1. Limitations and solutions to the exchange of macrobenthos community data between scientists and CZM managers in the frame of human impact monitoring studies in SW Netherlands NIOO, Netherlands Institute of Ecology, Centre for Estuarine and Marine Ecology Korringaweg 7, P.O. Box 140, 4400 AC Yerseke, The Netherlands Herman Hummel, Bart Schaub, Wil Sistermans, Mieke Rietveld, Rinus Markusse, Ko Verschuure, Olaf van Hoesel, Tom Ysebaert, Dick van Oevelen, Peter Bot & Peter Herman RIKZ, the Dutch Governmental Institute of Coasts and Sea, Den Haag, the Netherlands RIKZ

2. Presentation content: 1. Why monitoring of macrobenthos 2. Present-day problems regarding monitoring 3. Problem 1: Data stored but not analysed Data stored but not analysed 6. Solution to problem 2: Correspondence analyses Correspondence analyses Adjustment of sampling strategy Adjustment of sampling strategy Example: Grevelingen - impact abiotic factors Example: Grevelingen - impact abiotic factors 4. Solution to problem 1: Analyses of data - time series, ordination Analyses of data - time series, ordination Example: Grevelingen - major changes, not observed before Example: Grevelingen - major changes, not observed before 5. Problem 2: Causal relationships Causal relationships Mismatch of data-series Mismatch of data-series

3. Benthic organisms are suitable indicators for changes in environmental quality, because of : - their sessile character - relatively long life-span Thereby, benthic organisms - integrate environmental fluctuations and influences - at a particular place over a relatively long time span 1. Why monitoring of macrobenthos

4. The aim of the long-term studies on benthos is to obtain insight in: - natural development of estuarine and coastal areas - the anthropogenic influences in those areas Such in order to help coastal managers: - saveguard natural resources - allow optimal use of a system’s potentials 1. Why monitoring of macrobenthos

5. As most monitoring programma’s this kind of continuous long-term assessment (= many data) is perfect to detect: - small deviations from a standard or norm - over a long-term - in a large area Year-to-year changes may not be significant, but longer series of data may reveal trends 1. Why monitoring of macrobenthos

6. In the Netherlands TWO major PROBLEMS arise in the present-day evaluation and use of the monitoring data (mainly because of restricted funding). 2. Present-day problems regarding monitoring

7. Basic data are stored by funding governmental agencies often without any further processing and analyses. By that the benefit of monitoring-programmes is debated: - projects were costly - yet did not yield a proper end-product for the end-users (managers and the public in large) The first problem is: 3. Problem 1: data storage and analysis

8. Use new techniques which allow us to analyse and visualise monitoring data in a limited time and at (relatively) limited costs: - advanced databases - statistical analyses (e.g. ordination, correspondence analyses) - internet communication (web-pages) Solution to problem 1: data storage and analysis 4. Solution to problem 1: data storage and analysis

9. The Grevelingen example Visualisation of a long-term (10-year) data-set showed for the brackish lake Grevelingen dramatic changes in macrobenthos species composition - 4. Grevelingen example 1: data storage and analysis

10. - without having been noticed before by managers. - dramatic changes in macrobenthos species composition 4. Grevelingen example 1: data storage and analysis

11. In case of “ so what ?! “ remarks it may be helpful to communicate on changes in commercial species 4. Grevelingen example 1: data storage and analysis

12. Next step is a statistical analysis of the data by means of correspondence analyses Showed influence of : - year - season - depth 6-45 m0-2 m Spring Autumn 4. Grevelingen example 1: data storage and analysis

13. Next step is a statistical analysis of the data by means of correspondence analyses Showed influence of : - season - depth 1990 1999 - year (independent of depth and season) depth and season) 3 1 5 6 7 4 2 8 4. Grevelingen example 1: data storage and analysis

14. Thus a strong temporal evolution 4. Grevelingen example 1: data storage and analysis

15. Our second problem therefore is: - coastal managers nowadays ask for causal relationships - relations to (changes in) environmental quality The question arises: What are the causes of the changes ? Whereas we have only information on large-scale long-term processes 5. Problem 2: Causal relationships

16. Solution to problem 2: causal relationships More detailed information is needed on: - temporal and spatial dynamics in distribution of benthic populations (short-term / small scale) populations (short-term / small scale) - environmental variables 6. Solution to problem 2: causal relationships

17. Possible relationships, i.e. causes for the changes in Grevelingen ? - sedimentation of organic matter and silt (esp. in the deeper parts) more sediment surface feeders, more worms more sediment surface feeders, more worms - higher salinity, disappearance of seagrass-beds disappearance of seagrass-beds disappearance associated fauna disappearance associated fauna - high concentration of pollutants decrease in numbers / biomass of sensitive species decrease in numbers / biomass of sensitive species - lower light penetration change of primary production change of primary production decrease of suspension feeders or grazers decrease of suspension feeders or grazers 6. Grevelingen example 2: causal relationships

18. 1990-2002 West 1990-2002 East 1982-2002 Dreischor Benthos environmental variables Mismatch between benthos and environmental data 1972-1985 data 6. Grevelingen example 2: causal relationships

19. Nereis succinea Hydrobia ulvae

20. Relation with light penetration and freshwater inflow from polders 6. Grevelingen example 2: causal relationships More freshwater from polders > Lower light penetration > Lower light penetration > Lower benthic primary production > Lower benthic primary production > Decrease of epiphytic grazers > Decrease of epiphytic grazers

21. Relation with TBT 6. Grevelingen example 2: causal relationships All these relationships need further examination and verification Decrease TBT Still high TBT levels > imposex in molluscs > imposex in molluscs > decrease in numbers > decrease in numbers

22. Conclusion: In addition to a better use and co-ordination between existing long-term large-scale monitoring programmes a different type of integrated monitoring, at short-term and small-scale is desirable

23. Thank you