Nikolas Kuschnig (p)

In this paper, I present a modelling approach to jointly investigate connectivity between observations and its consequences — spillover effects.The approach is fully Bayesian, and uses hierarchical shrinkage priors to flexibly provide regularization where needed and let the data speak where it is possible. I make the prior information that is embodied in the restrictive assumptions of previous spatial models explicit, and loosen them by estimating connectivity parameters. For effective estimation, I develop efficient sampling procedures and a Gaussian process approximation to evaluate Jacobian determinants.

Alexander Kaiser (p)

Nonparametric analyzes of regional agricultural production is frequently motivated by sustainability goals. In theory, an efficient allocation of production inputs and increased production outputs induced by innovations and technical progress could allow to save on scarce natural resources while simultaneously expanding the provision of food and fiber. Policy recommendations derived from two-stage analyzes thus confidently advise policy makers and farmers to modernize, specialize or scale up to counteract technical inefficiency. In this paper two major objections are presented to these conventions within the agricultural economics literature. First, we show that when spatially differing climatic conditions are sufficiently considered in two-stage analyzes, conventional policy recommendations are not valid anymore. Second, we argue that from a production-theoretic point of view, the traditionally employed technical efficiency model fails in providing information on sustainability of agricul-tural production. We thus suggest to conceptually decompose technical efficiency into an operational and a physical efficiency measure. For the period 2004 to 2018, we find a stagnating trend in physical productivity in the agricultural sectors of 122 European regions. In conjunction with the subordinate role of contextual to environmental determinants of inefficiency we propose to neither motivate studies with sustainability goals by default nor derive policy recommendations whenever the impact of environmental factors is not sufficiently considered.

Richard Cupillard (p)

Urbanization processes are considered as major causes of biodiversity decline and other environmental issues because they create more competition between land uses. In this paper, we consider the case of a French urban area, and we focus on the role of ecological connectivity in biodiversity conservation. We apply optimal location models to address land use competition issues in an urban space on which environmental policies are implemented. More precisely, we use RICP to identify sites that are critical for local biodiversity, i.e., those whose elimination would be the most harmful for local fauna. Our study area is the SCoT du Dijonnais, an urban zone consisting of 59 municipalities around the city of Dijon, north-eastern France. To observe the number and type of the species sampled at the SCoT and SCoT+ levels, we use the most exhaustive multi-taxon database on regional biodiversity. Using RICP, we are able to quantify potential biodiversity loss if some municipalities decided to exit or to deviate from the urban planning document and then to abandon the collectively-defined biodiversity targets. Preliminary results show that if the municipality with the highest species richness was removed from the SCoT du Dijonnais, then 74.82% of local biodiversity would be under a potential local extinction risk. This rate increases as the number of municipalities to be interdicted rises, so that the elimination of 32 municipalities would potentially lead to disappearance of local species diversity.