Conference Agenda

Human activities with global scale impacts are rapidly changing the planet, in particular in the Arctic and sub-Arctic seas due to polar amplification of climate change. These developments are making an uncertain future even more unknown and could perhaps trigger abrupt changes. Much of our current Arctic and sub-Arctic knowledge and data were collected under different social and ecological conditions from today. To better guide future stewardship efforts, we may need to combine multiple types of knowledge and recognize the intertwined properties of change, including different scales and sources. Here we review methods from multiple fields and highlight whether and how they can contribute to the analysis of connectivity, time scale differences, diversity and redundancy, and uncertainties, all of which are important aspects of social-ecological systems dynamics. We then illustrate how these methods can be combined to study and plan for change, building on experiences from six case studies of fisheries in the Arctic and Sub-Arctic seas.

Oceans provide essential benefits to people and the economy. These benefits are underpinned by the functioning of marine ecosystems and the presence of ocean-based or “blue” capital. However, blue capital is increasingly at risk as human activities and climate change drive the loss and degradation of marine biodiversity and coastal infrastructure. Despite these growing threats, the impacts of climate change on the oceans and their societal repercussions have been largely overlooked and are not included in influential indicators such as the social cost of carbon. To address this omission, we integrate the latest ocean science and economics into a climate-economy model, capturing the climate impacts on corals, mangroves, seaports, fisheries, and mariculture to estimate their welfare repercussions at a global scale. We estimate the social cost of carbon for the ocean (blue SCC) to be $62 [47-90, interquartile range] per ton of CO2 in 2020, representing one third of the current U.S. estimate, which excludes ocean-related impacts. Half of the blue SCC comes from damages to fisheries and mariculture, one third from corals, followed by damages to mangroves (17%) and maritime ports (3%). Most of the blue SCC comes from nonmarket use values (e.g., nutrition value of fisheries and mariculture) and non-use values (e.g., the existence value of corals); market values (e.g., revenues from port-based trade) are significant but quantitatively small. These findings underscore the critical need to account for ocean-based welfare in climate policy, providing valuable insights for greenhouse gas mitigation efforts and sustainable ocean management strategies.

We study the management of natural resources that are weakly connected and exhibit tipping behaviour in their dynamics. We obtain approximate feedback optimal management rules of networks of weakly interaction natural resource systems by developing the value function with respect to the interaction strength. The method is general and rigorous, and allows to treat the effects of multiple interactions, stochastic dynamics, and multiple decision makers, without suffering from the curse of dimensionality.

Globally, many fisheries have experienced collapse even though most of these fisheries had management plans with harvest control rules and were supported by scientific modelling that explicitly accounted for uncertainty. Recognizing that an informed decision on risks of a stock collapse versus harvest is only possible when the outcomes of the technical measures are described explicitly. We propose that the cumulative probability of stock collapse over a range of harvest levels would provide a perspective of the future consequences of harvesting decisions. Adding to the harvest level negotiations the consideration of how long a fishery should sustain the livelihoods of fishers may provide managers, fishers, and other stakeholders with a more tangible understanding of the risks within the context of precautionary principles in decision-making. We use a time series from the Canadian Cod fishery of the Southern Gulf of St. Lawrence, from which we construct and calibrate a simplified model as an emulator of more comprehensive models to demonstrate the approach. The implications of adding an analysis of the probabilities of stock collapse for a range of harvest levels and using a risk matrix to inform decision-making are discussed for four selected years 1974, 1986, 1993, and 2017.