MARINE BENTHOSMethods for the Study of

Edited by

Anastasios Eleftheriou

FOURTH EDITION

METHODS FOR THE STUDY OFMARINE BENTHOS

Fourth Edition

METHODS FOR THE STUDY OFMARINE BENTHOS

Fourth EditionEdited by

Anastasios Eleftheriou

Hellenic Centre for Marine Research, Heraklion, Crete, Greece andDepartment of Biology, University of Crete, Heraklion, Greece

This edition first published 2013 C© 2013 by John Wiley & Sons, Ltd.Third edition published 2005 C© 2005 by Blackwell Publishing, Ltd.Second edition published 1984First edition published 1971

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Library of Congress Cataloging-in-Publication Data

Methods for the study of marine benthos / edited by Anastasios Eleftheriou, Hellenic Centre for MarineResearch, Crete, Greece and Department of Biology, University of Crete, Greece. – Fourth edition.

pages cmIncludes bibliographical references and index.ISBN 978-0-470-67086-6 (hardback) – ISBN 978-1-118-54236-1 (emobi) –

ISBN 978-1-118-54237-8 (epub) 1. Dredging (Biology) 2. Benthos–Research–Methodology.3. Marine biology–Methodology. I. Eleftheriou, Anastasios, 1935– editor of compilation.

QH91.57.D7M47 2013577.7–dc23

2013001796

A catalogue record for this book is available from the British Library.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not beavailable in electronic books.

Cover image: Underwater photograph on front cover reproduced by courtesy of Thanos DailianisCover design by Steve Thompson

Set in 11/13pt Times by Aptara R© Inc., New Delhi, India

1 2013

Contents

Contributors xiiDedication xivPreface to the Fourth Edition xvAcknowledgements xvii

Chapter 1 Design and Analysis in Benthic Surveys inEnvironmental Sampling 1Antony J. Underwood and Maura G. Chapman

1.1 Introduction 11.2 Variability in benthic populations 31.3 Appropriate replication 4

Appropriate spatial replication 4Appropriate temporal replication 9

1.4 Size of sampling unit 111.5 Independence in sampling 151.6 Multivariate measures of assemblages 161.7 Transformations and scales of measurement 201.8 Data-checking and quality control 221.9 Detecting environmental impacts as

statistical interactions 241.10 Precautionary principles and errors in interpretations 281.11 Precision and the size of samples 311.12 Gradients and hierarchies in sampling 331.13 Combining results from different places or times 371.14 Conclusions 39Acknowledgements 40References 40

Chapter 2 Characterising the Physical Properties of Seabed Habitats 47Andrew J. Kenny and Ian Sotheran

2.1 Introduction 472.2 Remote acoustic methods for surveying the seabed 49

Background 49Echo-sounders (single beam systems) 50

v

vi Contents

Acoustic ground discrimination systems based onsingle beam echo-sounder 50

Swathe bathymetry 562.3 Particle (grain) size analysis 63

Sample collection and storage 64Sediment grade scales 66Analytical techniques 68Presentation and analysis of grain size data 76

2.4 Other important sediment properties 81Bulk and dry density, water content and porosity 81Organic matter content 85Chlorophyll 87EPS carbohydrate 88Temperature 89Eh and pH 89In Situ Sediment Characterisation Methods 90

Disclaimer 90References 90

Chapter 3 Imaging Techniques 97Chris J. Smith and Heye Rumohr

3.1 Introduction 973.2 Acoustic imaging 99

Acoustic ground discriminating systems 99Sidescan sonar 100Swathe bathymetry 101

3.3 Video 101Underwater video camera systems 101Lenses 103Housings 103Data transmission 104Format 105Storage media 106Power supply 107Video monitors 107Illumination 107Calibration and measurement 109

3.4 Photography 1093.5 Carrier platforms 111

Diving 111Drop frames 112Specialised towed platforms 112Remotely operated vehicles 114

Contents vii

Autonomous underwater vehicles 114Manned submersibles 116Navigation and positioning of the carrier platform 117Data acquisition and processing 118

3.6 Special applications 118Sediment profile imagery 118Laser technologies 119Application of medical technologies 120

3.7 Laboratory imaging 1203.8 Image analysis 1213.9 Afternote 122References 122

Chapter 4 Diving 125Colin Munro

4.1 Diving systems 125SCUBA 126Remotely supplied systems 126Breathing gas and supply systems 127

4.2 Saturation diving and underwater habitats 1314.3 Data collection and recording 133

Slate or notepad and pencil 133Voice recording 134Image recording 136Video systems 142

4.4 Underwater site marking and relocation 144General considerations 144Air drills and underwater fasteners 147Acoustic pingers and receivers 148

4.5 Sampling methods 148Corers 148Suction samplers 149Yabby pumps and slurp guns 153Scrapers 153

4.6 Other study techniques 153Resin casting 153

4.7 Survey methods 154Manta tows 154Transect and quadrat surveys 155Plotless and rapid survey techniques 161Fish survey techniques 162

References 166

viii Contents

Chapter 5 Macrofauna Techniques 175Anastasios Eleftheriou and Derek C. Moore

5.1 Littoral observation and collection 175Position fixing and levelling on the shore 179

5.2 Remote collection 181Trawls 184Bottom sledges 186Dredges 189Semi-quantitative estimates with trawl and dredge 192Anchor dredges 194Grabs 195Box samplers and corers 204Suction samplers 207Other methods of sampling 210

5.3 Working sampling gear at sea 211Continental shelf 211Recovery of lost gear 213

5.4 Efficiency of benthos sampling gear 214Dredges and trawls 214Grabs 215Corers 219Comparative efficiency 219

5.5 Choice of a sampler 2205.6 Treatment and sorting of samples 221

Initial treatment 221Preservation 227Subsequent sorting 228

5.7 Data recording 230Acknowledgements 233References 233

Chapter 6 Meiofauna Techniques 253Paul J. Somerfield and Richard M. Warwick

6.1 Introduction 2536.2 Sample collection 254

Intertidal sediments 254Subtidal sediments 258Secondary substrata 262

6.3 Fixation and preservation 2636.4 Sample processing 264

Extraction 264Sediment 266Secondary substrata 270

Contents ix

6.5 Storage and preservation 2706.6 Sample splitting 2716.7 Examination and counting 272

Sorting 272Preparation for microscopy 273Counting 275Measurement 275

6.8 Biomass determination 2756.9 Cultivation of marine and brackish-water meiobenthos 2776.10 Experimental techniques 278References 279

Chapter 7 Deep-Sea Benthic Sampling 285Alan J. Jamieson, Ben Boorman and Daniel O.B. Jones

7.1 Introduction 2857.2 Sampling from research vessels 287

Deployment methods 287Tracking, monitoring and positioning 290

7.3 Collecting animals from the deep-sea floor 293Trawling 293Epibenthic sleds 296Traps 297Suction samplers 299

7.4 Collecting sediment from the deep-sea floor 300Grabs 300Box corers 304Tube corers 306ROV corers 309

7.5 Imaging the deep-sea floor 310Imaging survey design 311Photographic transects 312ROV imaging 314AUV imaging 317Time-lapse imaging 318Interpretation of images 324

7.6 Biogeochemistry of the deep-sea floor 327Benthic incubation chambers 327Sediment profiling systems 330

7.7 In situ manipulative experiments 3317.8 Future developments 333Acknowledgements 334Abbreviations 334References 335

x Contents

Chapter 8 Measuring the Flow of Energy and Matter in Marine BenthicAnimal Populations 349Jaap van der Meer, Thomas Brey, Carlo Heip, Peter M.J.

Herman, Tom Moens and Dick van Oevelen

8.1 Introduction 350State variables and units of measurement 351

8.2 Energy and mass budgets of individual organisms 351Ratios or ‘efficiencies’ 352Energy flux modelling 353

8.3 Methods for estimating the energy budget of anindividual organism 353

Mass, size, chemical composition and energycontent 354

Ingestion, absorption and defaecation 360Excretion 372Respiration 376Growth 379Reproductive output 380Regeneration 382Product formation 383

8.4 From the individual to the population 384Secondary production 385

8.5 Community-level measurements and modelling 396Community-level activity 396Community-level mass transfer 399Community-level modelling 402

References 404

Chapter 9 Phytobenthos Techniques 427Hans Kautsky

9.1 Introduction 4279.2 Phytobenthic communities 429

Guidelines for the study of phytobenthiccommunities 429

Data collection 4309.3 Overview of methods for sampling phytobenthos 4319.4 Transect line techniques 432

Overview of transect techniques 432Recommended ICES method 433SCUBA transect estimates (ICES method) 437Video transect method 443Continuous observation methods 443Photo frames 447

Contents xi

9.5 Other underwater surveying methods 448The manta tow technique 448Diver-propulsion vehicle technique 448Other underwater video techniques 449Remotely operated vehicles (see Chapter 3) 451Echo-sounding, sidescan sonar (see Chapter 3) 451

9.6 Other surveying techniques 452Satellite imagery 452Aerial photography 453Laser scanning techniques 453

9.7 Conclusion 454Appendix 455

Short review of methods used for monitoring inEurope and overseas 455

References 459

Index 467

Colour plate section 1 falls between pages 126 and 127

Colour plate section 2 falls between pages 302 and 303

Contributors

Ben Boorman, National Oceanography Centre, University of Southampton,Southampton, UK

Thomas Brey, Alfred Wegener Institute for Polar and Marine Research,Bremerhaven, Germany

Maura G.Chapman, Centre for Research on Ecological Impacts of CoastalCities, University of Sydney, Sydney, Australia

Anastasios Eleftheriou, Hellenic Centre for Marine Research, Heraklion, Crete,Greece and Department of Biology, University of Crete, Heraklion, Greece

Carlo Heip*, Royal Netherlands Institute for Sea Research, Den Burg, TheNetherlands

Peter M.J. Herman, Royal Netherlands Institute for Sea Research, Centre forEstuarine and Marine Ecology, Yerseke, The Netherlands

Alan J. Jamieson, Oceanlab, University of Aberdeen, Newburgh, UK

Daniel O.B. Jones, National Oceanography Centre, University of Southampton,Southampton, UK

Hans Kautsky, Department of Systems Ecology, Stockholm University,Stockholm, Sweden

Andrew J. Kenny, Centre for Environment, Fisheries and Aquaculture Science,Lowestoft Laboratory, Lowestoft, UK

Tom Moens, Department of Biology, University of Ghent, Ghent, Belgium

Derek C. Moore, Marine Scotland-Science, Scottish Government MarineLaboratory, Aberdeen, UK

Colin Munro, Marine Bio-images, Colin Munro Photography, Exeter, UK

Heye Rumohr, Leibniz Institute of Marine Sciences, IfM-GEOMAR, Kiel,Germany

Chris J. Smith, Hellenic Centre for Marine Research, Heraklion, Crete, Greece

Paul J. Somerfield, Plymouth Marine Laboratory, Plymouth, UK

xii

Contributors xiii

Ian Sotheran, Envision Mapping Ltd., Newcastle, UK

Antony J. Underwood, Centre for Research on Ecological Impacts of CoastalCities, University of Sydney, Sydney, Australia

Jaap van der Meer, Department of Marine Ecology, Royal Netherlands Institutefor Sea Research, Den Burg, The Netherlands

Dick van Oevelen, Royal Netherlands Institute for Sea Research, Centre forEstuarine and Marine Ecology, Yerseke, The Netherlands

Richard M. Warwick, Plymouth Marine Laboratory, Plymouth, UK

*Professor Carlo Heip of the Royal Netherlands Institute for Sea Research,co-author of Chapter 8, sadly passed away just as this volume of the Handbookwas in production. His contribution to marine science provided a great deal to ourunderstanding of the marine environment. He will be greatly missed.

Dedication

This edition of the handbook is dedicated to the memory of Alasdair McIntyre, co-editor and contributor from its inception. A marine scientist whose work achievedworldwide recognition, Alasdair McIntyre left an enduring legacy to benthic re-search, for which we are and will remain grateful.

xiv

Preface to the Fourth Edition

Bearing in mind that the present edition of this handbook has a long and honourablehistory, a short account of its provenance may prove useful for the first-time reader.The International Biological Programme’s global plan of coordinated research intoecosystem ecology (1964–1974) led to the publication of a series of handbooksdesigned to meet the needs of workers in a wide range of thematic areas anddisciplines, one of which was the study of marine benthos. The first edition of thehandbook targeted not only newcomers to the field but also the isolated workerwho had to have ready access to the existing literature, as well as others in relateddisciplines who needed to carry out seabed sampling and those who initiated benthicstudies.

It is now more than 40 years since the publication of that edition of the handbook(Holme & McIntyre, 1971), which was followed by two further editions (Holme &McIntyre, 1984; Eleftheriou & McIntyre, 2005). These later editions came aboutbecause major new approaches had emerged in response to ever-increasing demandsfor detailed information on bottom-living communities, as well as to the rapidadvances of twenty-first-century technologies. The present edition has retainedthe same overall layout of previous editions, though there have been substantialupdating and revisions as an outcome of the many changes that have occurred. Thisincludes the rearrangement of some chapters that focus on the latest advances inmarine technology and the reinstatement of a chapter on phytobenthos. The chapterson benthic deep-sea sampling, diving, imaging analysis, acoustic techniques usedfor the determination of the seabed characteristics and seabed sediment studieshave been substantially rewritten. However, where a specific sampler or techniqueis essential to the work to be carried out, the information has remained much thesame. During the rewriting of the handbook, care has been taken to keep to aminimum any significant overlapping in the descriptions of gear equipment andmethods to be used for different purposes or different biota, by cross-referencing orby means of brief descriptions of commonly used gears or methods. Nevertheless,it was felt that such overlapping was sometimes inevitable, as for instance, workerssearching for information concerning deep-sea sampling gears would not expectto find the relevant information available merely as a cross-reference to an entirelydifferent chapter.

There have been unavoidable changes in authorship, as over its 40 years’ contin-uum, new authors and co-authors have replaced those who have retired or who are

xv

xvi Preface to the Fourth Edition

no longer with us. Sadly, since the third edition, John Gage, expert on the deep-seamacrobenthos, senior author of Chapter 7, and Alasdair McIntyre, co-editor of thehandbook since its first edition, have both passed on.

During the last 20 years, it has been recognised that the underlying mechanismsand interactions in ecosystem functioning are complex and can be understood onlythrough multidisciplinary research networks. It is now accepted that the only way tounderstand the functioning of marine ecosystems is to formulate conceptual modelsbased upon information concerning exchanges and interactions of the ecosystemcomponents resulting from the collaboration between the subdisciplines of benthicecology and other disciplines. These ecosystems have been shown to be a sensitiveindex of alterations and changes and, as such, demand long-term and effectivemonitoring.

The editor has throughout been fully aware of the important priorities concerningthe identification and the linking of benthic patterns and processes and the develop-ment of suitable techniques for such linkages. While it is true that important inroadshave been made in several sectors of the marine sciences, such as biogeochemicalfluxes in the benthic boundary layer, the role of bacteria and meiobenthos in thebenthic environment, the dynamics of recruitment, the linking of biodiversity to theecosystem and carbon flow and its role in ecological stability, these are only a fewof the priority areas in ecological research that require concomitant technologicaldevelopment.

Over the past 30 years, though there has been a steady evolution in methodsand techniques in benthic investigations, which have seen significant advances inacoustic techniques, deep-sea exploration, diving and imaging techniques, methodsand techniques in the study of macrobenthos have remained relatively static. This isan indication of a slowdown in technological progress in this field, or perhaps of ascarcity of ideas in technical and methodological issues or a result of the noticeabledecline in large-scale and intensive benthic investigations, which were one of thefeatures of the previous 30 years.

It cannot be concluded that the existing methodology concerning sampling anextremely complex environment, which we cannot always understand, has reacheda stage of perfection. It should be stressed, therefore, that in an attempt to studymarine benthos as comprehensively as possible, the many tools and methods de-scribed in the present edition of the handbook are complementary and should beused in parallel when and where appropriate.

Anastasios Eleftheriou, Heraklion, May 2012

Acknowledgements

For this fourth edition of the handbook, I remain grateful to Norman Holme andAlasdair McIntyre, the two previous editors who were in the first instance instru-mental in pulling together all available knowledge on the subject, for the benefit ofso many researchers who have subsequently worked on marine benthos.

I express my deep gratitude to all the authors who have contributed their know-how and expertise to this volume; working with them has been both a valuable andmemorable experience.

I owe a great debt of gratitude to my wife, Margaret, without whose encourage-ment, support and forbearance this edition would not have appeared.

xvii

Chapter 1

Design and Analysis in BenthicSurveys in Environmental Sampling

Antony J. Underwood and Maura G. ChapmanCentre for Research on Ecological Impacts of Coastal Cities,University of Sydney, Sydney, Australia

Abstract

Measuring environmental impacts affecting benthic habitats requires detection ofspecific patterns of statistical interactions in data sampled before and after a potentialimpact, in the potentially impacted place and in control or reference locations. Thisis complex because ecological assemblages and populations vary at many spatialand temporal scales. Here, we introduce methods to ensure appropriate, indepen-dent replication of sampling at hierarchical scales in space and time. For statisticalanalysis, the logic of sampling design is critical. Determining precision of estimatesand maximising power to detect impacts require care in the design, analysis andinterpretation of the relevant data.

Keywords benthic variance, environmental impact, environmental sampling, in-dependence, precautionary principle, precision, replication, scale, sampling design,statistical interaction

1.1 Introduction

Quantified sampling, particularly to test applied and logically structured hypothe-ses about patterns and processes in marine habitats, is of increasing importancein underpinning the understanding of natural processes and to predict changesin response to environmental influences. There have been numerous advances insoul-searching (Peters, 1991), methods of analysis (Clarke, 1993; Anderson, 2001),commentaries on logic (Underwood, 1990; Resetarits & Bernardo, 1998; Lawton,1999) and the need for better understanding of environmental impacts (Schmitt &Osenberg, 1996; Sparks, 2000). As a result, it is not possible in a general summaryto review comprehensively even the new material, let alone everything relevant to

Methods for the Study of Marine Benthos, Fourth Edition. Edited by Anastasios Eleftheriou.© 2013 John Wiley & Sons, Ltd. Published 2013 by John Wiley & Sons, Ltd.

1

2 Methods for the Study of Marine Benthos

the topic of improved benthic sampling. Suffice it to say that it is also essentialto help with management and conservation of diversity, natural resources, systemsand functions. Taking care in the acquisition of quantitative information should,therefore, be of paramount importance to all marine biologists and ecologists.

This chapter, therefore, presents a general overview of the issues concerned. Itis not, nor could it be, a ‘cookbook’ of procedures that might work. Rather, it is anattempt to consider fundamental issues of replication, in space and time, the natureof variables examined, issues about designing comparative sampling programmesand so forth.

These topics are considered against a general background of the logical structureunderpinning sampling methodology. The issue is a simple one – unless the aimsand objectives of any study are clearly identified at the outset, the least damagingoutcome will be wastage of time, money and resources. The worst outcome wouldbe a complete lack of valid information on which to build understanding, predictivecapacity and managerial/conservatory decision-making. Where aims are vague,designs of sampling are usually (if not always) inadequate, data do not matchnecessary assumptions, analyses are invalid and conclusions suspect.

In contrast, where aims and purposes are logical, coherent and explicit, it isusually possible to design a robust, effective, efficient and satisfactory samplingprogramme, which will allow aims to be achieved with minimal uncertainty. Thisseems such common sense that it does not need to be stated – but common senseindicates that the world is flat and that the sun rotates round the earth. Commonsense is not enough.

For example, Hurlbert (1984) published a devastating critique of the failureof many published studies to demonstrate a valid basis for reaching conclusions,because the samples analysed were inappropriately or not at all replicated. His studywas confined to the published studies, in refereed journals, subject to independentscrutiny. The overall situation, taking into account rejected papers, less intensivelyscrutinised journals and the flood of unreviewed grey literature, was clearly muchworse. It is clear, from practical inspection of more recent literature and throughreviewing manuscripts and applications for grants, that the situation (though nowbetter) has not improved substantially (Hurlbert, 2004).

The starting point for studies needing quantitative sampling is that objectivesshould be clear, the variables to be measured should be defined and the sorts ofpatterns anticipated in the data should be clearly identified (as testable hypotheses).Wherever possible, as much information as is available should have been collected(and understood) about the operational processes operating, their spatial and tem-poral scales and about the biological interactions in assemblages and responsesto environmental variables. Ideally, the constraints of money, time and equipmentshould also have all been taken into account. In other words, the professional com-ponents of scientific work should all be in place. Under these circumstances, itshould be possible to design sampling to achieve minimal probabilities of error inanalyses.

Design and Analysis in Benthic Surveys in Environmental Sampling 3

As a result, the focus in this chapter is on general issues and procedures toprovide help and guidance with setting objectives, formulating hypotheses anddesigning sampling, particularly for measuring ecological impacts. This will serveas an aide-memoire for contemplating issues of logic when dealing with spatialand temporal variability in biological systems. It will also provide an introductioninto the broader literature where many advances have been made in methodologiesdealing with the problems of biological complexity in the real world.

1.2 Variability in benthic populations

Surveys must always be designed to take into account the fact that benthic animalsand plants are extremely patchy in distribution and abundance. Patchiness is causedby processes external to the assemblage, particularly disturbances and recruitment,in addition to processes operating within the existing assemblage. Although anthro-pogenic disturbances are often very severe (e.g. large-scale trawling or dredging cancause extreme changes in benthic assemblages; Hall & Harding, 1997; Lindegarthet al., 2000), natural disturbances are common and can be important contributorsto spatial variability of populations. These vary from small-scale disturbances, e.g.being overturned by waves affects the assemblage on a boulder (Sousa, 1979) andpotentially the assemblage in the sediment below it, to large-scale processes, suchas the erosion of nearshore sediments (Shanks & Wright, 1986) and the destructionof assemblages in response to large storms (Underwood, 1998).

However, the most important contribution to patchiness is probably due to un-predictable and variable patterns of recruitment (Underwood & Denley, 1984).Both settlement itself and post-settlement mortality typically vary at a hierarchyof spatial scales (Caffey, 1985; Gaines & Bertness, 1992). Patterns at larger scalestend to be more predictable because most species are confined to particular habitatswithin a biogeographic range (Brown & Gibson, 1983). However, at small scaleswithin patches of habitat, there is considerable variability in recruitment (Keough,1998), caused by local environmental variation (e.g. topographic features of habitator localised water currents) or by the existing assemblage itself (e.g. gregarioussettlement in response to conspecific adults or consumption of larvae by largenumbers of sessile species). The numbers of larvae competent to settle that arrivein any site are themselves influenced by a multitude of external processes, many ofwhich act in the water column well away from the site of settlement. The localisedprocesses, both physical and biological, that influence recruitment are interactive,so recruitment is extremely variable in space and time.

In addition, numerous interactions within the assemblages themselves continu-ally alter patterns of abundances and these effects, too, occur at a range of spatialscales. For example, though predation may decrease abundances at the scale of ashore or habitat, within that habitat predation may eliminate species from certainpatches, but leave other patches alone. Feeding by eagle rays or shore birds can

4 Methods for the Study of Marine Benthos

create extreme small-scale patchiness in abundances of their prey, although theseeffects are complicated by environmental factors, such as currents and movementof sediment (reviewed by Thrush, 1999). Even in areas with heavy predation, preymay settle in particular microhabitats, where they can grow large enough to escapepredation (Dayton, 1971).

Competition, either for space among sessile animals or plants or for food amongmobile animals, also contributes greatly to patchiness of assemblages. Therefore,over-growth or dislodgment of one species by another (Keough, 1984) causes verypatchy assemblages of sponges, ascidians and other colonial animals in subtidalhabitats and of barnacles and various types of algae in intertidal habitats. Althoughspecies that are superior competitors for space or food may eliminate inferiorspecies, the relative strength of interspecific competition may be balanced withthat of intraspecific competition. This ensures that neither species is eliminated,but that both persist in very variable and patchy numbers.

Processes such as these are better understood for benthic assemblages living onhard surfaces because, first, the patterns are often readily visible and, second, theprocesses are relatively easily investigated experimentally. They are, however, alsoimportant for assemblages in soft sediments, where recruitment may be equallyvariable (Skilleter, 1992; Whitlatch et al., 1998) and local disturbances, competi-tion and predation alter local abundances, causing very patchy distributions at ahierarchy of spatial and temporal scales (Morrisey et al., 1992a, 1992b; Ysebaert& Herman, 2002; Fig. 1.1). To estimate abundances of benthic animals and plantsaccurately, measures must be made at the range of spatial scales relevant for thespecies, assemblage or process under consideration.

1.3 Appropriate replication

Appropriate spatial replication

Whatever the hypothesis being tested and the ultimate use of the data from sampling,spatial replication is a mandatory component of any benthic study. The largevariability in numbers and varieties of benthic species from place to place at manyspatial scales (see Section 1.2) creates fundamental problems for determining atwhat scales replication is necessary.

Consider a relatively simple problem of determining the influence of type ofsediment on the numbers and types of benthic species. To keep the example verysimple, suppose that a particular species of polychaete is generally more abundantwhere sediments are coarse than where fine sediments form the major proportion. Inany ecological study of these worms in some new area, a relevant hypothesis to betested is, therefore, that abundance will, on average, be greater in an area of coarsesediment than in a corresponding area of fine sediment. Furthermore, suppose thatpatches of the different types of sediment are about 800 m in diameter. Finally, asis virtually inevitable, imagine that numbers of worms per m2 of habitat may vary

Design and Analysis in Benthic Surveys in Environmental Sampling 5

(a)

(b)

Fig. 1.1 Mean (Standard Error; SE) abundance of two species of amphipods (a) and (b) betweensites (S1, S2; tens of metres apart) in each of two locations (L1, L2; 100 m apart) in each of threemangrove forests (F1, F2, F3; kilometres apart). Note that each species shows significant variation ateach spatial scale, but these differ between the two species. Patterns of variation at the scale of sitesand locations also vary from one mangrove forest to another.

6 Methods for the Study of Marine Benthos

substantially at scales of tens of metres and at scales of hundreds of metres, evenin the same type of sediment. Consider a sampling scheme in which 10 box coresare sampled in one patch of coarse sediment and 10 cores are taken from a patch offiner sediment some 2 km away. The mean number of worms is greater in the coresfrom the coarser sediment, which is consistent with the hypothesis. Nevertheless,this does not allow a valid interpretation that the difference is associated with thedifference in sediment (as was predicted). Such an interpretation or influence isconfounded by the alternative that numbers are different simply because the twoareas are 2 km apart. In other words, if samples are taken in two patches of fine ortwo patches of coarse sediment separated by 2 km, numbers of worms may differas much as is observed in the two samples shown here. The alternative modelsexplaining why numbers of worms vary are that the sediments differ or that naturalvariation from place to place, regardless of sediment, caused the numbers to bedifferent. The only way to separate these two models is to predict (from the firstmodel) that differences from one type of sediment to the other are greater thanexpected from natural variation in either type of sediment.

The study, therefore, requires replication of sites of each type of sediment toestimate natural variation that is not associated with type of sediment. It is some-times argued that such a study as described is replicated because there were severalcores in each patch. This is an example of what Hurlbert (1984) called ‘pseu-doreplication’ – the replicate units in each sample are at the wrong scale and areestimating variability at tens of metres, not at the hundreds of metres at whichthere are differences among patches of the same type. A better-constructed designwould solve the problem by sampling several patches of coarse sediment spaced,say, 2 km apart and several patches of finer sediment at similar spacing, about 2 kmfrom the nearest area of coarse sediment sampled. The two types of patch shouldbe interspersed, i.e. chosen to be higgledy-piggledy on a map, so that no systematictrend or gradient makes them different for reasons other than the type of sediment(see Underwood (2000) for examples and illustrations of this issue).

Using such a design, the variation of scales of tens of metres within a patchand at hundreds of metres from patch to patch of the same type of sediment canbe estimated. A hierarchical or spatially nested analysis of the data can then beused to test the hypothesis that the difference, on average, between the two typesof sediment is greater than the natural spatial variation from patch to patch of thesame type. Examples of such analysis for benthic infauna are in Green and Hobson(1970) and Morrisey et al. (1992a, 1992b), and the form and structure of analysesare described in detail in Underwood (1997a).

The lengthy description of a very simple case is made necessary by the largenumber of unreplicated studies, with logically invalid conclusions, that still keepappearing in (or are submitted to and rejected from) ecological journals. It shouldbe noted that better sampling is no substitute for good biological knowledge. So,if the variation in numbers of polychaetes from site to site with finer sedimentsis known from previous studies to be of the order of tens to hundreds of worms

Design and Analysis in Benthic Surveys in Environmental Sampling 7

per m2 and there are 1500 more worms per m3 in the single coarser site than inthe single finer site sampled, it can be argued that this size of difference is muchgreater than natural variation among sites with finer sediments. In such a case, theconclusion that more worms are found in coarser sediments would be valid.

This argument will, however, only be correct if there has been adequate previousstudy to demonstrate the general validity (from area to area of the world andfrom time to time) of the notion that numbers of worms vary naturally by tens tohundreds per metre. It is not usually the case that sufficient information of this typeis available. It is, in fact, often the case that previous studies were not replicatedat appropriate spatial scales to justify reaching such general conclusions. If suchan argument is to be used, it is, therefore, essential to provide the details of theprevious studies that might justify it. Often, it is more efficient (and always morevalid scientifically, because it does not depend on inductive inferences) to useappropriate replication in any new study.

One further example of problems of logical conclusions from sampling at onlyone or two spatial scales will be considered. Suppose that dredging is being doneat several places in an estuary, to keep channels open for shipping. The sedimentsin shipping channels are contaminated by heavy metals. Sampling is required inorder to detect any impact on benthic infauna in areas around the sites beingdredged (not in the sites being dredged – they are not just impacted, but the habitatis actually removed). The concern is that fine sediments with associated heavymetals may wash from the dredged sites to areas up to 100 m away. A replicatedstudy can be designed (as in Fig. 1.2), with several dredged areas and severalcontrols being sampled. In each area, replicated patches of sediment are sampled.Natural spatial variation from patch to patch and area to area is estimated andanalysis can reveal any systematic difference between sites near dredging andcontrol sites.

Suppose, however, that the movement of contaminated sediment accidentallyreleased from a dredged area is actually much larger than anticipated. Contaminatedfines may now be dispersed over the whole estuary, thus deleteriously affectingall of the control sites, in addition to the sites immediately adjacent to dredging.Changes in benthic fauna due to heavy metals will now occur over all the sitessampled, but there will be no apparent impact because the control sites and thesites next to dredging will not show any differences, when the data are analysed.It would seem that, during the course of the study, there has been an estuary-widechange in fauna not associated specifically with dredging. This sort of situationrequires sampling at much larger scales, best of all in other estuaries where dredgingis not occurring.

Designs of this type and procedures for analysing the data to detect impacts insuch situations were discussed in detail by Green (1979) and Underwood (1992,1994). The moral of this example is clear – when in doubt about the relevant spatialscale, use a design that can detect changes or differences at one or more of severalof the possible scales.

8 Methods for the Study of Marine Benthos

(a) Predicted

(b) Actual

Fig. 1.2 Sampling to detect an impact due to escape of fine sediments from dredging at × in areasA, B and C in an estuary. In each area, there are sampling sites (•) within the distance predicted thatsediment would disperse if accidentally released (i.e. over the stippled areas in (a)). Control sites (◦)are outside the predicted area of impact and at similar distances apart as the potentially impacted sites.In (b) is the actual, much larger (stippled) area impacted; no impact would be detected because all thecontrols are also affected.

Design and Analysis in Benthic Surveys in Environmental Sampling 9

Appropriate temporal replication

Many hypotheses concern temporal changes, e.g. seasonal patterns of variationor potential changes in populations due to disturbances. A major problem associ-ated with many such studies is the confounding of temporal and spatial variability(Underwood, 1993; Stewart-Oaten & Bence, 2001). For example, to measure sea-sonal patterns of abundance, a common procedure is to collect a sample, usinga set number of replicates, each month (or each season) in one or more places.Tests of temporal patterns then typically compare the abundances from one month(or season) to another to the variability among replicates in the different seasons(using procedures such as analyses of variance). The problem with such compar-isons is that variation among seasons is indeed a measure of temporal variation,but variation within a sample is calculated from measures of spatial variation, be-cause the replicates taken at any particular time are all taken at the one time, eventhough spatially scattered. In such a design, seasonal (or other temporal) patternsare not contrasted against temporal variation within each season, but against spatialvariation.

To test for seasonal variation (or other a priori selected scales of temporalvariation), temporal variation among the factors of interest must be compared totemporal variation within each factor of interest. In other words, temporal variationamong seasons must be compared to the magnitudes of variation that occur in eachseason. To measure such variability, it is essential to collect samples several timeswithin each season. With two or more scales of temporal sampling, seasonal orother long-term trends can be identified against background noise. Where there isno measure of shorter-term temporal variation and such variation is large, quitespurious seasonal (or other temporal) patterns will be seen in the data (Fig. 1.3).

Different scales of temporal sampling are extremely important for identify-ing environmental impacts. Disturbances to the environment may either be short-lived (pulse disturbances) or persist for long periods of time (press disturbances)(Bender et al., 1984). The responses of organisms to either type of disturbancemay be relatively short-term (i.e. a pulse response); for example, abundances mayrapidly increase, but soon drop to normal levels, irrespective of whether the distur-bance persists or ceases. Alternatively, populations may show long-term responses(i.e. press responses) to continuing disturbances (because the disturbance continuesto exert an effect) or to pulse disturbances (because the disturbance, although itended long ago, caused a long-term change to another environmental or biologicalvariable). The experimental designs needed to distinguish among pulse and pressresponses to pulse or press disturbances have been thoroughly described by Un-derwood (1991) and Glasby and Underwood (1996). All require a sampling designthat can measure temporal variation at different temporal scales, measured at thespatial scales relevant to the pulse and press responses.

For examining most environmental impacts and many other ecological hypothe-ses, the temporal scales of change are not known and can seldom be predicted. The

10 Methods for the Study of Marine Benthos

(a) (b)

(c) (d)

Fig. 1.3 With only a single sample at a series of time intervals a long time apart (e.g. each sea-son), an apparent seasonal pattern could be identified in the variable being measured whether (a)there is, indeed, a long-term seasonal trend or (b) there is considerable short-term variability, but nolong-term trend. Short-term temporal sampling is needed within each season. This provides the cor-rect form of within-season replication to measure seasonal changes and identifies (c) long-term trendsfrom (d) background ‘noise’.

only way to identify important temporal change is to use a hierarchical temporalsampling scheme. Such designs (Underwood, 1991) not only identify whether anychange indicates a pulse or press response but also quantify temporal variances ata number of scales. Impacts that change variances may be more common than andas important as those that change means (Underwood, 1991). If an impact causesmuch greater fluctuations in abundance (e.g. by altering water currents so thatrecruitment is more unpredictable), the average abundance of a species may notchange over long periods of time; nonetheless the species may be very rare or verycommon at different times, depending on recent recruitment (Fig. 1.4). If a subse-quent impact occurs during a period when abundance is small, such populationsmay be far more vulnerable to cumulative, but relatively minor impacts, whichcan then cause local extinctions. Sampling designs that measure changes in meanabundance at different temporal scales, in addition to changes in temporal variancesof abundance, are most likely to be successful at identifying environmental impactsand natural ecological variation.