1. Ecological studies of Didymosphenia geminata in New Zealand, 2006-2007
Scott Larned
David Arscott
Neil Blair
Bill Jarvie
Don Jellyman
Kathryn Lister
Marc Schallenberg
Stu Sutherland
Kay Vopel
Bob Wilcock

2. The problems Near absence of information about
Environmental factors that control didymo abundance and distribution
Effects of didymo on river ecosystems
Need for quantitative relationships to predict
Didymo abundance as a function of environmental factors
Ecosystem responses to variation in didymo abundance

3. Two approaches to didymo ecology
Environmental factors that control didymo
Flow-related variables
Herbivory
Eco-physiological cycles
Effects of didymo on river ecosystems
Invertebrates
Fish
Water chemistry

4. Outline Environmental setting Time-course of didymo abundance
Relationships between didymo &environmental variables
Structure of invertebrate assemblages
Relationships between invertebrate assemblages & didymo abundance

5. Focal rivers & sampling reaches
Mararoa R
Waiau R
Excelsior Cr
Oreti R

6. Water temperature & solar radiation
Oreti at Three Kings
Manapouri Aero Met Station
May Jul Sep Nov Jan Mar May
May Jul Sep Nov Jan Mar May

7. Hydrographs for focal rivers
Median

8. Dynamics of didymo in the Oreti River
Biomass (g AFDM m-2)
% periphyton cover
Basic q is how D abundance changes over time – What is going on with Didymo at infested rivers
KBI

9. Dynamics of didymo in the Mararoa R

10. Dynamics of didymo in the Waiau River
Year

11. Relationships between didymo & environmental variables. 1
Relationships between didymo & environmental variables. 1. Instantaneous flow
Biomass = (Froude number)
R2 = 0.03, P < , N = 889
Biomass = -71.7(velocity)
R2 = 0.04, P < , N = 889
Oreti River
Oreti River
Mararoa River: Biomass = (velocity) R2 = 0.03, P <
Biomass = (Froude) R2 = 0.02, P =

12. Relationships between didymo abundance & environmental variables. 2
Relationships between didymo abundance & environmental variables. 2. Solar radiation
Mararoa River
Oreti River

13. Relationships between didymo abundance & environmental variables. 3
Relationships between didymo abundance & environmental variables. 3. Water temperature

14. Hydrographs for focal rivers
Median

15. Relationships between didymo abundance & environmental variables. 4
Relationships between didymo abundance & environmental variables. 4. Flood flows in the Oreti
Oreti River

16. Relationships between didymo abundance & environmental variables. 4
Relationships between didymo abundance & environmental variables. 4. Flood flows in the Mararoa
Removal is offset by delivery

17. Relationships between didymo abundance & environmental variables. 4
Relationships between didymo abundance & environmental variables. 4. Flood flows in the Waiau

18. Invertebrate communities in didymo-affected rivers

19. Invertebrate – didymo relationships, Oreti R
Didymo biomass (g AFDM m-2)
Didymo biomass (g AFDM m-2)
Didymo biomass (g AFDM m-2)

20. Invertebrate – didymo relationships, Mararoa R
Sites from upstream to downstream:
Red - Normans White - Haycock Hills
Yellow - Station Br Green – Princhester Cr
Black - Key Br

21. Invertebrate – didymo relationships across rivers
Mararoa R.
Oreti R.
Waiau R.
Invertebrate size structure:
No detectable effect of didymo
biomass on abundance-weighted
lengths of 4 most common taxa:
Deleatidium spp., Zelandobius spp.,
Orthocladiinae, Oligochaeta
Appr 8% of variability in invertebrate assemblages is explained by didymo biomass
Factor 1 scores vs. didymo
biomass: r = 0.43
Principle components analysis of log-
transformed invertebrate densities

22. Summary
Floods are a primary environmental control on didymo abundance, instantaneous flow variables are not. Seasonal cycles in growth are unknown.
Macroinvertebrate densities & biomass generally increase with increasing didymo abundance.
Proportions of EPT invertebrates generally decrease with increasing didymo abundance.
Direct effects of didymo on invertebrate assemblages are not large (e.g., < 10% variability explained by didymo abundance).

23. Future research needs
Continued didymo and invert monitoring to encompass a broader range of site & flow conditions. This will improve predictive power, expand scope of predictions, & reduced influence of individual events.
Baseline data on fish responses (abundance, composition, behavior) to didymo.
Targeted monitoring to improve information about didymo tolerance limits.
Mechanistic information about flow-didymo interactions.

24. Acknowledgements NIWA Christchurch analytical lab Cawthron Institute
Chris Cunningham, Sarah Braithwaite, Catherine Chague-Goff
Cawthron Institute
Karen Shearer, Yvonne Stark & invertebrate lab
MAF BNZ
Christina Vieglais & team
EAWAG
Chris Robinson

25. Cheers to Stu and Bill