1. III. RESULTING TRENDS OF SOME CONTAMINANTS
4Demon: Centralisation and valorisation of 4 decades of biota contaminant data in the Belgian Part of the North Sea (BPNS)
Bekaert Karen1, Hong Minh Le2, Ruth Lagring2, Ann Ruttens³, Nadia Waegeneers³, Bart Ampe1, Bavo De Witte1
1. Institute for Agricultural and Fisheries Research (ILVO), Belgium  +32(0)59/
2. Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
3, Sciensano, Service Trace Elements and Nanomaterials, Tervuren, Belgium
I. INTRODUCTION
II. THE MODEL
A linear mixed effects model (lme) was applied to assess temporal and spatial distribution of contaminants in biota in the BPNS. This is a linear regression model with fixed effect variables i.e. explanatory variables or predictors but also including a random effect term.
The fixed effect variables in our model were:
time,
time²
season
cluster zone (for shrimp and swimming crab)
groyne (for mussel)
laboratory analytical method
interaction term between time and cluster
tissue (only for flounder, liver or muscle)
The random effect included in the model was the station where the sample was taken.
As part of the 4DEMON project, 40 years of marine pollution data in sediment and biota was centralized from various data sources. A quality check was performed on the data (coordinates, units, duplicates,…) resulting for biota in a dataset of no less than analyt values with metadata including those of heavy metals and polychlorinated biphenyls (PCBs). The data were valorized by performing long-term trends modelling of shrimp (Crangon crangon), swimming crab (Liocarcinus spp.), mussel (Mytilus edulis) and flounder (Platichthys flesus) on the BPNS. The BPNS was divided into clusters following the Ward hierarchical clustering (1963) for the modelling of shrimp and swimming crab. 1 5 4 3 2
Figure 1: map of BPNS divided into different cluster zones
III. RESULTING TRENDS OF SOME CONTAMINANTS
IV. DISCUSSION
V. CONCLUSION
Most of the contaminants in biota show a downward trend. However, arsenic in mussel, chrome in swimming crab and shrimp, and cadmium in swimming crab tends to increase, contrarily as what was observed in sediment (results not shown here). The reasons for this could be the feeding and metabolism of the animals, the way organisms were sampled over 40 years (tissue or size differences) or the bioavailability of contaminants.
The model output gives a view on PCB and heavy metal pollution on the BPNS on a large time frame:
Most of the contaminants tend to decrease
There are few differences in trend between cluster zones for the same species
There are some differences in trends between species
Pictures: copyright Hans Hillewaert
4DEMON project funded by