Abstract
Urbanization leads to land-use changes and landscape fragmentation, impacting natural habitats and their connectivity. In principle, many local decision-makers are obliged to adopt a mitigation hierarchy whereby development projects must be designed to avoid impacts on biodiversity, reduce, and ultimately compensate for the remaining impacts to reach the goal of no net loss (NNL) of biodiversity. In practice, however, both developers and regulators lack relevant practical tools to support their strategies to better anticipate and plan this mitigation hierarchy. More importantly, the available tools generally ignore connectivity issues and ecological constraints. Here, we propose an original methodology that anticipates future urban needs under different development scenarios and selects the most relevant strategies for biodiversity offsets (BO). We used a spatialized digital simulator (called SimUrba) to model fine-scale urban dynamics, combining it with ecological networks modelling based on graph theory to assess the environmental impacts of urbanization on a habitat connectivity index for focal species. We test the different outcomes produced by adopting two offset ratios (1:1 and 2:1) using this approach. The methodology is applied to empirical data on the future urban sprawl of a large French city up to 2040 under two realistic development scenarios currently discussed by policy-makers, and on 20 species that we grouped by type of habitat. Our results reveal that that the most highly impacted species are those associated with open and semi-open areas, and cultivated plots. Then, we identify the most promising cells for BO implementation to compensate for negative effects on habitat area, according to gains in habitat connectivity. We further show that using both private and public land can maximize habitat connectivity by including larger plots and reducing the number of plots needing long-term monitoring. Finally, we demonstrate that using standard offset ratios that ignore connectivity issues is very risky and can compromise any BO objective. Overall, we show that this framework provides decision-makers with a valuable and precise strategic tool that articulates land-use planning with ecological constraints to identify whether, how and where NNL objectives can be achieved.