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

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

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

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

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

Water temperature & solar radiation Oreti at Three Kings Manapouri Aero Met Station May Jul Sep Nov Jan Mar May 2006 2007 May Jul Sep Nov Jan Mar May 2006 2007

Hydrographs for focal rivers Median

Dynamics of didymo in the Oreti River Biomass (g AFDM m-2) % periphyton cover 2006 2007 2006 2007 Basic q is how D abundance changes over time – What is going on with Didymo at infested rivers KBI 2006 2007

Dynamics of didymo in the Mararoa R 2006 2007 2006 2007 2006 2007

Dynamics of didymo in the Waiau River 2006 2007 2006 2007 2006 2007 Year

Relationships between didymo & environmental variables. 1 Relationships between didymo & environmental variables. 1. Instantaneous flow Biomass = -121.1(Froude number) + 79.2 R2 = 0.03, P < 0.0001, N = 889 Biomass = -71.7(velocity) + 79.2 R2 = 0.04, P < 0.0001, N = 889 Oreti River Oreti River Mararoa River: Biomass = -65.7 (velocity) + 116.2 R2 = 0.03, P < 0.0001 Biomass = -88.3 (Froude) + 112.5 R2 = 0.02, P = 0.0002

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

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

Hydrographs for focal rivers Median

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

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

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

Invertebrate communities in didymo-affected rivers

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

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

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

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).

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.

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

Cheers to Stu and Bill