The understanding and role of uncertainty and risk in climate change adaptation: local and central authorities in Norway

A common claim is that emerging and future climate change is rendering traditional conceptions of uncertainty and risk obsolete. This is because a changing climate makes it quite a challenge to calculate uncertainties, establishing the measurable uncertainty as the basis for quantifying risk. Approaches that are capable of accommodating and possibly countering the wickedness caused by increasing uncertainty are necessary, the argument holds. Following up on previous studies of learning–knowledge and adapting to a changing climate, this article provides an analysis of how differences in the understanding of uncertainty and risk inform and determine governmental adaptation policies and actions of the local and central government in Norway, also discussing governance implications. The study finds that the understanding of uncertainty and risk generally is poor at the local level, but better at the state level, especially among highly educated staff with a background in, for example, natural sciences and engineering. On the other hand, a traditional understanding of uncertainty and risk is dominating: seeking to establish measurable uncertainty as a basis for quantifying risk. The article discusses combining different approaches of uncertainty and risk, thereby introducing a broader basis for governance, also implying multi-level network governance. On the one hand, this may help the local–central government in handling wicked problems of adapting to a changing climate but on other hand, it also possibly nurture struggles between different knowledge bases and stakeholder interest, thereby fuelling the wickedness of adaptation policies.     

The impact of flooding on property prices: A repeat-sales approach

In this paper we use a repeat-sales model to analyse the price path of properties affected by flooding in England between 1995 and 2014. Our dataset contains information on 4.8 million houses with at least one repeat-sale. This database is merged with high-definition GIS data delineating the spatial extent of all recorded flood incidents in England covering a total area of 2,654 km². Our results show that immediately after a flood event the price of property in a postcode entirely inundated by inland flooding is on average 24.9% lower than non-flooded property, whereas for property in a postcode entirely inundated by coastal flooding the price reduction is 21.1%. Nonetheless, we find that this discount is short-lived and the discount is no longer statistically significant for properties affected by inland flooding after 5 years, which falls to just 4 years for properties affected by coastal flooding. For lower-priced properties however, the post-flood price discount can be observed up to 6–7 years for both inland and coastal flooding. The magnitude of the impact also depends on the characteristics of the properties, the characteristics of the flood and the existence of flood protection assets.     

Numerical analysis of non-constant pure rate of time preference: A model of climate policy

When current decisions affect welfare in the far-distant future, as with climate change, the use of a declining pure rate of time preference (PRTP) provides potentially important modeling flexibility. The difficulty of analyzing models with non-constant PRTP limits their application. We describe and provide software (available online) to implement an algorithm to numerically obtain a Markov perfect equilibrium for an optimal control problem with non-constant PRTP. We apply this software to a simplified version of the numerical climate change model used in the Stern Review. For our calibration, the policy recommendations are less sensitive to the PRTP than widely believed.     

A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation

In this study we combined an extensive database of observed wildfires with high-resolution meteorological data to build a novel spatially and temporally varying survival model to analyze fire regimes in the Mediterranean ecosystem in the Cape Floristic Region (CFR) of South Africa during the period 1980-2000. The model revealed an important influence of seasonally anomalous weather on fire probability, with increased probability of fire in seasons that are warmer and drier than average. In addition to these local-scale influences, the Antarctic Ocean Oscillation (AAO) was identified as an important large-scale influence or teleconnection to global circulation patterns. Fire probability increased in seasons during positive AAO phases, when the subtropical jet moves northward and low level moisture transport decreases. These results confirm that fire occurrence in the CFR is strongly affected by climatic variability at both local and global scales, and thus likely to respond sensitively to future climate change. Comparison of the modelled fire probability between two periods (1951-1975 and 1976-2000) revealed a 4-year decrease in an average fire return time. If, as currently forecasted, climate change in the region continues to produce higher temperatures, more frequent heat waves, and/or lower rainfall, our model thus indicates that fire frequency is likely to increase substantially. The regional implications of shorter fire return times include shifting community structure and composition, favoring species that tolerate more frequent fires.     

The response of the woodpigeon (Columba palumbus) to relaxation of intraspecific competition: A hybrid modelling approach

The recent rapid growth of the woodpigeon population in the British Isles is a cause for concern for environmental managers. It is unclear what has driven their increase in abundance. Using a mathematical model, we explored two possible mechanisms, reduced intraspecific competition for food and increased reproductive success. We developed an age-structured hybrid model consisting of a system of ordinary differential equations that describes density-dependent mortality and a discrete component, which represents the birth-pulse. We investigated equilibrium population dynamics using our model. The two hypotheses predict contrasting population age profiles at equilibrium. We adapted the model to examine the impacts of control measures. We showed that an annual shooting season that follows the period of density-dependent mortality is the most effective control strategy because it simultaneously removes adult and juvenile woodpigeons. The model is a first step towards understanding the processes that influence the dynamics of woodpigeon populations.