1. Assessing Ecological Changes in Freshwaters using Statistical Models Claire Ferguson Adrian Bowman, Marian Scott Laurence Carvalho (CEH, Edinburgh) http://www.antarcticconnection.com/antarctic/science/images/climate2.jpg A Case Study of Loch Leven

2. Loch Leven Dataset Length of dataset: 1968 - 2002 150 variables measured, covering… Physics Lake chemistry Lake biology Weather Sampling frequency: weekly to monthly Gaps in data: 1984, 1986-87

3. Loch Leven – Trends trend – a pattern in the long run average over time

4. Loch Leven – Seasonality seasonality – a yearly cyclic pattern in monthly data

5. For each key variable: Model: Correlated Errors (V ) based on AR(1) correlation. Circular smoother incorporated for month term (month 12 effect joins up smoothly with month 1 effect). Additive Models

6. Log SRP p-value = 4.0 x 10 -4 p-value = 0

7. Log NO 3 -N p-value = 0.011p-value = 0

8. Log Chlorophyll a p-value = 6.0 x 10 -5 p-value = 9.5 x 10 -7

9. Log Chlorophyll a

10. Log SRP - Seasonally p-value = 0.05 p-value = 0.09 p-value = 0.04 p-value = 0.05

11. Conclusions Additive and nonparametric regression models – Flexible tools for modelling Non-parametric trends and seasonality simultaneously with correlated errors. Changes in seasonality throughout time. Nonparametric trends within each season. Methodological modifications are required including circular smoothers and correlated errors.

12. Other Work Modelling chlorophyll a in terms of nutrients, water temperature and Daphnia. To explore: Lagged relationships Effects of covariates Changing relationships over time Modelling multiple responses of chlorophyll a and Daphnia to incorporate feedback relationships.