Temporal and spatial monitoring of eutrophication variables in CEMP

Typ: Rapport
Serie: RO 38
Författare: Philip Axe
Publicerad:

Sammanfattning

The OSPAR Revised Eutrophication Monitoring Programme (ETG 05/3/Info.1-E) requests that nutrient "monitoring should include sufficient samples to confirm that the maximum winter nutrient concentration has been determined", while para. 7 of the Terms of Reference for the preparation of guidance on the spatial and temporal resolution of monitoring for nutrients and eutrophication effects (ICG 003) states that "there are at least nine different water types covered by the OSPAR Maritime Area"..."guidance must, therefore, be at least complex enough to cover each type with sufficient clarity to guide contracting parties in their evaluation of the temporal and spatial coverage required to adequately assess the relevant water body". This document summarises the national reports submitted to the OSPAR Intersessional Correspondence Group on Eutrophication Monitoring, and highlights common problems faced in the monitoring of (primarily) inorganic nutrients and chlorophyll. In addition, it presents tests of different approaches to solving the spatial and temporal sampling problems associated with delivering marine eutrophication data. Based on tests of model data, monthly sampling appears adequate to give a good estimate of annual mean concentrations. Buoy data suggests that this would not be sufficient where there is tidal variability. It was not possible to determine maximum concentrations through a practical ship sampling scheme, or by using extreme value statistics. The optimum sampling programme to observe rapid events is likely to be a combination of ferrybox systems, which appear to be reliable and give both good spatial and temporal coverage, combined with buoy observations. To ensure data of sufficient quality, these must be controlled against conventional research vessel observations. Research vessels still have a role in seasonal mapping, and in providing data of sufficient quality for trend analysis from a large area. This is likely to remain so, at least until technologies such as gliders and optical nutrient sensors become widely available and capable of delivering reliable, high quality data.