The potential ecological effects of the sand mining activities for Maasvlakte 2 have been identified in an Environmental Impact Assessment (EIA). One of the identified effects in this EIA was an impact on the number of sea ducks in the Natura 2000 area 'Voordelta'. The sand mining activities will cause an increase of the silt concentration along the North Sea coast. Subsequently the light intensity in the water column decreases. A change of the light intensity can affect the growth of phytoplankton. An impact on the growth of phytoplankton can finally affect higher-order species in the food chain: phytoplankton is eaten by bivalves and bivalves form the main food of sea ducks like eiders.
Within this so-called impact-effect chain from sand mining to sea ducks, a large number of uncertainties play a role. In the EIA safe assumptions were used for a lot of these uncertainties. The final predicted impact is a result of the accumulation of several safe assumptions. Therefore, the probability of occurrence of this predicted impact will be small. Information on this probability of occurrence will be useful in the discussion about the necessity of mitigating and compensating measures. The main objective of this thesis is to give insight in the probability of occurrence of the possible effects of sand mining on sea ducks in the Voordelta.
The research started by analysing which uncertain factors and processes have a large influence on the final result. A Monte Carlo analysis was used to take the uncertainties of these factors into account in the modelling of the ecological effects. Probability density functions were estimated for the relevant variables and were finally combined in the Monte Carlo analysis. From the results of the Monte Carlo analysis probability distribution functions for the impact of sand mining on eiders are derived. These probability distribution functions show that the probability that the sand mining activities for Maasvlakte 2 have a significant effect on eiders in the Voordelta is very small and can be considered negligible.
In this thesis is shown that giving insight in the probability of occurrence of significant ecological effects by using a probabilistic analysis is possible. The methodology that is used in this thesis is also expected to be applicable for the assessment of ecological effects of other human activities.