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The Swedish wolf population has rebounded from near extinction in the 1960s to around 365 individuals in 2020, after the implementation of the Hunting Act (jaktlagen) in 1966. This recent increase in the wolf population has evoked a serious divide between "pro-wolf" and "anti-wolf" Swedish citizens. Despite the continuous efforts by the Swedish government to reconcile this antagonism, the conflicts are persistent with a sign of impasse. In this paper, we present a modelling tool, which can bring transparent and "structured dialogue to the opposing positions." This approach includes a stylized framework for quantitative modelling of stakeholders' satisfaction levels regarding their preferred size of the wildlife population in question, based on the concept of satisfaction functions. We argue that this framework may contribute to conflict resolution by bringing a common understanding among stakeholders, facilitate a societal discourse, and potentially help to assess likely support for conservation policies. We present a showcase application of this modeling tool in the context of the conflict over the Swedish wolf conservation policies. The model is informed using a thorough literature review as well as interviews, which identified relevant stakeholder groups and respective drivers of their attitudes towards wolves.

In July 2020, the European External Action Service of the European Commission launched a public consultation on the way forward for the European Union's Arctic policy. The consultation was held to re-examine the role of the EU in Arctic affairs, to revise the priorities of the current Joint Communication on an integrated European Union policy for the Arctic and the actions thereunder, and to identify possible new policy areas to be developed. As part of its work within the NDI Think Tank Action, IIASA responded to this call addressing specific questions of this public consultation. This paper presents the submitted material and provides further reflections on the discussed matters from the Northern Dimension perspective.

Reliable estimates of indirect economic losses arising from natural disasters are currently out of scientific reach. To address this problem, we propose a novel approach that combines a probabilistic physical damage catastrophe model with a new generation of macroeconomic agent-based models (ABMs). The ABM moves beyond the state of the art by exploiting large data sets from detailed national accounts, census data, and business information, etc., to simulate interactions of millions of agents representing \backslashemph{each} natural person or legal entity in a national economy. The catastrophe model introduces a copula approach to assess flood losses, considering spatial dependencies of the flood hazard. These loss estimates are used in a damage scenario generator that provides input for the ABM, which then estimates indirect economic losses due to the event. For the first time, we are able to link environmental and economic processes in a computer simulation at this level of detail. We show that moderate disasters induce comparably small but positive short- to medium-term, and negative long-term economic impacts. Large-scale events, however, trigger a pronounced negative economic response immediately after the event and in the long term, while exhibiting a temporary short- to medium-term economic boost. We identify winners and losers in different economic sectors, including the fiscal consequences for the government. We quantify the critical disaster size beyond which the resilience of an economy to rebuild reaches its limits. Our results might be relevant for the management of the consequences of systemic events due to climate change and other disasters.