A network optimisation approach to identify trade-offs between socio-economic and ecological objectives for regional integrated planning

Integrated regional planning aims to achieve sustainable development by considering multiple socio-economic, environmental, and ecological goals. However, determining the synergies and trade-offs between sustainability goals is a challenging task that requires an in depth analysis of the system-level effects of the implementation of planning policies. For example, polycentricity (i.e. multiple urban centres) is a common regional urban planning goal, which has shown to be beneficial for a region’s socio-economic conditions, but may also change the configuration of the settlement network (i.e. settlements connected by roads and traffic). Given the dependency of animal species on well-connected habitat networks, another possible planning goal is to maximise habitat availability (i.e. the total amount of habitat that is accessible for an individual animal). However, changes to a region’s settlement network can have a variety of impacts on the region’s habitat networks. Due to these interactions, it is unclear whether maximising polycentricity and habitat availability are compatible planning goals. To address this question, we developed a mathematical model of interacting settlement and habitat networks in a region of Switzerland. The settlement network model allowed us to predict commuter and traffic flows in our study region under a certain distribution of jobs and people across the municipalities. The level of polycentricity in our region was measured by calculating the hierarchy in the commuter flow network. The traffic flow network was linked to the habitat network, which was used to calculate the mean habitat availability. With multi-objective optimisations, both polycentricity and habitat availability were maximised by changing the distributions of jobs and people. Although both goals could be improved compared to the current situation, there was a trade-off between polycentricity and habitat availability along the Pareto front. Developing the region towards either of the planning goals could be achieved by changing the distribution of jobs and people mainly in mid-sized municipalities and by a strong collaboration between municipalities. Our results increase the understanding of the complex interactions in urban regions and can lead to recommendations for integrated urban and conservation planning.