Patterns in the microbial community Patterns in the microbial community structure in Swan River Estuary

Alice I. Gedaria, Prof. Tony O’Donnlell and Matthew Alice I. Gedaria, Prof. Tony O Donnlell and Matthew R. Hipsey

School of Earth and Environment, Faculty of Natural and Agricultural Sciences, University of Western Australia

Outline of Presentation

* Background* Research Objectives* Approach and methodology

– Field work– Flow cytometric analysisy y– Microscopic analysis

* Results and on going work

Harmful Algal BloomsHarmful Algal Blooms

•May cause harm through the production oftoxins or by their accumulated biomass

•Can affect co-occurring organisms and alterfood-web dynamicsfood web dynamics.

Impacts include human illness and•Impacts include human illness andmortality following consumption of orindirect exposure to HAB toxins

* Substantial economic losses to coastalcommunities and commercial fisheries

Swan River Estuary, WA

Major Bloom Occurrences2000 – Microcystis aeruginosa2003 Karlodinium micrum2003 - Karlodinium micrum

(syn. K. veneficum)

Controls on Phytoplankton Controls on Phytoplankton Blooms/Biomass

• Light– TurbidityTurbidity– Colour (DOC)

N i• Nutrients– Nitrogen (N), Phosphorous (P)( ) ( )– micro-nutrients

• Salinity Temperature• Salinity, Temperature• Biological (eg. grazing, viral infection)

– Hodgkin 1987:

Studies on Swan Primary Production

Hodgkin, 1987:• Salinity as the “master factor”

– John, 1987; Chan and Hamilton, 2001:, ; ,• Freshwater runoff and salt wedge evolution control succession

– Thompson and Hosja, 1996; Thompson 1998:• N as key limiting nutrient

– Kostoglidis et al., 2005; Harris et al., 2008:• CDOM and light climate highly variable• CDOM and light climate highly variable

– Hamilton et al., 2006:• Large spatial and temporal variability in biogeochemistry –a ge spat al a d te po al va ab l ty b ogeoc e st y

“high primary productivity need not be linked to a single limiting factor but were likely a response to coexisting environmental factors”

Main Objective of the Study

To gain an improved understanding of theinteractions of different microbial groups such asbacteria, phytoplankton and virus-like particles inSwan RiverSwan River

♦ seasonal/spatial timescale♦ seasonal/spatial timescale

♦ relation to hydrodynamics

♦ nutrient loading and cycling processes

Specific Objectives of the Study:

♦ Develop a novel microbial data set using flow cytometricanalysis- explore population structure and variability- gain insights of its physiological condition

♦ Improve our ability to understand and quantify nutrient flowthrough the ecosystem

i t ti b t i i t i t di l d i- interaction between inorganic nutrients, dissolved organicmatter and the microbial groups

♦Further develop our understanding of microbial ecology in the estuary- improved ability to predict likely impacts of environmental improved ability to predict likely impacts of environmental change to nutrient budgets, algal ecology and river health

Microbial dynamics in a temperate seasonal estuary

Microbial Community

Copepods Macro-grazers Micro-grazerslank

ton

Copepods Macro grazers Micro grazers

kton

Zoo-

pl

Chlorophytes

lank

ton

Mic

ro-p

lan

CryptophytesDinoflagellatesDiatoms

ktonN

ano-

plM

Pico-eukaryotes

(mixed, 0.2-2um)

Prochlorococcus(small cyano, <1um)

Synechococcus

(cyano, 0.8-1.5um)

Pico

-pla

nk

Bacteria Viruses/Phages

Pri

o/Vi

rio

ankt

on

/ g

Bact

e-p

la

Microbial Communityto

n

Copepods Macro-grazers Micro-grazers

Zoo-

plan

kt

on-pla

nkto

nZ

Chlorophytes

ano-

plan

kto

Mic

ro-

CryptophytesDinoflagellatesDiatoms

Pico-eukaryotes Prochlorococcus Synechococcus

plan

ktonN

a

(mixed, 0.2-2um) (small cyano, <1um) (cyano, 0.8-1.5um)

Pic

o-iri

on

Bacteria Viruses/Phages

Bac

terio

/Vi

-pla

nkto

nB

Methodology

Laboratory Protocol DevelopmentLaboratory definition and optimisation

Field Sampling Routine sample collections and strategic experiments 

Laboratory AnalysisFlow Cytometry and MicroscopyFlow Cytometry and Microscopy 

Data Analysis Seasonal and spatial  trends

Field SamplingField Sampling

Swan River Estuary

• Microtidal• Microtidal

• Seasonal variability in freshwater inflow

• Stratification: vertically homogenous (summer), two layer stratified system (winter)

• pioneering work in conducting microbial monitoring studies microbial monitoring studies (spatial/temporal)

Me e e tMeasurements

Properties Measurement

Physical Salinity, Temperature , Dissolved Oxygen, pH 

Chemical properties Ammonia  (NH3 ‐N), Nitrite and  Nitrate  , Soluble  Reactive 

Phosphorous (SRP) , Total Nitrogen/Phosphorous , DissolvedPhosphorous (SRP) , Total Nitrogen/Phosphorous , Dissolved 

Organic C arbon  (DOC,  Silica  (SiO2 ‐Si), Diss olved Organi c 

Nitrogen (DON),  Alkalinity (CaCO3)

Flow Cytometric Counts bacteria, pico and nano phytoplankton,  Virus ‐like  particles 

(VLP’s )(VLP’s )

Microscopic Cell  Counts diatoms, dinoflagellates, cryptophytes,

chlorophytes, cyanobacteria, euglenophytes,  raphidophytes p y y g p y p p y

Microscopic AnalysisMicroscopic Analysis

• Quantitative/Qualitative enumeration of phytoplankton

Bi l l l i• Biovolume calculation

Flow Cytometric Analysis

A B C

Flow Cytometric plots of picophytoplakton populations A) forward scatter vs. chl-a b) side scatter vs. chl-a and c) Accessory pigments (orange fluorescence)

vs. chl-a

Trends & patterns of various microbial S R Egroups along Swan River Estuary

Seasonal abundance: Autumn and winter

Seasonal Abundance: Spring and summer

Seasonal Carbon Distribution: Summer

Seasonal Carbon Distribution: Winter

Data AnalysisCharacterization of general microbial patterns (spatio-temporal)

♦ Pico‐plankton – how many? what are they doing? 

♦ Bacteria and virus – how many? what are they doing?

♦ Nano‐plankton – compare with microscopic data 

♦ Compare estuary gradients & seasonal changesg

♦ Link to environmental and nutrient driversnutrient drivers

♦ Statistical correlation b t d ibetween groups and various physico‐chemical  drivers

Management Implications

• Dynamics of pico/nano communityHi hl i bl– Highly variable

– Significant contribution to biomass & primary production

• Pico-plankton highly correlated with nutrientsCorrelation with N is high suggesting N as primary driver– Correlation with N is high, suggesting N as primary driver

• Viral patterns indicate potential for bottom up control• Viral patterns indicate potential for bottom up control

• Use to develop quantitative estimation of nutrient flux pathways • Use to develop quantitative estimation of nutrient flux pathways for different seasons/states

• Improved ability to develop ecosystem model

Acknowledgement♦ Dr. Matthew Hipsey, SEE-UWA

♦ Dr. Tony O’Donnell, FNAS-UWA

♦ Swan River Trust

♦ Drs. Kathy Heel and Paul Rigby- Centre for Microscopy, Characterization and Analysis, UWA

♦ Phytoplankton Ecology Unit, Department of Water

♦ Water Science Branch, Department of Water