Andrew Davies Supervised by Dr. Mark Johnson and Dr. Christine Maggs

1. Effects of grazing and wave exposure on Ascophyllum densityin Strangford Lough over different temporal scales Andrew Davies Supervised by Dr. Mark Johnson and Dr. Christine Maggs School of Biology and Biochemistry, Queen’s University Belfast

2. Background • Historical observations point to a major decline in Ascophyllum density. • Very little work has been done on Ascophyllum communities and the interaction with limpets. • Only 20 years ago the shores were dominated by Ascophyllum communities, so what has happened?

3. Typical sheltered Ascophyllum shore NILS (1986)

4. Mahee Island. • I-R Aerial imagery. • Loss of Ascophyllum over 30 year period. 1969 1997

5. Grazed Ascophyllum area Marlfield

6. Limpets grazing on Ascophyllum fronds Strangford

7. Biological Interactions

8. Limpet Feeding Preferences • Hypotheses / Aims • Prove there is a biological interaction between limpets and Ascophyllum. • Limpets will consume Ascophyllum even in the presence of an alternative food source. • Higher densities will consume significantly more Ascophyllum.

9. Limpet Feeding Preferences • Using tanks, set-up to imitate the rise and fall of the tide controlled using a timing system (LT: 12am / 12pm, HT: 6am / 6pm). Constant Flow in Direction of flow Solenoid Solenoid

10. Palmaria palmata Ascophyllum Fucus spiralis Limpet Limpet Feeding Preferences • 2 densities (5 limpets / 10 limpets) • 2 replicates • 3 choices of algae, Palmariapalmata, Fucusspiralis or Ascophyllum • Sampling every 3 days. • Limpets starved 5 days before start of experiment.

11. Limpet Feeding Preferences • 5 limpets: A clear divide between Ascophyllum and Fucus / Palmaria. • 10 Limpets: All algae appear to be consumed at similar levels.

12. Limpet feeding preferences • A significant different between the amount of Ascophyllum consumed at different densities (ANOVA p=0.041).

13. Conclusions • Limpets will consume Ascophyllum even with the presence of a readily available and potentially more palatable food source. • Limpets do not exhibit a preference for Ascophyllum. • Higher densities of limpets and thus more competition lead to substantially more consumption of Ascophyllum.

14. Physical habitat

15. Exposure In Strangford • With increased grazing damage, will changes in exposure cause further loss? • Ascophyllum is found almost exclusively on sheltered shorelines. • Any change in the strength of waves to the shore may have drastic effects on the community. • Use of localised wind data and fetch models to predict areas of high exposure. • UKCIP • Estimates of sea level change by the 2050s range between 13 cm and 74 cm. The coastal zone will experience rapid change over the next century. • Decadal trends in the NAO will increase, with significant “larger than natural” variation occurring by 2050, causing significantly more westerly winds. • The general picture is for an increase in wind speed in winter.

16. Wind data • UK Met Office Data. • Ballywatticock, Lough Cowey and Downpatrick. • 1 reading of speed and direction per day at 0900. • Standardised to 280 days year -1, to account for missing data (years with >25% data missing are excluded). • Killough. • Hourly readings of speed, direction and max gust speed and direction per hour.

17. Wind data Average wind speed, for Downpatrick ( --) (R2 = 0.22, P = 0.084), Lough Cowey ( --) (R² = 0.415 p= 0.001) and Ballywatticock ( --) (R² = 0.046 p= 0.349) • Large amounts of localised variation, even between sites that are relatively close together. • Suggests that assumptions of wind driven processes cannot be made from distant datasets.

18. Wind data Proportion of wind events exceeding near gale (>25 knots), for Downpatrick ( --) (R² = 0.1, P = 0.911), Lough Cowey ( --) (R² = 0.16 p= 0.05) and Ballywatticock ( --) (R² = 0.038 p= 0.313) • Again, localised variation present between sites. Downpatrick appears to be more exposed to wind events greater than 25 knots. • The strength and direction of wind is controlled by the topography of the surrounding landscape. Supporting arguments for the usage of local data.

19. Wind data • The model is dependent upon the strength and the direction of the wind. Strong winds along a long fetch distance increase the level of potential exposure. • Wind patterns follow large scale patterns. Average wind direction can change over the years. Direction of gale and near gale events Downpatrick

20. Model generation • Sample Points 500m apart. • Fetch distance measured at 10 degree intervals. • To generate the exposure index requires: • Weighted average of wind (speed / gales / occurrence) to bearing. • Fetch length and bearing. • For each bearing, the fetch length is multiplied with the weighted average of wind. The mean is taken per site and used in construction of output.

21. Model output • Frequency of wind events, Lough Cowey dataset. Strangford

22. Model output • Frequency of wind events, Lough Cowey dataset. Strangford

23. Model output • Frequency of near gale events, Lough Cowey dataset.

24. Model output • Frequency of near gale events, Lough Cowey dataset.

25. Conclusions • Need to factor in the three local wind data sets to create a cohesive picture. • Model successfully identifies areas that are potentially becoming more exposed. • Even with the confusing pattern of wind strengths, the model still demonstrates change. • Model shows wind speed may not be the best determinant of exposure and intricate changes in the direction may influence wind-wave generation to a greater degree.

26. General Conclusions • Established a biological interaction between limpets and Ascophyllum. • Wind-wave model indicates variable sea state, with evidence for changing exposure over time.