highlighting locations and issues that should be the focus of management priorities. 5. The BHI outcomes can be used to identify both pan-Baltic and subregional scale management priorities and to illustrate the interconnectedness between goals linked by cumulative pressures. Hence, the information provided by the BHI tool and its further development will contribute towards the fulfilment of the UN Agenda 2030 and its Sustainability Development Goals

Multiple forces drive the Baltic Sea food web dynamics and its response to environmental change

Understanding the interaction of multiple drivers and their compounded effects on ecosystem dynamics is a key challenge for marine resource management. The Baltic Sea is one of the world’s seas most strongly impacted by effects from both human activities and climate. In the late 1980’s changes in climate in combination with intensive fishing initiated a reorganization of the Central Baltic Sea (CBS) food web resulting in the current sprat-dominated state. In the future, climate change is projected to cause drastic changes in hydrodynamic conditions of the world oceans in general, and the Baltic Sea in particular.   In this thesis, CBS food web responses to the combined effects of fishing, nutrient loads and climate were tested for the past (1974-2006) and projected into the future (2010-2098). A new food web model for the CBS (BaltProWeb) was developed using extensive monitoring data across trophic levels. This model described the past food web dynamics well, and was hence also used for future (2010-2098) projections. Different ensemble modeling approaches were employed when testing the food web response to future scenarios. The results show that regardless the climate change, the management of nutrient loads and cod fishing are likely to determine the food web dynamics and trophic control mechanisms in the future Baltic Sea. Consequently, the variation in the food web projections was large, ranging from a strongly eutrophied and sprat-dominated to a cod-dominated CBS with eutrophication levels close to today’s values. The results also suggest a potential risk of abrupt ecosystem changes in the future CBS, particularly if the nutrient loads are not reduced. Finally, the studies illustrate the usefulness of the ensemble modeling approach, both from the perspective of ecosystem-based management as well as for studying the importance of different mechanisms in the ecosystem response.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: In press. Paper 5: Submitted.</p

Generalized modeling of empirical social-ecological systems

Modeling social-ecological systems is difficult due to the complexity of ecosystems and of individual and collective human behavior. Key components of the social-ecological system are often over-simplified or omitted. Generalized modeling is a dynamical systems approach that can overcome some of these challenges. It can rigorously analyze qualitative system dynamics such as regime shifts despite incomplete knowledge of the model's constituent processes. Here, we review generalized modeling and use a recent study on the Baltic Sea cod fishery's boom and collapse to demonstrate its application to modeling the dynamics of empirical social-ecological systems. These empirical applications demand new methods of analysis suited to larger, more complicated generalized models. Generalized modeling is a promising tool for rapidly developing mathematically rigorous, process-based understanding of a social-ecological system's dynamics despite limited knowledge of the syste