Multiple stakeholders’ perspectives of marine social ecological systems, a case study on the Barents Sea

The Barents Sea ecosystem components and services are under pressure from climate change and other anthropogenic impacts. Following an Ecosystem-based management approach, multiple simultaneous pressures are addressed by using integrative strategies, but regular prioritization of key issues is needed. Identification of such priorities is typically done in a ‘scoping’ phase, where the characterization of the social-ecological system is defined and discussed. We performed a scoping exercise using an open and flexible multi-stakeholder approach to build conceptual models of the Barents Sea social-ecological system. After standardizing vocabulary, a com plex hierarchical model structure containing 155 elements was condensed to a simpler model structure con taining a maximum of 36 elements. To capture a common understanding across stakeholder groups, inputs from the individual group models were compiled into a collective model. Stakeholders’ representation of the Barents Sea social-ecological system is complex and often group specific, emphasizing the need to include social scientific methods to ensure the identification and inclusion of key stakeholders in the process. Any summary or simpli fication of the stakeholders’ representation neglects important information. Some commonalities are highlighted in the collective model, and additional information from the hierarchical model is provided by multicriteria analysis. The collective conceptual stakeholder model provides input to an integrated overview and strengthens prioritization in Ecosystem-based management by supporting the development of qualitative network models. Such models allow for exploration of perturbations and can inform cross-sectoral management trade-offs and prioritiespublishedVersio

Management Strategy Evaluation: Allowing the Light on the Hill to Illuminate More Than One Species

Management strategy evaluation (MSE) is a simulation approach that serves as a “light on the hill” (Smith, 1994) to test options for marine management, monitoring, and assessment against simulated ecosystem and fishery dynamics, including uncertainty in ecological and fishery processes and observations. MSE has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers. Here we describe how and why MSE is continuing to grow from a single species approach to one relevant to multi-species and ecosystem-based management. In particular, different ecosystem modeling approaches can fit within the MSE process to meet particular natural resource management needs. We present four case studies that illustrate how MSE is expanding to include ecosystem considerations and ecosystem models as ‘operating models’ (i.e., virtual test worlds), to simulate monitoring, assessment, and harvest control rules, and to evaluate tradeoffs via performance metrics. We highlight United States case studies related to fisheries regulations and climate, which support NOAA’s policy goals related to the Ecosystem Based Fishery Roadmap and Climate Science Strategy but vary in the complexity of population, ecosystem, and assessment representation. We emphasize methods, tool development, and lessons learned that are relevant beyond the United States, and the additional benefits relative to single-species MSE approaches

An Ecosystem‐Based Approach To Marine Risk Assessment

Risk assessments quantify the probability of undesirable events along with their consequences. They are used to prioritize management interventions and assess tradeoffs, serving as an essential component of ecosystem‐based management (). A central objective of most risk assessments for conservation and management is to characterize uncertainty and impacts associated with one or more pressures of interest. Risk assessments have been used in marine resource management to help evaluate the risk of environmental, ecological, and anthropogenic pressures on species or habitats including for data‐poor fisheries management (e.g., toxicity, probability of extinction, habitat alteration impacts). Traditionally, marine risk assessments focused on singular pressure‐response relationships, but recent advancements have included use of risk assessments in an context, providing a method for evaluating the cumulative impacts of multiple pressures on multiple ecosystem components. Here, we describe a conceptual framework for ecosystem risk assessment (), highlighting its role in operationalizing, with specific attention to ocean management considerations. This framework builds on the ecotoxicological and conservation literature on risk assessment and includes recent advances that focus on risks posed by fishing to marine ecosystems. We review how examples of s from the United States fit into this framework, explore the variety of analytical approaches that have been used to conduct s, and assess the challenges and data gaps that remain. This review discusses future prospects for s as decision‐support tools, their expanded role in integrated ecosystem assessments, and the development of next‐generation risk assessments for coupled natural–human systems

Towards climate resiliency in fisheries management

International audienceIt is increasingly evident that climate change is having significant impacts on marine ecosystems and dependent fisheries. Yet, translating climate science into management actions and policies is an ongoing challenge. In particular, four aspects have confounded implementation of climate-resilient management: (i) regional management tools may not be well-suited for managing the same systems under climate change, (ii) individual management policies and climate research studies are often implicitly focussed on spatio-temporal scales that are rarely aligned, (iii) management approaches seldom integrate across spatio-temporal scales and are, therefore, maladapted to unidirectional change and extreme events, and (iv) challenges to modelling socio-economic implications of climate change impede projections of cumulative costs to society, disguise adaptive limits, and ultimately impact climate risk and management trade-off assessments. We suggest that addressing environmental change favours adaptive and dynamic management approaches, while addressing shifting socio-economic and political conditions favours fixed long-term measures; considering both jointly requires a combination of dynamic-adaptive-fixed approaches. We outline a framework to integrate climate-responsive tools into a unified climate-resilient management approach using nested dynamic-adaptive-fixed management portfolios that improve management effectiveness and efficiency. This approach may help reduce future conflict between marine resource extractive and conservation goals through more explicit characterization of management trade-offs and identification of social and ecological tipping points

An ecosystem‐based approach to marine risk assessment

Risk assessments quantify the probability of undesirable events along with their consequences. They are used to prioritize management interventions and assess tradeoffs, serving as an essential component of ecosystem‐based management (). A central objective of most risk assessments for conservation and management is to characterize uncertainty and impacts associated with one or more pressures of interest. Risk assessments have been used in marine resource management to help evaluate the risk of environmental, ecological, and anthropogenic pressures on species or habitats including for data‐poor fisheries management (e.g., toxicity, probability of extinction, habitat alteration impacts). Traditionally, marine risk assessments focused on singular pressure‐response relationships, but recent advancements have included use of risk assessments in an context, providing a method for evaluating the cumulative impacts of multiple pressures on multiple ecosystem components. Here, we describe a conceptual framework for ecosystem risk assessment (), highlighting its role in operationalizing , with specific attention to ocean management considerations. This framework builds on the ecotoxicological and conservation literature on risk assessment and includes recent advances that focus on risks posed by fishing to marine ecosystems. We review how examples of s from the United States fit into this framework, explore the variety of analytical approaches that have been used to conduct s, and assess the challenges and data gaps that remain. This review discusses future prospects for s as decision‐support tools, their expanded role in integrated ecosystem assessments, and the development of next‐generation risk assessments for coupled natural–human systems

Difference in predicted growth (<i>g</i>⋅<i>g</i>⁻¹⋅<i>d</i>⁻¹) of juvenile walleye pollock between the bioenergetics model and the IBM for 2005 (a) and 2010 (b).

<p>Areas of positive differences indicate where maximum growth potential from the bioenergetics model was higher than predicted growth from the IBM.</p

Summary of sensitivity analyses for the IBM model in 2005 and 2010 showing the minimum (min), mean, and maximum (max) growth potential and depth (m) over all stations.

<p>Base values are predicted growth (<i>g</i>⋅<i>g</i>⁻¹⋅<i>d</i>⁻¹) and depth (m) of juvenile pollock from the base model scenarios (<i>W</i> = 2.5 g, zooplankton prey distributed according to vertical profiles). All other values are predicted changes in growth and depth. Negative changes in depth indicate a shallower distribution; positive values indicate a deeper distribution. Weight is a constant value applied across all station, so varying the parameter acts as a scalar and results in similar spatial patterns across the area. The effect of applying a uniform distribution of zooplankton prey with depth varies across stations.</p

Predicted growth (<i>g</i>⋅<i>g</i>⁻¹⋅<i>d</i>⁻¹) of juvenile walleye pollock interpolated over the range of observed temperatures and prey energy density values across both 2005 and 2010, providing a continuous scale of growth over a broad range of possible environmental and biological scenarios.

<p>The observed fish energy density was higher in 2010 (<i>v₂₀₁₀</i> = 5.29 kJ⋅g⁻¹; used in plot shown); therefore this interpolation demonstrates the range of predicted growth for fish with high energy density. Temperatures included 0–16°C to show possible range under variable climate conditions. The dashed rectangle encompasses the range of temperatures and prey energy density values observed in 2005; solid rectangle encompasses values in 2010. Points are shown for average temperature and prey energy density conditions in 2005 and 2010. Predicted growth above 15°C was not possible (black) because the bioenergetics model has a temperature threshold of 15°C.</p

Parameter definitions and values used in the bioenergetics model to estimate maximum growth potential (<i>g</i>⋅<i>g</i>⁻¹⋅<i>d</i>⁻¹) of juvenile walleye pollock.

<p>Parameters were used as inputs to the bioenergetics model described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084526#pone.0084526-Ciannelli1" target="_blank">[16]</a>.</p><p>^a<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084526#pone.0084526-Holsman1" target="_blank">[25]</a>; <i>^b</i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084526#pone.0084526-Ciannelli1" target="_blank">[16]</a>.</p