Evaluating modelled natural capital values for planning processes: A case study in Stockholm, Sweden

Abstract: A commonly proposed principle for reducing impact on natural capital within the planning process is the mitigation hierarchy. The mitigation hierarchy means that impacts should primarily be avoided, otherwise minimized, and when this is not possible - restored or compensated according to an equivalency- and proximity principle. The outcome can be calculated in a model such as the Green Space Factor to achieve a certain goal, such as net gain. However, it is unclear how the levels and principles work in practice. There is also an indication about transparency issues in relation to the mitigation hierarchy within Green Space Factor. At the same time, the potential of a new model called NATURE Tool has been highlighted in Sweden, which creates a need for scientific studies. The aim of this study was therefore to evaluate modelled natural capital values based on the mitigation hierarchy in Green Space Factor and NATURE Tool. By comparing natural capital value changes of scenarios which contained poor and proper mitigation approaches, it was possible to evaluate how the models output reflected consideration to the mitigation hierarchy as well as the natural capital value changes derived from each level. A case study located in Stockholm, Sweden, was used to test the models through subjective sensitivity analysis. The mixed natural environment within the area consists of pine and deciduous forest, rock outcrop, grassland and individual trees. The results showed that NATURE Tool did not allow poor mitigations to the same degree as Green Space Factor and that NATURE Tool presented the results more transparently. At the same time, poor mitigations in Green Space Factor would not have been possible if the recommendations in the manual were followed. Furthermore, it is debatable whether the definition of poor mitigations in the models gives actual poor mitigations in reality. The study also showed that Green Space Factor needed less area and fewer compensatory measures given the net gain goal compared to NATURE Tool, indicating that either Green Space Factor was underestimating, or NATURE Tool was overestimating the natural capital values. The study finally showed that the total natural capital value change due to the mitigation hierarchy levels was highest for compensation compared to the earlier levels in mitigation hierarchy (avoidance, minimization and restoration). However, the previous levels were more space efficient compared to compensation. This shows that although the previous levels are more effective, compensation can play an important role in reaching net gain. The study's main finding is that the models could generate relatively high natural capital values also for poor mitigation approaches. Further model development should consider ensuring that such substitution does not generate similar results as proper mitigation approaches. This could be done by calibrating the models to a database of observations. Developing the communication strategies of the models may also encourage proper mitigation strategies.