A PhytoplanktonMethods ManualforAustralian Freshwaters

Gertraud Hötzel and Roger Croome

Published by: Land and Water Resources Research and Development CorporationGPO Box 2182Canberra ACT 2601Telephone: (02) 6257 3379Facsimile: (02) 6257 3420Email: public@lwrrdc.gov.au

WebSite: www.lwrrdc.gov.au

© LWRRDC

Disclaimer: The information contained in this publication has been published by LWRRDC to assist publicknowledge and discussion and to help improve the sustainable management of land, water andvegetation. Where technical information has been prepared by or contributed by authors external tothe Corporation, readers should contact the author(s), and conduct their own enquiries, beforemaking use of that information.

Publication data: ‘A Phytoplankton Methods Manual for Australian Freshwaters’, LWRRDC Occasional Paper 22/99.

Authors: Ms Gertraud Hötzel and Dr Roger CroomeDepartment of Environmental Management and EcologyLa Trobe University Albury–Wodonga CampusP.O. Box 821Wodonga VIC 3689Telephone: (02) 6058 3885Facsimile: (02) 6058 3888Email:thotzel@awcnet.aw.latrobe.edu.aur.croome@aw.latrobe.edu.au

ISSN 1320-0992ISBN 0 642 267715

Editing and layout: Green Words & Images, Canberra

Printing:

October 1999

iii

Contents

Glossary ..................................................................................................................................................vi

List of abbreviations ............................................................................................................................viii

Acknowledgments ...............................................................................................................................viii

Executive summary ............................................................................................................................... 1

1. Introduction ....................................................................................................................................... 3

2. Objectives of phytoplankton monitoring ........................................................................................ 5

2.1 Objectives of the phytoplankton methods manual ....................................................................................................... 5

2.2 Objectives of phytoplankton sampling ......................................................................................................................... 5

2.3 Design of phytoplankton monitoring programs ........................................................................................................... 6

3. Taking samples ................................................................................................................................... 8

3.1 Sampling in rivers ........................................................................................................................................................ 8

3.1.1 Site selection .................................................................................................................................................... 8

3.1.2 Location within the river .................................................................................................................................. 8

3.1.3 Sampling methodology .................................................................................................................................... 8

3.2 Sampling in standing waters ....................................................................................................................................... 10

3.2.1 Site selection .................................................................................................................................................. 10

3.2.2 Sampling methodology .................................................................................................................................. 12

3.3 Sampling in estuaries .................................................................................................................................................. 14

3.3.1 Site Selection ................................................................................................................................................. 14

3.3.2 Sample collection ........................................................................................................................................... 14

3.4 Frequency and timing of sampling ............................................................................................................................. 15

3.5 Phytoplankton nets .................................................................................................................................................... 15

3.6 Sample containers ...................................................................................................................................................... 15

3.7 Preservation, transport and storage ............................................................................................................................. 15

4. Analysis of samples .......................................................................................................................... 17

4.1 Enumeration .............................................................................................................................................................. 17

4.1.1 Microscope requirements ............................................................................................................................... 17

4.1.2 Subsampling preserved samples ...................................................................................................................... 17

4.1.3 Concentration of phytoplankton by gravity ................................................................................................... 18

4.1.4 Removal of buoyancy ..................................................................................................................................... 19

iv

4.1.5 Turbidity ........................................................................................................................................................ 19

4.1.6 Choice of chamber ......................................................................................................................................... 19

4.1.7 Counting with the Utermöhl chamber ........................................................................................................... 22

4.1.8 Counting with the Sedgwick-Rafter chamber ................................................................................................. 23

4.1.9 Counting with the Lund cell .......................................................................................................................... 24

4.1.10 Statistics of counting ...................................................................................................................................... 25

4.1.11 Remarks on counting filaments and colonies .................................................................................................. 27

4.1.12 Taxonomic identification ............................................................................................................................... 28

4.1.13 Recording results ............................................................................................................................................ 29

4.1.14 Algal coding system........................................................................................................................................ 29

4.1.15 Details of code ............................................................................................................................................... 30

4.1.16 ‘Dumping ground’ categories ......................................................................................................................... 31

4.1.17 Software for counting ..................................................................................................................................... 31

4.1.18 Area Standard Units (ASU) ............................................................................................................................ 32

4.2 Semi-quantitative enumeration .................................................................................................................................. 32

4.2.1 Concentration by filtration ............................................................................................................................ 32

4.3 Biomass measurements ............................................................................................................................................... 32

4.3.1 Volumetric biomass determination ................................................................................................................. 32

4.3.2 Chlorophyll-a ................................................................................................................................................ 33

5. Quality assurance ............................................................................................................................ 34

5.1 Quality assurance ....................................................................................................................................................... 34

5.2 Reporting of data ....................................................................................................................................................... 36

6. Staff ................................................................................................................................................... 37

6.1 Occupational health and safety issues ......................................................................................................................... 37

6.2 Training .................................................................................................................................................................... 37

7. Guidance on introducing a new method ...................................................................................... 39

References ............................................................................................................................................ 42

Appendices ........................................................................................................................................... 45

Appendix A List of agencies involved in development of this manual, including contact officers ...................................... 45

Appendix B Lugol’s solution............................................................................................................................................. 46

Appendix C Algal taxonomic literature ............................................................................................................................ 46

Appendix D Recommended field and laboratory equipment ............................................................................................ 48

Appendix E Examples of ‘Phytoplankton field sampling sheet’ and ‘Algal counting sheet’ ............................................... 50

Appendix F Hosepipe sampler .......................................................................................................................................... 52

Appendix G Taylor sphere sampler (TASS) ...................................................................................................................... 53

Appendix H Taylor integrated sampler (TISA) ................................................................................................................. 55

v

Index...................................................................................................................................................... 57

Tables

Table 3.1 Methods for taking phytoplankton samples in rivers ........................................................................................... 9

Table 4.1 Higher taxa codes for algae ............................................................................................................................... 31

Figures

Figure 3.1 Suggested sampling sites in a weir pool ............................................................................................................ 10

Figure 3.2 Suggested sampling sites in a large reservoir ..................................................................................................... 12

Figure 3.3 Possible vertical distribution of different algae in a stratified lake ..................................................................... 13

Figure 4.1 Microscopic details for Utermöhl method ....................................................................................................... 18

Figure 4.2 Quantitative algal enumeration with Utermöhl chamber ................................................................................. 20

Figure 4.3 Diagram of Utermöhl chamber ....................................................................................................................... 21

Figure 4.4 Diagram of Sedgwick-Rafter chamber with coverslip in ‘fill position’ ............................................................... 22

Figure 4.5 Diagram of Lund cell with coverslip in place ................................................................................................... 22

Figure 5.1 Quality assurance in algal enumeration ........................................................................................................... 35

Figure F.1 Diagram of hosepipe sampler ........................................................................................................................... 52

Figure G.1 Diagram of Taylor sphere sampler .................................................................................................................. 54

Figure H.1 Diagram of Taylor integrated sampler ............................................................................................................ 56

vi

Glossary

Accuracy The closeness of a measured orcomputed value to its true value.

Advected Moved downstream with thecurrent.

Alga A non-stem-forming plant, mayvary in size from microscopic singlecell organisms to gigantic seaweeds.

Algal unit The natural formation a speciesoccurs in; for example, single cell,filament or colony.

Anthropogenic Made or caused by humaninfluence.

Aqueous solution Solution based on water.

Autochthonous (Energy or matter) derived fromwithin the waterbody.

Benthos Organisms that live on and in thesediment of waterbodies, often onlyfor part of their life cycle.

Biomass The amount of biological materialpresent.

Benthic algae Algae that live on or in thesediment of a waterbody; oftendiatoms, but also mats ofcyanoprokaryotes.

Chrysophyte An alga of the class Chrysophyceae,typically having two flagella, a redeyespot, yellow-brown chloroplastsand often silica scales on the outside(eg. Synura).

Colony A group of algal cells of the samespecies that normally live togetherbut can function separately.

Cyanobacteria See ‘cyanoprokaryotes’.

Cyanoprokaryotes A group of very primitive, alga-likeorganisms (previously calledcyanobacteria) that do not containany cell structures. Contain blue-coloured accessory pigments(phycocyanin and phycoerythrin)which mask the green chlorophyll.Some species form blooms whichmay be toxic.

Cyanoprokaryote Substances formed bycyanoprokaryotes that act as liverand nervous toxins in animals andhumans.

Diatom An alga of the classBacillariophyceae, characterised by asilicified cell wall (frustule) andyellow-brown chloroplastscontaining fucoxanthin.

Diatom frustule The silicified cell wall of a diatomcell, consisting of two halves, theepivalve and the hypovalve.

Diurnal On a daily basis.

Detritus Non-living organic matter.

Dominant The species which is most abundantin the waterbody.

Enumeration The scientific counting andsimultaneous identification of algalcells.

Epilimnion The mixed surface layer in astratified waterbody.

Ergonomic A physical workplace arrangementdesigned to prevent operator injuryfrom long-term overstrainingbecause of wrong posture.

Eutrophication The progressive enrichment ofsurface waters with nutrients. Thisprocess can be anthropogenic oroccur naturally.

Euphotic zone The water column between thesurface and the depth at which thelight intensity is 1% of that at thesurface (Schwoerbel, 1970).

Filament A type of algal colony in which cellsare adjoined to each other to form achain-like structure.

Flagellates Unicellular organisms; for example,algae that have a flagellum and aretherefore motile.

Flagellum A whip-like structure occurring inmotile algae which propels the cell.

toxins

vii

Gas vesicles Gas-filled intracellular membranestructures in cyanoprokaryoteswhich regulate buoyancy.

Habitat The specific environment anorganism lives in. Examples ofhabitat for algae include anywaterbody, moist soil, on stones orother plants and hot springs.

Halocline Layer of largest density change in awaterbody due to salineconcentration.

Homogeneous Uniform.

In situ Directly in the waterbody, not in thelaboratory.

Inverted light Used to count algae; objectives aresituated underneath the stage.

Lentic Standing waterbody.

Lotic Flowing water.

Macrophytes Rooted aquatic plant with stems andleaves; can be submerged oremerged.

Meroplanktonic Organisms that live partly in theplankton and partly on thesediment.

Metalimnion Steep density gradient between theepilimnion and the hypolimnion instanding waterbodies.

Mixed zone The well-mixed, warmer surfacelayer of a stratified waterbody.

Motile The ability of an alga to propelitself, mostly by means of aflagellum or through mucussecretion (in diatoms).

Multiple counter A mechanical apparatus to registercounts for several categoriessimultaneously. Commonly used forbacteriological and algal counts.

Nanoplankton Phytoplankton species with a cellsize from 2 µm to 20 µm.

Nomenclature The rules on which taxonomiccategories are based and which forman ordering system for organismsbased on their evolutionarysimilarity.

microscope

Photomicrograph A photographic picture taken of anobject through a microscope.

Phycologist A biologist specialising in the studyof algae.

Phytoplankton Algae that live suspended in thewater.

Picoplankton Phytoplankton species with a cellsize from 0.2 µm to 2 µm.

Plankton Community of plants(phytoplankton) and animals(zooplankton) of microscopic sizewhich are adapted to suspension inwater and which are liable to passivemovement by wind and current.

Plankter A member of the plankton.

Poisson Similar to a normal distribution buttruncated on the left-hand side closeto the mean. Describes theprobability of random occurrencesin space or time; for example, thedistribution of algal cells in a watersample.

Potamoplankton True river plankton, which sustainsitself and grows under riverconditions.

Precision The closeness of repeatedmeasurements of the same quality.

Primary producer Organism which builds organicsubstances from inorganic materialusing photosynthesis to capturelight energy. All plants are primaryproducers.

Retentive zones Parcels of water under the banks orin backwaters which areincompletely mixed with the bulk ofthe flow and might act as incubatorsfor phytoplankton.

Stratification Formation of layers of differentdensity (temperature, conductivity)within a waterbody which canprevent the exchange of smallparticles and gases between thelayers.

Thermocline The plane at which greatesttemperature change occurs withdepth in a stratified waterbody.

distribution

viii

Taxon Any category used in theclassification and identification ofliving organisms; for example, class.

Transect A strip across the bottom of acounting chamber.

Vacuole An intracellular membrane structurecontaining an aqueous solution;often takes up a considerablevolume of the cell.

Whipple graticule A graticule, inserted in one of themicroscope eyepieces, with a squareof 1 mm x 1 mm etched onto it.The square is divided into 100smaller squares.

Zooplankton Organisms feeding on particles andliving in the plankton; for example,the water flea Daphnia.

AcknowledgmentsWe would like to acknowledge the support of, and manyhelpful discussions with, individual contact officers fromthe water resource agencies listed in Appendix A,particularly those with whom we had detaileddiscussions about individual algal counting procedures.We are grateful to Petrina Praitt and Vasele Hosja forcontributing the section on estuaries. We owe manythanks to Derek Cannon for critical reading of themanuscript and helpful suggestions.

The development of this phytoplankton methodsmanual was funded under both the National RiverHealth Program (managed by the Land and WaterResources Research and Development Corporation[LWRRDC]) and the National EutrophicationManagement Program (managed by LWRRDC and theMurray-Darling Basin Commission).

List of abbreviationsANZECC Australian and New Zealand

Environment and ConservationCouncil

APHA American Public Health Association

ARMCANZ Agriculture and Resource ManagementCouncil of Australia andNew Zealand

ASU Area Standard Units

EPA Environment Protection Authority

GPS Global Positioning System

ISO International Organization forStandardization

LWRRDC Land and Water Resources Researchand Development Corporation

NATA National Association of TestingAuthorities

PAR photosynthetically active radiation

PET polyethylene terephthalate

TASS Taylor sphere sampler

TISA Taylor integrated sampler

UNESCO United Nations Educational Scientificand Cultural Organization

1

The Phytoplankton Methods Manual for AustralianFreshwaters describes suitable methods for the sampling,fixation, preservation, identification and enumeration ofphytoplankton in Australian surface waters, andrecommends procedures for quality control, data storageand occupational health and safety. While covering allaspects of phytoplankton monitoring in Australia andproviding benchmark methods, the manual leaves manychoices and flexibility to the user. Guidelines for allaspects of phytoplankton monitoring in Australianfreshwaters are provided without attempting to imposea strict national standard. The manual has beendeveloped after extensive consultation with and inputfrom algal workers and water managers within theAustralian water resource industry and gains part of itssignificance from this process.

Potential users of the manual are algal workers(people who do the counting) and water quality andwater resource managers (people who design and runthe programs and analyse the data). The documentaddresses their needs for undertaking routinemonitoring as well as research-orientated programs.

Although the manual deals with all phytoplankton,it contains many specific recommendations on thesampling and counting of cyanoprokaryotes (blue-greenalgae), for example, dealing with potentially toxic scumor buoyancy. The Agriculture and ResourceManagement Council of Australia and New Zealand’s‘National protocol for the monitoring of cyanobacteriaand their toxins in surface waters’ (Jones, 1997b) dealsspecifically with the management of cyanoprokaryoteblooms by government bodies and is complementary toThe Phytoplankton Methods Manual for AustralianFreshwaters. Where appropriate, cross-references havebeen made and consistency in methods has been agreedwith the Agriculture and Resource ManagementCouncil of Australia and New Zealand National AlgalManager.

The imperative for monitoring phytoplanktonpopulations is to understand and manage the ecologicalfunctioning of our standing and running waters. Theterm ‘phytoplankton’ encompasses all suspendedmicroalgae in a waterbody belonging to all taxonomicalgal groups and includes the cyanoprokaryotes or blue-green algae. Phytoplankton, together with other aquaticplant life, are the primary producers in aquatic

ecosystems and form the basis of the food web.Freshwaters are complex systems in which a componentcan only be managed if its links to the others are wellunderstood. Phytoplankton is particularly sensitive toinorganic and organic nutrient levels and heavy metals,and responds to changes in nutrient levels faster and atan earlier stage of pollution than other groups oforganisms. Due to their short life cycle, planktonic algaerespond quickly to environmental changes and are thusa valuable indicator of water quality.

Objectives of phytoplankton monitoring inAustralia and elsewhere are numerous and vary fromcase to case (see section 2.2, ‘Objectives ofphytoplankton sampling’). While this manual providesguidelines for the design and conduct of phytoplanktonmonitoring programs, it is recommended that eachprogram be designed by an experienced algal ecologistwith appropriate statistical advice. A monitoringprogram will always be specifically designed for thewaterbody in question and cannot be transferred toother waters. The manual contains, apart from the puretechnical information, a wealth of limnologicalbackground information relevant to the design andrunning of phytoplankton monitoring programs.

For most monitoring programs, data on thedevelopment of the phytoplankton population (ie.species composition and abundance) are collected.Often, chlorophyll-a concentration is also determined asa measure of phytoplankton biomass. The objectives ofa monitoring program will determine the associatedcosts. The more specific the identification of the algae isrequired to be, the higher the costs of analysing asample. For example, if taxonomic identification tospecies level is required (as is the case for most blue-green algae programs) adequately trained staff must beemployed and the time required for counting thesample and cost of the program necessarily increase.

Information on sampling site selection in runningand standing waters and details on how to takerepresentative samples are given in chapter three.Considerations for sampling weir pools and reservoirsare included. The preservation, transport and storage ofalgal samples is discussed in detail.

Field and laboratory procedures for the analysis ofalgal samples are detailed in chapter four, giving achoice of three different counting chambers, all

Executive summary

2

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

currently used in Australia. Statistical backgroundinformation pertaining to algal counting is given,addressing issues of accuracy and precision of countingresults. Chapter five provides recommendationsregarding quality control and quality assurance matters,while occupational health and safety issues and trainingfor field and laboratory work are discussed in chaptersix. It is pointed out that regular and meaningfultraining of field staff does increase sample quality andaccuracy of data and therefore justifies the additionalcosts involved. In the event of a laboratory wanting tochange to a new method, chapter seven details how toproceed with the changeover.

Much useful and practical information is containedin the appendices. In addition to an extensive list oftaxonomic algae literature, including relevant Australianmaterial, field and laboratory standard data sheets andlistings of required equipment are presented.

3

In 1995, under the Monitoring River Health Initiative,a project was initiated to develop a phytoplanktonbioassessment protocol for Australian rivers. There weretwo reasons for the project:

1. To include phytoplankton as a representative ofprimary producers in the spectrum of organisms tobe used to assess ‘river health’.

2. To meet the need for a generally agreed manual forphytoplankton assessment in Australian rivers foruse by the water resources industry. The manual waspublished in 1998 as LWRRDC Occasional Paper18/98 and is superseded by the current manualwhich, due to industry demand, includes, amongother additions, a section on standing waters andestuaries. While covering all aspects of phytoplanktonmonitoring in Australia and providing benchmarkmethods, the current manual leaves many choices andflexibility to the user. The Agriculture and ResourceManagement Council of Australia and NewZealand’s ‘National protocol for the monitoring ofcyanobacteria and their toxins in surface waters’(Jones, 1997b) is a document dealing specificallywith the management of cyanoprokaryote bloomsby government bodies and is complementary to ThePhytoplankton Methods Manual for AustralianFreshwaters. Where appropriate, cross-referenceshave been made and consistency in methods hasbeen agreed with the Agriculture and ResourceManagement Council of Australia and New ZealandNational Algal Manager.

This manual has been developed at a time when lakesand rivers have become the focus of many water resourceissues in Australia, in particular the need to ensureecosystem sustainability. On the one hand, the publichas become aware of the occurrence of toxiccyanoprokaryote blooms in surface water systems and isdemanding action; on the other, there is less thancomplete scientific understanding of what determinesthe development of phytoplankton communities, ofwhich the cyanoprokaryotes are only one group, inthese systems.

The manual covers both lakes and rivers.Historically, it was believed there was no truepotamoplankton (riverine plankton) because the

residence time in rivers was too short for algae toreproduce and the light and hydrodynamic conditionswere too unfavourable for them to survive. The algaefound in rivers were believed to come from sources otherthan the rivers themselves – either from upstream lenticwaterbodies and tributaries, or from the benthos(Reynolds, 1988). We now have confirmation thatplanktonic algal species do reproduce within rivers and thatmany species, although originating from upstream lenticwaterbodies, develop substantial populations in situ(Reynolds, 1988) and contribute significantly to theproductivity of individual systems. The occurrence oftrue potamoplankton, as confirmed in recent literature,may be partially an outcome of the drastic hydrologicalchanges imposed on many rivers by humanintervention, resulting in increased residence times(Tubbing et al., 1994), as well as an effect ofanthropogenic eutrophication. This could well be true inAustralia, for instance, for the Murray, Lower Goulburnand Murrumbidgee rivers.

The concept of the hydrological dynamics of riverflow has developed from a simple model of an openpipe, well-mixed in its entire cross-section, to one of amuch more differentiated waterbody with a highlyvariable lateral profile of velocities and residence times.The observation that parcels of water are entrained inpockets of river bed or bank has led to the concept of‘retentive zones’, describing water that is incompletelymixed with the bulk of the flow and that might travel ata different velocity to that of the main current(Reynolds, 1988). It is important to keep these conceptsin mind in order to sample algae in rivers in arepresentative fashion, as the physical environmentlargely determines the distribution of phytoplanktonwithin the water.

Standing waterbodies (lagoons, lakes and reservoirs)are equally important in our consideration of surfacewaters. In many regions of Australia, they are the majorsources of drinking water, apart from providingirrigation supplies and areas for recreational use. Inparticular, many of our reservoirs have been plagued bytoxic cyanoprokaryote blooms in recent decades,jeopardising the use of the water for human purposes.

The ecology of phytoplankton in lakes has beenstudied for over a century and is relatively well-known.

1. Introduction

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

However, reservoirs or storages do not always function inthe same way as lakes, since their water level variationsare often unseasonal and water levels may be drawndown so low that large areas of lake sediment areexposed. Such events may drastically alter the ecology ofa reservoir for years to come.

In general, phytoplankton development in standingwaters is determined by the same physical and chemicalparameters (eg. temperature, light availability, nutrients) asin rivers, although these parameters create a different type ofenvironment. Most standing waterbodies undergodiurnal or seasonal thermal stratification. A consequenceof stratification might be the permanent loss of algalcells from the euphotic zone due to sinking below thethermocline. Also, during stratification, nutrientconcentrations in the epilimnion may be reduced togrowth-limiting concentrations by algal growth. Windaction may determine vertical and horizontaldistribution of phytoplankton. In standing waters at thescale of the whole waterbody, two nutrient pools mayinfluence phytoplankton growth:

1. those nutrients present in the water column; and

2. those trapped in the sediment if they are releasedinto the hypolimnion under anoxic conditions anddistributed throughout the waterbody in the nextmixing event.

At times, other biota such as zooplankton and parasitesmay alter phytoplankton cell density considerably.

In the past, the monitoring of algae in Australiansurface waters has not always had clearly definedobjectives, and comparison of results obtained bydifferent laboratories has been difficult because of theuse of different methodologies. It is hoped that thesedifficulties will be largely overcome with theimplementation of this manual and that informationgathering by individual organisations will becomecompatible across Australia. The manual has beendeveloped after extensive consultation with and input fromalgal workers and water managers in the water resourceindustry and gains part of its significance from thisprocess. Monitoring and assessing the development ofphytoplankton will remain an integral part of biologicalmonitoring in Australian surface waters. It isrecommended that the manual be re-evaluated fromtime to time, initially in the year 2002.

5

2. Objectives of phytoplankton monitoring

The objectives of the manual are described in thissection, together with the reasons for and objectivesof phytoplankton monitoring programs. The designof such programs is addressed with the suggestionthat a pilot study be conducted for unknownwaterbodies before a conceptual model is formed.Water quality parameters to be measured inconjunction with algal samples are listed.

2.1 Objectives of thephytoplankton methods manualThe objective of this manual is to describe suitablemethods for the sampling, fixation, preservation,identification and enumeration of phytoplankton inAustralian surface waters and to recommend proceduresfor quality control and data storage. While providingguidelines for all aspects of phytoplankton monitoringin Australian freshwaters, the manual does not attemptto impose a nationwide standard. While implementationof the manual will lead to greater uniformity in themethods applied in both field sampling and laboratorywork around the country, details of individual programswill depend on program objectives, client needs andavailable resources and methods may need to bemodified accordingly. For some procedures a benchmarkmethod has been highlighted against which othermethods, if used, should be compared for equality ofresults. Specific methods for managing potentially toxiccyanoprokaryote blooms are addressed in theAgriculture and Resource Management Council ofAustralia and New Zealand cyanobacterial protocol.

The manual has been written to address the needs ofalgal workers (people who do the counting) and waterquality and water resources managers (people whodesign and run the programs and analyse the data) toundertake routine monitoring as well as research-orientated programs.

2.2 Objectives of phytoplanktonsamplingPhytoplankton, together with benthic algae andmacrophytes, constitute the autochthonous primaryproducers in aquatic ecosystems and, as such, form partof the basis of the food web in terms of energy andmaterial input. To understand the biological functioningof individual rivers, lakes and reservoirs, and detectchanges in them, it is essential to investigate thedevelopment of their phytoplankton populations.Phytoplankton are particularly sensitive to changes innutrients, responding rapidly when levels increase. Dueto their short life cycle, planktonic algae respond quickly toenvironmental changes and are thus a valuable indicator ofwater quality. Most of our standing waters contain viablephytoplankton populations which, in many instances,are monitored regularly to ensure the availability of safewater for human consumption. It is well-known thatmany of our rivers contain substantial phytoplanktonpopulations which might, in their lowland sections, playa major role in the carbon cycle and thus need to beassessed as part of effective river management. If theprocesses that drive phytoplankton development inAustralian rivers were better understood, managersmight be in a position to manipulate environmentalconditions to achieve particular outcomes.

The term ‘phytoplankton’ encompasses allsuspended microalgae in a waterbody belonging to alltaxonomic algal groups and includes thecyanoprokaryotes, or blue-green algae, which might bepresent in insignificant numbers or constitute thedominant group in a waterbody at a particular time. Theimportance of cyanoprokaryotes for water managersarises from their possible toxicity to animals and humansand the ecological and aesthetic consequences of theirblooms to individual aquatic systems.

To obtain baseline data for water management, theentire phytoplankton (eg. ‘total cell count’ or‘phytoplankton biomass’) needs to be assessed. This isbecause the system is a complex one in which acomponent can be managed only if its links to the othercomponents are well-understood. To understand and

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

manage nutrient, carbon and energy cycles in a runningor standing water, the entire phytoplankton communityneeds to be evaluated.

The objectives of particular phytoplankton samplingprograms will vary and may include some of thefollowing:

• monitoring the concentration and composition ofphytoplankton as indicators of water quality, inparticular for nutrients and heavy metals;

• assessing ecosystem health;

• monitoring the abundance and composition ofmajor phytoplankton groups to assess theconsequences of, for example, land use andeutrophication on water quality within a river basinor reservoir catchment;

• monitoring the effects of remedial managementmeasures aimed at improving water quality orrestoring system health;

• providing data to determine long-term trends inphytoplankton composition and abundance within aparticular waterbody, including ‘problem species’, inorder to assess, for example, the effect of sewagedischarge and agricultural run-off containingfertiliser and harmful chemicals;

• monitoring the effects of management measuressuch as river regulation, river-to-river transfer,reservoir regulation and water abstractions within aparticular system;

• detecting the presence of and examining short-termtrends in the growth of ‘problem species’ (eg. algaeor cyanoprokaryotes producing taste and odourproblems or toxins, and algae responsible for filterclogging in drinking water supplies) to determinethe suitability of a particular water for drinking,recreational use, spray irrigation or stock watering;

• providing ecological data on particularphytoplankton groups;

• monitoring the raw water intake for public healthrisks in drinking water supplies; and

• increasing the knowledge of phytoplankton ecology,limnology and the state of the environment.

2.3 Design of phytoplanktonmonitoring programsThe details of a program will vary from case to case andfrom waterbody to waterbody. The design of anindividual phytoplankton program requires carefulconsideration of the precise aims of the program and ofthe inherent and potential variability of the system beingstudied. It is recommended that each individualphytoplankton program be designed by an experienced algalecologist with appropriate statistical advice.

For an unknown waterbody, a ‘pilot study’ should beconducted to determine the hydrodynamics of thesystem, horizontal and vertical distribution ofphytoplankton, species composition, range of celldensities and frequency of change in speciescomposition and abundance. Details of the samplingprogram such as sampling frequency (daily, weekly,fortnightly or variable), spatial distribution of samplingsites and location of sample (surface or depth integrated)will then be based on the background informationgathered in the pilot study or on data from previousinvestigations. Depending on the project objectives, thesampling regime may vary over time. For example, if theeffects of floods are studied, samples would be takenaround flood events rather than at regular intervals.

The major considerations in designing a samplingprogram are the program objectives and associatedinformation needs and how the program will meet them,taking into account the heterogeneity and variability ofthe physical environment, and the distribution andlikely behaviour of the phytoplankton within it. Themorphological, hydrological and geographicalcharacteristics of a waterbody largely determine thespatial and temporal development of the phytoplanktonwithin it. Consequently, a monitoring program will alwaysbe specifically designed for the waterbody in question andcannot be transferred to other waters. A useful guide indesigning a program is to ask what level of informationwill be obtained with a given sampling pattern. Forexample, if phytoplankton abundance and compositionin a stratifying weir pool were to be studied, a subsurfacesample would be insufficient to obtain the requiredinformation. In contrast, a subsurface sample would besufficient to obtain the same information from a well-mixed river. The spatial spread of sampling sites willrelate, among other factors, to water travel times down

7

OBJECTIVES OF PHYTOPLANKTON MONITORING

the river or to lake morphology. The temporal spread ofsampling will most importantly consider cell doublingtimes of algae which vary from less than a day to morethan a week. Depending on weather and conditions inthe waterbody, the population concentration andtaxonomic composition can change drastically within afew days. Therefore, a weekly sampling frequency isgenerally accepted as adequate for phytoplanktonprograms (see 3.3, ‘Sampling in estuaries’). In additionto investigating species composition and abundance, asample to determine algal biomass such as chlorophyll-amay be taken.

Detailed advice on designing sampling programs isgiven in Standard methods for the examination of waterand waste water (APHA, 1995), and in ISO 5667-1,Water quality – Sampling – Part 1: Guidance on the designof sampling programs (ISO, 1980). Additional advice onthe statistical and comparative aspects of biomonitoringare provided in the Australian and New ZealandEnvironment and Conservation Council ‘NationalWater Quality Management Strategy Guidelines forFresh and Marine Water Quality’, a draft of which iscurrently in use. The design of programs to monitorpotentially toxic cyanoprokaryotes and associated healthrisks in drinking water supplies and recreational waters isdescribed in detail in Jones (1997b) for Australia and inChorus and Bartram (1999) for other parts of the world.Jones (1997b) gives cell concentrations for the alertlevels framework system which the Australian statesagreed on in 1998.

Physical and chemical data sampled simultaneouslyGenerally, the following water quality data are collectedconcurrently with algal samples to help with theunderstanding of the phytoplankton data: discharge rateand velocity (for rivers), temperature, pH, electricalconductivity, dissolved oxygen concentration, turbidity,photosynthetically active radiation (PAR),determination of light extinction coefficient, Secchi disktransparency, and, if required, concentrations of thenutrients phosphorus, nitrogen and silica. Silica is anessential nutrient for diatoms, which often dominateriverine plankton. In standing waters, water temperaturein usually measured at discrete depths over the wholewater column to determine the presence of stratification.Often the ratio of euphotic zone to mixed zone iscalculated as an indication of light availability to thephytoplankton (Harris, 1978). Total phosphorusconcentrations give an indication of the carrying

capacity (maximum possible algal population size) of thewater and thus, in conjunction with other parameters,the potential for algal blooms (Chorus andBartram, 1999).

Conceptual modelOnce an understanding has been gained of the spatialand temporal distribution of the algae and theirresponses to environmental factors in the waterbody inquestion, a conceptual model can be formed and specificsampling programs tailored. For instance, if previousstudies have shown little change over winter in thephytoplankton community under investigation, amonthly sampling frequency for this season may beadequate. Again, it is recommended that an experiencedalgal ecologist be involved in this type of interpretation anddesign work. Monitoring programs should be reviewedregularly for their effectiveness in providing the requireddata and for the appropriateness of objectives undercurrent circumstances.

8

3. Taking samples

stream reservoir or weir pool on the phytoplanktonpopulation is to be traced further downstream, watertravel times should be taken into account whenselecting sampling sites.

Since the habitat of the phytoplankton is the runningwater itself, and the algae are continuously carrieddownstream (advected) with the water, phytoplankton isnot site-specific; rather the phytoplankton communitysampled at a particular site is the result of conditionsexperienced further upstream. Therefore, when takingphytoplankton samples in rivers, the actual site is oftenless important than the upstream stretch of river. Thisshould also be kept in mind when taking samples forphysical and chemical water quality variables. A river isoften conceptualised as a continuum which isintercepted at certain sites for sampling to provide a‘snapshot’ of present conditions.

3.1.2 Location within the riverConsiderations of where in the stream to sample andhow many samples to take are guided by the principleof taking a representative sample of the community.Within the river it is preferable to sample from themain current by boat, from a bridge or using asampling device which locates itself in the current(eg. Taylor integrated sampler, Appendix H). Rivers arenot homogeneous waterbodies and they may stratifythermally and chemically, either horizontally or vertically.Depending on circumstances, it may be appropriate totake several samples across the river to account forhorizontal heterogeneity caused by, for example,variations in flow velocity. If the river is not well-mixedvertically (eg. under low-flow conditions orstratification in weir pools), depth-integrated ordiscrete depths samples should be taken.

The counting of phytoplankton is generally timeconsuming and the degree of accuracy chosen shouldbe related to the representativeness of the sample. Abetter statistical result may be achieved by collectingseveral samples from slightly different spots at one siteand counting them to a lower level of precision(Vollenweider, 1969).

This section provides information on sampling siteselection in running and standing waters underdifferent flow and mixing conditions. Specialconsideration is given to the sampling of weir poolsand reservoirs. Details are given on how to take arepresentative sample in relation to programobjectives and on the preservation, transport andstorage of algal samples. This section also containslimnological background information relating tophytoplankton populations in both running andstanding waters.

3.1 Sampling in rivers

3.1.1 Site selectionSite selection will depend on the objectives of theindividual phytoplankton program. Two aspects are tobe considered:

1. choosing the site along the stream or within the riverbasin; and

2. choosing the exact location of sampling at thesampling site.

Sites are often chosen:

• upstream and downstream of a point source such as asewage treatment plant, weir pool or tributary;

• upstream and downstream of a source of majorecological impact such as a reservoir or weir pool; or

• at certain intervals along the river stretch underinvestigation, in order to explore longitudinaldistribution of phytoplankton.

If samples are collected upstream and downstream of apoint source or tributary, care needs to be taken tochoose the downstream site at a point where completemixing has occurred, or to take samples at two or morelocations across the width of the river if lateral mixing isincomplete. Vertical mixing of incoming waters mightalso be incomplete in a slow-moving river as a result ofthermal or other density stratifications. In someAustralian rivers, a vertical conductivity gradientdevelops under low-flow conditions because of theinflow of saline groundwater. If the influence of an in-

9

TAKING SAMPLES

3.1.3 Sampling methodologyThe sampling method chosen should:

a. guarantee a representative sample; and

b. be easy to handle.

The method will vary according to in-stream conditions.The preferred method is a depth-integrated sample takenfrom the main current. Water to be analysed for allvariables (eg. algae and chemical and physical data)should be collected in a single grab then subsampled.

If the river appears well-mixed vertically andhorizontally (presence of turbulence, lack of temperaturevariability), a sample taken at mid-stream 0.5 m belowthe surface (APHA, 1995) will suffice to characterise thephytoplankton present. For specific purposes, forexample sampling at a water supply offtake for drinkingwater, samples from a particular depth may be needed.Avoid sampling backwaters or backcurrents whensampling for phytoplankton. For procedures to monitorcyanoprokaryote blooms in rivers, refer to Jones(1997b). If a boat is not available, obtain a sample fromthe shore with either a dip stick sampler (more than 3 mlong), carrying a one litre glass sample bottle at the end,or a Taylor sphere sampler (see Appendix G). Bucketsare not recommended for sampling from the shore, or ifthe water surface is contaminated with non-planktonicmaterial. In the former instance, the water contained inthe bucket when pulling it out of the water is not thesame as when it first filled up out in the stream becauseof flow dynamics developing in the bucket. Furtherinvestigations will be needed to ascertain whether thephytoplankton is evenly distributed, vertically andhorizontally, in a well-mixed river (see O’Farrel andLombardo, 1998).

Under conditions of incomplete mixing or slow flowthe collection of a depth-integrated sample from themain current is recommended. Sampling may be byhosepipe sampler (Appendix F), requiring two operatorsand a boat, or using a Taylor integrated sampler(Appendix H), an apparatus designed to take depth-integrated samples from the middle of the streamwithout the need of a boat. Difficulties may beencountered when using the hosepipe sampler in astrongly flowing stream as the hosepipe will be draggedwith the current, making vertical sampling impossible.If there is uncertainty about even distribution of thephytoplankton across the river, take a sample from eachbank and from the middle, mix together even volumesin a container, and then subsample the usual samplevolume.

The sampling regime in weir pools depends on theprevailing flow conditions. Under high flow orconditions of incomplete mixing, sample as for a river.Under low flow conditions, where the water is likely tostratify diurnally (on a daily basis) or persistently (dayand night), depth-integrated samples are taken. Fordetailed information, see section 3.2, ‘Sampling instanding waters’. A temperature profile is taken to verifythe presence of stratification. It is also recommended thatan oxygen profile is taken to check for anoxic conditionsin bottom waters. If stratification is present in a weirpool, certain algae might layer at certain depths. Ifproject objectives are not achieved by taking anintegrated sample under such circumstances, thensamples from specific depths are taken with a standarddiscrete-depth water sampler, such as a Ruttner or VanDorn sampler or a Niskin bottle (see APHA, 1995). Forsome monitoring programs where the whole weir pool isto be monitored, it may be appropriate to take onedepth-integrated sample close to the weir wall for fullcounts to be entered onto a database and, for operationaluse, several subsurface samples around the weir pool forimmediate estimation of cell numbers.

The methods of sampling recommended for differentlocations within a river are summarised in Table 3.1together with codes suggested for use in data recording.Each three-letter code stands for a combination ofsampling method and location.

Table 3.1: Methods for taking phytoplanktonsamples in rivers

Equipment Location within the river

Shore/Jetty Bridge Boat

Dip stick (DS) SDS

Sphere sampler (SS) SSS BSS

Discrete depth sampler BDD KDD(DD)

Integrated sampler (IS) SIS BIS

Hosepipe BHP KHP(integrated sampler) (HP)

Notes: Codes indicate where to use each method. The three-lettercode indicates where and how the sample was taken.The first letter indicates the location: S, shore; B, bridge;K, boat. The remaining two letters indicate the method used.The code is for use on the ‘Phytoplankton Field SamplingSheet’ (Appendix E) and in the sample managementdatabase. For a technical description of samplers seeAppendices F, G and H.

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Depending on the life cycle of the algae present, it isadvisable to sample both water column and sedimentsurface. It has been reported from tropical rivers inCentral Queensland (Larelle Fabbro, pers. comm.) thatcyanoprokaryote species (eg. Limnothrix, Planktolyngbya,Nostoc) form metalimnetic and merolimneticpopulations under certain flow conditions and laterappear in the plankton. In other rivers, for example theLower Murray, large numbers of akinetes have beenfound on the river sediment. These will form acyanoprokaryote bloom under the right conditions. Insuch cases, it is advisable to take sediment surface as wellas water column samples at the same site.

Whole water samples (unfiltered) should be collectedfor quantitative evaluation of cell density. Samplevolume should be between 100 mL and 1,000 mL (upto several litres in upland streams), depending on thenumber of cells present as judged from the results of thepilot study. In general, cell density is expected to belowest in fast-flowing, clear upland streams and highestin large lowland rivers. A live sample might be taken,especially when flagellates or other delicate cells arelikely to be present, and filtered or centrifuged for same-day species identification. These organisms may not bereadily identifiable from preserved material as cell shapeand colour can be distorted and cells may losetheir flagella.

For chlorophyll-a analysis, a separate sample of 0.5 Lto 1 L is taken.

It is advisable to use a standardised phytoplanktonfield sampling sheet (see Appendix E) for each program toensure all samples and measurements taken in the fieldare properly recorded in the field. The field samplingsheet will also facilitate sample registration in thelaboratory and later data reporting. The sheet presentedin Appendix E is an example only and should bemodified for individual programs.

In addition to taking water samples for phyto-plankton and water quality parameters, it is useful torecord observations such as water colour, smell and scumformation as well as wind direction and strength.

3.2 Sampling in standing watersStanding waters with regard to this manual includelakes, reservoirs, billabongs, lagoons and weir pools aswell as rivers under unusual low-flow conditions.

3.2.1 Site selectionSampling sites may be chosen following a statisticalapproach or according to a set of criteria related to theaim of the program. The aim of the statistical approachis to entirely select sites by random, for example, byusing a grid network or transects and choosing sitesthereon at random and changing them on eachoccasion. In practice, it may be convenient to changesites only annually or every two years (Jones, 1997b).The statistical approach requires a large number of sites

Figure 3.1: Suggested sampling sites in a weir pool

Off take

x1

x2

x3

Weir

Sites:

x1 near the weir

x2 main basin

x3 inflow site

11

TAKING SAMPLES

to be sampled and is particularly useful for a pilot study.For most monitoring programs, however, due toresource limitations, only a minimum number ofpermanent sites are established. Most often, these sitesare chosen with the objectives of the sampling programin mind to best represent the true phytoplanktonpopulation in the waterbody, considering theinformation from the pilot project and the criteria listedbelow:

• to represent all lake basins or different arms of areservoir of importance (morphological and waterquality heterogeneity);

• to sample inflowing and outflowing waters;

• (in a reservoir) to investigate and monitor waterquality of the outlet point (about 100 m from thedam wall) and water supply off-take point;

• to monitor water quality and health hazards ofrecreational waters;

• to monitor accumulation of algal matter at thedownwind end of lake or shore; and

• to sample the deepest point.

The number of sampling sites and samples taken is afunction of the aims of the study, the morphology of thewaterbody and the financial resources available. In thefollowing paragraphs, many detailed recommendationsare made on how to select sampling sites. For anindividual program design, only some of these may beapplicable.

For a round basin, choose sites along twoperpendicular transects which extend from one shore tothe other. For a long and narrow basin, choose at leastthree sites covering the length of the basin, includingone site near the inlet and one near the outlet. A changein species composition between sites close to the inflow(fluvial species) and those distant from the inflow(lacustrine species) has been reported for Australianreservoirs (May, 1988). For a weir pool (see Figure 3.1)select at least one site near the weir; if the water backs upfor a considerable distance, select sites as for a long andnarrow basin.

In the presence of different morphological basins orseveral arms, it is recommended that several sites beestablished (see Figure 3.2). In a reservoir with two arms,for example, a site would be chosen in each of them andanother near the dam wall to monitor the water qualityof the downstream releases. Bays and inlets are oftenpoorly mixed with little exchange with the main basinand therefore might develop a water quality which is

different from that of the main basin. A site may beestablished here, if the bay is important ecologically orfor human use. If there is a prevailing wind direction,one site should be situated at the downwind end of thewaterbody if the area is used for recreation. Commonly,a site is established at the deepest point (if different fromthe dam wall site) to take depth profiles and, ifapplicable, at the drinking water off-take.

Sampling sites should be spaced far enough apart toensure spatial independence. Thus, the distance betweensites depends on the size of the waterbody, samplingobjectives and representativeness of the phytoplanktonpopulation. For many reservoirs, a minimum distance of100 m between sites is recommended. Samples shouldbe taken in the open water more than 50 m from theshore to avoid contamination of the sample with benthicspecies and wind-accumulated scums. For sampling ofnear-shore areas to monitor for health risks ofrecreational areas due to cyanoprokaryote blooms, referto the criteria for sample collection in Jones (1997b).

When sampling phytoplankton in lakes and reservoirs,one must consider the patchiness of the phytoplanktondistribution across the area of the water body(Wetzel, 1975). Patchiness refers to the uneven (for noapparent reason) horizontal distribution ofphytoplankton across a waterbody. Thus, to adequatelyrepresent the phytoplankton assemblage, samples mustbe taken at several sites and depths (Moss and Hunter,1992).

If the waterbody is heterogeneous, it isrecommended that several sites are sampled. The samplesare then treated as individual samples and each countedseparately. If resources are very limited, a representativesample is obtained by sampling several sites and poolingthese samples at equal volumes into a composite samplerather than sampling only one site. Subsamples of thecomposite sample are then treated as usual for algalidentification and enumeration or for chlorophyll-aanalysis. The counting of individual samples from severalsites provides greater statistical power to the results thancounting only one ‘pooled’ sample for the whole waterbody. The latter reduces algal counting costssignificantly.

Standing waters, under certain weather conditions,may thermally stratify. Many weir pools in Australia alsostratify under certain weather and flow conditions.During stratification, exchange between the warmer topwater layer (epilimnion) and the deeper waters(hypolimnion) becomes much reduced due to the

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

temperature-driven vertical density gradient. The layerof transition between the epilimnion and hypolimnion iscalled the metalimnion or thermocline. The epilimnionand hypolimnion often develop different physico-chemical characteristics during stratification. Whiledeeper water bodies often stratify persistently (over manydays or weeks) shallow (less than 2 m) water bodies maystratify diurnally or continuously for only a few days(Sherman and Webster, 1994). Usually, in shallow waterssuch as billabongs and lagoons, convective coolingoverturns the water column each night.

Stratification is considered a dynamic phenomenon.Its stability and duration depend not only on the size ofthe temperature difference between the top and bottomlayers, but also wind force, intensity of solar radiationand, in some water bodies, the mixing effect of seiches(internal waves). Australian research has shown that atemperature difference as small as 0.05oC, equivalent toa minimum temperature gradient of 0.25oC m-1, wassufficient to separate the surface mixed layer from thebottom layer in Chaffey Dam (Sherman et al., 1999). Inmany circumstances, a temperature difference of 0.2oC isappropriate to define the bottom of the surface mixedlayer (B. Sherman, pers. comm.). Heating of the top

water layers by solar radiation is intensified in colouredor highly turbid waters (such waters are typical in manyparts of Australia) due to increased energy absorption.Thus in shallow and turbid billabongs or lagoons,heating of the top layer and the onset of stratificationoccur faster than in comparable waterbodies withclear water.

Phytoplankton is not evenly spread through thewater column. In most waterbodies with stablestratification, a large part of the phytoplankton biomassis found in the euphotic zone because its downwardtransport is prevented. Many members of the plankton(eg. motile algae) actively vary their position in the watercolumn and often avoid the surface layer. Others(eg. buoyant cyanoprokaryotes) may accumulate at thewater surface under calm conditions or concentrate at aparticular depth, for example, Anabaena (see Figure 3.3).

3.2.2 Sampling methodologyA vertical temperature profile should be taken at

1 m intervals to verify the presence of stratification(Bartram and Ballance, 1996). The presence ofstratification is best recognised if the rate of temperaturechange with depth at the thermocline is significant

Figure 3.2: Suggested sampling sites in a large reservoir

x4

Beach

x1

x2

x3

x5

Sites:

x1 near off-take tower

x2 deepest point

x3 recreation area

x4 western inflow

x5 eastern inflow

Main wind direction indicated.

13

TAKING SAMPLES

(0.2oC m-1, B. Sherman, pers. comm.). In shallowwaters, a temperature difference between the top andbottom layers of 1oC or greater under low windconditions may be taken as an indication ofstratification.

The specific sampling method for phytoplanktondepends on the depth of the water body. In shallow waters(lagoons, billabongs) with a depth of less than 2 m, asubsurface grab sample at 0.5 m is taken if the waterbody is well mixed. However, if the water body isstratified or motile algae are present, a depth-integratedsample or discrete depth samples are taken. Surfacesamples such as subsurface grab samples are notadequate in water bodies deeper than 2 m because suchsamples are unrepresentative of the vertical spread of thephytoplankton population. In deeper waters, it isrecommended that a depth-integrated sample is taken froma boat over either the epilimnion (the mixed surfacelayer during stratification) or, if there is no stratification,the euphotic zone. The euphotic zone is commonlydetermined as 2.5 times the Secchi depth and is thewater column between the surface and the depth atwhich the light intensity is 1% of that at the surface(Schwoerbel, 1970).

At each site, three samples are taken within anecologically relevant sized area, mixed at equal volumes

in a clean container and the required volumesubsampled. For work on large reservoirs, where usuallyonly a limited number of sites are sampled, at each sitetake five integrated samples within an area of 100 m by100 m and mix even volumes into a composite sample.In this way, the sampling regime takes into account thehorizontal patchiness of the phytoplankton withoutincreasing the number of samples.

For deep lakes and reservoirs, in addition to theintegrated sample over the epilimnion or euphotic zone,deeper grab samples at 5 m intervals are recommendedfor at least one site. In some instances, discrete grabsamples above 10 m are mandatory if layering of algaehas been identified as a problem (eg. Anabaena in a weirpool or reservoir) (see Figure 3.3). Similarly, a haloclinemight exist with some algae layered above it.

In reservoirs, in addition to a depth-integratedsample, discrete samples are often taken at the depthfrom which the water is to be withdrawn or from thedepths at which alternative water off-takes exist. Thediscrete depth samples give an indication of algal celldensity in the water to be released into the downstreamriver stretch or used as raw water for drinking watertreatment, while the integrated sample detects thepossible presence of motile algae or distinct algal layersdue to seiches over the whole depth of the watercolumn.

Figure 3.3: Possible vertical distribution of different algae in a stratified lake

Dep

th (

m)

Cell densityMallomonas

Microcystis

Trachelomonas

Anabaena

1

2

3

4

5

6

7

8

9

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Do not sample for phytoplankton in an area withalgal scums unless the program objectives include thetargeting of algal blooms and scum material is needed.The following observations with regard to windconditions are important when sampling specifically forbuoyant algae. If buoyant algae are present and aconstant wind has blown, their largest concentration willbe found at the downwind end of the lake or reservoir.These algae will be dispersed through the whole watercolumn in that area, not just concentrated near thesurface. If wind blows consistently from one direction,the depth of the surface layer containing buoyant algaewill be larger at the downwind end than at the upwindend.

Permanent sites should be marked with a buoy or bythe Global Positioning System (GPS), greatlysimplifying work from a boat in windy conditions. Ifsampling from a boat, approach the sampling site at lowspeed, and take samples away from the motor and bowwaves to avoid the disturbances they cause in the water.

To take a depth-integrated sample, use a hosepipesampler (see Appendix F) of appropriate length.Alternatively, several grab samples at discrete depthscould be taken with an appropriate sampler (forexample, Van Dorn, Ruttner, Niskin bottle), pooled in acontainer (composite sample), thoroughly mixed and asubsample taken. To take a sample with a discrete depthsampler, open the bottle and ‘load’, lower to the desireddepth, send a ‘messenger’ or weight to close the bottleand then lift it into the boat. For details of suchsamplers see APHA (1995) or Bartram and Ballance(1996). Fill the sample bottle from the sampler outlet orempty sample into a bucket and take a subsample.

In oligotrophic (nutrient-poor) waters take a samplevolume of up to 6 L; in eutrophic (nutrient-rich) waters,0.5 L to 1 L is usually sufficient. A phytoplanktonsample is always taken as a whole water sample(unfiltered and unstrained). An additional sample of0.5 L to 1 L is taken for chlorophyll-a analysis.

Test for inflowing watersIf inflowing waters are colder than the main waterbodythey will sink to the layer of equivalent density. If theypose a problem (eg. high nutrient load) and theirdistribution in the waterbody needs to be tracked, thesampling program needs to be designed accordingly.

Visual inspectionIn addition to taking water samples, a visual inspectionof the water and the shoreline should take place,recording colouration and smell of the water, algal

colonies visible to the naked eye, the accumulation ofalgal matter and its colour, consistency (use gloves) andsmell. If the inspection is undertaken as part ofcyanoprokaryote monitoring, follow the details outlinedin Jones (1997b).

3.3 Sampling in estuariesAn ‘estuary’ can be defined as a semi-enclosed body ofwater having an open or intermittently open connectionwith the ocean. The term ‘estuary’ further applies to thetidally influenced lower reaches of a creek, river or lakewhere freshwater meets saltwater. An estuarine systemwill therefore vary in water composition due to theseasonal and periodic influences of catchment areas andtidal movements. The phytoplankton community willtherefore be a diverse mix of fresh and marine species.

Within an estuary, the water quality and associatedphytoplankton distribution will be determined by theinteractions of a number of processes, including importsand exports of materials, physical transportation andmixing, and the various chemical and biologicalprocesses.

Therefore when deciding where and when to samplephytoplankton in an estuary, consideration needs to begiven to the physico-chemical condition of the system.Salinity stratification needs to be assessed in addition totemperature stratification and integrated samples takenfrom layers of interest. When samples are integratedacross salinity layers, the total biomass sampled willinclude both fresh and marine species. The vertical andhorizontal salinity gradients move upstream ordownstream within the estuary according to changes inseasonal flow and weather conditions.

3.3.1 Site selectionIt is recommended that an experienced ecologist and/orstatistician be consulted before commencing aphytoplankton monitoring program in an estuary.

3.3.2 Sample collectionWhen sampling phytoplankton in an estuary,consideration should be given to both salinitystratification and temperature stratification. It istherefore necessary to measure the temperature andelectrical conductivity profile at the sampling site anddetermine which depths of the water column are to besampled in accordance with project objectives. It may bethat only the freshwater or saltwater layer is of interest,

15

TAKING SAMPLES

or it may be that both are. Samples are then takenaccordingly. To obtain an integrated sample, use ahosepipe sampler of appropriate length. To obtainsamples from different depths employ a discrete depthsampler. The discrete depth samples may then be pooledinto a composite sample if required.

3.4 Frequency and timing ofsamplingThe sampling frequency is determined by the growthrate of the organisms under study. The generallyrecommended frequency of sampling for phytoplanktonis weekly for both lotic and lentic waters. This willdetect the often rapid changes in phytoplankton speciescomposition and abundance; generation times of algaevary from less than a day to several days (Reynolds, 1984).Consequently, phytoplankton cell densities in naturalenvironments can double under favourable conditions intwo to three days. In standing waters, fortnightlysampling may be adequate in times of low cell growth. Ifthe sampling specifically targets cyanoprokaryoteblooms, a frequency of two to three days, or even daily,is recommended, depending on river levels, weatherconditions, anticipated releases from upstream andcurrent cell densities. Details are given in Jones (1997b).The same recommendation applies for standing watersunder stratified conditions. Many programs reducesampling frequency in winter due to the belief that algaegrow less quickly then. However, increased cell numbershave been observed in winter in rivers as a consequenceof low-flow conditions and lower turbidity (Hötzel andCroome, 1994; Hötzel and Croome, 1996), whileincreased cyanoprokaryote concentrations have occurredin a Victorian storage in midwinter and winter diatomblooms have been observed in rivers in the Sydneyregion (D. Cannon, pers. comm.).

In a standing waterbody, the time of day at whichsampling occurs may be critical to the result. Buoyant algamay rise to the surface in the latter half of the day undercalm, sunny conditions and be dispersed to deeper layersagain by evening winds or through cooling at night(G. Jones, pers. comm.). In contrast, under calm,stratified conditions at night, surface scums may befound in the morning which are mixed back into thewater column later by increased wind activity (Jones,1997a). Hence it is recommended that routine samplingbe conducted within the same predetermined timeperiod in the day for each sampling event. The pilot

study should provide the necessary information abouttemporal changes in vertical phytoplankton distribution.

3.5 Phytoplankton netsPhytoplankton nets catch only the algae that are largerthan their mesh size. They are unsuitable for taking aquantitative or even a presence/absence sample becausethey do not collect the smaller organisms. Algae in thesize ranges of picoplankton (less than 2 µm) andnanoplankton (2 µm to 20 µm) will pass through astandard phytoplankton net. The picoplankton andnanoplankton fractions of the phytoplankton, whichinclude most flagellates, small green algae and the smalldiatoms, often constitute the major proportion of a riverphytoplankton population. Nevertheless, a live sampletaken with a plankton net (mesh size of 25 µm to35 µm), in addition to a whole water sample, may aidthe identification of the larger species.

3.6 Sample containersDark brown glass or PET (polyethylene terephthalate)bottles are suitable sample containers for phytoplankton.Other plastic bottles such as polypropylene bottles areunsuitable since iodine fumes (corrosive) diffuse throughthem. Samples for chlorophyll-a analysis are preferablytaken in brown glass bottles (PET, polyethylene or clearglass are acceptable, but see section 3.7 ‘Preservation,transport and storage’ for transport details). The samplebottle should be rinsed thoroughly (at least three times),away from the sampling site (or the side of the boat) toavoid disturbing the water to be sampled. Correct andimmediate labelling of all sample containers with adurable label is essential.

3.7 Preservation, transport andstorageSamples for later counting should be preservedimmediately at the sampling site by adding Lugol’ssolution at a ratio of 1:100 (Vollenweider, 1969). Thisgives the sample a weak tea colour. If a higher ratio isneeded to preserve the sample, this should be noted onthe field data sheet and taken into account duringenumeration when calculating cell concentrations.Samples so preserved will keep for several years if storedcorrectly and topped up annually with the preservative(see below). Lugol’s solution is made by mixing 20 g of

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

potassium iodide (KI) with 200 mL distilled water, thendissolving 10 g of pure iodine in this solution. Glacialacetic acid (20 g) is added a few days before use(Schwoerbel, 1970). The stock solution must be storedin a dark and well-ventilated space (Vollenweider, 1969)in a glass bottle and remains effective for at least a year.

An advantage of Lugol’s solution is that flagellatespreserved with it retain their flagella. A disadvantage isthat the frustules of delicate diatoms and the scales ofsome Mallomonads may dissolve over a few months dueto the acidity of the solution. The type and degree ofalterations caused by fixation with Lugol’s solutiondepend on the composition of the algal population andthe water sampled. Cryptomonads, large diatoms,Peridineae, coccoid green algae, Desmidiaceae and singlecells and trichomes of cyanoprokaryotes are leastaffected by this preservation and may keep intact formore than two years. Identification might be difficult ifcells are overstained, although this might be overcomeby adding sodium thiosulphate (Throndsen, 1978). Theiodine in Lugol’s solution not only preserves the algalcells, but also increases their specific weight, sofacilitating sedimentation. Samples fixed with iodineshould be stored in the dark in amber glass bottles withan insert in the cap made of teflon to prevent iodinefumes from escaping (P. Baker, pers. comm.). For long-term storage, add one to three drops of Lugol’s solutionsaturated with iodine to the already preserved samplesand check annually for iodine content. The potentialhealth hazards of storing such samples are covered insection 6.1, ‘Occupational health and safety issues’.

Samples earmarked for identification only can also bepreserved with formaldehyde acidified with acetic acid.To make a 20% aqueous solution of formaldehyde(HCHO), mix equal parts of formalin (40% HCHO)and concentrated acetic acid. For fixation, add 100 mLof the water sample to 2 mL of the acidifiedformaldehyde (the final concentration of HCHO shouldbe 0.4%) (Throndsen, 1978). The advantage of thisagent is that samples can be stored for several years. Thedisadvantages are that the cell shape of naked flagellatescan be distorted, flagella will be thrown off and the cellcontent will bleach out. Samples can also be preservedwith neutralised glutaraldehyde (see section 6.1,‘Occupational health and safety’) to a finalconcentration of 1% to 2% (APHA, 1995) and thenstored for several years. Formaldehyde andglutaraldehyde are both toxic to humans (see section6.1, ‘Occupational health and safety’).

Preserved samples should be kept in the dark (foriodine preservation) during transport with the usual caretaken when handling chemicals. Live samples should bekept cooler than 10oC and in the dark. They need to beprocessed within 12 hours of taking the sample (Klee,1993). Water quality in an unpreserved sample canchange within hours, and zooplankton grazing canreduce algal numbers. Unpreserved samples forchlorophyll-a analysis should be filtered in the field andthe filter frozen immediately in liquid nitrogen or a carfridge and kept in the dark. The frozen filters may bestored for up to three weeks before processing.Alternatively, unpreserved samples are kept cool (but notfrozen) and in the dark and filtered in the laboratorywithin 12 hours of taking the sample in the field.

17

This section details procedures for the analysis ofalgal samples, beginning with the subsampling andconcentration procedures and then discussingidentification, enumeration and calculation of finalresults. Recommended benchmark methods areclearly identified, incorporating a choice betweenthe three different counting chambers currently usedin Australia. Statistical information pertaining toalgal counting is given, addressing issues of accuracyand precision of counting results. The section closeswith suggestions for an algal coding system.

4.1 EnumerationAccurate identification and enumeration of algal cellsunder a microscope requires an experienced taxonomicphycologist, and a good quality instrument. The level oftaxonomic identification will depend on the aim of thestudy, but it should be noted that habitat requirementsin algae are species specific rather than genus or familyspecific. For some groups (eg. the diatoms andchrysophytes), special preparation is needed beforeidentification to species level can occur.

The time required to count each sample will varygreatly depending on cell density, ease with which thecells can be identified, the desired level of precision andthe amount of detritus/turbidity in the sample.

Counting is recommended for Lugol’s preserved samplesonly. The counting of live samples is consideredinaccurate since flagellates and diatoms move around inthe counting chamber. The phytoplankton cell densityand species composition in a live sample may alsochange in the time between sampling and counting as aresult of zooplankton grazing and disintegration of cells.The basic procedure for counting algae is to fill acounting chamber with a subsample of the preservedsample and, after a period of settling, simultaneouslyidentify and count the algal cells under a lightmicroscope. Because of the statistics used to calculate theprecision levels of algal counts (see section 4.1.10, ‘Statisticsof counting’), algal units must be enumerated. ‘Algal units’may be single cells, filaments or colonies depending onthe species’ usual life form.

4.1.1 Microscope requirementsAn upright or inverted light microscope with white lightachromatic objectives of 10x, 20x, 40x and 100xmagnification is required. If an inverted microscope isused, the 20x and 40x objectives must be of longworking distance and a suitable condenser is required.To use a Sedgwick-Rafter chamber on an uprightmicroscope, the 40x objective needs to be of longworking distance, but the 20x objective may not. Forthe 20x and 40x magnifications, the use of phase-contrast objectives would be an advantage, especially forthe identification of live cells. For use with the Utermöhlchamber (see below), three hairlines or threads areneeded in the optical path (Lund et al., 1958). Twohairlines are arranged parallel and the distance betweenthem may be adjustable, while the third one runs at aright angle. For most modern inverted microscopes aspecial part with adjustable lines can be obtained.Otherwise fixed hairlines can be inserted into one of theeyepieces. Make a thin cardboard or plywood ring withan outer diameter so that it will lie on the flange insidethe eyepiece. Glue three fine glass threads onto the ringwith epoxy adhesive as shown in Figure 4.1(a). The ringis then inserted into one of the eyepieces. If hairlines areunavailable, a Whipple graticule (Figure 4.1(c)) placedin one of the eyepieces can be used instead.

Most often the sample is counted at more than onemagnification depending on the size of thephytoplankton present. Large cells or colonies arecounted at 100x while the majority of cells is counted at200x. If picoplankton is present in considerablenumbers, a count at 400x may be performed. Viewing at1,000x is used for identification only.

4.1.2 Subsampling preserved samplesTo avoid subsampling errors, gently shake and invert thepreserved sample thoroughly for at least 30 seconds sothat it is well mixed before subsampling. For the originalUtermöhl chambers (made by Zeiss) a separate fillingchamber (Füllkammer) is available which ensures evendistribution of algal units in the sedimentation chamber.The break-up of filaments and colonies during shakingis often unavoidable. The subsample is immediatelytransferred into either a counting chamber or into asedimentation vessel. The subsampling technique should

4. Analysis of samples

18

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

be checked regularly by taking several successivesubsamples from the same storage bottle and comparingthe counts of some species (Hasle, 1969). Tensubsamples should be taken and the five dominantspecies counted.

If the cell density is less than 105 cells per litre, thesample needs to be concentrated before counting(McAlice, 1971), preferably by sedimentation (forfiltration see section 4.2, ‘Semi-quantitativeenumeration’). If cell density is too high, dilute thesample with distilled water. If cell density in thecounting chamber is too high, smaller cells will beoverlooked and counting will take too long.Additionally, the count will be incorrect due to easytiring and the observer’s inability to accurately count somany units in the field of view. Dilution orconcentration factors need to be taken into account incalculating the final results.

Usually, only ‘live’ cells (cells with cell contents) arecounted, but if the age status of the population is ofinterest, ‘live’ and ‘dead’ cells should be countedseparately.

4.1.3 Concentration of phytoplankton by gravityWhile other methods are available, the concentration ofalgae by sedimentation is the preferred method.

After mixing, a subsample of between 5 mL and1,000 mL (depending on cell density) is taken andsedimented in a measuring cylinder of suitable size,allowing two hours for each 1 cm of water column at20°C. If small diatoms are present, a settling time of sixhours for every 1 cm of water column is recommended(Furet and Benson-Evans, 1982). For example, if a

100 mL subsample is sedimented in a standard 100 mLmeasuring cylinder (18.5 cm in height), sedimentationwill take 2.3 days for average plankton and 4.6 days forsmall centric diatoms. For most algal populations asedimentation time of 48 hours for a standard 100 mLmeasuring cylinder is recommended. Such a sedimentationtime will also settle ‘difficult’ species such asCylindrospermopsis and Planktolyngbya. There are shorter100 mL measuring cylinders available which will reduceaverage sedimentation time to 24 hours. Foroccupational health and safety reasons, placesedimentation cylinders under a fume hood or usestoppered cylinders. If these options are not available, atleast cover the top of the cylinders with a protective filmor foil.

After sedimentation, the top 90% of volume iscarefully siphoned off without disturbing thesedimented algae, the remainder is shaken gently and asubsample of appropriate volume (see sections 4.1.7 to4.1.9) is transferred to the counting chamber andallowed to settle before counting. From time to time,examine the supernatant for cells that have notsedimented. If the supernatant is siphoned off from apoint well below the meniscus, cells floating on thesurface will be pulled down into the concentrate andwill mix with the other cells when the sample is shakenbefore taking the subsample for counting.

The choice of sedimentation vessels should beguided by the following considerations. In tall settlingchambers an error might be introduced due to cellsadhering to the walls (Utermöhl, 1958). Investigationshave shown that this might happen with chain-formingand setae-bearing marine diatoms (Paasche, 1960) while

Figure 4.1: Microscopic details for Utermöhl method

(a) hairlines as seen in the field of view (b) sequence of directions for scanning (c) Whipple graticule

the chamber bottom

19

ANALYSIS OF SAMPLES

most other forms of phytoplankton are unaffected(Margalef, 1969; Hasle, 1978). The settling containers(usually measuring cylinders) should have aheight:diameter ratio not exceeding 5:1. Convectioncurrents will occur if the sedimentation chamber ishigher than five times its diameter (Nauwerk, 1963)resulting in a considerable amount of plankton failing tosettle, regardless of length of sedimentation time.

To satisfy client needs of short turnaround time,concentration by continuous-flow centrifuge, whichwould cut down the required time to a few minutes persample, is currently under investigation. The methodhas been used for marine work but is not documentedfor freshwater samples.

4.1.4 Removal of buoyancySpecies containing gas vesicles (that is, cyanoprokaryotes) areunlikely to fully settle despite the iodine fixation. The gasvesicles need to be collapsed before the sample is set upfor sedimentation. Keep some untreated sample foridentification purposes. In order to collapse the gasvesicles, expose the sample to brief (approximately 10seconds) ultrasonication (Furet and Benson-Evans,1982). Alternatively, apply pressure to the sample asfollows: after placing the sample in a strong rigid bottlewhich is closed with a tightly fitting rubber stopper,bang the stopper several times with a mallet. After suchtreatment the sample is sedimented as usual. It isadvisable to check the water surface in thesedimentation vessel for the presence of buoyant algalcells before siphoning off the supernatant. Note thatexperience indicates that the distinction between certaincyanoprokaryote taxa is no longer possible after gasvesicles have been collapsed. In this case, performidentification on the untreated sample and estimate theproportions of the different cyanoprokaryotes present,so that cell counts can be apportioned accordingly.Examine the surface within the settling chamber toascertain whether or not other algae may be floatingrather than sedimenting; for example, the green algaBotryococcus which floats because it contains a lighthydrocarbon oil.

4.1.5 TurbidityWater samples from rivers frequently contain high levelsof fine inorganic particles which obscure the algal cells.This is particularly the case during floods. Theseparticles are in the same size range as many algal cells,making it impossible to separate the two by a singleprocedure such as filtration. In this case, the subsample

can be diluted so that cells are visible enough to countand identify. This involves a trade-off between dilutingthe subsample in order to see the cells and reducing cellconcentration below statistically acceptable levels. Toovercome this problem, some authors suggest thatseveral subsamples should be counted and the resultssummed.

4.1.6 Choice of chamberIt is recommended that an Utermöhl chamber be used withan inverted microscope, or a Sedgwick-Rafter chamber or aLund cell with an upright microscope. The choice ofchamber and microscope will depend on the experienceof the algal worker and the financial resources availablefor the project. The use of any of the chambers isacceptable, even though the results obtained using differentchambers are not strictly comparable, as has been reportedby many algal workers. Their results are comparable interms of general trends of phytoplankton developmentand common species, but, because of technicaldifferences, for the same sample, the overall number ofspecies detected and the cell densities of each speciesmay vary considerably between chambers. Therefore, anacute statistical analysis of results obtained usingdifferent chambers is not possible.

For studies in which small nanoplankton andpicoplankton are prevalent, filtration through a mesh ofpore size 20 µm is recommended , followed by countingof the cells in the filtrate in a Neubauer cell orhaemocytometer (APHA, 1995). Small phytoplankton(less than 10 µm) found in Australian rivers in high celldensities include the genus Synechococcus. As the algalcells will not be randomly distributed across the floor ofany of the above counting chambers, the whole floorusually needs to be scanned to avoid serious errors(Lund et al., 1958; UNESCO, 1974). For organismsoccurring in large numbers, in the absence of an obviousnon-random distribution, transects or a suitable numberof fields may be counted (Lund et al., 1958). The fillingof cells (eg. Sedgwick-Rafter chamber or Lund cell) bypipetting does not ensure a random distribution of thealgal cells on the chamber floor (UNESCO, 1974).

An Utermöhl chamber (Figures 4.2 and 4.3) is acombined chamber (Röhrenkammer) consisting of abottom counting chamber plus a chamber cylinderwhich is temporarily attached for sedimentation. Around hole in the bottom plate (up to 2.5 cm diameter)closed with a coverslip on one side forms the chamber.The algae are sedimented directly onto the coverslip andcan thus be viewed with an inverted microscope without

20

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Figure 4.2: Quantitative algal enumeration with Utermöhl chamber

Gently shake and invert preserved sample for minimum 30 s

Subsample 5 mL to 1000 mL of

preserved sample

Remove buoyancy if present

Cell densities >107 cells/mL

Dilute sample

Cell densities < 105 cells/mL Cell densities 105 to 107 cells/mL

Transfer 1 mL subsample to counting

chamber

Let stand for 1.5 hours

Count whole chamber floor at

magnifications 100x, 200x or 400x

depending on algal cell size

Count minimum of 100 to 150 units of

dominant taxa

Calculate final counting result

If nanoplankton present, filter sample

through 20 µm filter, count filtrate in

Neubauer cell or haemocytometer

Sediment subsample for 48 hours

Remove supernatant, shake remainder and

transfer 1 mL subsample to counting

chamber

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21

ANALYSIS OF SAMPLES

optical impairment by the water column in the chamber.Tubes of varying heights and volumes are placed ontothe bottom slide, filled with the subsample and removedafter sedimentation. Various Utermöhl-type chambersare available from manufacturers of invertedmicroscopes (see Appendix D) but simple chambers canbe made readily at low cost (see Appendix D for details).The commercially available chambers with a hole of2.5 cm diameter allow direct sedimentation of volumesbetween 5 mL and 100 mL, in contrast to the chamberdetailed in Appendix D which may require an extrasedimentation step because its tube holds only 4 mL.The commercially available chambers are also faster toset up and clean because the coverslip that constitutesthe ‘bottom’ of the chamber is fixed in the bottom slidewith a metal ring that can be easily unscrewed to allowreplacement of a broken coverslip.

A Sedgwick-Rafter chamber consists of a 50 mm by20 mm microscope slide with a grid floor (1,000 fields)and a raised-rim well holding 1 mL (Figure 4.4). TheSedgwick-Rafter chamber is placed directly under anupright microscope. The chamber can be used with a10x, 20x and 40x objectives but the 20x and 40x shouldto be of long-working distance since for totalmagnifications greater than 100x, the working distanceof most objectives greater than 10x is less than the depthof the chamber. If only 10x and 20x objectives areavailable, the examination of nanoplankton (less than20 µm) is excluded. Glass Sedgwick-Rafter chambers,although considerably more expensive, are oftenpreferred to plastic ones because the latter are easilyscratched.

A third type of chamber is the Lund cell. It consistsof an ordinary microscope slide with two long, thinpieces of brass shim or glass glued to the longer edges.

Figure 4.3: Diagram of Utermöhl chamber(a) bottom counting chamber, (b) bottom counting chamber and chamber cylinder set up for sedimentation. See text and Appendix D forfurther explanation.

(a)

(b)

22

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Figure 4.4: Diagram of Sedgwick-Rafter chamber with coverslip in ‘fill position’

Figure 4.5: Diagram of Lund cell with coverslip in place

A rectangular coverslip is layed on top to form thechamber (Figure 4.5). A subsample of the originalconcentrated or diluted sample is placed in the chamberand, after short sedimentation, is counted under anupright microscope.

The advantages of the Lund cell are:

• it is easy to construct, does not have to be precision-made and is therefore inexpensive;

• it is easy to set up and clean; and

• it is used with an upright microscope with normal-distance 10x and 40x objectives to reach finalmagnifications of 100x and 400x.

With the Lund cell it is optically difficult to identify andcount nanoplankton. Users of the Lund cell havereported that the algal units do not always distributerandomly within it.

4.1.7 Counting with the Utermöhl chamberA suitable volume of either the original sample or theconcentrated or diluted subsample is placed in theassembled chamber and put aside for sedimentation.If the perspex chamber described in Appendix D isbeing used, 1 mL is sedimented for 1.5 hours beforeenumeration. Usually, the whole floor is examined sincethe distribution of the algal units on it is not always

23

ANALYSIS OF SAMPLES

random. For very abundant taxa it might be sufficient tocount every second or third strip or several centraltransects in different directions across the floor. Bymoving the mechanical stage, the chamber bottom istraversed backwards and forwards along adjacent strips(see Figure 4.1(b)) so that eventually the whole bottomhas been covered. All algal cells lying between the twoparallel hairs (Figure 4.1(a)), or within the edges of theWhipple graticule if no hairs are present (Figure 4.1(c)),are counted, as they seem to pass the vertical line. Cellsor units lying across the top hair are counted, but thoseacross the bottom hair are not. Care needs to be takennot to double count long filaments that lie across bothhairs. Different magnifications may be used to countdifferent-sized organisms within the same sample; forexample, 10x objective for taxa greater than 30 µm, suchas Ceratium, 40x objective for cells less than 5 µm, and20x objective for most other taxa. This approach isconsidered preferable to the suggestion of some authorsthat several subsamples of different concentrations becounted, an approach which introduces another level oferror.

The final result, expressed as number of cells permillilitre, is calculated employing factors relevant to thevolume sedimented, including concentration or dilutionfactors. The cell concentration C for each taxon iscalculated according to:

(a) for a concentrated sample, C [cells mL-1] = cellscounted/concentration factor; or

(b) for a diluted sample, C [cells mL-1] = cells counted xconcentration factor.

For example, after sedimentation, 100 mL of originalsample is reduced to 10 mL (concentration factor of 10),and a 1 mL subsample is taken for enumeration. In this,580 cells of species A are counted. The concentration ofspecies A in the original water sample is calculatedaccording to:C = 580/10 = 58 cells mL-1.If central transects are used, a factor is derived from theratio of the chamber floor covered by the transect to thewhole chamber floor. This factor is multiplied by thenumber of cells counted to obtain the concentration incells per millilitre for each particular taxon. To obtaintotal cell density per millilitre, sum all counting resultsof individual taxa expressed as cells per millilitre. Wherecolonial taxa are counted as units, multiply the count ofunits by the average number of cells per unit beforecalculating the cell concentration in 1 mL (seesection 4.1.11, ‘Remarks on counting filaments and

colonies’ for details). For the dominant (mostabundant) taxa, a minimum of 100 to 150 unitsshould be counted per sample.

Willen (1976) suggested a simplified version of theUtermöhl method in which a limited number ofspecies (six to eight) is counted so that approximately90% of total phytoplankton volume is included in thecount. This reduces the counting time by as much ashalf. Additionally, the number of units counted foreach species may be limited, for example, to 60,resulting in a maximum estimated error of ±26%according to equation 8 (below). Thisrecommendation was based on several years of algalcounts in Swedish lakes of varying nutrient status. Thisapproach appears preferable to imposing a time limitper count set a priori, or to counting only abundanttaxa, but its applicability would need testing forindividual programs.

If the genuine Zeiss chambers are employed(diameter of bottom plate = 2.5 cm), only part of thebottom is counted; that is, in several traverses of awidth between 50 mm and 200 mm. The number oftraverses depends on the cell density on the chamberfloor. After each traverse the chamber is turned apredetermined angle, relating to the number oftraverses counted (eg. for four traverses counted, angleis 360/4 = 90). A factor is calculated expressing theratio between the area counted (the transects) and thewhole bottom area. This factor is included in thecalculation of final count results.

4.1.8 Counting with the Sedgwick-RafterchamberEach chamber needs to be calibrated before use. Thevolume is determined by weighing, 10 times, the cellfilled with deionised water and calculating the average.For calibration the chamber is filled in the usualmanner. Calibration of each Sedgwick-Rafter chamberalso requires determination of its area (nominally50 x 20 mm = 1,000 mm2) with a planimeter and itsdepth (nominally 1 mm) with a micrometer. A recordshould be kept of the calibration measurements foreach chamber. If the chamber volume differs from1 mL by 5% or more a factor should be calculated tocorrect to 1 mL. This factor should be markedpermanently on the chamber and used whencalculating final counting results. Recalibrate eachSedgwick-Rafter chamber annually.

A Pasteur pipette is used to subsample 1 mL ofeither the original sample or the concentrated or

24

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

diluted subsample (Gilbert, 1942). The subsample isthen run into the chamber at one corner with thecoverslip lying at an angle across the chamber (seeAPHA, 1995). Once the chamber is filled, the coverslipis moved to cover the whole chamber and the sample isleft to settle for 30 minutes. To prevent formation of airbubbles due to evaporation of sample during counting,distilled water may be added to the edge of the cover slipfrom time to time. The cells are counted on the bottomof the chamber. The counting of live samples is notrecommended since flagellates and buoyantcyanoprokaryotes may accumulate under the coverslip andconstitute a source of error. All cells or units withinrandomly selected fields or traverses are counted.Depending on the density of the algae, a smaller orlarger number of traverses or fields is counted until theminimum number of units set for each species has beencounted. Since the units do not always distributerandomly in the cell, space the traverses or fields alongthe whole chamber to overcome this bias. A conventionneeds to be followed for cells or units lying on aboundary line of a field; for example, all cells or unitsoverlapping the right-hand and top boundary would becounted, but those overlapping the bottom and left-hand boundary would not. It is recommended that 30fields be counted within the chamber so as to include 90 to95% of the species present. Counting 25 fields willinclude 80 to 90% of species present (McAlice, 1971).

For a field count, the cell concentration C, expressedas the number of units per millilitre for each taxon, iscalculated according to:

(1)where:

N = number of cells or units counted

A = area of field (mm2)

D = depth of a field (Sedgwick-Rafter chamberdepth) (mm)

F = number of fields counted.

For colonial taxa, multiply the count of units by theaverage number of cells per unit (see section 4.1.11,‘Remarks on counting filaments and colonies’ fordetails) and use the resulting value as N in equation 1.To adjust for sample concentration or dilution, theresult is divided or multiplied by the appropriate factor.To obtain total cell density per millilitre, sum allcounting results of individual taxa expressed as cells permillilitre.

If cell density is low (less than 10 units per field),counting of long traverses to cover a larger proportion ofthe chamber floor is more appropriate. Several traverseswith a width of a chamber field are counted. Thenumber of traverses depends on the required precisionand the phytoplankton density.

For a traverse count, the cell concentration,C, expressed as number of units per millimetre for eachtaxon, is calculated according to:

(2)

where:

N = number of cells/units counted

L = length of each traverse (mm)

W = width of traverse (mm)

D = depth of a field (Sedgwick-Rafter chamberdepth) (mm)

S = number of traverses counted.

Treat counts of units as described above. To adjust forsample concentration or dilution the result is divided ormultiplied by the appropriate factor.

4.1.9 Counting with the Lund cellLund cells must be calibrated before use. Determine thevolume of each chamber by weighing it before and afterfilling with deionised water. Repeat this 10 times andcalculate the mean. The chamber should be filled in thesame manner as for counting, and completely driedbetween measurements. Calculate the area of thechamber by multiplying the length of the coverslip bythe distance between the two side pieces. These lengthsare measured either with the vernier scales on themicroscope table or with a separate vernier gauge.Repeat measurements at intervals along the lengthseveral times. After initial calibration always use thesame coverslip with each cell and recalibrate annually.If the coverslip is broken, repeat the calibration with anew coverslip.

Measure the area of the Whipple graticule at eachmagnification under the microscope using a stagemicrometer. The Whipple graticule, located in one ofthe eyepieces, defines the field of view, or width of thetraverse counted. Since only part of the chamber (eitherseveral fields of view or traverses) is counted, aconversion factor needs to be derived to relate the areacounted to the total area of the chamber. By knowingthe volume of the Lund cell and the area being

N x 1,000 mm3

A x D x FC [cells mL-1] =

N x 1,000 mm3

L x D x W x SC [cells mL-1] =

25

ANALYSIS OF SAMPLES

examined it is possible to relate the algal count recordedas a number of units per area to cells per millilitre in theoriginal sample.The total number of Whipple graticule fields within thetotal chamber area is calculated as:

(3)

The conversion factor Ff for counting fields of view iscalculated as:

(4)

The conversion factor Ft for counting short traverses iscalculated as

(5)

To perform a count, place the coverslip onto the cell(Figure 4.5) and run in a volume as determined by thecalibration of either the original sample or aconcentrated or diluted subsample into the chamber byplacing the tip of the pipette close to the open edge ofthe coverslip. The liquid will be sucked under thecoverslip by capillary action. Avoid the formation of airbubbles in the chamber. Let the filled chamber stand for10 minutes for the algae to settle onto the surface of theslide. If buoyant cyanoprokaryotes are expected, scan theoptical plane directly under the coverslip as well as thedepth of the chamber for their presence.

Only part of the chamber floor is counted. Anumber of randomly selected fields of view or short orlong traverses are counted until a minimum of 100 unitsfor each of the dominant species is counted. Thenumber of fields of view or traverses counted dependson the cell density in the chamber. Cells greater than12 µm are counted at 100x magnification, while smallercells are counted at 200x magnification. If high numbersof picoplankton are present these cells are counted at400x magnification.

Counting fields of view: The size of a field of view isdetermined by the outline of the Whipple graticule.

Counting traverses: The traverses are as wide as theWhipple graticule. The traverses are placed evenly acrossthe length (short traverses) or the width (long traverses)of the cell, avoiding the area close to the open edges.

Total area of chamber [mm2] Area of Whipple graticule [mm2]

Calculate the cell concentration C, expressed innumbers of units per millilitre, for each taxonaccording to:

(6)

where:N = number of cells or units countedF = number of fields countedFf = field conversion factor.

To adjust for sample concentration or dilution, theresult is divided or multiplied by the appropriate factor.To express final cell count results of colonial species incells per millilitre, follow the procedure in section4.1.11, ‘Remarks on counting filaments and colonies’.

4.1.10 Statistics of countingThe purpose of phytoplankton counting is to gain anestimate of the population in the sampled waterbodythat is as close as possible to the true size of thepopulation. Due to errors inherent in the methodology,we will never know the true value, but we can usestatistics to evaluate the probability of the measured valuelying within a certain range or confidence limits aroundthe true value. The true value of a phytoplankton countis a function of both the accuracy and precision of thecount. This section gives the steps and knowledgeneeded for the determination of accuracy and precisionof counts and explains sources of errors in algal counts,while in-depth treatments of the subject can be found inLund et al. (1958), Lund (1959), Baker (1986) andLaslett et al. (1997).

At the beginning of a program it is essential to evaluatethe precision of the algal count method used and to decideon the desired level of precision. To obtain a precise andreproducible result, amenable to statistical comparison,representative samples need to be collected in the field(see section 3, ‘Taking samples’) and representativesubsamples need to be taken from the preserved materialin the laboratory (see section 4.1.2, ‘Subsamplingpreserved samples’).

The agreed subsampling procedure should be testedat the beginning of the project since it is not practical todo this for each sample counted. It is advisable to keepthe number of subsampling steps to a minimum becauseeach one introduces a new source of error. There aregenerally two subsampling steps in algal enumeration:(1) taking a subsample from the storage bottle, and(2) counting only part of the chamber floor (strips orfields), thus introducing two sources of error – fillingerror for (1) and clumping error for (2). Determine for

Total numberof fields

1Lund cell volume [mL]

x total number of fieldsFf =

Ff(Cell/Whipple graticule length)

Ft =

NF

C [cells mL-1] = x Ff

=

26

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

[P (χ2) > 0.975] limit for the sample size used(McAlice, 1971). To obtain confidence limits for cellcounts of colonies or filaments, multiply the confidencelimits for the count of units by the mean number of cellsper unit.

The level of precision relates to individual taxa, not tothe overall sample, since it depends on the number of algalunits counted. A predetermined level of precision should beset for the most abundant taxa by the program designer,which in many cases will be the client. The level ofprecision should relate to the aim of the program, theability to make correct management decisions based onsuch algal counts and the desired cost of the algalcounts. The program designer needs to decide whetherreal change in cell abundance (for example, celldoubling) can be detected in successive samples andwhat the risks are of having a false positive (falseindication of change) or a false negative (false indicationof no change) at the chosen level of precision. Forrecommended precision levels in cyanoprokaryotecounts, see the paragraph on counting filaments below.For other phytoplankton, such as species with individualcells or small colonies, it is recommended to set the levelof precision to ± 20% error for the most abundant taxafollowing Lund et al. (1958). This level of precision isreached by counting a minimum of 100 algal units ofthe taxon in question per sample. The countingprecision for less common taxa will always be lower thanthat for common taxa since the required minimum of100 algal units will not be found in the sample.

The counting error (precision) can be estimated witha 95% confidence limit by:

(8)

where N is the number of units counted, if the algalunits do follow a Poisson distribution for bothsubsampling steps. For example, if 100 units arecounted, the error is ± 20%; if 400 units are counted theerror is reduced to ± 10%. Thus a fourfold increase incounted units is required to halve the error. Generally,100 to 150 units of the common taxa are counted,giving an approximate error of ± 20%. Of course, withina sample the error for individual species will vary widelyaccording to their individual densities.

One should be aware of the causes and magnitude ofall errors in one’s methods, firstly in order to reducethem, and secondly in order to decide on the level ofprecision wanted and the time involved to reach it. Twotypes of errors are generally recognised when estimating

2

Nx 100 = counting error (+ %)

=(n – 1)s2

xD =

k

t=1Σ (xi – x)2

x

each subsampling step the type of distribution of algalunits among repeated subsamples in order to estimatethe error introduced. Depending on the chamber usedand the mode of counting, compare either results fromseveral whole chamber floors filled from the samesample (Utermöhl chamber) or results from several fieldsor strips in one subsample (Lund cell, Sedgwick-Rafterchamber). The statistics describe the distribution of entitieswithin the samples with regard to calculating error levels.These entities, referred to as algal units in this text, maybe single cells, filaments or colonies, depending on thespecies.

As regards the filling error, the distribution ofcounting units of individual species among subsamplesfrom the same storage container can generally bedescribed with a Poisson distribution, but it is advisableto test this using the statistic D after Fisher et al. (1922).

(7)

This variance test has the chi-square (χ2) distributionwith k – 1 df, where k is the maximum number ofindividuals a sampling unit could contain and df isdegrees of freedom. The outstanding feature of thePoisson distribution is that the variance is equal to themean (σ2 = µ). The assumption of H

0: σ2 = µ (the null

hypothesis) is tested against H1: σ2 ≠ µ (the alternative

hypothesis) where the rejection criteria are P (χ2) >0.975 and P (χ2) < 0.025 using the statistic D, which isthe index of precision (the ratio of standard error to themean). Acceptance of the null hypothesis indicates anon-random distribution, that is, a Poisson distribution.

If only part of the chamber floor is counted (field orstrip count) and the counting chamber is filled with asubsample of the original sample, random distributionof algal units within the counting chamber needs to beverified. If algal units are not randomly distributed thedata need to be normalised before errors and confidencelimits can be estimated.

With regard to the clumping error, the distributionof counting units among subsamples within the onesample (fields or strips) does not usually follow a Poissondistribution. This should be tested by performing a one-tailed test for H

0: σ2= µ against H

1: σ2 > µ with

P (χ2) < 0.05. The null hypothesis can also be testedgraphically by plotting sample mean squares against thesample means. Most points should lie on or close to the45° line σ 2= x. The null hypothesis is rejected whenpoints fall outside the upper [P (χ2) < 0.025] or lower

27

ANALYSIS OF SAMPLES

4.1.11 Remarks on counting filaments andcoloniesTo obtain an accurate count, the number of cells perfilament or colony needs to be enumerated in eachsample, since the size of these algal units can varygreatly. For example, Anabaena filaments may containbetween five and several hundred cells, and the size of aMicrocystis colony can range from fewer than 10 cells toseveral thousand cells.

For filaments in which the individual cells are easyto recognise and are of regular length (eg. Aulacoseira),the number of cells per filament for the first 30filaments observed is counted and the mean number ofcells per filament for the sample is calculated. In yoursamples, establish whether the number of cells perfilament is normally distributed. If a skewed distributionis apparent, calculate the median rather than the meannumber of cells per filament for the species concerned.

For filaments of cyanoprokaryotes, it isrecommended to follow the procedures in Laslett et al.(1997) for calculating the precision according to theSichel distribution. The equation used:

(9)

where N is the number of units counted, calculates theoverall counting error in terms of variance and standarderror, thus taking into account the clumping error andthe error related to the variability of cells per algal unit.To achieve a ±20% precision, 50 trichomes need to becounted; to achieve a ±30% precision, 23 trichomesneed to be counted. In either case, the number of cellsfor each trichome counted must also be determined. Forspecific recommendations for the precision levels ofcyanoprokaryote counts please refer to the finalAgriculture and Resource Management Council ofAustralia and New Zealand national protocol for themonitoring of cyanobacteria (Jones, 1997b).

For filaments in which cells are not distinguishableat 100x or 200x magnification (eg. Limnothrix) in eachsample determine the average length of 30 cells at 400xor 1,000x magnification and measure the length offilaments during counting. Then calculate cellconcentrations of the species in question from these twomeasures. If the 1,000x objective cannot be used withyour counting chamber, after counting transfer somesample to a normal microscope slide and view at 1,000x.

In some genera of filamentous forms(eg. Oedogonium and Lyngbya) individual species can beidentified only when mature thalli or reproductive stages

phytoplankton densities: systematic errors and randomerrors. Systematic errors, which affect the accuracy of theresults, are inherent in the method used and introduce abias for all counts. They can be eliminated byappropriate change of methods. Sources of random errorare the naturally occurring non-random distribution ofalgae in the water (patchiness), subsampling, observererror, and errors in estimating the number of cells percolony or filament. Random error affects both theaccuracy and precision of counts. The size of the errorsalso depends on the counting methods used and the sizeof samples.

The accuracy of algal counts will never be very highdue to patchiness of the phytoplankton in the water.Most ecological studies that involve sampling naturalpopulations are concerned with generations or anabundance change of 100%, where a precision of ±50%would be quite adequate. Assuming the algal units aredistributed randomly on the chamber floor, it can becalculated how many algal units need to be counted toachieve a desired degree of precision for a givenconfidence level. The precision of a count varies inverselywith the square root of the number counted (Lund et al.,1958); for example, a count of 100 cells has a precision of±20% compared to a count of 400 cells which has aprecision of ±10% at the same level of confidence (95%).Consequently, to increase the precision level from ±20%to ±10% at the same level of confidence, the countingtime per sample increases fourfold. For most algalenumeration of field samples a precision of ±20% isgenerally accepted, in which case a count of100 units/mL for a taxon based on 100 randomlydistributed units in the chamber would mean that theestimated value lies somewhere between 80 and 120.

As a preferred method for reporting results, for eachalgal count the precision for the five most abundant taxashould be recorded and presented together with the countingresults in the data report. It is vital to interpret algalcounting results with their precision in mind. Forexample, if a count of 1,000 cells/mL with a precision of±20% is reported, the true cell concentration in thesample may be between 800 and 1,200 cells/mL. If thecounts from two samples were to differ by one order ofmagnitude, this might be a true difference in populationdensity or may have resulted from counting imprecision(McAlice, 1971).

2x 100 = counting error (+ %)N

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

are present. Nevertheless, size classes of varying filamentwidth can be readily distinguished and cell counts forthese genera should be recorded in separate size classes.The width of such filaments is measured between thecell membranes; for example, the sheath ofcyanoprokaryotes is not included.

To determine the average number of cells per algalunit for colonies shaped differently from filaments,record the number of cells in the first 30 coloniesencountered and calculate the mean if normallydistributed. If these measurements are skewed, calculatethe median. The number of units per millilitre countedin the sample is then multiplied by the mean or medianto obtain a final result of cells per millilitre.

Some species under bloom conditions form coloniesso large that only an estimate of cells per colony can bemade unless the colonies are dispersed and individualcells are counted. Some cyanoprokaryotes(Coelosphaerium, Gomphosphaeria, Microcystis) formlarge, three-dimensional, mucilage-bound colonieswithin which counts of individual cells are all butimpossible. Reynolds and Jaworski (1978) recommendrapid (less than 1 minute) ultrasonic disintegration ofcolonies as a quick, routine procedure in this situation,followed by a count of the individual cells at 400xmagnification. Alternatively, it may be appropriate toestimate the number of cells in each colony examined,rather than estimate the average number of cells percolony for a given sample size. For particularly largecolonies, this can be achieved by counting the numberof cells in a small proportion (area) of the colony (usingan eyepiece grid) and then estimating the total numberof similar areas in the total colony. If, however, estimatesrather than accurate counts are made, this needs to berecorded in the laboratory work sheet and indicated inthe final report to the client.

4.1.12 Taxonomic identificationThe level of taxonomic identification depends on theobjectives of the program, the training of staff and thefinancial resources available. Dominant species andproblem species should be identified to species level in anycase. For a general study, identification to genus levelmight suffice, while for ecological studies all the speciesimportant with respect to abundance and biomassshould be identified to species level. Althoughidentification to species level often takes considerablylonger than working to lower taxonomic levels (phylumor class), it will also supply the information essential forstudies of phytoplankton community structure and

succession (McAlice, 1971). Ecological studies requireidentification to species level to draw on the informationon autecology of the algae. The ecological requirements ofindividual algae can vary considerably within one genusand, although tedious, correct taxonomic identification tospecies level still forms the basis of any in-depth ecologicalinvestigation. In water quality monitoring, identificationto species level is critical for highlighting the presence ofpotentially toxic species; for example, Anabaena circinalisappears to be the only species of Anabaena to producetoxins in Australia.

For identification, fresh live samples arerecommended, especially if flagellates are thought to bepresent.

Some taxa, in particular the diatoms, cannot beidentified to species or even genus level at the magnificationused for counting. It is convenient to group such taxa intosize classes and count the cells accordingly. For instance,single centric diatoms might be grouped into size groupsof less than 5 µm, 5 µm to10 µm, and greater than10 µm. After additional preparation of sample material,diatom species can be identified and the size classesrelated to species names. If quantitative results for thediatoms are required, 300 valves on a permanent slideare counted and the relative proportion of each speciesin the sample calculated.

Diatoms are often counted in collective categorieswith defined size ranges such as ‘centric diatoms 5 µmto10 µm’, because detailed identification is impossible inthe counting chamber. Special preparations of thefrustules and viewing at 1,000x on a microscope slideare required for their identification. Diatoms areprobably the best-studied algal group with respect toautecology and there is now a large body of literaturedescribing ranges of environmental conditions such astemperature, pH and ion concentration for manyspecies.

For taxa occurring rarely within a particular algalprogram, it may be convenient to simply count them ingroups; for example, ‘cryptomonads’. When countingpreserved samples, the observer needs to distinguishbetween cells that were alive at the time of fixation andthose that were not. Only the cells that were alive arecounted. Complete and healthy looking chloroplasts andcell membranes are often used to characterise healthycells. Such distinction is especially important whencounting diatoms since their frustule can exist for manyyears after the cell has died.

For ongoing monitoring programs it is stronglyrecommended that a collection of photomicrographs

29

ANALYSIS OF SAMPLES

and permanent wet mounts or dry mounts (for diatoms)of the taxa observed be established for future referenceand training of new staff. Such collections can also behandy in identifying possible changes in shape and sizein particular species (eg. Ceratium) over the seasons.Keeping preserved material and photomicrographs willalso facilitate information exchange between workers atdifferent agencies. In addition to the photomicrographand permanent slide collection, written records need to bekept of unidentified taxa in a standard format containinginformation such as cell dimensions, colour, numberand shape of chloroplasts, presence or absence of cellorganelles, unusual features and a drawing.Identification by an algal taxonomist can then be soughtat a later stage.

4.1.13 Recording resultsA standard algal counting worksheet (hardcopy orelectronic form) should be used for all samples. It shouldgive essential information about the sample and havespace to record the counting results; for example, seeAppendix E. The sheet should contain information onlaboratory reference number, date and site of collection,number of the counting chamber used, magnificationused, the volume of subsample for sedimentation orfiltration, area counted and factors used to calculate thefinal cell count. The sheet should also contain the nameof the person identifying and counting the sample andof the person entering the counting results onto thedatabase. A record should always be made of whether it wascells or colonies or filaments that were counted. Theworksheet should also provide a space for generalcomments. To save time it is useful to employ a multiplecounter or, even better, one of the software programsdesigned for this purpose (see Appendix D).

The taxonomic level at which the counts arerecorded depends on the aim of the study. It may varyfrom recording only counts summed by algal class withthe exception of full identification of the dominant taxa(eg. green algae, diatoms, Euglenophyceae,cyanoprokaryotes, Aulacoseira granulata, Microcystisaeruginosa, Actinastrum falcatus) to identification tospecies level wherever possible.

Despite differing levels of accuracy, it is preferable toenter the enumeration results of all taxa, including therare ones, onto the database. Time will be saved duringdata entry if species names are ordered by taxonomicclasses. For routine monitoring at established sites, the15 or so most common taxa should be prelisted on theworksheet.

Phytoplankton density is a concentration measure andis usually expressed in cells per millilitre. For certainstudies, the phytoplankton load will be of interest. Thiscan be calculated as the product of the cellconcentration and the discharge. For statistical reasons,phytoplankton is usually counted in units. Units may beeither single cells, colonies or filaments depending onthe usual form of the species. If units are not single cells,the average number of cells per unit can be estimated bycounting the cells per unit for the first 30 units observedand calculating an average. The number of unitscounted in the sample is then multiplied by the averagenumber of cells per unit. This procedure needs to berepeated for each sample since the number of cells perunit can vary considerably in space and time.

4.1.14 Algal coding systemTo facilitate electronic data storage, reporting andanalysis, it is essential to use a coding system for thealgal taxa when recording the counts. Several codingsystems for algae have been suggested (for example,Lhotsky et al., 1974; Whitton et al., 1978; Williams etal., 1988). The latest and most comprehensive list is‘A Coded List of Freshwater Algae of the British Isles’, adigital version of which is also available (Whitton et al.,1999). Although this list cannot be adapted directly forAustralia because of differences in species, it is anexcellent example of such an endeavour. Any such systemassigns a unique code to each individual taxon. The codecan comprise a series of numbers or letters or both.According to Whitton (1991), all of the suggested algalcoding systems have shortfalls when screened againstfour criteria. One criterion demands the flexibility toaccommodate future nomenclatural changes. Suchchanges can be anticipated, since algal taxonomy is stillvery much subject to change and opinions about thevalidity of various taxonomic systems vary. A secondcriterion requests ‘dumping ground’ categories on themaster list for organisms that cannot be fully identified.

Setting up a comprehensive algal coding system willalways meet taxonomic difficulties since manyorganisms have yet to be clearly identified. Algaltaxonomy, in contrast to that for higher plants, for example,is still at a stage of continuous revision. In Australia,phycologists routinely resort to overseas texts foridentifications because an Australian key has yet to bepublished. The lack of local taxonomic texts addsuncertainty to taxonomic identifications. Therefore, theproposed algal coding system contains ‘dumping

30

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

ground’ categories in which cells that cannot beidentified to genus or species level are recorded. Ofcourse, such cells and the category they were counted inneed to be documented (see section 4.1.13, ‘Recordingresults’) to avoid recording the same cell in more thanone category.

The development of a national master list of freshwateralgae, the centrepiece of such a coding system, is beyondthe brief of this current project, but the establishment ofsuch a master list for use by all water resource agencies andother algal workers would be highly desirable. Use of sucha system would greatly enhance information exchangebetween agencies and improve the usefulness of algaland related environmental databases in describingfreshwater systems across basins or States.

The structure for the coding system suggested hereincorporates elements of Whitton et al. (1978) and thecode includes information on the phylum, genus andspecies of the algal cells. In the absence of an Australianflora, the phylum structure in Algae, an introduction tophycology (van den Hoek et al., 1995) is followed. Thisphylum structure has been adopted for the ‘Algae inAustralia’ series of taxonomic texts (see Appendix C).Additionally, the following considerations were takeninto account for the suggested format of the code:

• an eight-digit code can be used on all computersystems; and

• by allocating the first two digits for the protista andalgal phyla, the code meshes well with the eight-digit code developed for all Australian organisms bythe Victorian Environment Protection Authority(J. Dean, pers. comm.).

The adoption of the DIATCODE format for genus andspecies caters for the needs of diatom taxonomy.DIATCODE, a coding system for diatoms developedinternationally, is already being used in Australia bydiatom taxonomists. DIATCODE can be obtained bycontacting Dr Helen Bennion, Environmental ChangeResearch Centre, University College of London,26 Bedford Way, London WC1H0AP, UK or onhttp://www.geog.ucl.ac.uk/ecrc/.

By choosing to include both a low taxonomic level(phylum) and a high taxonomic level (species andvarieties), the coding system is useful for both generalmonitoring work and specific, in-depth taxonomic andecological research such as nutrient transfer functions fordiatoms where species identification is required. Thephylum level is included to allow a grouping ofdetected algal taxa into relatively general categories

which are relevant for managers as well as scientists.Possible groupings here could be, for example,‘cyanoprokaryotes’ versus ‘other groups’ for operationalpurposes or ‘green algae’, ‘diatoms’, ‘chrysophyta’,‘cryptophyta’, ‘cyanoprokaryotes’ and so on, to look atdifferent pigment composition or selective use ofnutrients (eg. SiO

2 by diatoms). The level of genus is a

relatively certain taxonomic unit. The identification togenus level is quite specific but does not require as manyresources (time and taxonomic expertise) asidentification to species level. Identification to specieslevel is relevant for a range of different purposes such asthe identification of potentially toxic cyanoprokaryoteblooms, identification of odour-producing or filter-clogging ‘nuisance algae’, and detailed ecological work,including the use of benthic diatoms as water qualityindicators.

4.1.15 Details of codeThe suggested code consists of eight digits, the first fourbeing alpha characters and the remainder usually beingnumeric characters. The first two digits code the highesttaxonomic category (phylum), characters three and fourrepresent the genus, characters five, six and sevenrepresent the species and character eight is reserved forvariety or form. Three characters for the species areneeded to record some genera of diatoms and desmidswhich contain more than 99 species. Varieties and formsare most common among the diatoms. The codes for thephyla (the first two digits) are given in Table 4.1. Thegenera within a phylum and the species within a genusare ordered alphabetically.

Example for code:CCAU003A Aulacoseira granulataCC Phylum Protista, Bacillariophyta

AU Genus Aulacoseira003 Species granulata

A type species

Example for varieties:CCAU003B Aulacoseira granulata var.

angustissimaCCAU003D Aulacoseira granulata var.

granulata

Example for different species:CCAU030A Aulacoseira crenulata

The designation of the last alpha character (digiteight) is arbitrary and can be assigned to either the typespecies or a variety. Normally, the type species gets apriority designation ‘A’, except where it has a nominated

31

ANALYSIS OF SAMPLES

variety. This is often the case, as in the followingexample.

Example for variety being the type species:CCAU005A Aulacoseira distans var.

distansTo describe an unknown variety of a known species,

the last digit would be a ‘1’, if it was the first unknownvariety found. Using the numbers ‘1’, ‘2’ and so oninstead of a ‘9’ will make is easier in the context of adatabase to rename records once the variety has beenidentified or described.

The code for the remaining six digits is found in themaster list that is to be developed. For diatoms theexisting DIATCODE may be used.

Where a taxon is recorded in several size classes usethe last digit to indicate the size class. An alpha characterother than the ones employed for variations is chosen.

4.1.16 ‘Dumping ground’ categoriesAn unidentified taxon is represented by a sequence of‘9’s. Where an alga can be recognised only at phylumlevel it would be recorded as

for exampleCG999999 Unidentified

Euglenophyteor at genus level asCGEU9999 Unidentified genus Euglena.

Where an alga can be recognised only to genus level,three possibilities exist for it to be recorded:

(a) If it is recognised as an alga belonging to a certaingenus, it will be recorded under the genus

for exampleCCAU9999 Aulacoseira sp.

b) If it can be clearly distinguished as a separate species,it will be coded as unknown species 1, 2 etc.

for exampleCCAU9919 Aulacoseira sp. 1

c) Similarly, if it can be distinguished into a particularsize category but not as a species, it will be coded asan unknown species using the last digit to indicatethe size class according to the rules above.

for exampleCCAU999R Aulacoseira size class

‘small’In some genera (eg. Lyngbya, Oedogonium), although

the cells show a large morphological range, speciescannot readily be recognised in the absence ofreproductive stages or mature thalli. In these instances,

it is suggested that the genus be divided into size classeswhich are coded in the same manner as an unknownspecies with different size classes. Size classes for suchgenera are established in accordance with thoseoccurring in the geographical area sampled.

The codes for the first two characters representingthe phyla are as follows in Table 4.1.

Table 4.1: Higher taxa codes for algae

Code Regnum Phylum

A Archaebacteria

AA Archaebacteria

B Eubacteria

BA Other phyla ofEubacteria

BB Cyanoprokaryotes

BC Prochlorophyta

C Eukaryota

CA Glaucophyta

CB Rhodophyta

CC Heterokontophyta(incl. Chrysophyceae,Xanthophyceaeand Bacillariophyceae)

CD Haptophyta

CE Cryptophyta

CF Dinophyta

CG Euglenophyta

CH Chloroarachniophyta

CI Chlorophyta

4.1.17 Software for countingSoftware is now available for recording cell countsdirectly into a computer data file during counting. Useof such programs saves time and eliminates data entry asa separate source of error. Most programs have minimalhardware requirements (eg. IBM-compatible 386machine). Depending on the program, it will calculatefinal counts and give statistical error margins for the

32

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

results obtained. Counting results can be directlyimported into analytical software. For details ofprograms and suppliers, see Appendix D.

4.1.18 Area Standard UnitsArea Standard Units (ASU) are calculated as the sum ofthe maximal cross-sectional areas of all the algal cellsfound in a sample.

The use of ASU in Australia is limited, the onlyknown example being in licence agreements for watertreatment plants in the Sydney region. The sole purposeof ASU is to provide to the plant managers an indicationof the filter-blocking capacity of the phytoplanktonpresent in the raw water. ASU are not a biomassmeasurement. The parameter ASU has no significance withregard to the ecological state of a waterbody and is of littlerelevance in water quality studies.

MethodFor each species occurring in the sample, the two longestcell dimensions (without spines or appendices) of aminimum of 30 individual cells are measured and themean cross-sectional area calculated. Cell areas areestimated for each algal species from formulas for solidgeometric shapes that most closely match the cell shape.Multiply the value of the cross-sectional area by thenumber of cells per millilitre for each species found inthe sample. To obtain ASU for the sample, sum allproducts from all species found in the sample. It is self-evident that cell size measurements need to be repeatedat different seasons and on algae originating fromdifferent waterbodies. For ongoing monitoring programsit is possible to set up a database of ASU for speciesoccurring by measuring at least 100 cells over severalseasons.

4.2 Semi-quantitativeenumerationIf time restrictions do not allow a full quantitativeanalysis of the preserved material, a semi-quantitativeestimate of cell numbers can be made from live samplesnot older than 24 hours. Semi-quantitative enumerationis not recommended as a benchmark method. Cells areconcentrated by filtration, then counted in a Sedgwick-Rafter chamber or Lund cell as described above. Always

indicate in the data report that results are only semi-quantitative.

4.2.1 Concentration by filtrationA defined volume of sample is filtered using amembrane-type filter (for example, cellulose) of poresize 0.45 mm at low suction pressure to a point wherethe filter is still just wet. The algae are then brushed offand resuspended in 5 mL of distilled water. A 1 mLsubsample is used to fill a Sedgwick-Rafter chamber orthe appropriate volume to fill a Lund cell. Observationsthen proceed as usual. If motile forms are present,narcotisation is recommended (McAlice, 1971) withdrops of isotonic magnesium chloride solution or onedrop of saturated uranylacetate (UNESCO, 1974).Alternatively, adding methyl cellulose will increase theviscosity of the sample (UNESCO, 1974).

The advantage of counting live samples is the shortturnaround time. The disadvantages are that naked algaeor thin-walled diatoms may be damaged duringfiltration (UNESCO, 1974) and that the count is onlysemi-quantitative. This procedure might be used foroperational purposes such as monitoring thedevelopment of an algal bloom at short intervals, butweekly or fortnightly counts from preserved material forverification should be maintained in parallel.

4.3 Biomass measurementsWhile cell counts give information on communitystructure and abundance of individual species they arenot satisfactory as a measure of algal biomass. The twomost common approaches to determine algal biomassare volumetric biomass determination and chlorophyll-ameasurements.

4.3.1 Volumetric biomass determinationAn inherent difficulty in relating algal densities toenvironmental parameters such as nutrients is theenormous size range of algal cells, from 1 µm to 10 µm(van den Hoek et al., 1995). A cell count value of one canrefer to a vast range of cell volumes. There is no easy wayto transform cell counts into volumes of living biomass.The most common method used by phycologists is tomeasure the dimensions of a representative number ofcells (minimum of 30, but most researchers measure 100to 200 cells) for each species and to calculate an averagevolume for each species using formulae for geometricalshapes closest to the cell’s shape. A more sophisticated

33

ANALYSIS OF SAMPLES

is faster than algal counts and can be performed withless training. It has two disadvantages: the loss ofinformation on the species composition of thephytoplankton, and the large natural variation ofchlorophyll-a concentration per cell which depends onsuch factors as species and physiological lightadaptation. Cyanoprokaryotes contain less chlorophyll-aper cell weight than eukaryotic algal groups.

Samples taken for chlorophyll-a analysis cannot bepreserved. To determine the chlorophyll-a concentration,a straight water sample of between 0.5 L and 5 L,depending on cell density, is taken and preferablyfiltered in the field. The sample is thoroughly mixed byshaking and a measured volume of it passed through aglass fibre filter (free of organic binder) with a pore sizeof 0.45 µm, using a suitable holder and hand pump(inexpensive hand pumps are commercially available).The filter is immediately placed in an opaque bag anddeep-frozen in liquid nitrogen or in a car freezer.Chlorophyll-a breaks down if exposed to light. The filtersare kept frozen until analysed in the laboratory.Processing of filters ideally occurs on the same day or, ifthis is not possible, they may be stored deep-frozen forup to three weeks (APHA, 1995) before analysis.Whichever procedure is adopted for the program, itsvalidity should be tested beforehand. The high turbidityoften present in Australian inland waters may interferewith the filtration and thus reduce the volume filtered.

There are various methods for measuring thechlorophyll-a concentration in water samples, includingspectrophotometry, fluorimetry and high-performanceliquid chromatography. In recent years, successful in situfluorescence methods have been developed. Therecommended spectrophotometric method is thatdescribed in ISO 10260:1992 (E), which uses hotethanol as the solvent. It is most commonly used inroutine and research work both in Australia (Clark andLidston, 1993) and overseas (Tubbing et al., 1994).Many workers prefer hot ethanol because it is non-toxicand yields a better extraction than, for example, coldacetone. Further information on chlorophyll-a methodscan be found in Nusch (1980), Marker et al. (1980) andNusch (1984).

approach includes the subtraction of the volume of thecell vacuole from the overall cell volume to gain a morerealistic value. The average volume for each species isthen multiplied by the cell count for the species inquestion and all the products summed to gain abiovolume per sample in mm3 per millilitre. The totalwet algal volume is calculated according to(APHA, 1995):

(10)

where:

Vt = total plankton cell volume (mm3/L)

Ni = number of organisms of the ith species/mL

Vi = average volume of cells of ith species (µm3).

The described procedure is time-consuming andtedious, but gives reliable results. The average size of cellsof a species may change by a factor of up to 10 during agrowing season or its life cycle. Lists of the meanbiovolumes of species are available in the literature(Reynolds, 1984) and from some of the Australian algalcounting laboratories. In using such values, keep inmind how much the average size of cells of a givenspecies may vary within during a growing season andthat the size of the same species may vary from onewaterbody to another.

Although such a detailed study may be reserved forspecial investigations, because of the required resources,data from monitoring programs that investigate theecological context of algal populations would be much moreuseful if they included some indication of algal biomass.It is therefore suggested that data on volumetric biomassbe determined at a lower frequency within the regularsampling program (eg. monthly for a weekly program)and that emphasis be placed on the dominant speciesand very large species. Useful information will thus begained for relating the development of phytoplanktonpopulations to in-stream nutrient concentrations or tothe biomass of higher levels in the food web(eg. zooplankton), since in most instances the dominantspecies make up 70 to 80% of the biomass.

4.3.2 Chlorophyll-aIn exploiting the fact that algae, like all plants, containthe pigment chlorophyll-a, one can measure itsconcentration in a water sample, then calculate algalbiomass using an average factor for the chlorophyll-aconcentration per cell: approximately 1 to 2% of dryweight in planktonic algae (APHA, 1995). This method

Vt = Σ

n

i = 1( N

ix V

i)

34

Recommendations are provided on how to applyquality control and quality assurance principles toalgal sampling and enumeration and how tocorrectly report data to clients. Correct databasecreation and maintenance are emphasised.

5.1 Quality assuranceQuality assurance consists of a set of guidelines that, iffollowed strictly for both field and laboratoryprocedures, will produce analytical results of knownaccuracy and precision. Quality assurance has twoaspects: internal quality control and external qualityassessment (Figure 5.1).Quality control extends to areas of:

• employing suitably trained staff;

• implementing a quality system including alaboratory quality manual;

• providing reasonable facilities and suitableequipment;

• documenting analytical methods;

• documenting procedures for handling and analysingsamples; and

• documenting procedures for data reporting andrecord keeping.

Basic principles of quality assurance can be found inthe literature (NATA, 1992; NATA, 1993; ISO, 1994;APHA, 1995), so only the main issues in algalenumeration are addressed here.

Internal quality control in algal enumerationinvolves documenting the procedures employed for allsteps involved and making them readily accessible to allstaff concerned. The documentation will includeacceptable error sizes and confidence limits for everystep of enumeration. Steps include, for example,subsampling from the original sampling bottle andsubsampling within a counting chamber if only part ofthe floor is counted. Quality of counting results will beenhanced by regularly (eg. annually) revising theprocedures with staff and documenting such changes.This process will create consistency amongst operatorsin terms of procedures and taxonomic identification,and will ensue that improvements are incorporated.

5. Quality assurance

Another element is operator competence. Thisincludes training staff in correct application of samplecollection and analysis procedures.

To check the validity of algal counting results andestimate their accuracy, the following procedures areimplemented. To test individual operator precision(operator error) a count on three subsamples of onesample is conducted every three months and relatederrors and confidence limits calculated. To test forprecision within the laboratory, every six months the samethree subsamples of a sample are counted by eachoperator and the error and associated confidence limitscalculated. Single species samples (cultures) are suitablefor these two tests. To test consistency of speciesidentification among operators and ensure that alloperators reach the predetermined level of precision, thelatter test should be repeated every six months withmixed species samples. A different operator shouldrecount 5% of the samples in the same laboratory to testfor precision of cell counts and species identification.

Equipment such as micropipettes, countingchambers and microscopes need to be regularlycalibrated and maintained.

There is no detection limit for algal counts inherent inthe method, rather the number of taxa found in a sampledepends to some degree on counting time andsubsample volume, and on the taxonomic proficiency ofthe operator. The precision and accuracy of counting resultsalways need to be stated (see previous statistical section)in the final report.

Each step in the algal enumeration should beverified by a person other than the operator whoperformed that step. For instance, calculation of finalcount results should be verified by a second person.Correct data entry could be checked by comparing aprint-out of the entered data with the original worksheet. At the point of data entry some automaticchecking procedures, such as acceptable ranges,reporting of outliers and so on, should be built into thedatabase program.

The second part of quality assurance, qualityassessment, is the implementation of external checks toensure adherence to the documented procedures. Thisincludes interlaboratory tests and external audits atregular intervals (eg. six-monthly). It is recommended

35

QUALITY ASSURANCE

Figure 5.1: Quality assurance in algal enumeration

Internal quality control

Quality assurance in algal enumeration

External quality assessment

Train staff for field and

laboratoy according to

methods

Ongoing quality control Write laboratory methods

manual – include all steps of

enumeration and error sizes

and confidence limits for each

step

Counting precision Day-to-day verification Make available to all staff

Operator precision

Every three months count

three subsamples, analyse

results, record results in

internal quality assurance sheet

for each operator

5% of samples recounted by

different operator

Revise annually with staff

involved

All calculation of final results

and transfer of raw data to

electronic database verified

by second operator

Laboratory precision

Every six months each

operator to count same three

subsamples, analyse results,

compare with set error and

confidence limits, record

results in internal quality

assurance sheet

Calibrate equipment regularly

Recount of 5% of samples by

external laboratory

� �

Conduct external audit

annually

Partake in interlaboratory

efficiency testing

� � �

� �

Document revision results

36

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

that 5% of samples be recounted by a differentlaboratory as advised by standard quality controlprocedures (APHA, 1995). In Australia, such externalquality assessment is provided within the framework ofNational Association of Testing Authorities (NATA)registration. In 1996, NATA began a proficiency testingprogram for laboratories performing algal enumeration.Eighteen laboratories participated in the first round oftests. Since 1998, participation in the interlaboratoryproficiency testing has been compulsory for NATA-registered laboratories. NATA’s address is given inAppendix A.

5.2 Reporting of dataA standard procedure which is documented in writing isfollowed for all steps in creating, transferring and storingdata. On arrival in the laboratory, each algal sampleshould be given a unique and permanent identificationnumber which will allow staff to link all records to therelevant sample from its arrival to issue of a final report.This procedure may be facilitated by an electroniclaboratory sample management program. Standard fieldand laboratory recording sheets are essential(see Appendix E).

For every step of transferring data from one mediumto another, a person other than the operator needs toverify the step. For example, final count results, ifrecorded on paper, need to be transferred from theoriginal data sheet to the electronic database for storageand reporting. A person other than the data entryoperator needs to verify the correctness of the dataentered. Typing errors during data entry of final countresults can be minimised by using an algal countingsoftware program (see Appendix D) to directly entercounts into the computer during counting.

The database should be established with the help of anexperienced phycologist to ensure an adequate taxonomicsystem is used and special considerations for algalenumeration are incorporated. The database for the algalcounting results should be relational, allow easy transferof data to other applications (eg. statistical analysissoftware) and facilitate report writing. An algal codingsystem (see above) encompassing different levels oftaxonomic identification (open system) is essential.While using a code for data storage, (embedded) actualtaxonomic names will appear on the database entry formif a relational database is used. Thus, fewer errors will be

made by the operator since names are easier toremember than codes.

Effective data storage depends on continuing databasemaintenance, including regular back-up, checks forcorrectness of entries, documentation of changes inprocedures for algal counting and data entry, andincorporation of changes in taxonomy. Such maintenanceis critical during long-term monitoring programs inparticular, in order to keep the data accessible and usefulfor data analysis. For example, organisms may have beencounted as unidentified flagellates at the beginning ofthe monitoring program then, after full identification,counted in a different taxonomic category and under adifferent code. Without documentation it is impossibleto interpret such data sensibly. Species names maychange over the years; for example, Melosira granulata(Ehrenb.) Ralfs, one of the more frequent members ofriverine phytoplankton in Australia, was renamedAulacoseira granulata (Ehr.) Simonson in 1989.In accordance with NATA requirements, data need to bestored for at least three years (NATA, 1992).

37

This section discusses occupational health and safetyissues for field and laboratory work, in particularwith regard to potentially toxic cyanoprokaryotes, aswell as staff training needs.

6.1 Occupational health and safetyissuesStandard occupational health and safety measures forfield work as laid down in the organisation’s fieldsampling manual and laboratory manual need to beimplemented. Issues to consider include: sending at leasttwo people into the field; carrying life saving gear;providing a mobile phone in working order; leavingclear information about the intended travel route andthe expected time and date of return; and carryingsufficient drinking water and food for emergencies. Staffshould have regular first aid training, includingresuscitation procedures for field and laboratory, and beaware of dangers in the work place.

When field work involves sampling for potentiallytoxic cyanoprokaryotes, especially where they haveformed scums, certain safety measures need to befollowed. Avoid all direct body contact with the watercontaining the cyanoprokaryotes or cyanoprokaryotescums, since toxins might cause allergic reactions on theskin and in the eyes. Use rubber gloves, waders andprotective eye gear when taking and handling thesamples. Avoid contact with water spray when travellingin a boat because aerosols from infested water may causerespiratory problems or bring on asthma attacks. Undersuch conditions, odour masks may be worn. Wash handsbefore drinking, eating or smoking. Ingested toxiccyanoprokaryotes can cause acute allergic reactions aswell as low level chronic damage of, for example, theliver. Working gear, such as waders, needs to be washedwith clean water and soap after use.

Care needs to be taken with transport of chemicals inthe field to avoid spillage and the inhalation of fumeswhile driving. Formalin and glutaraldehyde are toxicchemicals (carcinogenic) (see specification sheets fromchemical suppliers) which should be stored safely (eg.airtight container) and separate from food items. Use ofgloves while handling these chemicals is recommended.

Iodine, although not acutely toxic, is harmful andinhalation of vapours (eg. from open sedimentationvessels in the laboratory) should be avoided. Vessels canbe placed under a fume hood, temporarily sealed withflexible film or, if resources permit, stoppered measuringcylinders can be employed. Staff should not work inareas of sample storage where the inhalation of built-upfumes poses a health hazard. The usual safety measuresfor the laboratory apply with respect to the handling ofglassware and chemicals and to sample disposal.

Attention should be given to the ergonomics formicroscope work. For example, a desk-high bench(lower than normal laboratory benches) and anadjustable chair should be provided to avoid muscleinjury to workers, as should an appropriate light sourcethat does not interfere with the illumination formicroscopy. Ideally, a microscopy laboratory should havesouth-facing windows. The usual ergonomicrequirements apply for the computer set up.

The maximum daily duration for sitting at themicroscope is five hours. A good work routine includesgetting up from the microscope or computer at regularintervals to take breaks, and performing a variety oftasks each day. Staff should be encouraged to doappropriate daily exercises to counterpoise the restrictedsitting positions.

6.2 TrainingStaff involved in algal enumeration need to be trained byan experienced algal counter. It will take several monthsto train new staff to recognise the more common generaand to produce reliable counting results. Training of aqualified algal taxonomist takes several years. Acollection of preserved material and photomicrographswill be of great help. Staff from smaller laboratoriesoften benefit from spending a few days in a largerlaboratory with experienced staff.

It is strongly recommended that annual workshopsare held at a national level among the algal workers inwater resource agencies in Australia, to allow exchangeof information on procedures and identification, and anincrease in the level of taxonomic expertise. Specialistsfor particular algal groups may be invited to theworkshops. Algal taxonomy is complex and still under

6. Staff

38

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

constant review, and there is a constant need forphytoplankton workers to keep abreast of ongoingdevelopments. The first Australian National AlgalWorkshop was held in Adelaide in February 1999,providing an overview of the characteristics of algaeand dealing with the identification of commonAustralian cyanoprokaryote species and commondiatom genera under the guidance of Australiantaxonomic specialists. In future, such workshops willbe held on a regular basis, dealing with differenttaxonomic groups. Details will be announced in therelevant newsletters and on the Australian algaldiscussion list (ALGANTIPOD@latrobe.edu.au). Thefirst two Australian algal keys were produced for thisworkshop (see Appendix C).

It is essential that staff performing field sampling bethoroughly trained in the required procedures andunderstand the reasons for (a) taking the sample and(b) the protocol that needs to be followed when takingthe sample. It is recommended a refresher course beconducted for field staff annually. Such training willsignificantly increase sample quality and accuracy of dataand therefore justify the additional costs involved.

39

This chapter gives guidance on how to accomplish achange from an existing method for sampling, algalcounting and chlorophyll-a analysis to a benchmarkmethod recommended in this manual, withoutlosing continuity of data for ongoing monitoringprograms.

Before a change in methodology is undertaken, preparea document containing the following information:

• reasons for changing method

• improvements expected from method change

• documentation of existing and new method

• outline for introduction of new method

• comparison between existing and new method.

For the process of introducing a new method wherecontinuity of data is needed, the steps described belowmay serve as a guide.

Reasons for changing methodThe reasons for changing the method are documented.They will vary from laboratory to laboratory but mayinclude the following: the existing method is outdatedor semi-quantitative in nature; there is a desire to changeto a benchmark method; a new methodology hasbecome available; or, perhaps, the purpose of algalmonitoring within the organisation has changed andrequires a different methodological approach.

Improvements expected from method changeDetail the qualitative and quantitative improvements inresults the new method will bring. Explain how resultsfrom the new method will be more representative of thetrue value of what is being measured than thoseobtained with the existing method. For example, achange of method from the concentration of live algaeusing sand filtration to sedimentation of Lugol’s-preserved samples would represent a change from asemi-quantitative method to a quantitative method. As aconsequence, different species may be found and/ortheir cell concentrations may increase or decreasecompared to results gained from the existing method.

7. Guidance on introducing a new method

Documentation of existing and new methodA step-by-step description of each method should beprepared in the format usual for the laboratory’s qualitycontrol manual. The theoretical principles of the old andnew method should be entirely understood and documentedand the differences between the two clearly spelled out. Insome instances, the two methods would be based ondifferent principles so that a direct comparison wouldyield no conclusive results. Considering these principles,decide on whether a comparison between the twomethods is meaningful and how it can be accomplishedfollowing the considerations outlined below.

Outline for introduction of new methodPrepare an outline of how the new method will beintroduced, including the individual steps to be taken,the time frame for the changeover process, staff andfunding required, new equipment to be purchased andimplications for quality assurance and quality control.

1. Specify the outcomes expected from the comparisonand a time frame for the process of changeover,including the validation of the new method againstthe existing one.

If the comparison is undertaken by experiment, andif all the necessary samples have been collectedbeforehand (preserved samples only), the experimentcan be run as one block. Thus, it can be performedin a relatively short time (say, within a few months)depending on staffing and the time made availableoutside the routine counting. If, however, freshsamples are needed, the experiment can be runwhenever suitable samples occur and the data fromdifferent samples collated in due course.

If the comparison is undertaken by running the twomethods in parallel, a period of one year isrecommended to include samples from all seasons andsamples representing different environmental conditionsin the waterbody that occur during the course of theyear (Bartram and Ballance, 1996).

2. Perform the comparison, either by experiment or byconcurrently running the methods, and clearlydocument the differences in results gained from thetwo methods.

40

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

3. Completeness and representativeness of comparison

Regardless of whether the comparison is made byexperiment or by a parallel running of the methods,it is important to select a representative subset ofsamples.

Samples should:

• originate from different types of waterbodies(universal application of results);

• cover all flow conditions experienced;

• represent the different seasons normallymonitored;

• contain the whole range of species routinelyencountered in the laboratory; and

• represent the complete range of cellconcentrations routinely encountered.

Different algal species may be differently affected bysampling or counting with an alternative method.Therefore, it is essential to choose the subset ofsamples for the comparison in such a way that itcontains all species which are routinely encounteredin the laboratory.

4. Document the expertise of staff with the twomethods and the taxonomic keys used before andafter the changeover as this might impact on theoutcome of the comparison.

5. Quality assurance and quality control matters

Clearly flag in your database documentation thechange of method, indicating the date for eachwaterbody monitored and how it might affect futureanalysis of the data set.

Provide a reference to where in the laboratory’squality assurance and quality control documentationthe changeover is documented.

6. Review in detail the outcome of the comparison (eg.advantages and disadvantages) of the new methodagainst the expected outcomes under 1. Decide onhow the new method will be introduced.

Comparison between existing and new methodThe major component of the changeover will be theexecution and documentation of the comparisonbetween the two methods. Such comparison may be

achieved either by an experiment or by running the twomethods in parallel for a defined period of time.

Experiment: chlorophyll-a methodTo test for equivalence of the two methods in theanalysis of a single factor such as chlorophyll-a, aminimum of three different concentrations is testedusing a minimum of five subsamples for each method. Ifa large range of concentrations is normally encountered,test more than three concentrations. The results are thencompared applying the statistical analysis outlinedbelow, according to APHA (1995).

1. The data are tested for normal distribution andtransformed if necessary.

2. The standard deviation is calculated and a sufficientsample size is chosen accordingly.

3. Using the F-ratio statistic the variance of eachmethod is tested.

4. Finally the average values from each method aretested for differences using the Student t-test.

If the results from the two methods are significantlydifferent, plot the data and calculate the two regressionequations. A conversion factor can then be calculatedexpressing how data obtained by the new method relateto those obtained by the existing method according to

(11)

where Rold

is a test result obtained by the existingmethod, R

newis a result obtained with the new method

and f is the factor. References regarding details ofstatistical analysis can be found in APHA (1995).

Experiment: samplingIf the change concerns the sampling methodology, takesamples employing both methods at the same time. Takea minimum of 10 subsamples, but if possible 20subsamples, from the respective sample and count asusual. Repeat the experiment on several occasions, but atleast 10 times, so that samples represent the range ofconditions normally encountered for the waterbody inquestion (see ‘representativeness of samples’ above).Review the results as described under ‘Experiment: algalenumeration’ below.

Experiment: algal enumerationObtain a large enough sample volume to be able to takethe necessary number of subsamples. From a watersample, take a minimum of 10 subsamples, but if

f =R

old

Rnew

41

GUIDANCE ON INTRODUCING A NEW METHOD

possible 20 subsamples, for each method and proceedwith the algal identification and enumeration as perdescribed methods. In each sample, identify alloccurring algal taxa and count the 7 to 10 mostabundant. Also count any large (but not necessarilyabundant) taxa such as Ceratium, and any taxa that formlarge colonies. Additionally, determine the total cellcount for each subsample. Repeat the same procedureseveral times (at least 10 times) with different sampleschosen according to the criteria for representativeness setout above.

The results should give a clear indication as to whetherthere is, between the two methods, (a) a difference in thenumber and type of species identified (qualitative) and/or(b) an increase or decrease in cell concentrations(quantitative). In the documentation of the comparison,state in detail what the differences were; for example,which species were detected by one method but not bythe other, or which species had a higher or lower cellcount in the new method as compared to the existingmethod. Through this detailed descriptive data analysis apicture will emerge as to where the differences liebetween the two methods in question.

For multifactor analyses such as algal counts, a directstatistical comparison for a full count from a naturalsample is intrinsically very complicated. There is noproven model for such a situation available in Australia.The matter is further complicated by the fact that,within a sample, different levels of accuracy exist foreach taxon according to its concentration or the numberof algal units found in the sample. Thus, for algalcounts, the calculation of a single conversion factor isnot possible. However, it may be estimated by thepercentage of the results gained with the new methodthat are in general higher or lower than those gainedwith the old method.

Parallel use of methodsAs an alternative to the experimental approach, the twomethods may be used in parallel for a fixed period oftime. This period is generally one year in order tocapture samples representing the usual extent ofvariation experienced by the waterbody. This applies toalgal enumeration, sampling methodology andchlorophyll-a analysis.

If the two methods are used in parallel, it isadvisable to use a subset of the samples processed by thelaboratory in its routine work. The subset is chosenaccording to seasonal difference in species composition,cell concentration, source of water sample, type of

waterbody, type of sample and occurrence of problemspecies as the dominant algae.

For a comparison of chlorophyll-a analyses orsampling methodology, use the same guidelines withrespect to the number of occasions and number ofreplicate samples as for ‘Experiment: chlorophyll-a’. Foralgal enumeration, process five subsamples for eachmethod on each occasion. A minimum of 20 differentsamples should be analysed for this test. Tabulate resultsas per (a) and (b) under ‘Experiment: algalenumeration’.

42

APHA (American Public Health Association) 1995,Standard methods for the examination of water andwaste water, 19th edn, APHA, Washington D.C.

Baker, P. 1986, Enumeration of phytoplankton, Progressreport No. 1, State Water Laboratory, Engineeringand Water Supply Department, South Australia,Library reference number 86/48.

Bartram, J. and Ballance, R. 1996, Water qualitymonitoring UNEP, E & FN Spon, London.

Chorus, I and Bartram, J. (eds) 1999, Toxiccyanobacteria in water, a guide to their public healthconsequences, monitoring and management, E & FNSpon, London.

Clark, H. and Lidston, J. 1993, Photometric chlorophyll-adetermination method, State Water Laboratory,Victoria, Report no. WQ 57.

Fisher, R.A., Thornton, H.G. and MacKenzie, W.A.1922, ‘The accuracy of the plating method ofestimating the density of bacterial populations’,Annals of Applied Biology, 9, 325–359.

Furet, J.E. and Benson-Evans, K. 1982, ‘An evaluationof the time required to obtain completesedimentation of fixed algal particles prior toenumeration’, British Phycology Journal, 17, 235–258.

Gilbert, J.Y. 1942, ‘The errors of the Sedgwick-Raftercounting chamber on the enumeration ofphytoplankton’, Transactions of the AmericanMicroscopy Society, 61, 217–226.

Harris, G. 1978, ‘Photosynthesis, productivity andgrowth: The physiological ecology ofphytoplankton’, Arch. Hydrobiol. Beih. Ergeb.Limnol., 10, 1–171.

Hasle, G.R. 1969, ‘An analysis of the phytoplankton ofthe Pacific Southern Ocean’, Hvalraad ets Skriften,52, 1–168.

Hasle, G.R. 1978, ‘The inverted microscope method’,in Sournia, A. (ed) Phytoplankton manual,UNESCO, Paris.

Hötzel, G. and Croome, R. 1994, ‘Long-termphytoplankton monitoring of the Darling River atBurtundy, New South Wales: evidence andsignificance of cyanobacterial blooms’, AustralianJournal of Marine and Freshwater Research, 45, 747–759.

— 1996, ‘Population dynamics of Aulacoseira granulata(Ehr.) Simonson (Bacillariophyceae, Centrales), thedominant alga in the Murray River, Australia,Archiv für Hydrobiologie, 136/2, 191–215.

ISO (International Standards Organization) 1980, Waterquality – Sampling – Part 1: Guidance on the designof sampling programmes, ISO 5667-1.

— 1994, Quality management and quality assurancestandards, ISO 9000.

Jones, G. 1997a, ‘Limnological Study of cyanobacterialgrowth in three South-East Queensland reservoirs’,in Davis, J.R. (ed) Managing algal blooms, CSIROLand and Water, Canberra.

Jones, G. 1997b, National protocol for the monitoring ofCyanobacteria and their toxins in surface waters,Draft, CSIRO Land and Water in association withthe Agriculture and Resource Management Councilof Australia and New Zealand.

Klee, O. 1993, Wasser untersuchen, BiologischeArbeitsbücher (The examination of water, BioliogicalWorkbooks), Quelle & Meyer Verlag, Heidelberg.

Laslett, G.M., Clark, R.M., Jones, G.J. 1997,‘Estimating the precision of filamentous blue-greenalgae cell concentration from a single sample’,Envirometrics, 8(4), 313–339.

Lhotsky, O., Rosa, K. and Hindak, F. 1974, Supis Sinic aRias Slovenska, Bratislava, Czechoslovakia.

Lund, J.W.G. 1959, ‘A simple counting chamber fornanoplankton’, Limnology and Oceanography, 1, 57–65.

Lund, J.W.G., Kipling, C. and Le Cren, E.D. 1958,‘The inverted microscope method of estimatingalgal numbers and the statistical basis of estimationsby counting’, Hydrobiologia, 11, 143–170.

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Utermöhl, H. 1958, ‘Zur Vervollkommung derquantitativen Phytoplankton Methodik’ (Towards aperfection of quantitative phytoplanktonmethodology), Mitteilungen der InternationaleVereinigung für Theoretische und AngewandteLimnologie, 9, 1–38.

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45

Appendices

The appendices contain more useful and practical information. An extensive list of taxonomic algal literatureincluding relevant Australian material is presented together with field and laboratory standard data sheets andlistings of the equipment required. Detailed descriptions of different samplers are given as well as information onsoftware for algal counting.

Appendix A: List of agencies involved in development of this manual,including contact officers

Agency name Liaison officerEcowise Environmental–ACTEW Frederick BouckaertEnvironment Protection Authority, South Australia Peter GoonanAustralian Water Quality Centre (South Australian Water Corporation) Peter BakerDepartment of Lands, Planning & Environment, Northern Territory Armando Padovan/Simon TownsendEnvironment Protection Authority, Victoria Leon Metzeling/Peter NewallWater Ecoscience Kumar Eliezer/Frances CannonNatural Resources and Environment, Victoria Ross Perry/Warren WealandsGoulburn Murray Water Pat Feehan/Anne Graesser/

Graeme WilkensonMelbourne Water Commission Mike ChapmanParks Victoria Peter KempGippsland Water Jenny JelbartEnvironment Protection Authority New South Wales Sean Hardiman/Penny AjaniNSW Department of Land and Water Resources Lee BowlingAustralian Water Technologies Ensight Peter Hawkins/Jennie ThompsonHunter Water Corporation Bruce ColeDepartment of Primary Industry & Fisheries, Tasmania Chris BobbiWater and Rivers Commission, Western Australia Wasele Hosja/Verity Klemm/

Jane Latchford/Petrina RiattWater Authority, Western Australia Jeff KiteQueensland Health Scientific Services Maree SmithQueensland Department of Environment and Heritage Munro MortimerQueensland Department of Natural Resources, Water Monitoring Wojciech Poplawski/Glenn McGregorBrisbane City Council Brisbane Water Graham BaxterMurray–Darling Basin Commission Bob Banens/Martin ShafronARMCANZ Algal Manager Gary Jones/Mike BurchNational Association of Testing Authorities Tanya Orlova/Neil Shepperd

Address of NATA for interlaboratory comparisons of algal enumeration:Proficiency testing for algal counts (interlaboratory comparisons)Proficiency testingNational Association of Testing Authorities7 Leeds Street, Rhodes NSW 2138, Australia

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Appendix C: Algal taxonomicliteratureWorks marked with an asterisk (*) are basic keys. Worksmarked with a dagger (†) are needed for diatomidentification. An English translation of the keys inKrammer and Lange-Bertalot (1986) is being preparedat the EPA Victoria.

*Baker, P. 1991, Identification of common noxiouscyanobacteria. Part I – Nostocales, Urban WaterResearch Association of Australia, Research reportno. 29, June 1991, Australian Centre for WaterTreatment and Water Quality Research, Melbourneand Metropolitan Board of Works, Melbourne.

*— 1992, Identification of Common NoxiousCyanobacteria, Part II – Chroococcales Oscillatoriales,Research report no. 46, October 1992, AustralianCentre for Water Treatment and Water QualityResearch, Urban Research Association of Australia,Melbourne.

Baker, P.D. and Fabbro, L.D. 1999, A guide to theidentification of common blue-green algae(Cyanoprokaryotes) in Australian freshwaters,Cooperative Research Centre for FreshwaterEcology, Identification Guide No. 25, Thurgoona.

*Bellinger, E.G. 1992, A key to common algae freshwaterestuarine and some coastal species, 4th edn, theInstitution of Water and EnvironmentalManagement, London.

Bourrelly, P. 1966, Les Algues D’Eau Douce. Tome 1: LesAlgues vertes, Editions N. Boubee & Cie, Paris.

— 1968, Les Algues D’Eau Douce. Tome 2: Les Alguesjaunes et brunes. Chrysophycees, Xanthophycees etDiatomees, Editions N. Boubee & Cie, Paris.

— 1970, Les Algues D’Eau Douce. Tome 3: Les Alguesbleues et rouges. Les Eugleniens, Peridiniens etCryptomonadines, Editions N. Boubee & Cie, Paris.

Brook, A.J. 1981, The biology of desmids, Blackwell,London.

Canter-Lund, H. and Lund, J.W.G. 1996, Freshwateralgae: their microscopic world explored, Biopress Ltd,Bristol, England.

Cox, E.J. 1996, Identification of freshwater diatoms fromlive material, Chapman & Hall, London.

Day, S.A., Wickham, R.P., Entwisle, T.J. and Tyler, P.A.1995, Bibliographic checklist of non-marine algae inAustralia, Australian Biological Resources Study,Canberra.

Entwisle, T.J., Sonneman, J.A. and Lewis, S.H. 1997,Freshwater algae in Australia, Sainty and AssociatesPty Ltd, Potts Point, Australia.

Foged, N. 1978, ‘Diatoms in eastern Australia’,Bibliotheca Phycologica, 47, pp. 1–255.

Gell, P.A., Sonneman, J.A., Reid, M.A., Illman, M.A.and Sincock, A.J. 1999, An illustrated key tocommon diatom genera from Southern Australia,Cooperative Research Centre for FreshwaterEcology, Identification Guide No. 26, Thurgoona.

Hallegraeff, G.M. 1991, Aquaculture’s guide to harmfulAustralian microalgae, Fishing Industry TrainingBoard of Tasmania, Hobart.

Hodgson, D., Vyverman, W. and Tyler, P. 1997,‘Diatoms of meromictic lakes adjacent to theGordon River, and of the Gordon River estuary insouth-west Tasmania’, Bibliotheca Diatomologica,Band 35, J. Cramer in der Gebrüder BornträgerVerlagsbuchhandlung, Berlin, Stuttgart.

Holland, J. and Clark, R.L. 1989, Diatoms of theBurrunjuck Reservoir, New South Wales, Australia,Divisional report 89/1, CSIRO, Institute of NaturalResources and Environment, Division of WaterResources, Canberra.

Huber-Pestalozzi, G. 1983, ‘Das Phytoplankton desSuesswassers, Systematik und Biologie’, DieBinnengewaesser, Band XVI, Teil 1–8. E.Schweizerbart’sche Verlagsbuchhandlung, Stuttgart.

Hustedt, F. 1930, ‘Bacillariophyta (Diatomeae)’, in A.Pascher 1930, Süßwasserflora von Mitteleuropas,Heft 10, Gustav Fischer, Jena.

Komarek, J. and Anagnostidis, K. 1998,‘Cyanoprokaryota I. Chroococcales’, inSüßwasserflora von Mitteleuropa, Band 19, KoeltzScientific Books, Koenigstein.

Appendix B: Lugol’s solutionMix 20 g of KI (potassium iodide) with 200 mL

distilled water and dissolve 10 g pure iodine in thissolution. Add 20 g of glacial acetic acid a few daysbefore use (Schwoerbel, 1970). The solution must bestored in the dark (Vollenweider, 1969).

47

APPENDICES

†Krammer, K. and Lange-Bertalot, H. 1986,Süßwasserflora von Mitteleuropa Band 2/1,Bacillariophyceae (Naviculaceae), Gustav FischerVerlag, Stuttgart, Jena.

†— 1988, Süßwasserflora von Mitteleuropa Band 2/2,Bacillariophyceae (Bacillariae, Epithemiaceae,Surirellaceae), Gustav Fischer Verlag, Stuttgart, Jena.

†— 1991, Süßwasserflora von Mitteleuropa Band 2/3,Bacillariophyceae (Centrales, Fragilariaceae,Eunotiaceae), Gustav Fischer Verlag, Stuttgart, Jena.

†— 1991, Süßwasserflora von Mitteleuropa Band 2/4,Bacillariophyceae (Achnanthaceae,Literaturverzeichnis), Gustav Fischer Verlag,Stuttgart, Jena.

Leedale, G.F. 1967, Euglenoid flagellates, Prentice-HallBiological Science series, Englewood Cliffs, NewJersey.

Ling, H.U. and Tyler, P.A. 1986, A limnological survey ofthe Alligator Rivers Region II. Freshwater algae,exclusive of diatoms, Supervising Scientist of theAlligator Rivers Region, Research report 3, AGPS,Canberra.

— 1986, A limnological survey of the Alligator RiversRegion. Part 2: Freshwater algae, exclusive of diatoms,Supervising Scientist of the Alligator Rivers Region,AGPS, Canberra.

McLeod, J. 1975, The freshwater algae of South-EasternQueensland, PhD thesis, University of Queensland.

Patrick, R. and Reimer, C.W. 1966, The diatoms of theUSA, Vol. I, Monographs of the Academy NaturalScience, Philadelphia.

— 1975, The diatoms of the USA, Vol II, Monographs ofthe Academy Natural Science, Philadelphia.

Prescott, G.W. 1951, Algae of the Western Great LakesArea (1982), rev. O. Koeltz Science Publishers,Germany ed. Wm. C. Brown Company Publishers,Dubuque, Iowa.

*— 1978, How to know the freshwater algae, Wm. C.Brown Company Publishers, Dubuque, Iowa.

Prescott, G.W. and Scott, A.M. 1952, ‘Some SouthAustralian desmids’, Transactions of the Royal Societyof South Australia, 75, pp. 55–69.

*Streble, H. and Krauter, D. 1988, Das Leben imWassertropfen, 8th edn, Franckh’scheVerlagsbuchhandlung, Stuttgart.

†Thomas, D.P. 1983, A limnological survey of theAlligator Rivers Region. Part 1: Diatoms(Bacillariophyceae) of the Region, AGPS, Canberra.

Vyverman, W., Wyverman, R., Hodgson, D. and Tyler,P. 1995, Diatoms from Tasmanian mountain lakes:a reference data-set (TASDIAT) for environmentalreconstruction and a systematic and autecologicalstudy, Bibliotheca Diatomologica, Band 33,J. Cramer in der Gebrüder BornträgerVerlagsbuchhandlung, Berlin, Stuttgart.

West, G.S. 1909, ‘Algae of the Yan Yean Reservoir,Victoria, A biological and oecological approach’,Journal of the Linnean Society (Botany), 39, 1–88.

Wetzel, R.G. 1975, Limnology, W.B. SaundersCompany, Philadelphia.

The publications by Day et al. (1995) and Ling andTyler (1986) contain the most comprehensive records onpapers published about Australian freshwater algae.Among the earliest papers to describe Australian algaewhich are still useful today are those of West (1909),Prescott and Scott (1952) and Playfair (listed in Day etal., 1995).

A new taxonomic series called Algae of Australia willbe published by the Australian Biological ResourcesStudy (Environment Australia) including descriptions offreshwater and marine microalgae and macroalgae forthis continent. The first volume is due to be publishedin 1999.

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Appendix D: Recommended fieldand laboratory equipment

Field gear10 L bucketClipboardEskies or refrigerator for live samplesStandardised phytoplankton field sampling sheetIceLiquid nitrogenLugol’s solution and/or formalinPen and waterproof labelsPhytoplankton net – mesh size around 20 µmSafety equipmentSampling bottlesWadersWater sampler

Laboratory equipment(See also items mentioned in section ‘Microscope

equipment’)Algal counting softwareBench space for sedimentation, preferably under a

fume hoodComputer for counting programCounting chambers, calibrated if necessary –

chambers are available from commercialmicroscopy suppliers

Dark storage spaceEyepiece graticuleLight microscope, either an upright instrument or

an inverted microscope, depending on thecounting method employed

Measuring cylinders of varying sizes (10 mL to1,000 mL)

Mechanical counting bank or computer withcounting software

Microscope slides and coverslipsPasteur pipettesPlanimeter for Sedgwick-Rafter calibrationStage micrometerStandardised algal counting sheetTaxonomic literatureVacuum pumpVaseline, hot plate and pointed tweezers if home-

made Utermöhl chambers are usedVibration-free microscope benchWhipple graticule

Suppliers of specialised itemsPrecision-built Utermöhl chambers:

PhycotechSuite 100, 620 Broad St, St Joseph MI 49085,USAPhone +616 983 3654, Fax +616 983 3653Email phycotech@parrett.net

Hydro-Bios Apparatebau GmbHP.O. Box 8008, D-24154 Kiel-Holtenau,GermanyPhone +0431 36960 0, Fax +0431 36960 21Email hydrobios@t-online.de

Micrometers and Whipple graticules:Graticules LtdMorley Rd, Tonbridge, Kent, TN9 1RNPhone +0732 359061, Fax +0732 770217

Utermöhl chamber building instructionsA slide 3 mm thick to fit the inverted microscope athand is cut out of perspex and a hole of 1 cm diametercut in the centre position (bottom slide). The bottomedge of this slide needs to sit on the microscope stage tocoincide with the optical plane. A second slide of thesame dimensions, also with a hole but 4 mm thick, iscut and a tube with an inner diameter of 1 cm and aheight of 5.5 cm is glued permanently to the slide (topslide). These two slides are assembled into a chamber byapplying a thin film of vaseline on facing surfaces andpressing together. A thin film of vaseline is applied tothe other side of the bottom slide around the hole and acoverslip preheated on a hot plate is attached. The algalcells will sediment onto this coverslip and can thus beviewed directly through the objectives. If concentrationof the sample is required, such small chambersnecessitate an additional step of subsampling.

Larger Utermöhl chambers, allowing the directsedimentation of 5 mL, 10 mL, 50 mL and 100 mLwithout an additional subsampling step, arecommercially available from the suppliers given above.

Lund cell building instructionsOnto the long edges of a thoroughly cleaned and driedmicroscope slide, glue two pieces of brass shim 54 mmlong, 2.4 mm wide and 0.5 mm high with epoxy glue.To cure the glue, place in an oven at 16oC for at leasttwo hours. Any excess glue on the insides of the shims isremoved with a scalpel. Place a rectangular coversliponto the shims (see Figure 4.3), large enough to coverthe area between them. The above method follows thatused by the Water Research Association in the United

49

APPENDICES

Kingdom. In the original method (Lund, 1959), thinglass is used instead of brass shims.

Electronic software for algal countingThere are a number of software programs availablewhich have been developed by algal researchers. The listbelow is by no means exhaustive and the programs listedare included as examples only. Inquiries should be madeto the authors.

Program Author/contact person

Species Count Dr S. Cooper, Duke Wetland Centre, Box 90333, Durham NC 27708, USA.

Algal counting Dr Paul Hamilton, Canadian program, Museum of Nature, Canada.program Email: phamilton@mus-nature.ca

Free. Useful for all types of chambers. Measurements for cell dimension can beentered and biovolumes calculated.An improved version of ‘Algal counting program’ is available from:Dr Veronique Gosselain, Laboratory of Freshwater Ecology, Facultés UniversitairesNôtre-Dame de la Paix, Rue de Bruxelles 61, B-5000 Namur, Belgium.Email: veronique.gosselain@fundp.ac.be

Countem Dr R. Oliver, Murray–Darling Freshwater Research Centre, PO Box 921,Albury NSW 2640, Australia.$50.00. Useful for Lund cell and Sedgwick-Rafter chambers only.

Biocount Dr Gary Jones, CSIRO Land and Water, Science Centre Block B, Meiers Rd,Indooroopilly Qld 4068.$350.00 single copy, discounts available. Useful for Lund cell and Sedgwick-Rafterchamber.

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Appendix E: Examples of ‘Phytoplankton field sampling sheet’ and‘Algal counting sheet’

PHYTOPLANKTON FIELD SAMPLING SHEET

Site name:

Site code: Sample ID:

Date: Time: am pm

Weather:

Water:

Field Measurements to take

Temperature Conductivity

pH Dissol. O2

Secchi Transp. Velocity

Water Depth Gauge height

Particulars of water samples

Depth taken at: m Method of sampling:

Type of sample: surface integrated 0 – m

Location sampled: left side right side main current

Water samples to take for

Phytoplankton (fixed)

Turbidity

Phosphorus

Nitrogen

SiO2

Chl-a (algal biomass)

Phytoplankton net sample (unpreserved)

Comments:

Check all measurements and sampling completed

Entered into d/b by: on date:

Verified by: on date:

51

APPENDICES

Algal Counting Sheet

Sample ID: ................................ Site Code: ............................................ Sampling Date: .............................................

Aulacoseira granulata (fil.)

Aulacoseira granulata (cells/fil.)

Melosira varians (fil.)

Melosira varians (cells/fil.)

Centric diatoms < 5 µm

Centric diatoms > 5 µm & < 10 µm

Fragilaria

Navicula

Synedra

Carteria

Chlamydomonas

Pandorina

Actinastrum

Ankistrodesmus

Crucigenia

Dictyosphaerium

Elakatothrix

Golenkinia

Oocystis

Pediastrum

Scenedesmus

Sphaerocystis

Ulothrix (fil.)

Ulothrix (cells/fil.)

Closterium

Euastrum

Staurastrum

Dinobryon

Mallomonas

Synura

Chroomonas

Cryptomonas

Rhodomonas

Ceratium

Euglena

Trachelomonas

Microcystis

Lyngbya

Anabaena

Comments:

Units counted

Slid

e N

o.:

Volu

me

sed.

:A

rea

coun

ted:

Fact

or:

Iden

tifie

d by

:on

dat

e: Ve

rifie

d by

: o

n da

te:

Ente

red

into

d/b

by:

on d

ate:

Veri

fied

by:

on d

ate:

52

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Appendix F: Hosepipe samplerUse a clear PVC pipe (25 mm diameter) of 2 m to 10 mlength, depending on depth of river or lake, with aweight (W) and a rope attached to one end.

1. The weighted end of the pipe is lowered into thewater until the whole pipe is in the water. Make surethe boat does not move so that the hosepipe entersthe water vertically.

2. Close top end with a rubber stopper and pull upbottom end until a U-shape is formed. Place theweighted end in a container and remove the stopperfrom the other end. Allow sample to empty into thecontainer.

3. Take required subsamples. The hosepipe should berinsed with clean water or with the water to besampled between sites.

Figure F.1: Diagram of hosepipe sampler

1. 2. 3.

W

W

W

53

APPENDICES

Appendix G: Taylor spheresampler (TASS)The Taylor sphere sampler is an inexpensive samplerwhich allows an uncontaminated near-surface sample tobe taken at the recommended depth of 0.5 m to 0.7 m(APHA, 1995) from a river by a single operator from thebank or a bridge. It has been developed at La TrobeUniversity Albury–Wodonga to improve the quality ofnear-surface samples taken from river banks for routinemonitoring or research programs under circumstanceswhere a boat is not available to reach the well-mixedzone of the stream. It is suitable for taking samples forphytoplankton as well as other water quality parameters.

The sampler is constructed from inexpensive partsreadily available in irrigation supply shops. Thematerials used in the sampler construction were chosento avoid chemical contamination of the sample byleaching substances.

The sampler consists of a 0.2 m diameterpolypropylene sphere (by Philmac) holding a volume ofjust over 4 L (Figure G.1). An upper (0.15 m) and alower (0.45 m) riser tube are connected to the spherewith bushes. The lower tube is weighted with a sleeve ofstainless steel tubing. A modified plastic foot valve (byPhilmac) at the end of the lower riser tube regulates thewater inflow. The upper riser tube has a polystyrene floatplaced around it to keep the sampler upright in thewater. The elbow fixed to the end of the upper riser tubeallows for the water to be poured out. The sampler isheld by a rope (approximately 10 m long).

To take a sample, the sampler is thrown into the river asfar as possible from the bank or bridge. The samplersinks slowly while filling (approximately 40 s) with thesample taken at a depth of 0.5 m to 0.7 m. The sampleris then pulled into the shore to retrieve the sample. Sincethe sampler is completely closed the sample cannot becontaminated while retrieving it from the river. Thewater sample is drained into a sample container throughthe plastic pipe attached to the elbow on the upper risertube, preventing the formation of air bubbles. Thus thesample taken is also suitable to measure oxygenconcentration.

The sampler has been used in a number of differentrivers under a variety of flow conditions in aphytoplankton and water quality research project andhas performed satisfactorily. Advantageous features ofthe sampler include:

• it is made from durable and readily availablematerials;

• it is relatively small, with a sample volume of 4 L;

• it is easy to handle from either shore or bridge; and

• the sample is taken at the point of first contact withthe water.

Enquiries can be addressed to Peter Taylor at theDepartment of Environmental Management andEcology, La Trobe University, Albury–Wodonga campus,phone 02 6058 3885 or emailptaylor@awcnet.aw.latrobe.edu.auA technical note on this sampler is in preparation.

54

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

Figure G.1: Diagram of Taylor sphere sampler

foot valve

tail

elbow

riser pipe

float

bush

polypropylene

sphere

bushriser pipe

stainless steel

tubing

R

R

R

R

R

R

R

R

R

R

55

APPENDICES

Appendix H: Taylor integratedsampler (TISA)The Taylor integrated sampler allows an integratedsample to be taken in a river from the surface to a depthof 3 m. It is assembled by one person and operatedremotely from the bank so that a sample is taken fromthe main current without using a boat.

The integrated sampler consists of a radio controlledcatamaran (1.2 m long) which carries the sampling pipe(3 m long) vertically. An aluminium beam which joinsthe two catamaran floats carries the radio equipment,motors, batteries, winch and a mast (see Figure H.1).Two pulleys are fixed to the top of the mast. Thesampling tube is attached to a cord which runs over thepulleys to the winch, allowing the sampling tube to bevertically raised out of and lowered into the water bymeans of the electric winch. The winch is operated byremote control. The catamaran is driven by twopropellers run by electric motors and directed by ashorebound operator via radio control. The samplingtube is made of transparent acrylic plastic with amodified self closing foot valve fixed to its lower end toretain the water.

The catamaran and sampler are assembled at shore.With the sampling tube in its raised position, thecatamaran is sailed into the main current. The samplingtube is then lowered into the water at constant speedwhile the catamaran is floating downstream with thecurrent. In this way, one complete water column issampled. Once the sampler is filled, the tube is lifted outof the water and the catamaran sailed back to shore toretrieve the sample. The sample is drained into acontainer through a tap at the base of the sampling tube.

The sampling tube can be taken apart into three1 m pieces for ease of transport. The catamaran alsodissembles into a series of parts. It takes approximatelyhalf-an-hour to assemble the whole apparatus, take thesample and pack it up again. The catamaran can belaunched from any gently sloping river bank or a jetty.The sampler is currently being validated against a hosepipe sampler.

For enquiries, please contact Peter Taylor at theDepartment of Environmental Management andEcology, La Trobe University, Albury–Wodonga campus,phone 02 6058 3885 or emailptaylor@awcnet.aw.latrobe.edu.auA technical note on this sampler is in preparation.

56

A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

sampler tube

Figure H.1: Diagram of Taylor integrated sampler

mast head with pulleys R

cord from winch R

R

radio gear/winchmotors/batteries

R

57

INDEX

Index

Aaccuracy vi, 25–29, 34–36Actinastrum falcatus 29akinetes 10algal coding system 29–31, 36algal ecologist 5–6algal units vi, 17, 22–28Anabaena 27Anabaena circinalis 28Aulacoseira 27, 30–31Aulacoseira granulata 29, 30, 36

Bbenthic algae vi, 5bloom 3, 5, 10, 28, 30–33buoyancy, removal of 19

Ccalibration 23, 24, 48Ceratium 23, 28chamber, choice of 19chlorophyll-a 7, 33code, details of 30Coelosphaerium 28concentration by gravity 18conductivity gradient 8counting, colonies 27counting, filaments 27counting, statistics of 25counting software 29, 31–32, 36, 49cyanoprokaryotes vi, 3, 19, 24, 28, 29–32Cylindrospermopsis 18

Ddatabase 9, 29–30, 36data storage 5, 29, 36desmids 30detection limit 34DIATCODE 30–31diatoms vi, 15, 17, 18, 28–31dumping ground categories 31

Eenumeration vi, 17, 20, 32, 34, 45eutrophication vi, 3, 6

Ffiltration, concentration by 18, 32fixation 5, 15–16formaldehyde 16frequency of sampling 6–7, 15

Ggas vesicles vii, 19glutaraldehyde 16, 37Gomphosphaeria 28green algae 15, 29groundwater inflow 8

Hhabitat vii, 8, 17haemocytometer 19hosepipe sampler 9, 52

Iidentification 17, 28–31, 36

LLimnothrix 10, 27live sample 15–17, 24, 28, 32, 48location 6, 8, 9Lugol’s solution 15–16, 46Lund cell 19, 22, 24, 25, 32, 48Lyngbya 27, 31

Mmacrophytes vii, 5measured value 25merolimnetic population 10metalimnetic population 10Microcystis 27, 28Microcystis aeruginosa 29microscope, inverted light vii, 17microscope requirements 17

Nnanoplankton vii, 15, 19, 22Neubauer cell 19

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A PHYTOPLANKTON METHODS MANUAL FOR AUSTRALIAN FRESHWATERS

OOedogonium 27, 31operator accuracy 34, 36

Ppatchiness 27photomicrograph vii, 28, 37phytoplankton, concentration of by gravity 18phytoplankton load 29phytoplankton net 15, 48picoplankton vii, 15, 19pilot study 6Planktolyngbya 10, 18point source 8Poisson distribution vii, 25–27potamoplankton vii, 3precision vii, 17, 23–27, 34preservation 5, 15–16

Qquality assessment 34–36quality control 5, 34–36

Rrandom distribution 19, 26random error 26, 27recording results 29retentive zones vii, 3

Ssample container 15sampling 8 et seq.Sedgwick-Rafter chamber 17–24, 32sedimentation 17 et seq.settling time 18site selection 8statistic D 26stratification vii, 8 et seq.subsampling preserved samples 17–18Synechococcus 19systematic errors 26

Ttaxonomic identification 17, 28–29true value 25–26turbidity 17, 19

Uultrasonication 19, 28Utermöhl chamber 17, 19–23, 48

Vvolumetric biomass determination 32

Wweir pool 8, 9, 10Whipple graticule viii, 17–18, 23, 24, 48