In the Netherlands, the probabilistic analysis of cause-effect chains was applied for the first time in ‘A probabilistic analysis of the ecological effects of sand mining for Maasvlakte 2’ (Van Kruchten, Y.J.G. , 2008). This study showed that it is possible to give insight into the probability of occurrence of ecological effects by using a probabilistic analysis.
The study focused on the possible impact of the sand extraction activities for Maasvlakte 2, the Netherlands, on protected sea-ducks in the nature reserve Voordelta. The results showed that the probability of occurrence of significant effects (in the sense of the Birds Directive) was very small, which was valuable information in the discussion about the necessity of implementing mitigating- or compensating measures. In ‘Knowledge – Cause – effect chain modelling of sand mining using Sandwich terns‘, the probabilistic analysis was applied to assess the cause-effect chain from dredging activities to Sandwich Terns. The methodology is applied on a fictitious case, which shows how the probabilistic analysis can be used if effects on Sandwich Tern populations are expected.
Applying a probabilistic analysis in cause-effect chain modelling is particularly useful, if the deterministic modelling requires very conservative or even worst-case assumptions. In such cases, the probabilistic approach can make the difference between a very conservative and a realistic estimate of effects. If the deterministic approach is based on realistic assumptions, a probabilistic analysis will still provide extra information, viz. the probability density function of the effect. Using a probabilistic approach for the simulation of the impact of dredging on mussels by a Dynamic Energy Budget model (see Knowledge – Cause – effect chain modelling of sand mining using mussels) turned out to have little benefits, because the deterministic estimate provided enough information. Even if no conservative assumptions in the deterministic model are needed, a probabilistic approach can still be useful to place the estimated ecological impact in the context of natural variability.