Sammendrag
The main objective of these studies was to utilize the large amount of co-occurring fauna and chemical data collected in different contamination zones around offshore installations to derive ecologically relevant protection levels for marine benthic communities on the Norwegian Continental Shelf (NCS). The data used are collected in regular monitoring surveys in the vicinity of oil- and gas installations at the NCS and stored in the OLF-database (OLF = The Norwegian Oil Industry Association). The methods developed in this thesis try to integrate chemical and biological criteria to provide better and more ecologically relevant guidance in environmental management and risk assessment.
In the first study we developed a novel approach to derive field-based species sensitivity distributions (f-SSDs) and field-data-derived sediment quality guidelines (SQGs) based on concurrent data of sediment chemistry and the abundance of common benthic species (I). The f-SSDs may be used as benchmarks for probabilistic risk assessment and the SQGs can be used as site specific guidelines or integrated into existing SQGs. A 50% decrease in abundance of 5% (HC5, the 5% Hazardous Concentration) of the taxa was used as a measure of effect. The effect concentrations of sensitive benthic species were derived by ordinary least square regression (OLS). To try to strengthen the link between ecological theories and our response model and to reduce the effect of confounding factors, the ecological concept of limiting factors (Liebig’s law of the minimum) was incorporated in constructing f-SSDs, by using quantile regression methods to quantify the limiting response functions along contamination gradients (II). The practicalities of the f-SSDs approach in other polluted areas and on a smaller scale were investigated by deriving f-SSD and site specific SQGs for the marine environment of Hong Kong (III). In this study, the data screening criteria of acceptable minimum resolution on the y-axis (abundance) was also tested. Our result suggested that it is possible to halve or more than halve the maximum abundance from the original criteria of 100 individuals per species, in the Hong Kong environment (dataset).
Rare species constitute a major part of the species richness in marine benthic ecosystems (25% - 60%, in these studies depending on scales and definitions). Without knowing the sensitivity of these rare species towards chemicals, it is impossible to know whether a predefined protection level (e.g. HC5) can be protective to 95% of species in biological assemblages. We utilized the f-SSD approach to investigate whether field-data derived SQGs for common benthic species are likely to be protective also for rare species; using both real field data and computer simulated species distributions (V). Our results suggest that rare benthic species, as a group, are relatively tolerant towards the contamination levels found around offshore installations on the NCS. Inclusion of our estimates of rare species sensitivity had little effect on both the shape of the original f-SSD and the SQGs estimates for all examined chemicals, except barium, suggesting that the majority of rare species are also protected in our previously estimated SQGs for the NCS.
All SQGs derived from the f-SSDs approach (I, II, III, IV) were in general more conservative than the existing guidelines derived from laboratory test data; suggesting that benthic fauna on the NCS are affected at lower concentrations than used in international guidelines presently in operation. In some cases our highest estimated effective concentrations for sensitive species were lower than the suggested threshold levels in use, e.g. for PAHs (polycyclic aromatic hydrocarbons) from HK waters. Interpreting the currently used SQGs in countries worldwide to the potentially affected fraction of species in our f-SSDs translates to a protection level that would on average protect around 80% of the investigated taxa (II, III). The reason for an observed effect at lower contaminant concentration levels in these studies may be due to: (1) differences between biological and environmental conditions in the field and laboratory and (2) differences between guidelines derived for single contaminants and for a mixture of contaminants.
Experience shows that multivariate analyses techniques (e.g. Nonmetric MultiDimensional Scaling, NMDS) are well suited to detect changes in species composition in benthic biological communities. Multivariate analyses techniques were therefore used to test the results from the SSDs studies, and to test the hypothesis that setting SQGs at 4-times background concentrations will give sufficient protection for the benthic fauna on the NCS (V). Slightly disturbed fauna assemblages were identified in 121 contamination gradients, incorporating more than 2,000 species from different habitats and geographic regions on the NCS. The contamination levels in sediment samples having disturbed fauna were compared with the levels in control samples, and if statistically significantly different, they were used to estimate the effect level for structural disturbance of the benthic communities. Our results from this study supported the f-SSD-analysis in that benthic fauna on the NCS are affected at lower levels than existing SQGs, but also demonstrated the need for more site-specific SQGs. The protection levels derived using the f-SSDs approach (II) was too low (i.e. overprotective) in habitats with naturally occurring high metal concentrations and too high (i.e. underprotective) in habitats with natural occurring low metal concentrations. Our hypothesis that setting SQGs at 4-times background concentrations in various habitats will give sufficient protection for the benthic fauna on the NCS may be a useful rule of thumb for metals, as the overall background concentrations eliciting effect was 3.6 times. In the same gradients, the total hydrocarbon levels eliciting effect ranged, on average from 26 mg/kg to 99 mg/kg.
The increase in abundance of known opportunistic species at increasing contamination levels provides strong evidence of a pollution induced disturbance in the benthic communities. We utilized this to develop a simple biotic index (BIOSTRESS) based on the relative abundance of only five well-known opportunistic polychaetes species that are common in polluted sediments (VI). Its performance to detect changes in community structure was comparable to NMDS in sediment samples with relatively high hydrocarbon levels (> 50 mg/kg).
The results from these studies emphasize the need for better integration of ecology within the field of ecotoxicology. It highlight the importance of establishing field monitoring programs and appropriate database for chemical and biotic data so that we better can better assess the actual risk and effect of contamination on natural ecosystems. Our results provided favourable evidence in support of the use of the f-SSD approach and multivariate analysis to derive ecologically relevant SQGs with a view to protecting the natural biological assemblage.