Description: Productivity of marine fish stocks is known to be affected by environmental and ecological drivers, and global climate change is anticipated to alter recruitment success of many stocks. While the direct effects of environmental drivers on fish early life stage survival can be quantified experimentally, indirect effects in marine ecosystems and the role of adaptation are still highly uncertain. We developed an integrative model for the effects of ocean warming and acidification on the early life stages of Atlantic cod in the Barents Sea, termed SCREI (Simulator of Cod Recruitment under Environmental Influences). Experimental results on temperature and CO2 effects on egg fertilization, egg and larval survival and development times are incorporated. Calibration using empirical time series of egg production, temperature, food and predator abundance reproduces age-0 recruitment over three decades. We project trajectories of recruitment success under different scenarios and quantify confidence limits based on variation in experiments. A publicly accessible web version of the SCREI model can be run under www.oceanchange.uni-bremen.de/;SCREI. Severe reductions in average age-0 recruitment success of Barents Sea cod are projected under uncompensated warming and acidification toward the middle to end of this century. Although high population stochasticity was found, considerable rates of evolutionary adaptation to acidification and shifts in organismal thermal windows would be needed to buffer impacts on recruitment. While increases in food availability may mitigate short-term impacts, an increase in egg production achieved by stock management could provide more long-term safety for cod recruitment success. The SCREI model provides a novel integration of multiple driver effects in different life stages and enables an estimation of uncertainty associated with interindividual and ecological variation. The model thus helps to advance toward an improved empirical foundation for quantifying climate change impacts on marine fish recruitment, relevant for ecosystem-based assessments of marine systems under climate change.

Description: Climate change and ocean acidification are anticipated to alter marine ecosystems, with consequences for the provision of marine resources and ecosystem services to human societies. However, considerable uncertainties about future ecological changes and ensuing socio-economic impacts impede the identification of societal adaptation strategies. In a case study from the Barents Sea and Northern Norwegian Sea region, we integrated stakeholder perceptions of ecological changes and their significance for societies with the current state of scientific knowledge, to investigate the marine-human system under climate change and identify societal adaptation options. Stakeholders were engaged through personal interviews, two local workshops, and a web based survey, identifying the most relevant ecosystem services potentially impacted and developing an integrated system dynamics model which links climate change scenarios to the response of relevant species. Stakeholder perceptions of temperature-dependent multiannual fluctuations of fish stocks, interactions among fish, marine mammal, and seabird populations, and ecological processes such as primary production are represented in the model. The model was used for a discourse-based stakeholder evaluation of potential ecosystem changes under ocean warming and acidification scenarios, identifying shifts in ecosystem service provision and discussing associated societal adaptation options. The results pointed to differences in adaptive capacity among user groups. Small-scale fishers and tourism businesses are potentially more affected by changing spatial distribution and local declines in marine species than industrial fisheries. Changes in biodiversity, especially extinctions of polar species, and ecosystem functioning were a concern from an environmental conservation viewpoint. When considering potential additional impacts of ocean acidification, changes observed in the model projections were more uniformly valued as negative, and associated with an increased potential for conflicts among user groups. The stakeholder-informed ecosystem modeling approach has succeeded in driving a discussion and interchange among stakeholder groups and with scientists, integrating knowledge about climate change impacts in the social-ecological system and identifying important factors that shape societal responses. The approach can thus serve to improve governance of marine systems by incorporating knowledge about system dynamics and about societal uses and values.

Description: Global climate change affects marine fish through drivers such as ocean warming, acidification and oxygen depletion, causing changes in marine ecosystems and socioeconomic impacts. While experimental and observational results can inform about anticipated effects of different drivers, linking between these results and ecosystem-level changes requires quantitative integration of physiological and ecological processes into models to advance research and inform management. We give an overview of important physiological and ecological processes affected by environmental drivers. We then provide a review of available modelling approaches for marine fish, analysing their capacities for process-based integration of environmental drivers. Building on this, we propose approaches to advance important research questions. Examples of integration of environmental drivers exist for each model class. Recent extensions of modelling frameworks increase the potential for including detailed mechanisms and improving model projections. Experimental results on energy allocation, behaviour and physiological limitations will advance the understanding of organism-level trade-offs and thresholds in response to multiple drivers. More explicit representation of life cycles and biological traits can improve description of population dynamics and adaptation, and data on food web topology and feeding interactions help to detail the conditions for possible regime shifts. Identification of relevant processes will also benefit the coupling of different models to investigate spatial–temporal changes in stock productivity and integrated responses of social–ecological systems. Thus, a more process-informed foundation for models will promote the integration of experimental and observational results and increase the potential for model-based extrapolations into a future under changing environmental conditions.