The Role of Mucus and Silk as Attachment and Sorption Sites in Streams

Submitted by

Chris Brereton

for the degree of

Doctor of Philosophy

University College London

1998 ProQuest Number: U642856

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ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 Abstract

This thesis is an examination of the characteristics of mucus and silk within

freshwaters. The source of mucus was snail pedal mucus from Lymnaea peregra and

Potamopyrgus jenkinsi, the source of silk was first instar silk threads of Simuliidae

spp. Each chapter examines a different aspect, or role, of such materials within the

habitat of snails and blackfly. In particular, the interactions of suspended particles,

pollutants, sediments and biofilms are examined in relation to snail trail mucus (STM)

and blackfly silk.

The search for a particle type, suitable as a marker for STM is detailed. This was

used to characterise STM, including the examination of the duration of STM integrity,

the effect of water flow upon STM, the effect of disturbance and bacteria (airborne,

waterborne and those included within the mucus trail). The advantage that different

substrates offer in maintaining STM presence, as well as the physical dispersal of

STM are aspects that are also examined. A comparison is made between the STM

of two species of freshwater snail.

The examination of the interactions of a range of pesticides to mucus and silk finds

sorption to a degree previously unmeasured for any other natural substance. This

presents many implications in terms of the bio-accumulation of pollutants within the

freshwater ecosystem. The effect that STM has upon benthic sediment stability was

found to be immeasurable. In looking at the role o f STM in the development of

biofilm, it is found that STM can accelerate the accumulation of particulate matter as

well as acting as a "seed-bed" for specific types of bacteria.

This study provides evidence that organic materials, produced by freshwater

macroinvertebrates are an understudied resource that have considerable impact on

biological and chemical processes. They exist in considerable quantities and present

a large surface area within the freshwater environment. In so doing, they act as a trap

or sink for a wide variety of particulate material. Acknowledgements

I would like to thank my three supervisors Dr.P.D.Armitage, Dr.W.A.House and

Dr.R.S.Wotton for initiating this project and for each providing an invaluable source of information, advice and enthusiasm.

In addition, I would also like to thank Dr.G.P.Irons for his patience and instruction regarding the operation of various software packages, as well as the commissioning of a computer. Mr.D.Orr and Mr.I.S.Farr provided a great deal of time in demonstrating the operation of various pieces of equipment, and Miss.F.M.Buchanan provided invaluable advice in the execution of those techniques described in Chapter

6. Mr.R.Clarke exhibited a great deal of patience in suggesting appropriate statistical tests. Dr.G.EImes kindly loaned his scanning electron microscope for which I am indebted to him, as I am to Mr.D.Hornby for his remote instruction regarding operation. I am also indebted to Miss F.M.Buchanan for performing the microbiological identifications, used in Table 6.1.

I am also thankful to Dr.D.T. Chaloner for his ceaseless willingness to debate the finer points of experimental design and failure.

Grateful thanks are also extended to those who have kindly offered their time to proof­ read this manuscript during its various stages o f completion, notably my three supervisors, and also Miss.F.M.Buchanan, Dr.S.Brown, Dr.M.Ladle, Miss C.Cannan,

Dr.G.P.Irons and Mr. M. Bowes.

I am grateful to the River Laboratory at East Stoke, at which I spent three years carrying out this work, for the provision of a friendly working environment as well as finest purpose built facilities imaginable for work o f this nature.

A special acknowledgement is extended to Miss.F.M.Buchanan, without whose support and encouragement, this thesis would never have reached fruition.

Finally I would like to thank EPSRC, who made this project possible. Table of Contents

Page No.

Title Page

Abstract

Acknowledgements

Table of Contents

List of Figures

List of Tables 12

List of Plates 14

List of Abbreviations 15

Chapter 1 General Introduction 16

1.1 Introduction 16

1.2 The "re-cycling" of sites of attachment 17

1.3 Organisms chosen for use in this study 18

1.4 Review o f materials used: silk and STM 20

1.5 Characterisation of STM 22

1.6 Mucus and silk as sites o f attachment to DOM 23

1.7 Mucus as a potential agent of sediment consolidation 25

1.8 Sediment consolidation in aquatic environments 26

1.9 Consolidating properties of polysaccharide 27

1.10 Examination of estuarine consolidation 28

1.11 STM as a site of biofilm development 29 1.12 Formation of biofilm 31

1.13 Note on sorption 32

1.14 The progression o f study within this thesis 32

Chapter 2 Selection of a marker particle suitable for the

observation of snail trail mucus 34

2.1 Introduction 34

2 . 1.1 Previous uses of marker particles in freshwater biology 34

2.1.2 Particle types available 35

2.1.3 Experimental objective 37

2.2 Materials and methods 37

2.2.1 Experimental protocol 37

2.2.2 Particles used in this trial 39

2.3 Results and discussion 42

2.3.1 Efficacy of particle types 42

2.3.2 Subjective approaches in the selection of an

appropriate marker particle 50

2.3.3 Objective approaches in the selection o f an

appropriate marker particle 51

2.4 Conclusion 52

Chapter 3 The physical behaviour of snail trail mucus 53

3.1 A background to the properties and functions of mucus 53

3.1.1 Experimental Objectives 56

3.2 Materials and Methods 56

3.2.1 Experimental protocols 60

3.2.2 Methods of counting and comparison by

statistical analysis 62 3.3 Results and Discussion 65

3.3.1 W ithin treatment analysis - the uniform ity of 6

replicate response 65

3.3.2 Comparison of the snail trail mucus of

two freshwater species 70

3.3.3 For how long does snail trail mucus remain sticky? 86

3.3.4 The effect of water speed upon snail mucus

trail integrity 89

3.3.5 The effect o f sampling and snail action as

disturbance events 91

3.3.6 The effects of ageing, water depth and airborne

bacteria upon snail trail mucus longevity 97

3.3.7 The distribution mechanism of snail trail mucus

and the effect upon it of waterborne consumers of mucus 100

3.3.8 Snail gut bacteria and mucus trails 102

3.3.9 Waterborne bacteria as consumers of snail trail mucus 103

3.3.10 The protection offered by surface relief in

freshwater systems 106

3.3.11 Identified properties of the mucus trails of each species 107

3.4 Conclusions 109

Chapter 4 The affinity of pesticides to mucus and silk 110

4.1 Introduction 110

4.1.1 Parameters used to describe pesticide

affinity for materials 110

4.1.2 Research developments into the role of pesticides

in the environment: examining appropriate materials 111

4.1.3 Materials that have been overlooked by

conventional techniques 113

4.1.4 Pesticide affinity for organic material produced

by invertebrates 118

4.1.5 The aims of this study 118

4.2 Materials and Methods 119 7

4.2.1 Experimental Protocols - Mucus I 19

4.2.2 Estimation of mucus mass 121

4.2.3 Sample sizes - Mucus 121

4.2.4 Experimental Protocols - Silk 122

4.2.5 Sample'Sizes - Silk 124

4.2.6 Extraction and analysis of the pesticides 125

4.3 Results and discussion 126

4.3.1 Comparison with previously published pesticide

affinity constants for various sediments and soils 139

4.3.2 Mucus sorption 141

4.3.3 The water content of mucus 142

4.3.4 Silk sorption 142

4.3.5 Individual pesticide sorption 143

4.3.6 Are certain pesticides sorbed to a greater extent

than others? 144

4.3.7 Experimental constraints 145

4.3.8 Mucus and silk as water purifiers 146

4.3.9 Placing blackfly silk and snail mucus in the

context of other materials studied 148

4.3.10 The importance of accounting for pesticide affinity to

biological material 149

4.4 Conclusions 152

Chapter 5 Sediment stability 154

5.1 Introduction 154

5.1.1 The role of macroinvertebrates in sediment

stabilisation and disturbance 155

5.1.2 Experimental objectives 156

5.2 Materials and Methods 157

5.2.1 Experimental Protocols 159

5.2.2 Equipment design 163 5.2.3 Calibration of light meter 163

5.2.4 Calibration of speed o f water in jars at each

paddle setting 163

5.2.5 Sampling 164

5.2.6 Data manipulation 164

5.3 Results and Discussion 165

5.3.1 Water speed generated by paddle speed 165

5.3.2 Light meter readings at each paddle speed 165

5.3.3 Experimental improvements and suggestions 177

5.4 Conclusions 181

Chapter 6 Biofilm growth and the role of snail mucus 182

6.1 Introduction 182

6.1.1 The potential advantage offered by snail mucus

to biofilm development 182

6.1.2 Experimental objectives 183

6.2 Materials and methods 184

6.2.1 Experimental protocols - SEM 186

6.2.2 Experimental protocols - M icrobiological analysis 186

6.2.3 M icrobial identification 188

6.3 Results and Discussion 191

6.3.1 Analysis of treatments using SEM 191

6.3.2 Distribution of Microorganisms 194

6.3.3 Analysis of microbial cells attached to stubs 198

6.3.4 Mucus availability 206

6.3.5 Suggestions for further work 208

6.4 Conclusions 209

6.5 Microbial Identification 210 Chapter 7 General Discussion 217

7.1 Introduction 217

7.1 Mucus rich environments 217

7.2 Physical properties o f mucus and silk,

characterised by this study 220

7.3 Bioturbation 221

7.4 Mucus, biofilm, particles and pollutants 223

7.5 Designing biofilm 225

7.6 Existing applications of polysaccharide 227

7.7 Further work, identified by this study 229

Bibliography 233 10

List of Figures

Figures 2.1 - 2.20 Cover of snail trail mucus on glass slides over time,

for 20 particle preparations 45

Figures 3.1-3.23 Erosion rates of L. peregra mucus trails over

time treatments A1 - Y1 71

Figures 3.24 - 3.45 Erosion rates o f P. jenkinsi mucus trails over

time treatments A2 - Y2 77

Figure 4.1 Molecular structures of triazine herbicides 115

Figure 4.2 Molecular structures of triazine herbicides 116

Figure 4.3 Molecular structures of organophosphate herbicides 117

Figure 4.4 Schematic diagram of the preparation of mucus samples 120

Figure 4.5 Schematic diagram of the preparation of silk samples 123

Figure 4.6 Mean association constants for pesticides on mucus produced

by groups of different densities of of L. peregra 135

Figure 4.7 Mean association constants for pesticides on

mucus produced by L. peregra 135

Figure 4.8 Mean association constants for pesticides on mucus produced

by groups of different densities of of P. jenkinsi 136

Figure 4.9 Mean association constants for pesticides on

mucus produced by P. jenkinsi 136

Figure 4.10 Mean association constants for pesticides on silk

attached to cellulose nitrate membranes 137

Figure 4.11 Mean association constants for pesticides on silk

attached to glass fibre filters 137

Figure 4.12 Mean association constants for pesticides on silk 138

Figure 4.13 Comparative studies presenting distribution

coefficients for various materials 140

Figure 5.1 Schematic diagram of sediment preparation 158 11

Figure 5.2 Schematic diagram of turbidity measurement 161

Figure 5.3 Calibration curve of light detector 162

Figure 5.4 Water speed generated at each paddle speed setting 166 Figure 5.5 - 5.12 Progression of light restriction due to turbidity

for treatments A l, A2, 31, 32, Cl, C2, D1 and D2

at 24 and 48 hours 167

Figure 6.1 Key to identification methods for Gram negative bacteria 189

Figure 6.2 Key to identification methods for Gram positive bacteria 190

Figure 6.3 A l - A4 SEM images of mucus coated stubs over time 192

Figure 6.3 B 1 - 34 SEM images of control stubs over time 193

Figure 6.5 Comparison of Pseudomonas counts at 15°C 202

Figure 6.6 Comparison of Pseudomonas counts at 25°C 202

Figure 6.7 Comparison of Coliform counts at 37®C 203

Figure 6.8 Comparison of Total Anaerobic counts at 20®C 203

Figure 6.9 Comparison of Total Aerobic counts at 15°C 204

Figure 6.10 Comparison of Total Aerobic counts at 25®C 204

Figure 6.11 Comparison of Yeast and M ould counts at 15°C 205

Figure 6.12 Comparison of Yeast and M ould counts at 25°C 205 12

List of Tables

Table 2.1 Particles and particle preparations 41

Table 2.2 Coefficient of determination for each particle type and

preparation, for both a linear and an exponential

regression of the decay o f mucus on glass against time 43

Table 2.3 Student's t-tests for differences between mucus coated

and control slides - to assess the affinity o f Radiant

Color® Particle preparations for clean glass against STM 51

Table 3.1 Description of all treatments 57

Table 3.2 Breakdown of data manipulation with representative

examples for between treatment analysis 64

Table 3.3 a W ithin treatment analysis using A N O V A to test

replication against error for treatments featuring the

STM o f L. peregra 67

Table 3.3 b W ithin treatment analysis using A N O V A to test

replication against error for treatments featuring the

STM o f P. jenkinsi 68

Table 3.4 Decay rate (pooled regression coefficient of

log transformed data) o f STM on 5 replicate glass

slides for each treatment 84

Table 3.5 Treatments used to determine how long STM

remains “ sticky” 86

Table 3.6 Treatments used to determine the effect of current

velocity on STM 89

Table 3.7 Treatments used to determine the effect of

sampling and snail action as disturbance events 91

Table 3.8 Treatments used to determine the effects of ageing,

water depth and airborne bacteria onSTM 97

Table 3.9 Treatments used to investigate the mechanism of

distribution of STM and its effect on waterborne 13

consumers of mucus 00

Table 3.10 Treatments used to assess the effect of snail gut

bacteria on STM 102

Table 3.1 1 Treatments used to assess the effect of waterborne

bacteria on STM 103

Table 3.12 Treatments used to assess the protection afforded

to STM by the relief o f a surface 106

Table 4.1 Predicted distribution coefficients from

octanol - water partition coefficients 112

Table 4.2 Mucus sample values 127

Table 4.3 Mucus sample values 128

Table 4.4 Mucus sample K j values 129

Table 4.5 Mucus sample values 130

Table 4.6 Silk sample K j values 131

Table 4.7 Silk sample K j values 132

Table 4.8 S ilk sample values 133

Table 4.9 Silk sample values 134

Table 4.10 Percentage sorption o f pesticides 147

Table 4.11 Comparison of distribution coefficients for silk

with other distribution coefficients 151

Table 4.12 Definition of parameters used 153

Table 5.1 A Comparisons between treatments and controls

using Student's t-test 172

Table 5.IB Comparisons between jars against time examining

the effect of disturbance using Student's t-test 173

Table 5.2 A N O V A (using balanced designs) for turbidity 174

Table 6. Comparison of identified colonies 197 14

List of Plates

Plate 2.1 Snail trails (L. peregra) 36

Plate 2.2 Re-circulating water channel 40

Plate 6.1 Alum inium stub holding tray 185

Plate 6.2 Pseudomonas sp. x 1000 213

Plate 6.3 Flavobacterium sp. x 1000 213

Plate 6.4 Micrococcus sp. x 1000 214

Plate 6.5 Bacillus sp. X 1000 214

Plate 6.6 Actinomyces sp. x 1000 215

Plate 6.7 Rhodotorula sp. x 1000 215

Plate 6.8 Cladosporium sp. x 1000 216

Plate 6.9 Pénicillium sp. x 1000 216 15

List of Abbreviations

CEP Colloidal Exopolymer Particles

CN Cellulose Nitrate

CPOM Coarse Particulate Organic Matter

CPU Colony Forming Units

DOC Dissolved Organic Carbon

DOM Dissolved Organic Matter

EPS ExoPolymer Secretions

GC Gas Chromatography

GF Glass Fibre

HPLC High Pressure Liquid Chromatography

FPOM Fine Particulate Organic Matter

Kj Partition coefficient (K), (usually of a pesticide) between water and any

specified material

Partition coefficient (K), (usually of a pesticide) between Mucus and

Water

K„ Partition coefficient (K), (usually of a pesticide) between Mucus

produced by a known mass of Snails and Water

Kgc Partition coefficient (K), (usually of a pesticide) onto Organic Carbon

from water

Kon, Partition coefficient (K), (usually of a pesticide) onto Organic Matter

from water.

Partition coefficient (K), (usually of a pesticide) between Octanol and

Water

Kj, Partition coefficient (K), (usually of a pesticide) between Silk and

Water

LC Lethal Concentration

POM Particulate Organic Matter

SEM Scanning Electron Microscope

STM Snail Trail Mucus

TEP Transparent Exopolymer Particles 16

Chapter 1. General Introduction

I . I Introduction

The aim of this project is to investigate the role of mucus and silk in retaining particles and dissolved organic matter over the substratum of streams. An additional aim is to try and determine the consequences of such retention. Streams, by their very nature, involve flowing water, which acts as a vehicle for the transport of particulate and dissolved matter. As water flows it will mobilise particulate material, causing erosion in certain areas of the benthic environment (stony, fast flowing areas), and deposition of erosional and other materials (sediments and fine organic materials), where circumstances allow. Such displacement of material is part of the fundamental nature of flowing water. This process is responsible for the movement of particulate and dissolved organic matter o f various sources, and is described, in part, in the "River

Continuum Concept", (Vannote et al., 1980). In addition to natural materials of organic origin, "un-natural" materials such as pollutants from construction, road run­ off, as well as agricultural and domestic pesticides are also carried by river water. In the same way that natural materials such as sediments, allochthonous riparian organic material, invertebrate faecal matter, exuviae etc. are moved downstream and deposited, so too are pollutant materials.

Particulate and dissolved materials are subject to entrapment by potential sites of attachment. These binding sites may consist o f organic materials such as biofilm

(Armstrong and Barlocher, 1989), algal exudates, associated polysaccharide (DeFlaun and Mayer, 1983), and macrophyte exudates (Bronmark, 1985), as well as inorganic materials such as charged clay minerals. Alternatively, particles and dissolved materials may be consolidated by filter feeding macroinvertebrates, via the production of faecal pellets (Wotton, 1976; Dudgeon, 1990; Wotton, 1990; Wotton et al., 1996b).

In addition, sites of attachment are also offered by macroinvertebrate excretions such as snail trails (Connor and Quinn, 1984) and blackfly larval silk (Kiel, 1997; Kiel et al., 1998). It is this mucus and silk, their potential as binding sites, their retention of particulate and dissolved matter, and the processes that occur following binding, that 17 forms the basis of this study.

1.2 The "re-cycling" of sites of attachment

What is particularly interesting about binding sites in aquatic environments is that they are self perpetuating, via a complicated and variable cycle. This cycle may be illustrated by considering bacterial cells. Individual bacteria, as free floating

(planktonic) organisms may be considered to be particles, in that they are subject to current flow, are utilised by filte r feeders and are o f the appropriate size range (0.45

|im - 1 mm). Planktonic bacterial cells also offer sites of attachment to smaller particles or dissolved organic matter (DOM) on their cell surfaces, either through the inclusion of polysaccharide in the cell wall (Gorshkova et al., 1992), or via the secretion of extracellular polysaccharides (EPS), (Hood and Zottola, 1995). Acting as particles, on which other particles have attached, bacteria stick to sites o f attachment such as sediments (Allison and Sutherland 1987), macrophytes (Costerton et ai, 1987), algae (Heissenberger et ai, 1996) as well as, snail trail mucus (STM), (Calow, 1979), blackfly silk (Kiel et al., 1998) and other bacteria (Cowen, 1992). Landing on such sites, there may be the potential for biofilm development, which again offers further sites of attachment (White, 1995).

Biofilm is grazed by a number o f organisms (Bronmark, 1985), which produce faecal pellets, bound by polysaccharide (observations within this study for freshwater snails).

Faecal pellets themselves also offer sites of attachment due to the adhesive nature of their binding material (M attingly, 1988), and their variable density and aggregation

(Wotton, 1990). Faecal pellets are carried by flow ing waters and deposit onto sediments (Ladle and G riffiths, 1980; Ladle et al., 1987; Wotton 1990). Sediments themselves are sites of attachment of materials such as STM (as snails move across benthic sediments), blackfly silk (Wotton et al., 1996) and bacterial cells (Allison and

Sutherland, 1987). Benthic sediments are also worked materials, often coated in organic matter due to the action of oligochaetes (Reynoldson et al., 1991), chironomid tubes (Berg, 1995), as well as settled, planktonic polysaccharide (Crocker and Passow,

1995). 18

This continuous cycle of attachment, removal, carriage and reattachment, or incorporation and re-attachment provides a variety of routes for dissolved nutrients and pollutant DOM such as pesticides to enter the food chain. It may also mean that they continue to linger within the freshwater system, long after they have been assumed to have been flushed away. In the same way, particulate organic material, elements, nutrients etc may spiral through the freshwater ecosystem via a number of different organisms and trophic levels (Allan, 1995). The opportunity for attachment of particles is offered repeatedly within streams. The same material re-used and recycled offering new sites of attachment in the ever continuing accrual and release, or spiralling of particles within freshwater systems (Cushing et al., 1993).

1.3 Organisms chosen for use in this study

In planning for this study, various freshwater macroinvertebrates were initially selected, (including leeches, flatworms, chironomids and tubificids), as well as

vertebrates such as fish and eels. The criteria for selection was the production of

mucus or silk in a utilisable form, ie free of DOM or POM.

Leeches, fish and eels produce mucus in considerable quantities when stressed.

Unfortunately, the gathering of mucus from such sources required the capture and

potential stressing o f organisms, and was deemed unacceptable to this study. In

addition, the mucus released from these organisms tends to be released sporadically,

directly into the water column, rather than onto benthic sediments where it would have

a greater chance of offering itself as a site for retention of particles. Flatworms and

snails are preferable in that they lay their mucus trails directly onto benthic substrata,

while tubificids offer the greater advantage of actually working their mucus directly

into benthic sediments. However, both flatworms and tubificids were either difficu lt

to obtain locally and/or presented greater difficulties in terms of husbandry than either

snails or blackfly larvae. Chironomids also offer a great advantage in that they

produce silk directly on to particles, serving to bind items such as perspex beads.

However, numbers that were locally available, and the practicalities of achieving fresh

silk, free of particulate matter, made them less suitable. Snails and blackflies were 19 therefore selected for being locally abundant, low maintenance organisms that would produce relatively copious quantities of mucus and silk in relatively particle free

(artificial) environments. In addition, freshwater snails are recognised as key species, due to the range of work performed using them as bioindicators (Elder and Collins,

1991).

The use of the two species o f snails selected, and the random utilisation of (possibly) different species of blackfly egg masses, were not without problems. (The following species are found within the stretch o f the River Frome that was sampled: Simulium omatum (Meigen); S. equinum (Linnaeus); S. lineatum (Meigen); and to a far lesser extent, S. erythrocephalum (De Geer); J. Bass, pers. comm.). W hile Lymnaea peregra

(Müller) is available all year round, maintained in an outdoor water tank filled with mains and rain water, Potamopyrgus jenkinsi (Smith) were found to be only seasonally available in the local area. This presented a number of difficulties in terms of experimental design, and in some cases prevented the execution of comparative experiments. For example. Section 3.3.9 relies on the examination of L. peregra mucus alone rather than both species together, because the local population o f P. jenkinsi crashed in autumn 1996. This crash is an example o f patch dynamics as related to life cycles, described by Pringle et al., (1988).

There were also problems associated with the collection and maintenance o f animal populations once a supply had been identified. Larval blackflies are difficult organisms to keep in the laboratory due to their reliance on the flow of natural waters, without which they will suffer both oxygen and nutrient deprivation. A compromise was found by utilising the silk threads o f first instars as they hatch, and having to incubate egg masses only (as described in Chapter Four). Blackfly egg masses were collected from trailing vegetation along the banks of the River Frome in East Stoke,

Dorset (Nat. Grid Ref: SY 867 868). P. jenkinsi were collected, as required, from the

Wool Stream, a fast flow ing shallow stream that acts as a drainage stream to a watercress bed (Nat. Grid Ref: SY 869 846). Animals were subsequently stored in the fridge at 10°C and fed on lettuce for no more than 5 days, before being returned to the

Wool Stream. Attempts were made to introduce P. jenkinsi to the experimental 20 channels at East Stoke (Nat. Grid Ref: SY 867 868), but this failed to realise the densities required for experimentation, or those achieved at the Wool Stream.

Attempts were also made to farm blackfly larvae within an experimental channel at

East Stoke, using a series o f wooden dam boards to create an almost horizontal surface, over which a thin film of fast water flowed. W hile this was successful in attracting ovipositing females, and egg masses did hatch, the silk that was produced was instantly coated with organic material, rendering it effectively useless for particle attachment experiments.

1.4 Review of materials used: silk and STM

Freshwater STM and blackfly larval silk are understudied substances. It is known that silk is a fibrous protein of unknown water content. Arthropod silks and the silks of other freshwater organisms, such as chironomids, have been described as repeated structures of amino acids (Case and Smith, 1994), which are specific to the producer species (Case et al., 1994). Invertebrate silks are similar in composition to synthetic polypeptides (Rudall and Kenchington, 1971). Freshwater invertebrate silk has also been described as a dynamic composite biopolymer, spun from aqueous solutions, yet not soluble in water (Viney, 1993). It is composed of repeated secretory protein sequences (Case and Wieslander, 1992). In examining the effect of larval blackfly settlement upon further substrate colonisers, Kiel et ai, (1998) noted that silk is a)

"sticky", b) being "sticky", it may initiate biofilm development and, c) remains chemically un-characterised.

As with silk, there has yet to be a definitive characterisation of the components of snail mucus. It is understood that molluscan pedal mucus varies considerably in terms of water content, from 90.1 to 99.7%, (Denny 1983). Mucus is a highly hydrated complex of inorganic salts, protein and polysaccharide. Mucopolysaccharides (which include STM) are heteropolysaccharides of two alternating monosaccharide units. Of the two units, at least one is usually a negatively charged acidic group, either a carboxyl or a sulphuric functional group (Livingstone and De Zwaan, 1983).

Mucopolysaccharides are essentially a long, linear chain, of high weight, carbohydrates 21

(Denny 1983). The properties of a mucus rely solely on the chemical functions of the polysaccharide component. The protein content and type are of little consequence

(Denny 1983). It is understood that the contents of mucus varies between species.

However, to give a broad idea of the content of STM, some examples can be given from the very few analyses that do exist. The pedal mucus o f the marine limpet.

Patella vulgata contains 29% (of the dry weight) sulphated mucopolysaccharides which are linked by electrovalent bonds to the 33% protein content (Grennon and Walker,

1980). The mucus o f Buccinum undatum (a marine whelk) by way of contrast contains glycoprotein (including 8% neutral sugars such as mannose, glucose etc) and an acidic polysaccharide which includes 4.5% amino sugars such as glucosamine and galactosamine (Hunt, 1970). O f those few studies that examine mucus content of

Gastropoda, even fewer examine STM (Livingstone and De Zwaan, 1983).

The role that mucus plays within the freshwater biome is both considerable and complex. Mucus is an energetically costly material, accounting for up to 80% of all gastropod consumed energy (Peduzzi and Herndl, 1991), yet has received comparatively little attention in studies of community energy flow. Mucus is produced by a range o f freshwater invertebrates for a number o f reasons. Primarily produced as an aid to locomotion, it is also of use in preventing desiccation (Peck et al., 1993), a basis for biofilm development by enhancing microbial growth (Decho,

1990), and a food trap (Connor and Quinn, 1984). Mucus also facilitates aggregation of substratum (Davies et al, 1992a) by acting as a cohesive substance within sediment. Lasting effects of mucus within a particular environment w ill depend both on physical factors and the producer species of the mucus (Davies, 1993). Factors such as water flow and DO M concentration w ill affect the longevity of mucus trails as will the community of micro organisms that mucus trails w ill eventually support

(Decho, 1990). Both Otten and Willemse, (1988) and Lock (1993), describe how fresh mucus trails present an excellent site for bacterial colonisation. However, there have yet to be any studies examining such processes. Furthermore, beyond the producer species uses of mucus and subsequent colonisation by bacteria, its ultimate fate remains unknown. As a primary layer of biofilm growth, it is rapidly colonised and entrapped beneath bacterial polysaccharide secretions and the DOM , metal ions and 22 micro organic compounds that biofilm adsorbs (Decho, 1990). Fisher et ai, (1991) described how mucus actively scavenges metal ions in a marine environment. Mucus therefore plays an essential role in the entrapment and spiralling processes of nutrients and micro-organics described by Allan (1995) and Vannote et al., (1980). Yet, little previous work exists on the characterisation of the biological rather than physical role, of invertebrate mucus.

There is considerably more information on invertebrate mucus than there is on invertebrate silk. However, most of that information relates to the longevity of mucus trails (Davies et al, 1992b), energy budgets (Coffroth, 1984; Connor and Quinn, 1984;

Davies et ai, 1990 a and b; Decho, 1990; Davies, 1991 ; Davies et al., 1992 a, b and c; Davies, 1993; Peck et al., 1993; Davies and W illiams, 1995; Nozais et al., 1997), and mucus production as affected by heavy metal pollution (Davies, 1992). There is also a body of information relating to the source and uses of gastropod mucus by gastropods, (Lissman, 1945; Denny, 1980; Denny, 1989). The wider role of snail mucus trails (apart from its uses to Gastropoda) is less well examined, if at all.

Lastly, there is a large volume of literature exploring some of the more unusual uses of mucus, such as a vehicle for an enzyme or toxin etc. For example, the use of mucus to immobilise prey by copepods (Klein and Koomen, 1994). Such a variety of evidence gives an indication of the range o f potential roles that mucus plays within the aquatic environment. It also indicates that such a versatile material should be studied for aspects other than those that relate directly to the producer organism.

1.5 Characterisation of STM

A wide body of literature exists cataloguing the constituent parts of mucus from virtually all known sources. Most such literature is concerned with the medical significance of mammalian mucus or the commercial applications of the physical properties of bacterial mucus (Miles and M orris 1989; Tandavanitj et ai, 1989; 1990;

1992, etc). Although there have been attempts to correlate the properties of other mucus types with their potential uses (Silverberg 1989; Sutherland 1989; Vacelet and

Thomassin, 1991), there is little literature dealing with the mucus of Gastropoda, and 23 in particular freshwater snails. Davies et al., (1990b), who have performed much pioneering work on limpet pedal mucus, noted that mucus was almost always overlooked in the calculation of energy budgets. Yet when included in the energy budgets o f limpets and winkles, accounted for some 23% of all energy consumed.

This figure was later revised to 68% by Davies et al., (1992a), and has also been stated to be 80% by Peduzzi and Herndl (1991), who examined intertidal mud snails.

The characterisation of mucopolysaccharides of vertebrates is widely covered in the literature (Ehrlich et at., 1981), however, attempts to produce reviews of invertebrate mucopolysaccharides (marine invertebrates, Ehrlich et al., 1981; mammalian parasites,

Singh 1993; and, marine gastropods, Grenon and Walker, 1980), still overlook freshwater macro-in vertebrates.

1.6 Mucus and silk as sites of attachment to DOM

There is an extensive literature on the uptake of pollutants by macroinvertebrates (Cain and Luoma, 1990; Elder and Collins, 1991; Hare et al., 1991; Davies, 1992; Hare, ek O.L., 1992; Galassi^, 1994; Dorgelo et al., 1995 etc), but most, if not all, focus on the uptake of pollutants such as heavy metals or pesticides by whole organisms. Such studies are extremely important, because of bioaccumulation processes. However, less attention has been paid to the means of uptake o f pollutants and the process by which pollutants enter the individual organism in the first place. STM and blackfly silk are of particular interest because, in addition to their primary functions, which benefit the

snails and larval blackflies respectively, they are also a food source to other organisms

(Calow, 1979; Kiel, 1997). In addition, they are also potential sites o f biofilm

development, which are a food source to a wide variety of freshwater organisms

(Barlocher and Murdoch 1989) and can therefore play a role in introducing pollutants

into the foodchain.

Pesticides are ubiquitous, deleterious synthetic compounds. Largely manufactured for

agricultural, horticultural and domestic purposes to protect against pests, they

contaminate ecological systems beyond the sphere of intention (Standley and Sweeney

1995). The contamination of the environment by pesticides is a subject that has 24 caused concern for decades (Meyer and Thurman 1996). Because all compounds are soluble in water to a certain extent, pesticide residues are transported into water bodies via rain water, either as direct land run-off, or via percolation through soil into aquifers (Miltner et al., 1989). Less soluble compounds {ie the more lipophilic compounds) are transported by adsorption to particles (Deschauer and Kogel-Knabner

1992). The presence of pesticides in water bodies has led to the development of a considerable research industry which monitors pesticide levels in whole organisms, aquatic plants, algae, biofilm communities and benthic sediments (Thurman and

Meyer, 1996; Verbrugge et al., 1991; Ebise et al., 1993; Domagalski and Kuivila,

1993; Corwin and Farmer 1984; Rao and Davidson, 1980 etc). This results in a

large amount of research published every year, expanding our knowledge of the occurrence of pesticides in water, soils and biota, examining the fate and breakdown products of pesticides, and looking at the possible means of sorption and desorption onto various materials (Kurtz, 1990; Petit et al., 1995; Vettorazzi, 1995; Flury, 1996).

Very little work exists in bridging these three general fields. Whilst we know how

biota may transform the structure of individual xenobiotics via metabolic processes,

little is known about the pathways by which pesticides enter biota. Little is known

about pesticide affinities for materials other than soils or sediments. Equally, it is

unknown which fraction of sediments exhibit the greatest affinity for a particular class

of pesticides. There is little information available on the effects of interactive surface

chemistry between pesticides and potential sorbents. More research is needed to

explore the areas between established information resources. Appropriate research is

needed to investigate pesticide interactions within different environments, with

emphasis on biotic (rather than abiotic) systems. Such research has the potential (in

combination) to allow successful use of the published literature in predicting, and

minimising, pesticide contamination (Hornsby et at., 1996).

A common material for the examination of pesticides is soil / sediment, or rather the

organic component of sediments. However, organic coatings (pedal mucus secretions,

silk, humic and fulvic deposits, colloidal aggregations etc) and attached materials have

not previously been studied in any detail, if at all. In addition, the role of

macroinvertebrates in the transport of pesticides (rather than the accumulation of 25 pesticides) has been overlooked. The feeding processes of benthic invertebrates play a role in the downstream transport of particle-bound hydrophobic organic compounds

(Sallenave et al, 1994). Combined with the fact that periphyton (a food source for many classes of macroinvertebrates) has a tendency to accumulate contaminants by provision of a sorptive surface (Lau, 1990) leads one to the realisation that macroinvertebrates can play a considerable role in the transport and fate of pesticides.

1.7 Mucus as a potential agent of sediment consolidation

Polysaccharide offers potential in terms of consolidation of DOM and POM, while macroinvertebrates are generally considered to be agents of bioturbation (Blauchard et al, 1997). Suspended solid concentrations in rivers are important indicators of water quality, while suspended organic loads have a major impact on energy budgets

(Farr and Clarke, 1984, and references therein; Pozo et al., 1997). Fine natural sediments, without consolidation of some kind, in association with poor management practices, can have deleterious effects on aquatic biota. Organic material coating river sediments lends stability in resisting current erosion, or by consolidating sediment

(Wood and Armitage, 1997). Particle aggregation, and hence eventual settlement, can be engineered in a number of different ways, depending on circumstances and environment. For example, humic fractions are likely to adsorb dissolved organic matter (DOM) due to their surface charges. DO M is capable o f providing sustenance for microbial growth (Leppard, 1997). Assimilated DOM which is subsequently exuded by surface-bound, or free-living bacteria, serves to increase inter-particle binding. Plentiful DOM allows bacteria to produce substantial quantities of exudates which in turn allow the development of more stable aggregates. The combination of stability and increasing size of aggregates increases the rate o f particle collision

(Johnson et al, 1990). Particle collision leads to aggregation, resulting in settlement which can result in blanket coating of sediments and eventually, interstitial binding of materials (Decho, 1990). Humic fractions and DOM are however just one of many means by which sediments may be consolidated. 26

1.8 Sediment consolidation in aquatic environments

Mucus is involved in the consolidation o f sediments at many levels and from many sources. For example, the burrows of the Red Sea shrimp Callichirus laurae are coated by a layer of mucopolysaccharide l-2mm thick which binds selectively-sorted fine sediments, organic matter, humic and fulvic acids (de V a lia s and Buscail, 1990).

On a smaller scale, Decho and Lopez (1993) did much to categorise exo­ polysaccharides in their review of microbial extracelluar polymer secretions (EPS).

O f particular interest was their observation that exopolymers often coat the surfaces of sediment particles, and in so doing more than double the bioavailability of DOM to particle feeders. EPS is highly likely to sequester DOM, which otherwise would be unavailable to most consumers. Biofilm slime coatings in particular contribute toward DOM packaging and availability. They further went on to describe the various forms of mucus that a single bacterial cell can produce with variations in integrity

(digestibility) depending on environment and food availability. EPS is thought to be a way o f excreting excess carbon (assimilated in bulk compared to nitrogen assimilation) as slime is low in protein and therefore low in production costs.

W hilst my study is of freshwater processes, it is important to describe relevant advances in other comparable environments. The increasingly large volume of recent papers on transparent exopolymer particles (TEP) has brought attention to a recently discovered class of ocean-based organic particles (Alldredge et al., 1993, Passow and

Alldredge, 1994, 1995). TEP are gel-like particles that form the matrix of marine snow (Alldredge and Jackson, 1995), which is a polysaccharide based aggregate of microorganisms and attached particles first defined by Suzuki and Kato (1953). The appearance of such material is largely due to algal blooms. Alldredge and Passow

(with co-workers) have defined the study of this material, examining its sticky nature and ability to sequester particles from the water column (Jackson, 1995), as well as its propensity to appear in large quantities. Most pertinent was the study by Logan et al., (1995) which noted the rapid formation and sedimentation of aggregates based on TEP. They concluded that TEP controlled, and drove, the cycle of mucus aggregate bloom and sedimentation rather than phytoplanktonic producers of TEP. 27

While TEP is hardly comparable to macroinvertebrate polysaccharide secretions in terms of quantities available and physical behaviour, it is essentially the same material

(Chin et ciL, 1998), and therefore capable of performing the same functions to a certain degree. Interestingly, TEP has also been noted in fresh waters, albeit lakes (Logan et al., 1994) and in estuarine conditions (Syvitski et al., 1995). The study o f TEP is a relatively new phenomena, such that to date, the effect o f settled TEP aggregates upon sediment consolidation has yet to be examined.

The observation o f benthic mucilaginous aggregates in the Mediterranean Sea by

Olianas et ai, (1996) was viewed primarily as an opportunity to produce structural models of aggregates. Most of this material was produced by diatoms found within a matrix of acidic glycoprotein. The authors were mainly concerned with the ability of such material to filter sea water by physical and chemical (ligand binding) means.

Despite recognising the potential for physical entrapment, no mention was made of n sediment biding potential, or the fate of such aggregates. Yet, in looking at bioturbation o f deep sea Pacific sediments. Meadows and Meadows (1994) speculate that the mucus binding o f particulates and faecal pelletisation are important in lending stability to marine sediments.

1.9 Consolidating properties of polysaccharide

Mucopolysaccharide is one o f the most obvious materials responsible for the phenomenon of sediment stability as it is produced in slightly different forms by a range of Mollusca, crustaceans and, more importantly, by many different bacteria. In attempting to monitor such a physical process, various papers have looked at different aspects of sediment stability, mainly concentrating on bacterial exopolymer, with varying degrees of success. Lab are et al., (1989), in examining a range of periphytic, marine, bacterial polysaccharide exopolymers for use as natural adhesives, found that such secretions can be used to scavenge metal ions commercially. Dam and Drapeau

(1995) published a modelling paper on coagulation efficiency of organic matter glues.

They surmised that particle aggregation was the driving force in ending phytoplankton blooms for, as particles aggregate, particle mass increases. As the mass increases, the 28 probability of particie-particie cohesion following collision, decreases. There is a negative correlation between particle stickiness and mass which, at a critical point, dependent on current velocity, will cause the particle to sink. Working in the marine environment, Logan et al., (1995) looked at algal blooms, and attempted to model the formation and size limitations of TEP, which they viewed as "raw glue". The similarities between TEP and river polysaccharide floes from other sources, had yet to be made. W orking on similar material, Dade et al., (1990) demonstrated the cohesive properties of mucus by examining the erosion of plugs of sand that had been fashioned using extracted bacterial mucopolysaccharide. In measuring the critical shear velocity of the sand plugs, they found that it was proportional to the nitrogen content of the bacterial growth media and linearly related to total amount of polysaccharide used.

1.10 Examination of estuarine consolidation

Underwood and Patterson (1993) performed a series of experiments in an effort to determine the degree of biostabilization lent to estuarine sediments by diatom mucopolysaccharide. Using a biocide to remove diatoms they measured sediment shear and noted a dry cracked appearance to the sediment, with no evidence of bioturbation. They also noted that shear strength can increase in the absence of animals as compaction increases due to reduced bioturbation. They almost overlooked the link between diatom presence and sediment stability except in their use of low- temperature-SEM (freeze drying in liquid N j renders desiccation unnecessary) to examine sediment structure. In looking at the effect of diatom secretions, Gerdol and

Hughes (1994) noted that salt marsh sediments were capable o f withstanding far greater shear stress when Corophium volutator (a facultative deposit feeder of, among other items, diatoms and bacteria) was removed. Using a cone penetrometer to measure core stability, their assumption was that by removing C. volutator, greater numbers of microflora would produce a greater net amount of mucopolysaccharide, serving to increase sediment stability. More recently, Blauchard et ai, (1997) have demonstrated the kinetics of tidal re-suspension and microbiota. They found that 29 bioturbation of the top few sediment layers of tidal mud flats enhanced the planktonic biomass of microbiota, (the resuspension o f microbial cells from sediment is taken as an indication of sediment erosion). Interestingly, in using a mud flat snail {Hydrobia ulvae) as an agent o f bioturbation in a channel subject to an erosive current, they noted that mucus trail material, with associated sediment and microbial cells was more likely to be eroded, than undisturbed sediment. This suggests that snail trails w ill consolidate sediment and cells to a certain degree, and that if left un-eroded, could function as a temporary, stabilising, intermediary layer.

1.11 STM as a site of biofilm development.

B iofilm communities develop on any wetted surface (as reviewed in many papers eg.

Lock et al. 1984; Lamberti and Resh, 1985; Golladay and Sinsabaugh, 1991 ; Couch and Meyer, 1992; Wetzel et al., 1997). In rivers and streams, biofilm refers to a community that may include algae, bacteria, cyanobacteria and fungi bound within a complex structure of bacterial extracellular polysaccharide, known as the glycocalyx

(Lock et at., 1984). Such a complex structure binds biotic and abiotic material, retains extracellular enzymes and other cellular products and enables development of a

"multistorey" autotrophic assemblage o f structural heterogeneity (Costerton et al.,

1987; Lawrence et al., 1994). The extracellular polysaccharide matrix that forms the bulk of biofilm structure also affords protection to the constituent cells. Biofilm communities are very efficient at retention and degradation of harmful compounds

(Costerton, 1992). In addition, removal of biofilm from the substratum is extremely difficult without physical disturbance. For example, chemicals designed to restrict biofilm development are o f limited use due, in part, to the largely impenetrable mucus glycocalyx coating the biofilm community. Biofilm s have also been shown to capture and utilise colloidal fibrils (by precipitation and assimilation of colloids), suggesting that they are also therefore capable o f the selective adsorption of materials and compounds from the water column (Leppard, 1997).

The structure of biofilm communities has been shown (using non-destructive confocal scanning laser microscopy) to be a series of cellular aggregates suspended in 30 polysaccharide matrices (Lawrence et ai, 1994). Separating such microcolonies are channels that connect the bulk liquid {ie the river water) to the colonised surface, which allow penetration o f large molecules and act as a circulatory system (Costerton et al, 1994; Bishop et al., 1995). B iofilm communities can therefore degrade harmful compounds via a combination of the circulatory system that allows controlled release of degradative enzymes and the protection afforded by extracellular polysaccharide

(White, 1995). Decho and Lopez (1993) noted that extracellular polysaccharide secretions (EPS) not only vary widely between species, but also that an individual cell can vary the type o f EPS it produces. EPS produced by a single cell can vary in terms of density, structural cohesion and hence digestibility to bacterivores according to environmental factors. They also noted that EPS is likely to sequester DO M that is otherwise unavailable to most organisms. In this way, EPS surrounding bacterial cells may gather nutrients either from within the biofilm community, or as planktonic cells. Biofilm s are also known to selectively adsorb certain amino acids, a process which is facilitated by the structure of biofilm communities (Armstrong and Barlocher

1989). Biofilm communities are also involved in nitrogen spiralling via the degradation of cellulose (Fieburg and Lock, 1991; Biddanda and Rieman, 1992).

Utilisation of organic matter within biofilms was further explained by Decho and

Moriarty (1990) who found more than 80% selection by copepods for beads coated with C''*-labelled EPS from sediment. B iofilm on sediments has also been found to be enhanced as a potential food source for interstitial (sediment-dwelling) organisms through its removal o f dissolved substances from the water column and subsequent conversion of these into particles (Barlocher and Murdoch, 1989). In their feeding strategies, deposit feeders also respond to the presence of organic film (biofilm or

EPS) rather than the amount of microbial food present, suggesting sensory detection of biofilm as a food source (Lopez and Levington, 1978; DePlaun and Mayer 1983).

In examining the consumption of dissolved contaminants by biofilm, Lau ( 1990) found that the deeper the biofilm , the greater the sorption of xenobiotics. He reasoned that, by increasing the thickness o f a biofilm layer, the flow of the boundary layer o f the bulk liquid is slowed, such that resistance to diffusion into the biofilm is decreased.

WinterboLirne (1986), in reviewing bacterial and fungal slimes of the benthic layer of 31 streams, noted that metal ions, particles and DOM were all trapped and processed.

Xenobiotic compounds may also be included with such materials (White, 1995).

Such information suggests two important ideas. Where xenobiotics are involved, biofilm w ill sorb such material and either transform it, or store it. Grazers actively select biofilm and EPS-coated cells as a food source, and in so doing w ill ingest sorbed xenobiotics. B iofilm is therefore yet another means by which xenobiotic compounds enter the food chain. Benthic biofilms therefore play an important role in nutrient cycling, packaging of DOM, metal ion and micro-organic sequestering, sediment binding, and in suspended particle binding and relocation (Decho, 1990).

1.12 Formation of biofilm

Whilst a considerable body of evidence has been gathered regarding the role, structure and manipulation of biofilm communities, greater attention is turning toward bacterial succession in the development of a biofilm community (Korte and Blinn, 1983; Paerl,

1985). It is known that the EPS coatings surrounding bacterial cells vary depending on the cell type and the condition of the cell. EPS is made up of polysaccharide and is therefore likely to be "adhesive". However, not all cells in biofilm communities are capable of producing EPS, and not all do so at all times. The settling of floe material, planktonic cells surrounded by secreted polysaccharide may in certain circumstances explain the initial genesis o f a fresh biofilm . However, only certain cells at specific times within specific conditions will produce EPS of sufficient quantity, or quality, to allow floe formation w ith other unattached cells, or to adhere themselves on to a surface (Decho, 1990).

It is therefore reasonable to assume that certain cells capable of producing sufficient polysaccharide material are required as "primary colonisers" on to a biofilm-free surface. A clean surface may be considered to be a freshly-produced material such as a strand of silk, a fresh snail trail or a recently upturned stone. Primary colonising cells attach to such surfaces using extracellular polymers, and in so doing, condition a surface, enhancing the attachment of other cells (Hood and Zottola, 1995). Korte 32 and Blinn (1983), in examining bacterial succession on to various materials placed in a river, noted that certain diatoms such as Achnanthes and Cocconeis produce a great deal o f mucilage that acts as an anchor, promoting further colonisation. It has also been observed that "polysaccharide fibres in the organic matrix, which are generally negatively charged, trap organic and mineral molecules circulating in the vicinity of the biofilm " (Carpentier and Cerf, 1993). This suggests that free-floating planktonic cells that impact upon biofilm can also be captured, and added to the assemblage.

1.13 Note on sorption.

The verb "sorb" rather than adsorb or absorb is regularly used when describing the attachment or processing of xenobiotic compounds to mucus, silk or biofilm. As yet, we do not know whether such compounds are either adsorbed, absorbed, or subject to a combination of the two processes.

1.14 The progression of study within this thesis

Essentially, mucus, silk and particles are known as "sticky" materials, and are et out. occasionally described as such (Ogren, 1995, Kiel, 1998). The word sticky is not A. particularly descriptive, yet that word best describes the nature o f the interactions between these three materials and others found in the water column. Having identified materials and processes o f interest, the initial aim o f this study is to characterise STM.

Accordingly, Chapter Two is an attempt to identify a suitable means of recording the presence / absence of STM, using marker particles. Having identified an appropriate marker particle, and developed a suitable methodology for the examination of STM, various treatments are employed in Chapter Three in order to determine many facets of the behaviour or responses o f STM to various environmental factors. Chapters Two and Three are based on the study of retention of particles or particulate matter by

STM. Chapter Four moves on to the study of the retention o f dissolved matter to

STM and silk, notably, a suite of 10 different pesticides. Broadening the study somewhat. Chapter Five is an attempt to examine the retention of particulate matter to STM on a far grander scale, by looking at the stability (if any) conferred to 33 sediments by STM. Lastly, Chapter Six looks at the retention of bacteria by STM and the potential that this offers in terms of the development of biofilm . This last chapter brings the study full circle. Having established that organic material of invertebrate origin is a site of attachment for particles and dissolved matter, this chapter establishes the potential offered by such materials to provide the basis of yet further sites of attachment. 34

Chapter 2 Selection of a marker particle suitable for the observation of

snail trail mucus

2.1 Introduction.

Freshwater snail trail mucus (STM) is a little studied substance that exists in considerable quantities in aquatic systems (STM is produced continually during locomotion, and snails are known to exist in high densities, as detailed in Chapter 4).

This chapter records the processes employed in the selection of a marker particle, appropriate to the observation of freshwater STM (L. peregrd). Markers are employed to monitor the decay, or removal, o f STM, in response to various experimental treatments, described in Chapter Three. Without the use of marker particles, STM would remain a material that is effectively inaccessible to study, due to its structure, size and the habitat of freshwater snails. W hile marker particles have been used to mark marine gastropod pedal mucus, they have not been used for freshwater snails.

A range of particle types was investigated to select the one most suitable for the experiments described in Chapter Three.

2.1.1 Previous uses of marker particles in freshwater biology.

Marker particles allow the tracking o f organisms and materials (such as sediments, suspended particles, faecal pellets etc). They are usually quick and easy to apply, and allow investigation of systems and processes that would otherwise be d ifficu lt to monitor. Fluorescent marker particles (e.g. Radiant Color® particles) have been used with a wide variety of aquatic organisms, such as fish and invertebrates, generally to measure feeding rate, particle (size/type) selection, or the fate of particles. These are brightly coloured microparticles of 2-4 |i.m length that fluoresce strongly under UV light. Their advantage is that they are small enough to be subject to water currents and are within the size range selected by many lotie suspension feeders. Lopez and

Elmgren (1989) used Radiant Color® particles to mark the pellets of deposit-feeding amphipods, while Miller et al. (in press) examined collector/gatherer behaviour in larval black flies, noting the colour preferences exhibited by feeding larvae, and also 35 examined fine particulate organic matter (FPOM) retention in pellets. Radiant Color® particles were also used by M ille r et al., (1995) to evaluate filter feeding by simuliids, measuring fluorescent particles using UV light, as well as looking at the size of particles ingested by means of a Coulter counter. Spiralling of particles has also been investigated using Radiant Color® particles in a series of experiments based on the examination o f the guts of suspension feeders in lake outlets, (Wotton et al., 1995).

Marker particles have also been used to tag whole organisms. Strange and Kennedy

(1982; 1984) used fluorescent particles as markers o f brown trout, Atlantic salmon and cyprin ids, as did Eric et at., (1982) and Andrews (1972) working with brook sticklebacks. A fluorescent pigment was applied by means of a high pressure spray gun to mark each whole fish, held captive in a net. The means o f attachment of particles to the fish was not described, other than to suggest that particles became embedded in the dermis layer (Strange and Kennedy, 1984).

Biotic, and abiotic, processes can also be illustrated by means o f easily-tracked particles. Lindgarth et al., (1991) used Radiant Color® fluorescent microparticles to visualise sedimentation, larval settlement and mucus-based entrapment of food particles. Decho and Lopez (1993) used Radiant Color® particles as inert tracers to monitor DOM uptake by particle-ingesting animals following coagulation on bacterial exopolymer. Of particular relevance to this study is the work of Davies and Williams

(1995) and Davies et ai, (1992 a, b and c). They used activated charcoal in suspension, to adhere to and monitor, the longevity of limpet and winkle mucus on plexiglass plates, affixed to the rocky inter-tidal zone. The method developed in my study was based on that described in Davies et al., (1992b). Davies' study also provided an indication of the sort o f decay curve expected of gastropod mucus when using marker particles.

2.1.2 Particle types available

A total of twenty different types of particles were chosen for examination, (listed in

Table 2.1). A number of those were selected because of their proven efficacy as 36 marker particles in other studies (Radiant Color^, activated charcoal, etc). Others were chosen for being easily available and inexpensive to prepare (soot, etc), for chemical stability, and for being of the appropriate size range (e.g. similar to particles previously described in the literature, or known from other studies at < 250 |im, e.g. kaolinite, aragonite, etc). In addition to such known particles, and those that were chemically and physically suitable, a further consideration was that the chosen particle would be a non-synthetic material, representative of material already present in streams. Such a material has the advantage of posing no health risks to the operator and presents minimal pollution effects when used in the field. For these reasons a series of size fractions of dried sediment were prepared. An example of the use of marker particles to highlight an otherwise "invisible" material, which also demonstrates the ability of fresh snail trails to retain particles, is illustrated in Plate 2.1. This was prepared by allowing a number of L. peregra to crawl across a piece of glass immersed in shallow mains water. Once the snails had been removed, sediment that had been dried and sieved was sprinkled onto the surface of the water and the glass sheet agitated within the water. The glass was then removed from the sediment / water suspension, gently rinsed, allowed to dry and photocopied.

1 » ;

Plate 2.1 Snail trails (L. peregra), highlighted using dried sediment,

sprinkled onto glass on which snails have been allowed to crawl. 37

2.1.3 Experimental objective

The objective of this experiment, of twenty separate trials, was to determine which particle preparation would be the most suitable for the study o f STM on glass. The most appropriate particle w ill be chosen for ease of focus, and high reproducibility of counts based on replicate slides. In addition, particles must not be susceptible to disturbance by single-celled animals moving on, or within, the mucus layer. For these reasons the chosen particle should be small and of little resistance to the flow o f the water current, such that marker particles do not increase resistance beyond the boundary layer within which STM is laid, described by Hynes (1970). Importantly, the particle should stick to mucus but not to glass, so that particles allow examination of STM and not the substratum. Comparison with mucus-free control slides allows distinction between particles that are attracted equally to a clean glass surface or to a mucus trail. Particles should also be consistent in their shape, size, and position on the slide in order to provide accurate, meaningful data. Particles that fragment, dissolve, or are structurally unstable in water are of limited use. Finally, particles should highlight a measurable decay, or physical and biological conditioning of the mucus which we know to be under attack from both water flow and bacterial decomposition.

2.2 Materials and methods

2.2.1 Experimental protocol

Preliminary experiments (not included in this study) were concerned with the physical removal of STM, from a substratum, produced by Planorbis and Lymnaea spp., using activated charcoal as marker particles, (similar to the approach of Davies et ai,

1992b). These experiments allowed considerable advances in the development of the

methodology, and also offered an indication, not only of the rate o f decay of STM,

but also of the expected shape of a decay curve over time.

Five clean glass slides were placed in a plastic tray containing deionised water, so that 38 the surface of the slides were just under water. Deionised water was used for two reasons. Firstly, to minimise the amount of particulate matter that snails would leave in their mucus trails, and secondly, in an attempt to stress snails toward greater mucus secretion, (to ensure as total a coating of STM on the glass slide as possible). The slides had snails placed upon them, and the snails were allowed to move over the surface o f the slides for up to 30 minutes, long enough to ensure as complete a covering of the slides with mucus trails as possible. (Observations of the number of snails used, and their size and speed on a particular day, gave a good indication as to when a slide was fully coated in snail trails. An unbroken mucus coating of the slide surface allowed greater observation of the decay of mucus, as well as allowing observation of the density of marker particle attachment). The snails were then removed and the slides sprinkled with the particle preparation under examination, in dry powder form. (In the case of Radiant Color®, suspensions were used and slides were immersed in the suspensions). The tray was agitated so that the powder, if unable to break the surface tension of the water, might have access to all of the upper surface o f the mucus on the slide.

Ensuring that the slides did not dry, each slide was, in turn, rinsed by being dipped five times into a beaker of clean deionised water to remove excess unattached particles, and examined under a microscope with a mechanically adjustable stage.

Each slide was examined daily at the same 10 co-ordinates using a 1 cm^ eyepiece micrometer (ruled into 100 squares) within which area individual particles, or percentage cover by particles, was recorded. The means of recording particle presence, either by numbers o f particles or by percentage cover, was determined by the size range of particles within each preparation. Radiant Color® particles were of relatively uniform size, and so were recorded by counting each particle. Sediment preparations, for example, exhibited a considerable range of individual particle sizes within each preparation, and were accordingly recorded by means of percentage cover provided within each field of examination. The means of counting was based on presence of particle cover within each of the 100 squares o f the examination site.

Total cover within a single square represented 1%, fractions of cover within each square were summed. Immediately after examination, each slide was carefully placed 39 in (or returned to), a plexiglass re-circulating channel of unfiltered water drawn from the M ill Stream, a side channel of the River Frome, East Stoke, Dorset (Nat. Grid Ref:

SY 867 868). This was re-circulated by means of a motor-driven paddle (Plate 2.2), and set to move the water (20 cm depth) at 10 cm s ', roughly equivalent to the surface flow velocity o f the M ill Stream. Water contained 3-4 meq alkalinity units, roughly equivalent to 2 m M of dissociated calcium ions, and was maintained at room temperature. In addition, a sixth (blank control) slide, free o f snail mucus, was subjected to the same means o f particle application and examined in the same way.

Each slide was examined 6 times, once upon the application of particles, and, subsequently, once a day for the next five days. In this way, a series o f 10 readings per slide per day was achieved. In the case o f kaolinite (which coagulated and expanded on contact with water, so presenting obstruction to microscopic examination), only one reading per day for the whole slide was possible, providing an estimate of total slide cover. This was achieved by placing the slide on to squared paper, in the same way that the cover of individual examination sites was recorded.

Otherwise, readings of the ten examination sites were averaged for each slide, and the total for each of the five replicate slides plotted against time. Each series of scatter plots (one per particle type) had a linear and an exponential regression curve applied, and the coefficient of determination (r^, Sokal and Rohlf, 1981) and associated probability calculated for each (Table 2.2). Those particles that exhibited attachment to the mucus-free control slide were examined for differences between the experimental and control slides using Student's t-test (Section 2.3.3).

2.2.2 Particles used in this trial

The following range of particles were used in this experiment, each preparation representing one of the twenty trials involved. Wherever possible, information has been supplied about particle size and source. 40

'*'&’■ ■-«t;

Plate 2.2 Re-circulating water channel 41

Table 2. Particles and particle preparations chosen were:

Aluminium Oxide Analytical reagent, calcined, AnalaR grade, fine white

powder (BDH 10008 4D), 1-10 |im.

Glass Beads Spherical 100 |im glass balls.

Silt 250 - 210 |lm Dried, ground and sieved stream sediment.

Silt 210 - 125 |im Dried, ground and sieved stream sediment.

Silt 125 - 63 p,m Dried, ground and sieved stream sediment.

Silt 63 - 45 )LLm Dried, ground and sieved stream sediment.

Silt <45 p.m Dried, ground and sieved stream sediment.

Calcite Calcium carbonate (linear crystal structure), fine white

powder (AnalaR grade, BDH 471 -34-1 ), surface area of

0.22 m^g ' (as described in House, 1986).

Fine Quartz Fine white powder (British Industrial Sands Ltd,

commercial preparation of ground Fontainbleau quartz),

0.5 - 2.5 jim (as described in House and Orr, 1992).

10 Aragonite Calcium carbonate (rhombohedral crystal structure), fine

white powder, surface area 7 m^g ', from Sturge

Chemicals Ltd.

11 Activated Charcoal Decolorizing powder, activated, acid washed (BDH

33032 4E), 4-7 |im.

12 Soot Chimney scrapings, >125}im.

13 Kaolinite Fine white powder (from St. Austell, preparation

described in Bidwell et ai, 1970), >2|lm

14 Green Radiant Color® Saturated suspension in water, 0.018 g l '

15 10% of 14 0.0018 g 1'

16 1% of 14 0.00018 g I '

17 Green Radiant Color® 50% of a saturated suspension in a 10% ethanol-water

mix

Chartreuse Radiant Color® Saturated suspension in water, 0.0019 g 1'

19 10% of 18 0.0019 g f

20 1% of 18 0.00019 g I ' 42

Particle types 1-13 were stored and applied as a dry powder. Silt fractions were prepared by drying river silt at 60°C, grinding the resultant brick using a mortar and pestle and sieving to the appropriate fraction. Radiant Color® particles are small (2-4 pm) and are able to spread over large distances on the slightest o f air currents. They are also exceedingly difficult to remove from any surface with which they come into contact, an indication of a high surface charge. As such, by creating a suspension of these particles they are easier to handle, present fewer problems in terms of contamination of other surfaces as well as being quantifiable in terms of suspension density. Saturated suspensions, chosen as a quantifiable standard, were created by adding an excess (usually 0.5 g) of dry Radiant Color® particles to deionised water in a 1 litre Duran flask. An ultra-sonication probe was introduced to agitate the clumps of hydrophobic particles that had formed on contact with water. A saturated suspension was defined as the concentration of Radiant Color® particles that remained

in suspension for one minute after agitation ceased. In addition, a 10% ethanol : 90% water mixture was used in an effort to "wet" the surface of Radiant Color® particles and so reduce their surface charge and hence their hydrophobicity - particle preparation number 17, (M iller et al. in press). Radiant Color® particles were supplied by Radiant, a Magruder Color Company, Richmond, Ca. USA.

2.3 Results and discussion

2.3.1 Efficacy of particle types

Decay curves of transformed data for each particle type are presented in Figures 2.1 - 2.20.

Using the coefficient of determination (r^) o f a particular regression. Table 2.2 lists the

r~ value and associated probability of such a regression. The higher the r^ value in

each case (and the higher the significance o f correlation), the greater the indication of

uniformity between replicate slides, an indication that the particle type used has

behaved in a uniform manner, and is not subject to erratic detachment from the STM. 43

Table 2.2. Coefficient of determination for each particle type and

preparation, for both a linear and an exponential regression of

the decay of mucus on glass against time.

Linear regression Exponential regression

Aluminium Oxide (r"= 0.587, df = 28, P<0.001) (r= 0.631, df = 28, P<0.001) Glass Beads (F= 0.282, df = 28, P^f:0.05) No result available* Silt 210-250pm (r^= 0.417, df = 28, P<0.05) (r= 0.431, df = 28, P<0.05) Silt 125-210pm (r^= 0.141, df = 28, Pi^O.05) (r"= 0.264, df = 28, P^0.05) Silt 63-125pm (r"= 0.388, df = 28, P<0.05) (r"= 0.501, df = 28, P<0.01) Silt 45-63pm (r"= 0.439, df = 28, P<0.01) (r"= 0.435, df = 28, P<0.01) Silt<45pm (r"= 0.554, df = 28, P<0.01) (r^= 0.532, df = 28, P<0.01) Calcite (r"= 0.540, df = 28, P<0.01) (r^= 0.492, df = 28, P<0.01) Fine Quartz (r"= 0.938, df = 28, P<0.001) (r^= 0.832, df = 28, P<0.001) Aragonite (r"= 0.766, df = 28, P<0.001) (r"= 0.706, df = 28, P<0.001) Activated Charcoal (r^= 0.439, df = 28, P<0.05) (r"= 0.396, df = 28, P<0.05) Soot No result available* No result available* Kaolin (r"= 0.466, df = 28, P<0.01) (r"= 0.507, df = 28, P<0.01) Saturated Green Radiant Color® Particles (r"= 0.202, df = 28, PitO.05) (r"= 0.187, df = 28, PitO.05) 10% Saturated Green Radiant Color® Particles (r"= 0.245, df = 28, Pit0.05) (t^= 0.200, df = 28, P^0.05) 1% Saturated Green Radiant Color® Particles (r"= 0.034, df = 28, Pi(:0.05) No result available* 50% Saturated Green Radiant Color® Particles in 10% Ethanol (r"= 0.067, df = 28, Pi(:0.05) (r"= 0.003, df = 28, Pit0.05) Saturated Chartreuse Radiant Color® Particles (r"= 0.160, df = 28, P«^0.05) (r^= 0.095, df = 28, P^0.05) 10% Saturated Chartreuse Radiant Color® Particles (r"= 0.117, df = 28, P^0.05) (r= 0.135, df = 28, PitO.05) 1% Saturated Chartreuse Radiant Color® Particles (r"= 0.022, df = 28, P^0.05) (r"= 0.034, df = 28, P^0.05) * No data are presented for these particles as no particles remained attached to the mucus upon application. Soot was so hydrophobic as to fail to attach to the mucus 44

on the glass at all, (it floated instead). Glass beads were sufficiently large to protrude above the protective boundary layer, so presenting too great a resistance to the water current within the re-circulating channel, and were accordingly swept away after the first examination. Green Radiant Color® particles increased in attachment over time due to particle surface charges causing forces of attraction toward the glass slide (see section 2.3.3).

Using effectively a sample size of 50 (ten sites on each of five slides) over six observation intervals, a certain degree of noise in the regressions is to be expected. However, these values illustrate that certain particle types are more appropriate than others. Some of the particle types exhibit a high degree of uniformity between replicate slides within each treatment with associated probability values of P<0.05. Those particle types that do not exhibit such a high probability value (all Radiant Color® preparations, glass beads, soot and silt of 125-210 p.m) may be discounted at this stage. Remaining particle types are worthy of further examination. However, as a large number of particle types exhibit a high degree of uniformity between replicates, this study will concentrate on those with a higher probability value (P<0.01). Hence, aluminium oxide, silt (of size(s) 63-125, 45-63 and <45p.m), calcite, fine quartz, aragonite and kaolin are particle types worthy of further examination.

Comparison of the decay curves of the above mentioned particles (Figures 2.1, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10, 2.13), with those decay curves described by Davies et al., (1992b) is a further test of particle efficacy. While not strictly comparable, in that Davies et al., (1992b) were looking at the mucus trail of an intertidal limpet over 80 days instead of a freshwater snail over 6 days, their findings suggested that an exponential curve is expected. Only some particles in my study exhibit the predicted exponential decay curve. An exponential decay function best describes the biological and physical decay of mucus trails, as noted not only by Davies et al., (1992b), but also by trials preliminary to this study (section 2.2.1). Accordingly, those particle types that exhibit greater r^ values for exponential rather than linear regression functions were deemed worthy of further examination. (While it is noted that some particle types exhibit significant linear decay functions, for the purposes of particle selection required by this study, importance was placed upon achieving a decay function comparable to published data and preliminary trails). All other particle types can at this stage be dismissed. By means of these two tests, particles remaining under consideration are aluminium oxide, silt (63-125 |im) and kaolin. Further means of selection are however necessary in order to select an appropriate particle type. 70 Û Q (/) CO 8 60 1 7 o5 50 I 40

8 . C 1 0 8 I 0 { ♦ 20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours

Figure 2.1 Figure 2.2

60

030 -—- 50 4^ Q U1 ^ 5 CO ± 4 0 #20 8 §30 #20 r: i o 10 I 0 c 0 20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours Figure 2.3 Figure 2.4

Percentage cover of snail trail mucus on a glass slide over time, as indicated by the presence of the following marker particles at 10 examination sites on each of tlve replicate slides: Figure 2.1 Aluminium Oxide Figure 2.2 Glass Beads (100 pm diameter) Figure 2.3 Silt 210-250 pm Figure 2 4 Silt 125-210 iim _ 90 80 Q œ 80 CO 70 1 70 60 g 60 0 50 50 I 40 2 40 1 30 8 30 I 20 û. 20 s. 10 1 10 5i ^ 0 ^ 0 H i c 20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours Figure 2.5 Figure 2.6

^00 100 ^90$ ^80 80 m p o 60 8 m50 40 2 40 § 30 20 5 20 I I c 10 —t— S 0 >— 20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours Figure 2.7 Figure 2.8

Percentage cover of snail trail mucus on a glass slide over time, as indicated by the presence of the following marker particles at 10 examination sites on each of five replicate slides: Figure 2.5 Silt 63-125 pm Figure 2.6 Silt 45-63 pm Figure 2.7 Silt <45 pm Firm re 2 8 C a lcite 100 100 S 90 90 80 80 70 70 60 60 50 50 40 I 40 30 5 30 6 20 20 10 I 10 i 0 I 0 (— 20 40 60 80 100 120 0 20 40 60 80 100 120 Hours Hours Figure 2.9 -e2. 10

70 1 0.9 60 0.8 M 50 0.7 0.6 i 40 o3 0.5 8 30 0.4 & 20 5 0.3 0.2 I ,0 0.1 I 0 0 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Hours Hours Figure 2.1 1 Figure 2.12

Percentage cover of snail trail mucus on a glass slide over time, as indicated by the presence of the following marker particles at 10 examination sites on each of five replicate slides: Figure 2.9 Fine Quartz Figure 2.10 Aragonite Figure 2.1 1 Activated Charcoal F ipu re 2 12 .Soof 100 ^ 500 i 450 ^ 400 1 350 ^ 300

i Q 250 5 ^ 200 150 100 50 5 0 »- 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Hours Hours Figure 2.13 Figure 2.14

400

■c 350 tr 2. 300 & 00 250 ■â co 200 - "+ 150 P :I 100 Z 10 50 5

0 ^ 0 - (-■ 0 20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours Figure 2.15 Figure 2.16

Cover of snail trail mucus on a glass slide over time, as indicated by the presence of the following marker particles at 10 examination sites on each of five replicate slides: Figure 2.13 Kaolin (percentage cover). Figure 2.14 A saturated suspension of Green Radiant Color® (individually counted particles). Figure 2.15 1 0% dilution of a saturated suspension of Green Radiant Color® (individually counted particles). Fipiire 2 16 1 % dilution of a saturated snsnension of Green Radiant Color® tindividiiallv counted narticlesV 300 160 2 140 250 -T- Î 120 §. 200 a ce 100 150 Q 80 1> CO .1 60 100 o d 40 50 Z c 20

0 1 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Hours Hours Figure 2.17 Figure 2.18

250 60

-c 200 •c 50 2. CÜ CO 40 150 5 Q ■è ?30 100 H 0 20 50 z 1 0 I------20 40 60 80 100 120 20 40 60 80 100 120 Hours Hours Figure 2.19 Figure2.20

Cover of snail trail mucus on a glass slide over time, as indicated by the presence of the following (individually counted) marker particles at 10 examination sites on each of five replicate slides: Figure 2.17 50% dilution of a saturated suspension of Green Radiant Color® Figure 2.18 A saturated suspension of Yellow Radiant Color® Figure 2.19 10% dilution of a saturated suspension of Yellow Radiant Color® Fipiire 2.20 1% rliliition of a saturated snsnension of Yellow Radiant Color® 50

2.3.2 Subjective approaches in the selection of an appropriate nnarker particle

Particle types dictated a certain approach to counting, or estimating particle retention. It was possible to count individual Radiant Color® particles, being of reasonably uniform size (2-4 p.m), and being so clearly visible under UV light. Counting individual particles, rather than percentage area cover, precludes the use of either orange or pink Radiant Color® particles, which are prone to fragmentation when subject to this method. Radiant Color® particles proved problematic in many other ways. In addition to two colours fragmenting under examination and so being rejected during preliminary trials, green and chartreuse were also occasionally prone to fragmentation. Further, due to their high surface charge they present difficulties in producing a suspension in water. In attempting to produce a quantifiable standard saturated suspension, a long series of alternate sonication and dilution treatments was required. Such a suspension was defined as one where no particles amass at the surface as a scum layer, and where particles do not begin to settle out for a minute after agitation ceases. (Thereby utilising the smallest, individual rather than clumped, particles). Dilution series of a saturated suspension were easier to work with and were also an attempt to discourage particles from coagulating and sinking. The attempt to "wet" the surface of Radiant Color® particles and so encourage "permanent" suspension, using a solvent (10% ethanol solution) proved somewhat easier to handle in terms of particles remaining in suspension. Concern is raised however, about the effect that such a solution might have on STM. Such a suspension may be of use, however, for the application of such particles directly into freshwater systems, as found by M iller at al. (in press).

Glass beads were the only other particle type that facilitated individual particle counting. All other particles were of such a variable size range that a percentage cover count was made within the squared 1 cm^ eyepiece micrometer at each of the 10 coordinates. Silt preparations in particular often contain very large mineral grains. Removal of such a single grain could account for the loss of up to 100% cover of a single examination field, introducing an unacceptable bias. Such large grains are obviously subject to greater shear forces within the water How, hence their removal would suggest an unrepresentative removal of mucus from the slide. The different size ranges of silt (particle types 3, 4, 5, 6 and 7 in Table 2.1) illustrated varying degrees of efficacy. The larger fractions offered lesser reproducibility (a lower I' value). However, the real disadvantage is the range of particle sizes within each silt particle type, such that the removal of just one large mineral piece can make a drastic 51 alteration to the trend of decay of mucus.

2.3.3 Objective approaches in the selection of an appropriate marker particle

The use of certain particles can be discounted after these trials. Hydrophobic soot, for example, or glass beads of 100 p.m diameter that present too great a resistance to water flow, are of no use as marker particles for mucus. Radiant Color® particles are of limited use in that they necessitate UV light to be fully visible. This suggests the efficacy of low density preparations, yet even then. Radiant Color® particles tend to settle unevenly, a phenomenon not apparent with any other preparation. Such aggregation toward high densities raises difficulties in counting individual particles. They are also extremely difficult to focus on, and seem to settle on mucus at a number of different focal depths. Whether this suggests that STM is porous, remains a moot point. Most importantly. Radiant Color® particles have a surface charge such that they are almost equally attracted to clean glass as they are to STM. Where particles showed a consistent affinity for the mucus-free control slide. Student's t-tests were carried out to discern differences between controls and replicates (all were two-tailed t- tests - see Table 2.3). All Radiant Color® suspensions, except saturated green and saturated chartreuse illustrated no difference between clean glass and mucus coated glass. Other Radiant Color® particle preparations used in this study, can be eliminated on this basis alone. A significant difference was found for the 1% saturated green suspension, however, the greater number of particles is on the control rather than the mucus-coated slides. Saturated green and saturated chartreuse Radiant Color® particle preparations may also be eliminated from this trial however, for the problems they raise in preparation (Section 2.3.2).

Table 2.3 Student's t-tests for differences between mucus coated and control slides - to assess the affinity of Radiant Color® Particle preparations for clean glass against STM.

Saturated green t=2.77jf^ 4, P= <0.001 Saturated chartreuse t=2.36jf^4 4, P= <0.001

10% saturated green suspension t=2.22jf^ 4 , P=0.545 1 % saturated green suspension t=2.77jf^4 4. P=0.027 50% saturated green suspension in a 10% ethanol solution t—2-22jf^4 4, P=0.06 10% saturated chartreuse suspension t=2.22j,-^4 4, P=0.332 1 % saturated chartreuse t=2.36jf^4 4, P=0.459 52

Davies et al., (1992b) and Davies and Williams (1995) used activated charcoal in their monitoring of limpet mucus decay in intertidal zones. Activated charcoal comes in a wide range of individual particle sizes, and in a very irregular series of shapes (spheres to elongated splinters), such that counting individual particles will only realise a general idea of mucus decay. By monitoring percentage cover afforded by attached particles, greater accuracy will be achieved. However, estimating the cover of long thin splinters of widely variable size is not as convenient, or accurate, as for spherical objects of similar size when using a squared counting grid eye-piece.

Calcite and aragonite particles both underwent a cycle of dissolving and re-crystallising, resulting in places in a large crystal sheet across areas coated in mucus. This resulted on occasion in large portions of particle coating that would float away on removal or replacement of slides from the re-circulating channel.

By far the most suitable particle for further experimentation was aluminium oxide. It was subject to neither crystalline alteration or fragmentation. While it is of variable particle size, such that percentage area cover must be recorded rather than individual particles, it has a sufficiently narrow range, which means that the removal of a single particle does not impose a bias upon the overall trend of decay.

2.4 Conclusion

Of those 20 particle types and preparations tested to monitor the decay of STM, aluminium oxide was found to be most appropriate. Other particle types that have successfully been used in other studies were rejected for a mixture of objective and subjective reasons. This suggests that the selection of a particular particle type as a marker of biological processes should be a carefully considered choice. 53

Chapter 3 The physical behaviour of snail trail mucus

3.1 A background to the properties and functions of mucus

Snail trail mucus (STM) is a versatile substance, that provides more than a means of locomotion or decreasing friction between the foot and substratum (Grenon and

Walker, 1980). The functions o f snail mucus have been described by various authors:

Lissman (1945) categorised the musculature of the gastropod foot, and assumed that snail trail mucus was produced simply as a means to aid locomotion; Denny (1980) quantified this work with his study of the role of mucus as an aid to locomotion, where he observed the breakable and reformable bonds that provide the gel-like properties of mucus.

Further to the physical aspects o f pedal mucus, it has been noted to perform various biological functions, for example, gastropod pedal mucus is used for trapping food.

The mucus trail can subsequently be consumed with attached energy rich particles and cells (Conner and Quinn, 1984) or, indeed, used directly to capture prey (Ogren,

1995). Mucus trails can also be a means o f navigation by the inclusion of metal granules, the directional polarity of which is recognised by the producer and local conspecifics (Bretz and Dimock, 1983; Davies and Hutchinson, 1995). Marine invertebrates also utilise mucus for a number of diverse purposes. It can act as a vector for antibacterial agents and compounds that debilitate prey, such as haemagglutinin which causes the thickening o f vertebrate blood (Astley and Ratcliffe,

1989). Mucus secretion can also act as the trigger for population d rift or dispersal, from substrate that has been burrowed into (O livier et al., 1996). The potential uses of mucus as a vector are numerous. Beninger and Le Fennec (1993) demonstrated that mucus is used to carry enzymes for extracellular digestion, while Coffroth (1984) noted that floating mucus aggregates were capable of trapping particles, thus providing a means of food capture for the mucus producer. Lastly, mucus in snails can also be a vector of venom, capable of immobilisation, death and subsequent expansion o f the victims flesh out of the rasp hole (Andrews, 1991). 54

The above examples provide some indication of the potential value of mucus to invertebrates such as gastropods, corals and bivalves, although few apply to snails and none to the two snails in my study (L. peregra and P. jenkinsi). As mucus is a material that has evidently been overlooked in previous studies, I have set out to categorise the physical properties of the mucus of these two common freshwater snails.

Clearly, gastropods produce a considerable quantity o f pedal mucus, up to 68% o f all energy consumed is invested into mucus production (Davies et al., 1992a). Yet, the durability o f a snail trail, and its effect within an ecosystem (apart from those benefits specific to the producer) are unknown quantities. Davies et al., (1992a), while examining the ability o f limpet pedal mucus to desiccate and rehydrate, noted that the presence o f mucus on a surface plays a considerable role in the colonisation of that surface by microalgae and the early stages o f macroalgae. This raises questions about the role of freshwater snail mucus trails, their facilitation of bacterial colonisation of a surface and subsequent potential particle binding properties.

Perhaps the most interesting aspect of Davies' work to my study concerned his measurements o f the longevity of limpet pedal mucus. Davies et al., (1992b) noted that limpet mucus can withstand up to eighty days of wave action in the rocky intertidal zone. This is a considerable length o f time for a substance that is often considered an easily disposable waste product, of limited use and longevity. In addition, limpet pedal mucus, while losing the ability to trap microalgae over time, continues to be energetically viable as a food source to its producer over an eighty day period. Once more, comparisons must be drawn with freshwater mucus production and its durability.

Other work by Davies et al., (1990a) reveals the seasonal variation in the composition of mucus, the variations in composition between populations (Davies 1993; Davies and

W illiams, 1995) and the toxicological modification of limpet pedal mucus in response to environmental stress (Davies, 1992). This body of work demonstrates that

gastropod mucus is not simply a means of locomotion, and should not therefore be 55 otherwise considered a waste product. It is a highly variable and durable material, capable of many functions, not only to its producer, but also to other organisms. As such, it is worthy of examination.

Alternative functions of invertebrate mucus were examined in detail by Denny (1989).

He argued that most of our understanding of this ill-defined and highly variable

material comes from our knowledge of mammalian secretions. Yet, invertebrates

utilise mucus to a far more diverse degree. Denny (1989) categorised the various uses of mucus mentioned above, and many more besides, including the ability to act as an agent to prevent desiccation, as a physical and chemical defense against predation and as a food source / food trap, means of egg attachment etc. Of most interest to my study however was his attempt to define the material properties of mucus (certain slugs and snails are able to produce mucus threads capable o f supporting their own body weight, plus that of a mate, Denny (1989)). The considerable potential offered by this material is demonstrated by the fact that mucus is versatile enough to be fashioned into a net, curtain or web (Denny, 1989). However, Denny (1989) concentrated mainly on terrestrial organisms and there remains little or no examination of freshwater mucus trails in their natural state. M y study aims to increase our

understanding of this ubiquitous material, by categorisation of the mucus of two species of freshwater snail. In particular, mucus trails offer sites of attachment to

DOM and POM (as demonstrated in Chapter 2). The behaviour of STM as a site of

DOM and POM attachment is examined within this chapter, while the attachment of

DOM (in this case, pesticides) is further examined in Chapter 4, and the attachment

of living POM (bacterial cells) is further examined in Chapter 6.

Using the method of marker particle attachment and monitoring, described in Chapter

Two, many factors presumed to affect on the longevity or integrity of snail trail mucus

may be examined. Comparison of particular treatments w ill identify the degree to

which water speed, sampling interval, disturbance by sampling, disturbance by snail,

degradation by bacteria that are airborne, waterborne and mucus-borne etc have on

snail trail mucus. In addition, the degree to which mucus acts as a sealant upon an

existing layer of mucus or biofilm is examined. 56

3.1.1 Experimental Objectives

A full description of all treatments used in this study is given in Table 3.1.

1 Comparison of the behaviour and responses of the mucus snail trails of two

freshwater species.

2 To examine the loss of "stickiness", or integrity, of snail trail mucus over time.

3 To examine the effect o f current velocity upon snail trail mucus.

4 To determine the effect of the sampling interval.

5 To examine the effect of airborne bacteria.

6 To examine the spread o f snail trail mucus.

7 To examine the effect o f bacteria - incorporated within STM, or from faecal

pellets.

8 To examine the effect of water borne bacteria.

9 Investigation of stability lent to STM by the relief or "micro-topography" of

the substrate.

10 To examine the disturbance that snails cause to STM.

3.2 Materials and Methods

Mucus application and subsequent marker particle application was described in

Chapter Two. Specific treatments of STM within this study are detailed in Table 3.1.

In all treatments, the particle used was aluminium oxide. For each treatment o f five

replicate slides, a single control slide (which was not coated in mucus) was used to

determine the attachment and maintenance o f particles on glass without the aid of snail

mucus. Such controls were also used for within-treatment statistical analysis.

Snails were gathered locally as required, and maintained at room temperature in tanks

of tap water for at least two hours to allow the snails to acclimate. This also allowed

the snails to evacuate their digestive systems so as to minimise the presence of faecal

pellets on glass slides. These are particularly undesirable as they interrupt an

otherwise uniform surface of mucus, and also cause problems with focus, when using

a high power microscope objective. 57

Table 3.1 Description of all treatments

Test Mucus laid Mucus Flow Sampling Sampling Other

in: maintained in rate frequency duration comments

(depth): (cm/s)

AI Distilled water River water 10 4 Hourly 48 hours

A2 (200 mm) Days 0-2

Bl Distilled water River water 10 2 Hourly 24 hours

82 (200 mm) Days 0-1

Cl Distilled water River water 10 Daily Days Particles applied C2 (200 mm) 6-12 after 6 days storage in river

water at 1 Ocm/s

Dl Distilled water Distilled water 0 Daily 6 Days

02 (5 mm) Days 0-6

El Distilled water River water 20 Daily 6 Days

E2 (200 mm) Days 0-6

FI Distilled water River water 40 Daily 6 Days

F2 (200 mm) Days 0-6

Gl Distilled water River water 10 Daily 6 Days Mucus re-applied

G2 (200 mm) Days 0-6 to particle-coated

mucus layer

HI Distilled water River water 10 Daily 6 Days Mucus applied to

only (200 mm) Days 0-6 established biofilm

11 Distilled water River water 10 Daily Days Particles applied

12 (200 mm) 6-12 after 6 days

storage in still

river water of 5

mm.

Jl Distilled water River water 10 4 Hourly Days Particles applied

J2 (200 mm) 1-3 after 24 hours

storage in distilled

water of 5 mm.

Kl Distilled water River water 10 Daily Days Particles applied

K2 (200 mm) 1-7 after 24 hours

storage in distilled

water of 5 mm. 58

Test Mucus laid Mucus Flow Sampling Sampling Other in: maintained in rate frequency duration comments (depth): (cm/s)

M l Un filtered river River water 10 4 Hourly 48 Hours

M2 water (200 mm) Days 0-2

01 Distilled water River water 10 4 Hourly 48 Hours

02 plus antibiotic (200 mm) Days 0-2

PI Distilled water River water 10 2 Hourly 24 Hours Mucus re-applied

P2 (200 mm) Days 0-1 to particle-coated

mucus layer

Ql Distilled water River water 10 Daily 6 Days 5 alternate layers Q2 (200 mm) Days 0-6 of mucus and

particles

Ri Distilled water Distilled water 0 Daily 6 Days

R2 (200 mm) Days 0-6

SI Distilled water River water 40 4 Hourly 48 Hours

32 (200 mm) Days 0-2

Tl Distilled water River water 20 4 Hourly 48 Hours

T2 (200 mm) Days 0-2

Ul Distilled water Distilled water 10 4 Hourly 48 Hours

U2 plus antibiotic Days 0-6

(200 mm)

VI Distilled water Distilled water 10 Daily 6 Days

V2 plus antibiotic Days 0-6

(200 mm)

W l Distilled water River water 10 Daily 6 Days

W2 plus antibiotic (200 mm) Days 0-6

XI Distilled water Distilled water 0 Daily 6 Days

X2 plus antibiotic Days 0-6

(5 mm)

Yl Distilled water River water 10 Daily 6 Days

Y2 (200 mm) Days 0-6 59

L. peregra were raised and gathered from an experimental channel at East Stoke,

Dorset (Nat. Grid Ref: SY 867 868 ). Attempts to maintain L. peregra in the laboratory met with limited success, therefore snails were gathered fresh from the stream for each treatment and subsequently returned. P. jenkinsi were harvested from a cress bed drainage stream in Wool, Dorset (Nat. Grid Ref: SY 869 846).

Unfiltered river water was drawn directly from the M ill Stream, a side channel o f the

River Frome, East Stoke, Dorset (Nat. Grid Ref: SY 867 868 ). Particulate material

was allowed to settle out and the water was decanted directly into the plexiglass experimental channel (as described in Chapter Two) that was used for most o f the following treatments. River water was alkaline, approximately equivalent to 0.002M Ca^^.

Snails were rinsed in distilled water prior to placement upon a glass slide, to remove any particles attached to the snail outer surface. The snails were allowed to lay down

mucus trails in distilled water, to minimise the deposition of any waterborne particles

in the mucus. W hile the use o f distilled water rather than filtered river water may

cause some degree of stress to the snails, it was necessary in order to minimise the

inclusion of POM or DOM. | Distilled water used in the treatments described in Table 3.1 and throughout this thesis, refers to deionised, sterile filtered ultra-pure water (0.2 pm filtered, at 18 MTi resistance).

An antibiotic was used in a number of treatments to eliminate bacterial growth. The

antibiotic selected was chloramphenicol (Fisher C/4322/47) in distilled water, at a

concentration of 1 g 1‘. This concentration inhibits the growth of Gram positive and

Gram negative bacteria, yet is harmless to eukaryotic organisms (Stanier et al., 1976).

However, snails of either species, when placed in this solution, were sluggish and

required prolonged recovery periods before full mobility was once again achieved.

For this reason, greater quantities of snails were used to minimise the time required

for complete mucus cover o f the glass slides. Subsequently, all snails were thoroughly

rinsed and fed, incubated at 10°C for 24 hours, and returned to their habitat. 60

3.2.1 Experimental protocols

A full list of all treatments (performed with the mucus of both L. peregra and P. jenkinsi, except where noted), is to be found in Table 3.1, where parameters such as water speed, source o f water, sampling frequency etc are detailed, together with criteria that defined each treatment. By measuring the rates o f decay of STM on each of five replicate slides, subject to each treatment, comparisons between treatments were made. Differences between treatments test various hypotheses, matching the listed objectives.

1 Comparisons were made of the behaviour and responses of the mucus of snail

trails of two freshwater species, L. peregra and P. jenkinsi in all treatments

described in Table 3.1 (excepting treatment H). Each treatment for one species

compared against each appropriate treatment for the other species.

2 Loss of "stickiness", or integrity, of snail trail mucus over time was examined

by the ageing o f STM. Where STM is stored for a number of days or hours

in water, information on the decrease in integrity may be determined by

comparison of the following treatments; Y against C (maintained for 6 days

in flowing water before particles applied); Y against I (maintained for 6 days

in shallow, still river water); J against A (mucus held in sterile water for 24

hours examined every 4 hours); Y against K (mucus held in sterile water for

24 hours, examined daily).

3 Examination of the effect of water flow upon the longevity of STM was

achieved by comparison of treatment Y with treatments D, E and F for an

indication of decay on a daily basis; and treatment A with treatments S and T

for an indication over a shorter time interval (48 hours instead of 6 days).

Direct comparison of corresponding treatments (E with T, F with S and Y with

A) give an indication of the effect of disturbance to the mucus conferred by

the sampling interval.

4 Examination of the effect of the sampling interval and quantification of the 61 disturbance lent involved examination of treatments Y, A and B. In addition, effects of the sampling interval were determined by examination of treatments

J against K (where mucus is stored in sterile water for 24 hours prior to the application o f particles); O against W (where mucus is secreted in an antibiotic solution, but stored in river water); S against F (at 20 cm s '); E against T (at

40 cm s '); U against V (where mucus is secreted in a sterile environment and maintained in a sterile (flowing) environment).

The effect o f airborne bacteria on snail trail decay was determined by comparison of treatments D, I, R and X (variable depths of still water, with use of antibiotic compounds in the still water of treatment X). Comparison of treatment C with treatment I determined the effect o f storage in shallow still water compared with storage in deeper flowing water.

The spread o f snail trail mucus and bacterial degradation of mucus at the standard depth used for most treatments (200 mm), in flowing water was analysed by comparison of the follow ing two treatments; A and M (mucus secreted in sterile water and in unfiltered river water).

Comparison of treatments V and W provided information on the effect of bacterial degradation of the snail mucus trail by bacteria laid down within, or on, the trail from the snail gut.

The effect of bacterial action upon snail trail integrity, where the bacteria originate in the river water that flows over the mucus trails, was examined by comparison o f treatments A and O. The comparison o f treatments O and U enabled assessment o f the effect o f bacteria that settled upon the mucus trail as it was laid down. Mucus trails were subsequently stored in flowing water that contained an antibiotic to prevent bacterial proliferation, thus preventing subsequent bacterial degradation after having achieved the production o f mucus trails in a bacteria free environment.

The possible stabilising effect of biofilm on snail trail longevity was examined by comparison of treatment Y against treatment H. No results for P. jenkinsi 62

mucus are available for treatment H due to an inexplicable local population

crash, observed mid-study.

10 Lastly, treatments G, P and Q were compared with treatment Y to determine

whether snails themselves disturb existing mucus trails.

For the mucus trails of L. peregra, tests are described by a letter and the number " 1 for the mucus trails of P. jenkinsi, tests are described by a letter and the number "2".

3.2.2 Methods of counting and comparison by statistical analysis

As described in Chapter Two, the percentage cover o f particles (and hence of mucus) on the slide, as seen through a 1 cm^ eyepiece graticule was recorded at ten specific locations at each recording interval. Each location was specified by coordinates, using two vernier scales on the mechanical stage of the microscope.

A ll statistical analyses were based on the mean cover of the ten locations for each slide. For each slide, the log-transformed, mean, percentage cover, was regressed against time to obtain an estimate of the slope (b), which measures the exponential decay rate of STM. Student's t-tests were used to assess the difference between rates of decay (b) for different treatments. The within-treatment variances in rates of decay were compared in order to determine the efficacy of Student's t-tests assuming either equal or unequal within-treatment variance.

Differences between slides within a treatment were assessed by two way ANOVA

(factors: slide and time), on the log transformed data (Table 3.3).

Results o f undogged data are shown in Figures 3.3.1 - 23 A and 3.3.1 - 22 B. Error bars are not included on these figures as this aspect of the data is examined within section 3.3.1 and discussed throughout section 3.3. 63

The analyses were based on the natural logarithms of the percentage cover, rather than the more usual arcsine transformation for percentage data for two reasons: I) to enable estimation of the exponential rate o f decay for linear regression, and 2) the high initial variability in cover between slides suggested that either a log or arcsine transformation would stabilise the variance. (Examples of data manipulation are presented in Table 3.2). 64

Table 3.2 Breakdown of data manipulation with representative examples

for between treatment analysis

1) Data from each of the 10 examination fields on each slide have beensummed

for each examination interval.

2) Each summed data point was log transformed.

3) Regression was performed for the decay of STM on each slide.

4) Regression coefficients are calculated for each of the five replicate slides

within each treatment, (plus the control slide, wherever particles attached).

Example I : L. p e re g ra Treatment A:

Slide Gradient Intercept Proportion ;t Average SD

1 -0.162 6.936 0.149 0.128 0.019 2 -0.159 7.522 0.147 3 -0.110 6.707 0.104 4 -0.122 7.315 0.115 5 -0.135 7.315 0.126

Example 2: L. pe re g ra Treatment Y;

Slide Gradient Intercept Proportion it Average SD

1 -0.021 6.677 0.021 0.024 4 X 10-' 2 -0.020 5.613 0.020 Based on five replicates only 3 -0.023 5.570 0.022 4 -0.032 6.635 0.032 5 -0.024 5.192 0.024 Control 0.019 0.930 -0.019

5) Regression coefficients are compared between treatments using Student's t-test.

Example 3; A/A2 T-Test: Two-Sample Assuming Unequal Variances, Performed for Section

3.3.1 t Stat 2.622 P(T<=t) one-tail 0.029 t Critical one-tail 2.131 P(T<=t) two-tail 0.058 t Critical two-tail 2.776

Example 4; Y l/D l T-Test: Two-Sample Assuming Unequal Variances, Performed for Section

3.3.3

-95.435t Stat -95.435t P(T<=t) one-tail I.3E-06 t Critical one-tail 2.353 P(T<=t) two-tail 2.5E-06 t Critical two-tail 3.182 65

3.3 Results and Discussion

3.3.1 W ithin treatment analysis - the uniform ity of replicate response

W ithin treatment analysis is a measure of the uniform ity o f the rates o f decay measured for the five replicates of each treatment (Tables 3.3 a and b), described in section 3.2.2. The reproducibility within a treatment is important as it is a factor that w ill help to explain otherwise unexpected or inexplicable results in the comparison of two treatments. It is also an indication of the reliability of the decay rates that subsequently describe a certain treatment. It is worth noting, for example, that those treatments that do not exhibit significant uniform ity of response are generally the same for both species o f snail used (B, C, G, U and V for both species, O and X for L. peregra only, and K and W for P. jenkinsi only; see Figures 3.2, 3.25 (Treatment B);

3.3, 3.26 (Treatment C); 3.7, 3.30 (Treatment 0 ); 3.19, 3.41 (Treatment U); 3.20, 3.42

(Treatment V); 3.13 (Treatment O l); 3.22 (Treatment X I) ; 3.33 (Treatment K2); 3.43

(Treatment W2)). This suggests that the above treatments are particularly disruptive to the integrity of STM, resulting in an individual response to the treatment rather than a true indication o f rate o f decay. Indeed, those treatments that are common to both species which show varied within treatment responses, are those that are sampled at

2-hourly intervals (B), where mucus is aged (C), overlaid onto existing trails (G), or secreted in water dosed with an antibiotic (which affected both species of snail, whereby prolonged exposure led to decreased mobility, U,V).

However, while no other treatments involved the laying o f mucus trails in water dosed with an antibiotic, other treatments consisted of sampling at 2 hourly intervals (P), the ageing of mucus (I, J, K ) or mucus overlaid onto existing trails (P and Q). A ll of these treatments exhibit uniform response in the decay o f STM, (except treatment K for P. jenkinsi). Such findings raise an element of doubt that the above treatments were disruptive to STM integrity, suggesting a combination of factors led to within 66 treatment variance, such as sampling interval and treatment. Consequently, individual factors such as sampling interval w ill be returned to (Section 3.3.5). 67

Table 3.3 a W ithin treatment analysis using A N O V A to test replication

against error for treatments featuring the STM of L. peregra

All ANOVA tests are performed on the five replicate slides of each treatment, excluding the control slide, unless otherwise specified.

Treatment

A (F , 2 3y= 12.82, P = 0.000)

B(F,2 .3„= 0.21, P = 0.997)

C Without Controls (F, „= 0.77, P = 0.581)

C With Controls (Fg 0.61, P = 0.694)

D (F; „= 12.12, P = 0.000)

E (F, ,,= 22.35, P = 0.000)

F (F; ,^= 60.90, P = 0.000)

G (p 5 „= 2.17, P = 0.103)

H Without Controls (Fg „= 14.23, P = 0.003)

H With Controls (F 5 ,,= 3.82, P = 0.026)

I Without Controls (F5 ,,= 2.83, P = 0.047)

I With Controls (F5 2.69, P = 0.045)

J Without Controls (F |2 3ç,= 12.75, P = 0.000)

J With Controls (F,2 .3,= 9.81, P = 0.000)

K(F5 „= 3.73, P = 0.017)

M (F|2.39= 10.61, P = 0.000)

O (F,2 .3,= 1.08, P = 0.399)

P(F,2 .3^= 15.07, P = 0.000)

Q (F5 5.09, P = 0.004) R (F; ,g= 8.98, P = 0.000)

S (F,2 .3ç,= 6.91, P = 0.000)

T (F,23,= 3.49, P = 0.001)

U (F,239= 0.2, P = 0.998)

V (Fs.ik” 1-62, P = 0.206) w (F 5 „= 6.55, P = 0.001)

X (F 5 ,,= 2.30, P = 0.088)

Y (F, ,,= 25.52, P = 0.000) 68

Table 3.3 b W ithin treatment analysis using A N O V A to test replication

against error for treatments featuring the STM of P. jenkinsi

A ll A N O V A tests are performed on the five replicate slides o f each treatment, excluding the control slide, unless otherwise specified.

Treatment

A2 (F ,2 3 y= 23.99, P = 0.000)

B2 (Fi2 .3 9 = 0 69, P = 0.755000)

C2 Without Controls (Fj 0.74, P = 0.606)

C2 With Controls (Fj 0.89, P = 0.504)

D2 (p 5 ,x= 3.67, P = 0.018)

E2 (p 5 „= 39.12, P = 0.000)

F2 (P5 ,x= 7437.43, P = 0.000)

G2 (P5 ,),= 0.65, P = 0.666)

1 2 Without Controls (P5 ,x= 3.44, P = 0.023)

1 1 With Controls (p 5 ,s= 3.47, P = 0.017)

J2 Without Controls (F|2 .3 9 = 7.67, P = 0.000)

J2 With Controls (F|2 .3 9 = 9.51, P = 0.000)

K 2 Without Controls (p 5 „= 1.51, P = 0.236)

K 2 With Controls (p 5 „= 1.11, P = 0.383)

M2 (Fi2 .3 9 = 9.63, P = 0.000)

0 2 (Pi239= 2.3, P = 0.025)

P2 Without Controls (p, 2 .3 9 = 5.26, P = 0.000)

P2 With Controls (P,2 .3 9 = 7.84, P = 0.000)

Q2 (p 5 ,s= 7.33, P = 0.001)

R2 (p 5 ,s= 24.12, P = 0.000)

S2 (P,2 .3 9 = 4.86, P = 0.000)

T2 (P,2 .3ç,= 13.23, P = 0.000)

U2 (P,2 .3,= 0.15, P = 0.999)

V2 (p 5 ,«= 1.32, P = 0.301)

W2 (P5 ,x= 0.92, P = 0.490)

X2 (p 5 „= 6.16, P = 0.002)

Y2 (p 3 ,x= 61.83, P = 0.000) 69

Using AN O V A to test replication against error, all other treatments exhibited P values of < 0.05 (Tables 3.3 a and b), many considerably smaller, illustrating the uniform ity of response to most of the treatments. W ithin treatment analysis tested the reliability of the methods, which were found to be satisfactory. These tests showed that the laying o f mucus trails within water dosed with antibiotics is both distressing for the snails and results in mucus trails that are unstable and unpredictable in their response to the experimental treatments.

These tests also show the purpose o f the control, which is to distinguish the experimental replicate from the mucus-free control. For the majority of treatments, the within-treatment analysis was applied to the replicates only, ie without the control

(see Tables 3.3a and b). The only treatments that were examined both with, and without, the control slide were those where particles adhered to the control slide beyond the first sampling interval. It is expected that those treatments examined with control data would exhibit a larger P value than those examined without the control data, except those treatments already shown to be in some way unstable or to respond in a non-uniform manner (Treatments C, H, I, J, K and P).

In fact, this is largely the case. For those treatments where the rate of decay o f mucus from the five replicates is uniform, the P value is greater when the control data are included (H, K2), or the same (II, J l, 12). However, where the response o f the five replicates to a particular treatment is significantly non-uniform, the P value is neither consistently lower or higher when the control data are included (Cl (higher), C2

(lower), 12 (lower), K2 (higher)). The types of treatment that caused particle adherence to otherwise clean control slides are however, most interesting. Treatment

H, where slides are left to condition in flowing river water for six months was expected to result in a biofilm surface to which particles would attach. Treatment C

may have developed a similar film to a far lesser extent, and at the very least have developed some layer o f calcium carbonate deposition due to the high levels of 70 dissolved calcium in the local chalk stream waters. Calcium deposits were observed to develop on the sides of the plexiglass recirculating channel after 24 hours from the unfiltered river water. Treatment I resulted in particle attachment to the clean glass control slide for similar reasons to treatment C. However, the reasons for particle attachment to control slides on treatments J and K are less obvious. In both cases, distilled water is used as a storage medium in which STM was aged. However, in both cases the distilled storage water was shallow, again suggesting the possibility of penetration of airborne particles or cells that would subsequently settle and develop into biofilm that would trap marker particles. While section 3.3.6 has disproved the hypothesis behind this, it is one more piece o f otherwise anecdotal evidence that led to such an investigation in the first place.

Finally, the attachment of marker particles to the control slide of treatment P is easy to explain. When a slide is coated in mucus trails (the second o f two layers applied in this treatment), yet no marker particles are applied, it is a simple process o f particle drift and attachment from one slide to another as the STM on an adjacent slide decays.

This observation illustrates two important points: Firstly, the efficacy of methodology in mimicking real systems is indicated by the fact that such unattached particles can settle at random continually, throughout this study. Secondly, that unattached particles were able to attach to a mucus coated particle free slide, yet were unable to do so to mucus coated, particle-applied slides indicates the limited availability o f either surface area, or sites o f attachment on mucus trails.

3.3.2 Comparison of the snail trail mucus of two freshwater species

Comparisons were made between the two species, with each treatment for L. peregra

(as described in Table 3.1) compared with its counterpart for P. jenkinsi. O f the twenty two comparable treatments (treatment H was performed for one species only). 90 90 4 80 80 ' I 70 ■ \ 60 ^ 60 i i ' ' 50 ^ 40 • ' 40 - 30 - 30 - 20 • 20 - -A- 10 : 10 - 0 #— 0 » 0 20 30 50 0 10 15 20 25

Time (h) Time (h)

Figure 3.1 Figure 3.2

25 80 -J g 70 20 I 60

15 = 50 8 10

I 20 - 5 ^ 10 0 0 0 20 40 60 80 100 120 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.3 Figure 3.4

Erosion rates of L. peregra mucus trails over time - Figure 3.1 (Treatment A); Figure 3.2 (Treatment B); Figure 3.3 (Treatment C); Figure 3.4 (Treatment D), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 90 90 80 80 70 60 50 40 \ 30 20 10 0 » i ± i = = a 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.5 Figure 3.6

ISJ 40 -• ^ 30#^ \

- i ' 10 ^ 0 . ----- 0 20 40 80 100 120 120

Time (h)

Time (h)

Figure 3.7 Figure 3.8

Erosion rates o f L peregra mucus trails over time - Figure 3.5 (Treatment E); Figure 3.6 (Treatment F); Figure 3.7 (Treatment G); Figure 3.8 (Treatment H), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 45 25 40 5 20

20 10 -

5 V

10 20 30 40 50 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.9 Figure 3.10

60 - 80 -J 1 70 I E 60 - -, 40 • ■ 2 50 - 1 40. 2a, 30 - 5 20 B 20- I '0 ^ ^ 10 0 0 1 - 1,. 0 10 20 30 40 50 0 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.11 Figure 3.12

Erosion rates o f L. peregra mucus trails over time - Figure 3.9 (Treatment 1); Figure 3.10 (Treatment J); Figure 3.1 1 (Treatment K); Figure 3.12 (Treatment M), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 100 , 12 90 • — m. 10 80 Am 70 8 60 ■ -.m \ 50 6 40 4 30 4k 20 4s 2 10 - 0 Im 0 10 20 30 40 50 10 15 20 25

Time (h) Time (h)

Figure 3.13 Figure 3.14

30 ■ 90 - 4 80 I 25 • ' 70 20 • 60 4 XV W\ 3 40 -h 30 T 20 + 10 - 1 0 e- 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Time (h) Time (h)

Figure 3.15 Figure 3.16

Erosion rates o f L peregra mucus trails over time - Figure 3.13 (Treatment O); Figure 3.14 (Treatment P); Figure 3.15 (Treatment Q); Figure 3.16 (Treatment R), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 50 80 45 % 70 40 60 35 30 50 25 - r 40 20 - 30 ‘V 20 10 la** 0 0 10 20 30 40 50 10 20 30 40 50 Time (h) Time (h)

Figure 3.17 Figure 3.18

90 ; -J 3 70 80 ♦ LH 5 60 1 70 K . 2 50 - Ô

♦ . ; 50 • 3 40 3 30 'à a — ^ Ü 20 ^ i 30 + 2 a: 10 I 2 20 r 0 »- 10 t 0 10 20 30 40 50 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.19 Figure 3.20

Erosion rates o f L pere^^ra mucus trails over time - Figure 3.17 (Treatment S); Figure 3.18 (Treatment T); Figure 3.19 (Treatment U); Figure 3.20 (Treatment V), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 100 90 90 80 80 70 70 60 60 50 40 40 30 - 30 20 2 0 -T 10 ,o | 0 #- 0 #- 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.21 Figure 3.22

'O CT\

S 20

120 Time (h)

Figure 3.23

Firosion rates of' L peregra mucus trails over time - Figure 3.21 (Treatment W); Figure 3.22 (Treatment X); Figure 3.23 (Treatment Y), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 60

é 50

!..

o 30 a. 10 20 30 40 50 Time (h) Time (h)

Figure 3.24 Figure 3.25

80

70 60

50 I, 3 20* 40 *

30 c 10 20 s\ 10 0 80 100 120 0 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.26 Figure 3.27 Erosion rates of P. je n k in s i mucus trails over time - Figure 3.24 (Treatment A2); Figure 3.25 (Treatment B2); Figure 3.26 (Treatment C2); Figure 3.27 (Treatment D2), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). . 60 \ 40 ^ i 50 \ \ 35 - 30 - I . . w i

y if 10 . 0 # 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.28 Figure 3.29

00 S 1 2 : \

Ï 1 0 # 'c . ' I:*' S 4 -

0 #— ' v t - - 0 20 40 60 80 100 120 60 120 Time (h) Time (h)

Figure 3.30 Figure 3.31 Erosion rates of P. je n k in s i mucus trails over time - Figure 3.28 (Treatment E2); Figure 3.29 (Treatment F2); Figure 3.30 (Treatment G2); Figure 3.31 (Treatment 12), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 50 I. . 7% 5 45 i 6É

3 § 'S ' , 2 I ^ 'si ^ *_ 4 * : : 0 —■a A 0 20 40 80 0 10 20 30 40 50 60 100 120 Time (h) Time (h)

Figure 3.32 Figure 3.33

60 *

5 50

| . > 3 30

#20 0 ^ 10 r A % ■A - A - 0 é 40 50 0 10 40 50 “ T.™,h, '°

Figure 3.34 Figure 3.35 Erosion rates of P. je n k in s i mucus trails over time - Figure 3.32 (Treatment J2); Figure 3.33 (Treatment K2); Figure 3.34 (Treatment M2); Figure 3.35 (Treatment 02), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). ô 20

8

I 10 N I s " 0 i 0 20 40 60 80 100 120

Time (h) Time (h)

Figure 3.36 Figure 3.37

90 60 oo 80 o 50 Î t 70 60 ~ 40^t 50 * 30 40 - 30 • 2 20

20 • 10 - 10 • 0 H i % » 20 40 60 80 100 120 10 20 30 40 50 Time (h) Time (h)

Figure 3.38 Figure 3.39 Erosion rates of P. Jenkinsi mucus trails over time - Figure 3.36 (Treatment P2); Figure 3.37 (Treatment Q2); Figure 3.38 (Treatment R2); Figure 3.39 (Treatment S2), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 90 , g 80 I 70 - Ç 6 0 -

I ^“é_ 5 d 20 t 20 -

10 4- 0 #- 20 30 40 50 10 20 30 40 50 Time (h) Time (h)

Figure 3.40 Figure 3.41

60 4 5 - 00 \ 40 j \ 50 - 35 4 \ = 40 30 V 0 25 “ 1 30 b V. 20 20 l o i 10 5 I 0 4- 0 #■ —e -■ I 20 40 60 80 100 120 20 40 60 80 100 120 Time (h) Time (h)

Figure 3.42 Figure 3.43 Erosion rates of P. jenkinsi mucus trails over time - Figure 3.40 (Treatment T2); Figure 3.41 (Treatment U2); Figure 3.42 (Treatment V2); Figure 3.43 (Treatment W2), (see text for details). Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). ^ 10

Time (h)

Figure 3.44

100 1 00 90 to 80 1

70 -■ 60 *

50 r 40 - 30 1 20

10 --

0 20 40

Time (h)

Figure 3.45

Erosion rates o f P. jenkinsi mucus trails over time - Figure 3.44 (Treatment X2); Figure 3.45 (Treatment Y2); Five replicate slides (broken lines) for each treatment, with one control, (represented on all figures by a solid line). 83 only five show any significant differences between species (Treatments E, G, K, M and V). These included treatment E (see Figures 3.5 and 3.28), (mucus examined daily at 20 cm s ', t = 12.75^^^^ P <0.01). That no such difference was found at 10 or

40 cm s ', or at any speed where the sampling interval was increased to every 4 hours suggested that either the mucus of P. jenkinsi has a critical shear stress induced by the current velocity of 20 cm s ', or that this result can be overlooked (see section 3.3.4).

Treatment G also exhibited significant differences between species, where mucus trails are applied to existing trails already coated in marker particles (t = -3.49^^^^ P < 0.05).

No significant differences were detected when the same treatment was sampled at a shorter time interval of 2 hours rather than 4 (treatment P), or where the number of existing mucus layers totalled five rather than one (treatment Q) suggesting that this result is erroneous. In addition, within-treatment analysis for both treatments G (see

Figure 3.7) and G2 (see Figure 3.30), suggested considerable variation among replicates (F = 2.17jf_^ ,g P = 0.103 and F=0.65jf_^ ,g P = 0.666, L. peregra and P. jenkinsi respectively), which is a possible explanation for the differing results between species.

Similarly, the remaining three treatments to exhibit significant differences (K, M, and

V), do so in isolation to comparable and similar treatments (of differing sampling interval or ageing interval). For this reason, it is suggested that differences between these treatments are chance events and may be dismissed. Furthermore, section 3.3.1 shows that within-treatment analysis indicated non-uniform response to certain treatments, (including treatment G) for both species of snail, as well as treatments V

(both species) and treatment K (P. jenkinsi only). 84

Table 3.4

Decay rate (pooled regression coefficient of log transformed data) of STM on 5 replicate glass slides for each treatment.

Treatment L. peregra P. jenkinsi

A 0428' 0.249

B 0.168 0.194

C 0.444 0.462

D 0.969 0.679

E 0.488 0.930

F 0.984 0.997

G 0.703 0.394

H 0.224 No data

I 0.414 0.293

J 0.350 0.126

K &828 0.487

M 0.144 0.340

O 0.091 0.075

P 0.451 0.275 Q 0.762 0.673 R 0.760 0.777

S 0.395 0.390

T 0.445 0.295

U 0.039 0.048

V 0.340 0.695

w 0.671 0.558

X 0.679 0.594

Y 0.024 0.030 85

Far from suggesting that results be dismissed where they are unexplainable or appear erroneous, this illustrates the quantifiable nature of this study. The description of treatments (3.2.1) shows that many treatments act as controls for each other. All

treatments were (in effect) repeated many times with minor variations between them

to allow for the isolation and identification of minor factors that might affect

He physical behaviour of mucus, eg sampling interval, disturbance by conspecifics, loss

of integrity of STM over time, effects of water flow, bacterial degradation etc. For example, in examining the effect upon STM stability caused by sampling interval,

there are a whole series o f complimentary pairs o f treatments that examined the same

phenomenon, but at different sampling intervals (A and Y; J and K; O and W etc).

Each of these pairs o f treatments are also used in other capacities to provide

information on other examination fronts {eg. O and W provide information on the

effect of bacterial degradation, while J and K (when compared with other treatments

acting as controls) offer information on the loss o f the stickiness o f STM as sites of

particle attachment are utilised over time). Unless major differences are noted

between identical treatments of the STM of the two species in this primary

comparison, it is safe to assume that there are no fundamental differences between the

mucus trails of L. peregra and P. jenkinsi.

However, it cannot be assumed that mucus of the two species o f snail w ill behave

identically. The two snails differ from each other considerably in terms of preferred

habitat, life cycle and size. Differences w ill be isolated and identified when specific

comparisons are made (Sections 3.3.3 - 3.3.10). However, the mucus trails of these

two particular species are not only comparable (17 out of 22 comparisons showed no

significant differences), but, because of the considerable differences in physical size,

population density, habitat, diet and behaviour between the two species, may also be

assumed to represent a broad cross section of all available freshwater snail mucus

trails. Comparison of decay rates of STM (mean regression coefficients) for each

treatment (see Table 3.4) reveals a highly significant correlation between STM decay 86 rates for both species. Pearson's correlation gives r = 0.771^^^22’ P<0.00i. Application of Spearman's ranked correlation produces an r value of 1.000^,^22’ P«0.001. This suggests that despite slight individual differences in the decay of STM from two different species when subjected to various treatments (E, G, K, M and V), the STM of these two different species of snails responds in the same way to the various treatments applied.

3.3.3 For how long does snail trail mucus remain sticky?

Table 3.5 Treatments used to determine how long STM remains “sticky’

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

AI Distilled water River water 10 4 Hourly 48 hours

A2 (200 mm) Days 0-2

Cl Distilled water River water 10 Daily Days Particles applied

C2 (200 mm) 6-12 after 6 days

storage in river

water at lOcm/s

11 Distilled water River water 10 Daily Days Particles applied

12 (200 mm) 6-12 after 6 days

storage in still

river water of 5

mm.

Jl Distilled water River water 10 4 Hourly Days Particles applied

J2 (200 mm) 1-3 after 24 hours

storage in distilled

water of 5 mm.

Kl Distilled River water 10 Daily Days Particles applied

K2 water (200 mm) 1-7 after 24 hours

storage in distilled

water of 5 mm. 87

Mucus is often thought of, and occasionally described as "sticky" (Ogren, 1995).

Indeed, an aspect of snail trail mucus of particular interest in my study is its

"stickiness", as a site of particle attachment. Whilst this is a problematic concept to describe, and harder still to quantify, it is an aspect that each chapter of my study has attempted to demonstrate for different materials. This section is concerned with quantifying the longevity of the stickiness of STM.

A stream may be considered as a vehicle for particles, cells, POM and DOM. When a new material such as STM that presents a fresh surface, untouched by particles, is created or introduced within a stream, the new material is instantly bombarded with

such objects as they flow past. Fresh organic material (such as snail trail mucus, created from material otherwise untouched by the POM in the river) has a fixed

surface area, and therefore has a limited number of adhesive binding sites. A number of possibilities may be considered at this stage. Does fresh STM have a fixed surface area on to which particles may attach, or does it have a specified depth into which particles may embed themselves? Over time it may become either coated in attached

material, or spread too thin by cratering to accept and hold any further particles or

POM/DOM. In either case, it is possible to measure the length of time for which it

may be considered sticky.

The loss of stickiness o f snail trails can be measured by ageing mucus trails in various

environments before the application of marker particles. The environments in which

the mucus trails are maintained also give some indication of the physical behaviour

of snail trails.

Where STM is aged in flow ing river water for six days before marker particles were

applied (treatment C), there was a significant difference in the rate of decay from the

control treatment (Y) for both species (t = -3.77^^^^ P < 0.05 and t = -3.21 ^,^4 P < 0.05

for L. peregra and P. jenkinsi respectively). In both cases, the aged mucus has a faster

rate of decay than the fresh mucus, which suggested that the adhesive ability o f the

trail to remain attached to the glass slide had diminished over time. The comparison

of treatment I (see Figures 3.9 and 3.31) against control treatment Y (see Figures 3.23 88 and 3.45), was a further examination of the hypothesis that older mucus decays faster than fresh STM. In this comparison, mucus trails were again aged for six days in shallow still water rather than flowing river water. The difference in depth and water current were the main factors here, and again, a significant difference is found for both species (t = -3.91 P < 0.05 and t = -7.15jf^4 P < 0.01 for L. peregra and P. jenkinsi respectively). Once again, the aged mucus decayed in its attachment to the glass slide at a faster rate than the fresh mucus (see Table 3.4 for rates o f decay of STM for each treatment).

What is interesting about these two comparisons is not so much the confirmation that aged mucus trails are less adhesive, but that storage, or ageing, in shallow water, accelerates decay to a greater extent than does storage in deep flowing water. This suggests that water depth plays a part in the integrity of snail mucus trails, and is a concept that w ill be more fully examined in section 3.3.6.

In order to further examine the effect of ageing upon mucus trails, comparison was made between treatments A (see Figures 3.1 and 3.24) and J, both of which were sampled every 4 hours over 48 hours, A being fresh mucus trails, J (see Figures 3.10 and 3.32), being 24-hour-old mucus trails. Significant differences were not detected for either species (t = - 2 .33jf^4 P = 0.102 and t = 1. 88 j ^=4 P = 0.109 for L. peregra and

P. jenkinsi respectively). This suggests that 24 hours is not a long enough ageing period to make a difference, but that the critical time period is between 24 hours and six days. However, comparison of treatments Y and K, where mucus was sampled on a daily basis, and where treatment K (see Figures 3.11 and 3.33) had been aged fo r

24 hours, significant differences are detected for both species (t = -15.29jf^4 P < 0.01 and t = - 5.77j ,-^4 P < 0.01 for L. peregra and P. jenkinsi respectively). This suggested that the speed of sampling or rather sampling interval is a factor of greater importance in measuring the decay o f mucus trails. This issue w ill be explored more thoroughly in section 3.3.4. Furthermore, these comparisons illustrate that 24 hours is a sufficient time to detect a significant decrease in the adhesive quality of snail trails to their underlying substrate. 89

3.3.4 The effect of water speed upon snail mucus trail integrity

Table 3.6 Treatments used to determine the effect of current velocity on

STM

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

El Distilled water River water 20 Daily 6 Days

E2 (200 mm) Days 0-6

FI Distilled water River water 40 Daily 6 Days

F2 (200 mm) Days 0-6

51 Distilled water River water 40 4 Hourly 48 Hours

52 (200 mm) Days 0-2

T1 Distilled water River water 20 4 Hourly 48 Hours

T2 (200 mm) Days 0-2

Yl Distilled water River water 10 Daily 6 Days

Y2 (200 mm) Days 0-6

Water velocity is a controlling factor on erosion and deposition, as well as the growth of, or retention of material. Responses of periphyton to water velocity have been

found to be accrual of material at up to 60 cm s ‘, with loss above that velocity

(Horner et al., 1990). The decay of pedal mucus o f Patella vulgata (L.) is dependent

on water movement, as well as the period of the drying and re-hydration cycle (Davies

et al., 1992a). It is reasonable to assume, therefore, that less robust, or less persistent,

freshwater STM w ill also be affected by water movement (Chapter Two demonstrates

that freshwater STM lasts for up to 6 days, while Davies et al., (1992b) showed that

limpet pedal mucus can last for up to 80 days). The freshwater equivalent of wave

action as an erosive force is current velocity. Most treatments within this study were

subject to a fixed speed of 10 cm s ', approximately equivalent to the River Frome or

Wool Stream (P. Armitage and S. Clough, pers. comm.), from which the study

organisms were collected. However, the effect o f current velocity is an important one.

Current velocity cannot be assumed to be constant, and rarely is in lotie conditions.

Accordingly, as this study progressed and fresh treatments were devised to explain 90 hypotheses raised by examination of preceding treatments, so studies were set up to examine the decay rate of mucus trails at 20 and 40 cm s ' (E and T, F and S) examined at daily and 4 hourly intervals (E and F, S and T).

Comparisons between treatment Y (control at 10 cm s ') and treatments E and F (see

Figures 3.5 and 3.28, 3.6 and 3.29) made on a daily basis, illustrated that the decay rate of mucus was increased by a greater water velocity for the mucus trail of both species of snail, (t = -20.41 P < 0.01 and t = -32.88^^^^ P < 0.01 for L. peregra and

P. jenkinsi respectively comparing 10 to 20 cm s '; t = -92.35jf^4 P « 0.01 and t = -

893.29jf^4 P « 0.01 for L. peregra and P. jenkinsi respectively comparing 10 to 40 cm s '). Additionally, the decay rate was fastest at 40 cm s ' and slowest at 10 cm s ' for both species (see Table 3.4).

By decreasing the sampling interval from 24 hours to every 4 hours over 48 (thus increasing the number o f samples taken) the results were quite different. Significant differences were still found between 10 and 40 cm s ' treatments for both species (t

= -5.86 j ,^4 P < 0.01 and t = -3.14^^^4 P < 0.05 for L. peregra and P. jenkinsi respectively), but at 20 cm s ', only the mucus of L. peregra exhibits significant differences (t = -3.193^f^4 P < 0.05). The fact that no significant difference was found at 20 cm s ' for P. jenkinsi cannot be explained (see section 3.3.1). At this sampling interval, mucus decay rate was fastest at 40 cm s ', slowest at 10 cm s ' for P. jenkinsi only, yet for L. peregra the decay rate was marginally faster at 20 cm s ' than at 40 cm s '.

These results suggest that the decay rate o f mucus trails may be influenced by the sampling interval. This possibility, including the comparison of treatments of similar water velocities over differing sampling regimes will be examined in section 3.3.5. 91

3.3.5 The effect of sampling and snail action as disturbance events

Table 3.7 Treatments used to determine the effect of sampling and snail

action as disturbance events

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

Al Distilled water River water 10 4 Hourly 48 hours

A2 (200 mm) Days 0-2

Bi Distilled water River water 10 2 Hourly 24 hours

B2 (200 mm) Days 0-1

El Distilled water River water 20 Daily 6 Days

E2 (200 mm) Days 0-6

FI Distilled water River water 40 Daily 6 Days

F2 (200 mm) Days 0-6

Gl Distilled water River water 10 Daily 6 Days Mucus re-applied

G2 (200 mm) Days 0-6 to particle-coated

mucus layer

Jl Distilled water River water 10 4 Hourly Days Particles applied

J2 (200 mm) 1-3 after 24 hours

storage in distilled

water of 5 mm.

Kl Distilled water River water 10 Daily Days Particles applied

K2 (200 mm) 1-7 after 24 hours

storage in distilled

water of 5 mm.

01 Distilled water River water 10 4 Hourly 48 Hours

02 plus antibiotic (200 mm) Days 0-2

PI Distilled water River water 10 2 Hourly 24 Hours Mucus re-applied

P2 (200 mm) Days 0-1 to particle-coated

mucus layer

Ql Distilled water River water 10 Daily 6 Days 5 alternate layers Q2 (200 mm) Days 0-6 of mucus and

particles 92

Te.st Mucus laid in: Mucas Flow rate Sampling Sampling Other comments maintained in (cm/s) frequency duration (depth):

51 Distilled water River water 40 4 Hourly 48 Hours

52 (200 mm) Days 0-2

Ti Distilled water River water 20 4 Hourly 48 Hours

T2 (200 mm) Days 0-2

Ui Distilled water Distilled water 10 4 Hourly 48 Hours

U2 plus antibiotic Days 0-6

(200 mm)

VI Distilled water Distilled water 10 Daily 6 Days

V2 plus antibiotic Days 0-6

(200 mm)

Wi Distilled water River water 10 Daily 6 Days

W2 plus antibiotic (200 mm) Days 0-6

Yl Distilled water River water 10 Daily 6 Days

Y2 (200 mm) Days 0-6

Results of previous sections have suggested that in order to quantify the treatments used within this study, it is essential to identify the effect that sampling interval had upon the integrity of the STM. A glass slide is not a surface commonly available to freshwater snails within their natural environment. Therefore, the use of such material for the handling and examination of mucus imposed certain constraints. Glass slides were selected for their ease o f manipulation, availability and sim ilarity to materials used in similar studies (Davies et al, 1990 a and b, Davies et al., 1992 a, b and c).

However, it would be beneficial to our understanding of the properties of STM to identify the effect that every experimental factor might have upon the material studied.

Preliminary trials suggested that for the species under examination, the time interval of greatest mucus decay was the first 48 hours. Accordingly, trials were designed to examine the integrity of mucus over 48 and 24 hours. However, in order to provide greater detail of the decay o f mucus within a shortened time scale, a greater number of shorter sampling intervals were required. Such an increase in sampling intervals

must be accounted for, as the decay of mucus may be an artifact of the disturbance to the mucus on the glass by the sampling procedure. / 93

Sampling is potentially a destructive procedure, as STM attached to the surface of a glass slide is lifted from the water, it is subjected to a variety of different angles of incidence of current. The slide is then placed on a warm microscope examination stage, under-lit by a bulb, which causes drying of the mucus trail. Réintroduction of the slide to the water current after examination repeats the potential disturbance before the slide is placed firm ly back, flat on the base of the channel within the boundary layer of the current velocity, described by Hynes (1970).

It was noted by Davies et al., (1992a) that dehydration and re-hydration does not affect the adhesiveness o f limpet pedal mucus, and that integrity remains unaffected, so long as dehydration is not total. However, such a statement was subjective rather than measured, and cannot be assumed to apply to freshwater pedal mucus. Therefore, for the purposes o f this study, sampling must be assessed in terms o f the degree of damage it causes to STM integrity.

Accordingly, all comparable treatments over 6 days and 48 or 24 hours were analysed for differences in the rate of decay of STM, regardless o f the individual aspect that each treatment was designed to test. It was found that sampling interval can indeed have an effect. The proportion of mucus lost per sampling interval was significantly greater at 4 hourly intervals than at 24 hourly intervals (t = -10.31 P < 0.01 for L. peregra, t = -5.73^^^^ P < 0.01 for P. jenkinsi when comparing treatments A against Y for each species). However, when the sampling interval was decreased to every two hours, the proportion lost per sampling interval diminished, resulting in no significant difference between treatments B (see Figures 3.2 and 3.25) and Y for either species

(t = -2.34jf^4 P = 0.100 and t = -5.03^f^4 P = 0.150 for L. peregra and P. jenkinsi respectively). Treatment Y (control treatment where mucus is examined daily for six days, secreted in distilled water, maintained in river water at 10 cm s ') exhibited the slowest rate of mucus decay for either species when compared to any other treatment. 94

In addition to this conflicting evidence, the remaining comparisons appropriate to this aspect of this study all illustrated that sampling interval has no effect upon the decay o f mucus. Comparison of treatments J and K (where mucus was held for 24 hours in distilled water prior to the application of particles, J examined daily, K examined every 4 hours) found that the decay rate o f treatment K was significantly greater than that of treatment J (t = -3.70^^^^ P = 0.005 - one tailed), the two treatments also being significantly different from each other (t = -3.70^^^^ P < 0.05 - two tailed). This was not the case for the mucus of P. jenkinsi (t = -4.18jf^4 P < 0.01 - one tailed) for the decay rate of K being faster than J. However, the treatments decay rates do differ significantly, (where t = -4.18P < 0.05 - two tailed). Similarly, treatments F and

S; E and T (where mucus is subject to accelerated water speed (40 and 20 cm s ' respectively) showed that sampling interval had no effect. Those treatments subject to a greater sampling frequency exhibited the lowest rate of mucus trail decay

(Treatments S (see Figures 3.17 and 3.39) and F differed significantly, where t = -

12.31,1,^4 P < 0.01 for L. peregra and t = -9A6^f^4 P < 0.01 for P. jenkinsi. Treatments

E and T (see Figures 3.18 and 3.40) for P. jenkinsi also differ significantly where t =

14.59j,^4 P « 0.01). However, the same treatments applied to the mucus trails of L. peregra exhibited almost no difference, with a two tailed Student's t-test between the treatments giving P = 0.990 (t = 0.02^^^^), illustrating that sampling interval played no part in the rate o f decay of snail mucus trails of these two species.

Furthermore, comparison of treatments O (see Figures 3.13 and 3.35) and W (see

Figures 3.21 and 3.43), (where mucus was secreted in distilled water dosed with an antibiotic and subsequently maintained in unfiltered river water, examined at daily (W) and four hourly (O) intervals), were not significantly different from each other (t =

1-84j,^4 P = 0.139 and t = 0.681^f^4 P = 0.526 for L. peregra and P. jenkinsi respectively). They did however illustrate a slower rate of mucus decay for that treatment examined every 4 hours rather than every day for the mucus o f both species.

Finally, comparison of treatments U (see Figures 3.19 and 3.41), and V (see Figures 95

3.20 and 3.42), where mucus was secreted in water dosed with an antibiotic and maintained in water dosed with an antibiotic to prevent bacterial proliferation and subsequent decay of snail trails, examined daily (V) and every 4 hours (U), also exhibited a slower rate o f decay for treatment U, the more disturbed or more sampled treatment (treatments were significantly different from each other, t = -8.85^^=4 P <

0.01 for L. peregra and P. jenkinsi, t = P < 0.01). Sampling interval or the number of samples taken therefore seems to have an effect depending on the prior treatment of the STM. In this case, ageing and maintenance in antibiotic solution does cause a difference in the rate o f decay o f STM (see also section 3.3.9).

The effect of snails on their own mucus trails was examined using treatments G, P and

Q. Treatments G and P were essentially the same, albeit at different sampling intervals, where mucus trails were secreted upon a glass slide, marker particles applied and mucus trails reapplied again, creating in effect a mucus trail sandwich of marker particles. Treatment G was examined daily, treatment P (see Figures 3.14 and 3.36), every 2 hours over 24 hours. Differences between the rate of decay of these treatments and treatment Y (control) indicated the ability of snails to disrupt their own trails, raising the question of whether snails automatically lay fresh trails, or whether they utilise existing mucus trails. Significant differences were noted between treatments Y and G for both species (t = -9.54^^^^ P < 0.01 and t = - 7.68 jf^4 P < 0.01 for L. peregra and P. jenkinsi respectively), suggesting that snails do indeed disturb their own trails when covering the same ground. The same comparison when made over a shorter time scale showed no significant differences for L. peregra, (t = -1.59 jf^4

P = 0.210), but significant differences for P. jenkinsi (t = -3.32jf^4 P < 0.05) suggesting

that the mucus trails o f L. peregra were more tenacious and less prone to conspecific

disturbance than were the mucus trails o f the smaller snail.

Such tests raise the question of whether mucus trails act as a sealant to the substratum,

and specifically to existing STM? For instance, if STM is repeatedly overlain, would 96 particles be trapped in between layers of mucus? Furthermore, would the original trails be preserved beneath the uppermost layer o f mucus? Or, would the layering of mucus trails cause the structure to be unstable and therefore more prone to erosion?

Accordingly, a series of five alternate layers of snail mucus and marker particles were prepared for each species (treatment Q) (see Figures 3.15 and 3.35), and compared to treatment Y (the control). In both cases significant differences were found between the two treatments, whereby treatment Q exhibited a greater rate of decay than treatment Y (t = -1.91 P < 0.01 and t = -5.73^^^^ P < 0.01 for L. peregra and P. jenkinsi respectively). This suggested that snail mucus trails not only cause disturbance of existing layers o f mucus and particles by the overlying layer of mucus, but that the mixture of mucus and particles which does remain w ill be weakened in their hold upon the surface on which they were secreted. Finally, comparisons were made between treatments G and Q to examine the effect of multiple layers of snail mucus trails. No significant differences were found for either species, illustrating that snails were disruptive o f existing mucus trails, regardless of the amount or depth of existing mucus, (t = -0.69P = 0.513 and t = -1.93 P = 0.101 for L. peregra and

P. jenkinsi respectively). This suggested the possibility that wherever snails meet existing trails, they are pushed aside, or apart, as the foot of the snail glides through rather than across. Such a hypothesis was confirmed by observing snails under low power microscopy, using sediment as markers of trails. 97

3.3.6 The effects of ageing, water depth and airborne bacteria upon

snail trail mucus longevity

Table 3.8 Treatments used to determine the effects of ageing, water depth

and airborne bacteria on STM

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

Cl Distilled water River water 10 Daily Days Particles applied

C2 (200 mm) 6-12 after 6 days

storage in river

water at 1 Ocm/s

Di Distilled water Distilled water 0 Daily 6 Days

02 (5 mm) Days 0-6

11 Distilled water River water 10 Daily Days Particles applied

12 (200 mm) 6-12 after 6 days storage in still

river water of 5

mm.

Rl Distilled water Distilled water 0 Daily 6 Days

R2 (200 mm) Days 0-6

XI Distilled water Distilled water 0 Daily 6 Days

X2 plus antibiotic Days 0-6

(5 mm)

Mucoglycoproteins present in vertebrate mucins are known to bind to bacteria and vice versa (Hata and Pick, 1991; Nilius et al., 1994), possibly via the inclusion within

mucins of ligands (Fang et al., 1993, Irache et al., 1994). Specifically, compounds known as adhesins within bacterial membranes bind to unidentified receptors within

mucus or mucus-secreting cells (Widdicombe, 1995). Such processes are of interest

to the medical research industry where the specific attachment of bacteria to mucus,

or particles to the respiratory mucus membranes, is of great concern to those studying

cystic fibrosis, respiratory mucus etc (Wang et al, 1996; Deneuville et al, 1997).

However, bacteria, spores and airborne particles, are rarely considered in freshwater

biology. Airborne bacteria (or more importantly, spores) generally originate from 98 another source such as soil, leaf litter or faecal material. Such sources may provide an increase in bacterial density surrounding the habitats of freshwater snails. If the effects of waterborne-bacteria and bacteria from the mucus producer are to be assessed, then so too must airborne entities. Furthermore, some of the treatments designed to assess the impact of potential mucus degraders from the air w ill also provide information on the importance of water depth to the preservation of snail trails. The primary consideration regarding water depth for bacteria is ease of penetration (see section 3.3.3). It is to be expected that shallow water is easier to access in order to reach the nutrient-rich mucus trail at the bottom of the water column, than is deeper water. By the same reasoning, still water should be easier to access than moving water as water currents and boundary layers w ill not affect deposition.

Treatments D (see Figures 3.4 and 3.27) and I compared fresh mucus, maintained in still shallow water against mucus that had been stored in shallow water for six days before being subjected to a water current of 10 cm s '. These two treatments were therefore a comparison of the effect of ageing on mucus integrity. Surprisingly, a significant difference is found only for L. peregra (t = 6.85^^^^ P < 0.01; t = 2.97 ^,^4

P = 0.059 for P. jenkinsi), although it could be argued that the latter result is "almost significant". This suggests that the effect of ageing is o f lesser importance to the smaller species.

The second comparison featured treatments D and R (see Figures 3.16 and 3.18), where fresh mucus trails maintained in shallow water were compared to fresh mucus trails maintained in distilled water of standard depth. This highlighted the lack of significance of water depth to bacteria. Once again, a significant difference was found only for the mucus trails o f L. peregra (t = 4.36j^^4 P < 0.01, t = P = 0.798

for P. jenkinsi). This presents the additional hypothesis that the mucus trails o f the

larger snail contain degradative bacteria as they are secreted (see section 3.3.7). From

these results, the influence of water depth did not appear to be significant to mucus

longevity. 99

Comparison of treatments I and R combined the effects of ageing and water depth.

Significant differences were found for both species (t = -4.38^jf^4 P < 0.01 and t = -

4 .66jf^4 P < 0.01 for L. peregra and P. jenkinsi respectively), when aged mucus trails subject to contamination from airborne organisms were compared to fresh mucus, secreted in a normal depth of still water. W hile the effects o f water depth cannot be completely eliminated, the predominant factor here was the effect of age.

The effect of airborne bacteria on the mucus decay rate, where water was shallow and still, was examined by comparison of treatments D and X. No significant difference was found between treatments illustrating that the penetration o f water masses and subsequent utilisation o f food sources by bacteria was insignificant within this time scale (t = 2.75jr^4 P = 0.071 and t = 0.60j(^4 P = 0.568 for L. peregra and P. jenkinsi respectively). This was confirmed by comparison of treatments R and X, both in still water of variable depth, the shallow treatment (X) was dosed with an antibiotic. Some difference would be expected, if only because treatment X (see Figures 3.23 and 3.44), is maintained in an effectively sterile environment. However, no significant differences were found (t = 0.77^,^4 P = 0.471; t = 0.97j^^4 P = 0.367 for L. peregra and P. jenkinsi respectively), confirming that water depth and the presence o f airborne bacteria have no significant effect upon the integrity of snail trail mucus.

The effect of ageing was once again examined by comparison o f treatments I and X.

In addition, the factor of ageing was combined with depth, current and the potential of airborne bacteria to accelerate mucus degradation. Mucus trails were secreted and

stored in still river water of shallow depth for six days before introduction to a water current in treatment I. Treatment X examined fresh mucus trails from shallow water

dosed with an antibiotic to prevent bacterial proliferation. Despite the considerable

number and combination of factors potentially detrimental to the integrity of snail

mucus trails, significant differences are noted only for L. peregra (t = -2.68 j ^=4 P <

0.05; t = -2.14j,^4 P = 0.122 for P. jenkinsi). This confirmed that airborne bacteria do

not affect the integrity o f mucus trails, and that the difference observed was most

likely due to the inclusion o f snail borne bacteria from the larger species of snail only.

(In Chapter 6, the attachment of bacteria to STM, and the inclusion of bacteria within 100

STM is examined in more detail).

Finally, by comparison of treatments C (see Figures 3.3 and 3.26) and I, the effects of water depth combined with ageing of mucus were examined. Aged mucus trails, stored in a water current o f 10 cm s ' at normal depth were compared to mucus trails aged in still shallow water. No significant differences were found for either species

(t = 0.66jf^4 P = 0.528 and t = 1.13P = 0.340 for L. peregra and P. jenkinsi respectively) after they shared the common factor of ageing, illustrating that neither water depth nor airborne contaminants were of specific concern to the study of the decay of mucus trails. Either because too few airborne organisms exist to cause serious contamination o f the mucus trail, or because airborne organisms are not suited to the freshwater environment - airborne organisms make no appreciable difference to the behaviour of freshwater snail mucus trails. Therefore, the depth of water overlying the mucus trail is immaterial, as long as the trail remains fu lly hydrated.

3.3.7 The distribution mechanism o f snail trail mucus and the effect

upon it of waterborne consumers of mucus

Table 3.9 Treatments used to investigate the mechanism of distribution of

STM and its effect on waterborne consumers of mucus

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

AI Distilled water River water 10 4 Hourly 48 hours

A2 (200 mm) Days 0-2

M l Unflltered river River water 10 4 Hourly 48 Hours

M2 water (200 mm) Days 0-2

Snails produce mucus from point source glands on the underside of the foot (Denny,

1980). This secretion is then shaped by the foot to form a sheet across which the

snail moves. The expansion of pure mucus when exposed to water was demonstrated

by Downing et ai, (1981), raising the question as to whether or not mucus

incorporates material as it expands, and what subsequent effect such material might 101 have upon the integrity of mucus.

The examination of the degradation of snail trail mucus caused by bacteria or other waterborne organisms is a complicated issue. Degraders o f STM can arise from more than one source. They w ill be present in the river water in which a snail secretes its mucus trail, and so may attach, or attack, from the surface o f the STM. They may also be incorporated from the surrounding stream water into the STM as the mucus expands and is spread by the pedal musculature from one o f the point sources of secretion (goblet cells in the underside of the gastropod foot). Lastly, bacteria may be incorporated into the STM from the snail itself, either from the underside o f the foot, or from the deposition of bacteria-rich faecal pellets onto the mucus trail, (See

Chapter 6 of this study), which may, in turn, reduce, or enhance, the durability o f the snail trail. This particular section of this study sought to determine whether ambient material was incorporated during the expansion of snail mucus from a point source secretion into the sheet like structure that enables locomotion. It was hypothesised that the incorporation o f such material would assist degradation of the snail trail.

Therefore, snails were allowed to produce trails in sterile, filtered water (the control, where foreign material can only originate from the foot of the snail), and in unfiltered river water. The sterile, filtered water had undergone reverse osmosis to remove

micro-particulates, filtration at 0.2 jam to remove bacterial cells, ion exchange to

remove ions, and was used only when at 16.5 M i2 resistivity (an indication o f ion

removal). No significant differences were found between this treatment against the control for either species, suggesting either snail mucus does not incorporate foreign

ambient material as it expands or is shaped into a flat sheet, or that such material has

no effect upon the degradation of the mucus trail, (t = -0.71^^^^ P=0.504 for L. peregra,

t = - 1.86 jf^4 P = 0.110 for P. jenkinsi when comparing treatments A against M for

each species), (see Figures 3.12 and 3.34). 102

3.3.8 Snail gut bacteria and mucus trails

Having demonstrated that ambient material is not incorporated into the snail mucus trail as it is secreted, it was necessary to investigate the fate of material incorporated into the trail from the snail itself. Foreign material that could be included in a snail trail may derive from two possible sources. The first is the underside of the foot, which may contain material from the surface the snail has previously traversed. The second potential source o f foreign material is the snail gut. Faecal pellets are continually excreted by snails, and are often deposited on their own mucus trail , or that of conspecifics, allowing the incorporation of viable excreted bacterial cells into the mucus trail.

Table 3.10 Treatments used to assess the effect of snail gut bacteria on

STM

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

VI Distilled water Distilled water 10 Daily 6 Days

V2 plus antibiotic Days 0-6

(200 mm)

W i Distilled water River water 10 Daily 6 Days

W2 plus antibiotic (200 mm) Days 0-6

The potential influence of snail gut bacteria upon the integrity of the mucus trail is a complicated issue. It is argued in Chapter Six that snail mucus trails provide the ideal environment for the early stages o f biofilm colonisation for certain species of bacteria.

However, the aim of this section of the study was to determine if those bacteria contribute polysaccharide material toward the integrity of the mucus trail, or release enzymes that assist in the degradation of the snail trail.

Treatments V and W were compared, where mucus trails were secreted in distilled water dosed with an antibiotic. This served to inhibit bacterial growth on the outer surface of the snails, and also within the environment in which mucus was laid. They 103 were subsequently maintained in either distilled water dosed with an antibiotic (to prevent growth and development of bacteria laid within the mucus trail - Treatment

V) or maintained in unfiltered river water (Treatment W). Both treatments were maintained in a water current of 10 cm s ' and sampled daily.

No significant differences were found between treatments for P. jenkinsi, (t = I 20^^^^

P = 0.274). However, the decay rate of mucus trails o f L. peregra were significantly different and (t = -5.28 P < 0.01), with the decay rate o f treatment V approximately half that of treatment W (See Table 3.4). This suggested that mucus trails of the larger species of snail included bacteria from the snails body-surface or gut that would disrupt the integrity of the mucus trail. This trial did not account for the potentially disruptive effect of airborne and river waterborne bacteria (shown to be negligible in section 3.3.6); however, it did demonstrate the effect that gut-dwelling bacteria have upon the mucus trail within which they are deposited. That this applied to one species only is o f particular interest, suggesting either the mucus o f P. jenkinsi is less prone to bacterial attack, or that it supports a different range of gut and body surface microflora bacteria, dependant on its food source.

3.3.9 Waterborne bacteria as consumers of snail trail mucus

Table 3. Treatments used to assess the effect of waterborne bacteria on

STM

Test Mucus laid in: Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

AI Distilled water River water 10 4 Hourly 48 hours

A2 (200 mm) Days 0-2

01 Distilled water River water 10 4 Hourly 48 Hours

02 plus antibiotic (200 mm) Days 0-2

Ui Distilled water Distilled water 10 4 Hourly 48 Hours

U2 plus antibiotic Days 0-6

(200 mm) 104

The ability of microalgae to adhere to mucus trails has been demonstrated by Davies and W illiams (1995) and Davies et ciL, (1992a) among others. Furthermore, the utilisation of the carbohydrate component of limpet mucus trails has been demonstrated by Peduzzi and Herndl (1991), where bacterial numbers were found to be significantly enhanced wherever snail mucus trails were secreted. This section examines the hypothesis that waterborne bacteria w ill adhere to and consume freshwater STM.

The effect of bacteria and other cells upon the integrity o f the mucus trail where such cells are laid within the snail trail have been examined (Section 3.3.7 and 3.3.8).

However, the medium in which freshwater snail mucus trails are laid is teeming with

(among others), bacteria, algae and fungal spores. The effect of these organisms was examined by comparison of treatments A, O and U, all of which were sampled every

4 hours over 48 hours. Treatment A involved the laying of mucus in distilled water, and its maintenance in unfiltered river water, compared to treatment O where mucus was secreted in distilled water dosed with an antibiotic, and subsequently maintained in unfiltered river water. Finally, treatment U consisted o f mucus secreted in distilled water, and maintained in distilled water dosed with an antibiotic. The current velocity for all three treatments was 10 cm s '.

The comparison of treatments A, O and U, should illustrate the influence of snail gut bacteria upon mucus trail integrity. Comparisons were made between the three treatments to assess the effect of waterborne bacteria and other organisms,

(detrimental, or beneficial to STM), on the mucus trail. The effect of river water organisms upon STM was assessed by comparison of treatment A (control) against treatment U, where snail trails are protected from the growth of river organisms, post

STM production, in an environment hostile to the growth of bacteria. Significant differences are detected for both species, confirming that river organisms do have an effect on mucus trail integrity, in both cases serving to accelerate the decay of mucus

trails (t = 7.25jf^4 P < 0.01 for L. peregra and t = 4.31^f^4 P < 0.01 for P.jenkinsi). 105

To establish the effect (if any) o f the incorporation of STM disrupting organisms, either from the snail body, or any other source, comparison is made between treatments O and U, where mucus is secreted in a sterile environment and maintained in a non-sterile one and vice versa. A significant difference is detected for L. peregra only (t = 3.47jf^4 P < 0.05, t = 0.84^f^4 P = 0.435 for P. jenkinsi). This suggested a fresh hypothesis; that either L. peregra carry far larger quantities of STM disrupting bacteria, or that P. jenkinsi are far more efficient at scouring conspecifics shells for biofilm , thus removing any bacteria during the preparative starvation o f the snails (as per observations during these trials). It may also suggest that the mucus trails of P. jenkinsi are in some way more densely bound, perhaps less hydrated and therefore less susceptible to bacterial attack.

In order to confirm the hypothesis that the STM of L. peregra is more vulnerable to bacterial decomposition, comparison was made between treatments A and O, where mucus is secreted in a sterile environment, but subsequently maintained in river water, full of material now known to be detrimental to the integrity of mucus trails. If the mucus trails o f P. jenkinsi really were less susceptible to bacterial attack, then a significant difference should only be found for the larger snail (L. peregra). However, a significant difference is found only for P. jenkinsi (t = 4 .43^f^4 P < 0.01 ; t = 1.85j^^4

P = 0.113 for L. peregra), refuting the notion that the mucus trail of either species of snail is more or less susceptible to bacterial degradation. Instead, these tests showed that organisms within the water column assist the degradation of snail mucus trails, but there is no tangible evidence to support the concept that these organisms are

incorporated within the mucus trail as it is secreted. In addition, comparison of treatments O and A, also illustrates the benign effect of the antibiotic used, upon the

integrity of STM. 106

3.3.10 The protection offered by surface relief in freshwater systems

Table 3.12 Treatments used to assess the protection afforded to STM by

the relief o f a surface

Test Mucus laid in; Mucus Flow rate Sampling Sampling Other comments

maintained in (cm/s) frequency duration

(depth):

HI Distilled water River water 10 Daily 6 Days Mucus applied to

only (200 mm) Days 0-6 established biofilm

Yi Distilled water River water 10 Daily 6 Days

Y2 (200 mm) Days 0-6

It is known that snails graze biofilm-covered surfaces (Lopez and Levington, 1978), and actively harvest bacterial acquisitions to their own mucus trails. Established

biofilm s tend to be rough, uneven surfaces (Lock et al., 1984), as opposed to the comparatively smooth surface o f a glass slide used in my study. The differences

between the two surfaces raises questions^what effect a biofilm layer underlying a

snail trail w ill have on STM. For example, it is possible that the presence o f a biofilm

layer may increase the longevity o f the mucus trail by affording a greater surface area

of considerably greater detail and varied profile. The presence of an established

biofilm will also effect the stability of STM by affording greater protection in the

troughs and dips of its surface, yet may also raise the STM to a different depth within

the benthic boundary layer. Alternatively, the smothering (if not grazing) of the

biofilm layer may result in the starvation of the biofilm and subsequent detachment

of that layer from the underlying glass slide. For these reasons, this section is an

examination of the effect of the presence of biofilm beneath STM.

Accordingly, glass slides were allowed to condition for six months in the River Frome

until they were coated in biofilm . By observation and manipulation of the snails, they

were allowed to graze the biofilm , but were prevented from removing the biofilm

completely at any location. Unfortunately for this trial, only one species of snail (L.

peregra) was available. Furthermore, only three experimental slides were recovered,

due to losses of slides to the water current within the river. B iofilm takes about 6 107 months to become established and completely cover a glass slide in the River Frome, and despite starting with over 20 glass slides, attached to house-bricks, using rubber bands, only three slides remained in a usable state for this section of the study.

Significant differences were found between the control and treatment group, suggesting that biofilm does lend additional stability to a snail mucus trail, (t = -22.91 P <

0.01 for L. peregra comparing treatments Y against H), (see Figure 3.8).

3.3.11 Identified properties o f the mucus trails of each species

There were a number of similarities between the treatments described for the mucus trails of the two species chosen. O f the twenty-three treatments, differences were found between species in only five of those treatments. These differences are not considered significant for reasons described in section 3.3.2. This does not suggest that all freshwater snail mucus trails would behave in a similar fashion, or that mucus of the two species studied here is identical, but it does illustrate that snail mucus is a material that may be examined and which will provide measurable responses.

The length of time for which snail mucus trails remain "sticky" is a difficult question to answer. It was observed in my preliminary studies, that mucus trails may remain attached to glass slides in tanks occupied by chironomid larvae, for up to 12 days, and w ill withstand the flow o f river water at 10 cm s ' for up to 10 days. However, studies described in section 3.3.3 and 3.3.6 show that mucus loses its ability to hold and retain marker particles from the time o f secretion onwards. The greatest decay occurs within the first 48 hours. For an accurate description o f the rate of decay of mucus (loss of stickiness over time), decay rates are quoted for each treatment in

Table 3.4. Essentially, mucus becomes conditioned, or loses its ability to remain attached to the surface on which it was secreted, relative to other factors that affect

its integrity.

The effect of water velocity upon the tenacity of snail trail mucus is a destructive one.

In general, the faster the current of water, the greater the rate of decay of the snail

trail. Mucus trails are subject to disturbance by the sampling procedure employed, but 108 were not found to be significantly affected. Sampling by the methods described may therefore, be considered non-destructive. However, the snails themselves were found to have a disruptive effect on conspecific mucus trails. This was more noticeable in the trails of P. jenkinsi than L. peregra which is consequently thought to produce a more robust mucus trail. The surface on which a mucus trail is secreted also plays a part in the subsequent decay rate o f that trail. Experiments where trails were secreted on to established biofilm (uneven, possibly sticky surface) increased the longevity of mucus trails, suggesting that relief from current scour is offered by an uneven surface, or even that chemical bonding takes place between the STM and the biofilm .

Three sources of bacteria were examined for their role in the decay o f STM, (air­ borne, water-borne, and bacteria from faecal pellets and/or from the snails foot). The depth of water overlying a mucus trail was found to be unimportant, suggesting that airborne bacteria, cells or other particles, play no part in the decay o f snail trail mucus. The incorporation of cells, bacteria or other particles into mucus as it is secreted is also found to be negligible. Snails do incorporate viable bacterial cells into their trails, and observations of trail development reveal the incorporation of faecal pellets (see Chapter Six). This suggests that mucus is spread from a point source secretion which is shaped into a sheet by the musculature of the gastropod foot, expanding and hydrating to incorporate ambient material as it does so (Downing et ai,

1981). Differences in the rate of decay o f STM between species due to the inclusion of faecal bacteria suggests that such a viable excreted bacteria are species and possibly diet specific. Finally, bacteria within the water column are shown to facilitate the degradative processes that result in the detachment of mucus trails from the surface on which they are secreted. Neither species was more prone to such attack, although

the mucus of L. peregra does contain larger quantities of bacteria that were detrimental to the integrity o f STM. Alternatively, the STM of L. peregra, is less tightly configured, and so more vulnerable to bacterial enzymic digestion in the same way that bacterial exopolymer secretions (EPS) can vary in its density and hence in its

susceptibility to digestive attack (Decho and Lopez, 1993). 109

3.4 Conclusions

STM from the two species of freshwater snail studied, responds to the treatments described, in the same way. Considering the differences between species, this is an indication of the relevance of this study's results to all freshwater polysaccharides.

However, the STM of L. peregra is more prone to disturbance by conspecifics and bacterial attack, suggesting a looser, less tight structure to the STM of this species.

Older mucus decays faster than fresh mucus. Such a phenomenon is noticeable after

24 hours, but decay is accelerated with respect to age.

Sampling interval was found to have no effect on STM longevity or integrity.

Water velocity is a factor in the durability of STM. Greater velocity over the trail, providing greater scour or bombardment of particles, will effectively shred the mucus trail.

There is no evidence to suggest that waterborne material is incorporated into STM as it is secreted and spread. I f incorporation of material does take place, it has no effect on the longevity of STM. Stream water bacteria assist the degradation of snail mucus trails. Airborne bacteria, and hence, water depth, have no measurable impact on STM

longevity.

Snails disturb conspecifics STM, by ploughing through, rather than gliding over, existing trails.

As mucus ages, sites available for particle attachment become limited as sites are

occupied or, as the physical structure of the trail is altered (spread out) by the

continual impact of particles within the water column.

The surface over which a snail crawls will influence the longevity of a mucus trail.

Rough surfaces such as natural biofilm, offer greater stability to STM. 1 10

Chapter 4 The affinity of pesticides to mucus and silk

4.1 Introduction

4.1.1 Parameters used to describe pesticide affinity for materials

The properties of individual synthetic organic compounds can be described in a number of different ways. One of these is the ratio of equilibrium concentrations of a dissolved compound in a mixture of two immiscible solvents. The standard two solvents are Octanol and Water (OW), water being the most likely solvent to contain pesticides in the environment, octanol being a more lipophilic solvent, which has come to represent biotic material. A large number of reports exist, detailing the partition coefficient (K^^) of nearly all synthetic pesticides, reviewed by Noble (1993). K is the distribution coefficient, and the letters in subscript refer to the materials between which a partition coefficient has been measured. For example, refers to the ratio or partition of a pesticide between octanol and water. and refer to the ratio between water and Organic Matter, and between water and Organic Carbon respectively. refers to the distribution coefficient of a pesticide between water and any other specified material such as soil, sediment, mucus or silk.

values are relatively easy to measure, using a number o f different methods (shake flask, column generator, reversed-phase high-performance liquid chromatography etc).

From such values for each pesticide compound, various predictive constants have been calculated to describe distribution coefficients using materials other than octanol and water. Briggs (1973; 1981) devised a simple equation describing the affinity of pesticides for four soil types found around Rothamsted, UK. Briggs' equation is log

Koni = 0.524 log Kg^ + 0.618, where refers to the distribution coefficient of organic matter (in this case, the organic matter in the soil). Brown and Flagg (1981) published a variation on Briggs' equation, with log = 1.00 log Kq^-0.21, where

is the distribution coefficient for organic carbon. Their organic carbon samples were coarse pond sediment from Georgia, USA. Briggs (1973) used thirty different

chemicals to formulate his equation. Brown and Flagg based theirs on nine pesticide compounds.

Kenanga and Goring (1980) collated every variation on these two equations that they could find, as many authors have developed their own predictive equations based on specific soil samples. Notably, despite considerable variation in the range o f sorption values that they used, the predictions are similar to those listed in other papers

(see Tables 4.1 ; 4.11 ). Briggs' equations facilitated prediction of pesticide distribution coefficients (KJ in the environment. They allowed calculation of the affinity of a particular compound for a material other than water, so that when pesticides enter fresh waters, we can estimate the retention on different substrata.

4.1.2 Research developments into the role of pesticides in the

environment: examining appropriate materials

An important field of pesticide research is modelling the sorption and subsequent desorption of pesticides from soils and sediments, with increasing reliance being placed on mathematical models (Leake and Gatzweiler, 1995). Goldberg (1982) defined a linear relationship between pesticide concentration and sediment sorption, dependent on the surface area of the sediment particles. Gerstl and M ingelgrin (1984) realised the important consideration of surface chemistry, and used it to form links between the hydrophobicity of a compound and its affinity for certain materials. This provided the background to the field of pesticide modelling. Others have developed algorithms describing the movement and bonding o f pesticides (eg Grzyb, 1996).

Another area o f pesticide research is the determination o f breakdown products of certain pesticides, as well as the conditions required to achieve each potential product, and its likely toxicity. Petit et ai, (1995) comprehensively listed the probable fates of three organic pesticides, asking the question; " If a chemical is likely to sorb onto a material, but unlikely to undergo desorption, is it prone to biotransformation?"

However, they did not consider sorption by mucus or by biofilm s and so failed to examine the cycling o f compounds by organisms within sediments. Bottero et ciL,

(1994) examined sorption properties of pesticides on to various types of clay, and I 12

Table 4.1 Predicted distribution coefficients from octanol - water partition coefficients (ml mg ')

Pesticide ■’Range o f logK,,^ "No. of methods "Mean logK,* "Predicted K,^. ^Predicted K,„„

Simazine 1.51-2.26 (5 methods) 2.00 62 46 Atrazine 2.21-2.75 (9 methods) 2.56 224 91 Propazine 2.6-3.02 (3 methods) 2.97 575 149 Desmetryn No data available Prometryn 3.34-3 48 (2 methods) 3.41 1585 254 Terbutryn 3.43-3 74 (4 methods) 3 59 2399 316 Fenitrothion 3.3-3.47 (4 methods) 3.40 1549 251 Malathion 2 84-2.94 (3 methods) 2.89 479 136 Cyanazine 1.66-1.8 (2 methods) 1.73 33 33 Parathion 2.15-3.76 (4 methods) 3.41 1585 254 a Values presented in Noble (1993) b Values calculated from Brown and Flagg (1981) (log K,^. = 1.00 log K,,^ - 0.21 ) using mean values of from Noble (1993) c Values calculated from Briggs (1973) (log K„,„ = 0.524 log Kow + 0.618) using mean values of Kow from Noble (1993) I 13 found that sorption depends on the type o f clay as well as the type, and concentration, of the pesticide. This suggests that the surface chemistry of the mineral is indeed a factor in sorption. They used dextran as an example of a polysaccharide, and found that it did not exhibit the same behaviour as tannic acid, a substitute for clay. Dextran was found to sorb pesticide compounds to a far greater degree than were clay minerals. However, having made the connection between sediment minerals and organic coatings, they did not go on to examine the behaviour of natural sediment coatings such as mucopolysaccharides.

The desorption of certain pesticides such as organochlorines is more complicated than previously thought, as organochlorines favour an intermediary transport particle rather than water (Ding and Wu 1993). As organochlorines are so hydrophobic, they are more likely to be associated with soil particles or DOM (dissolved organic matter) than to remain dissolved in the water column, and in this form are transported into lakes and the sea. DO M is readily entrapped by materials such as silk and mucus

(Chapters Two, Three and Six). In addition, DOM is an important intermediate transport vehicle and sink for synthetic organic chemicals (Grzyb 1996).

For monitoring pesticide contamination in humans, the use of saliva rather than tissue or urine has been suggested and tested to a limited extent (Nigg and Wade, 1992;

Nigg et al., 1993). These authors argued that saliva is an appropriate medium to

sample, being easy to collect through non-invasive collection and avoiding bio-assay.

They did not identify the constituent of saliva for which pesticides had the greatest

affinity, but saliva contains mucopolysaccharides. Mucopolysaccharides are also a

major component of biofilm s (Decho 1990), known (because of their large total

surface area) to accumulate pesticides from the water column (Lau 1990). This

suggests that mucopolysaccharide may be suited to sorption of pesticide compounds.

4.1.3 Materials that have been overlooked by conventional techniques

W hile the predictive equations of Briggs (1973; 1981) and Brown and Flagg (1981)

may apply to the specific types of soil examined, and to the narrow range of 1 14 adsorption affinities measured, it cannot be assumed that such equations w ill provide accurate estimates of pesticide affinity for all sediments or organic material. They can only provide guidelines for expected retention of pesticides in natural environments, following exposure events. Furthermore, such equations are not designed to predict whole-scale pesticide retention in freshwater systems, owing to the diverse range of materials within these environments. Sediments are coated in organic material, allochthonous or autochthonous breakdown products, invertebrate secretions, bacterial extracellular polysaccharide secretions and so on. Zhou et al., (1995 a) noted that the calculation of from would be inappropriate without first defining the organic carbon source. They found sorption varied depending on the quality and quantity of sorbent material and suggested that the most likely form of bonding is hydrophobic, indicating that polarity of the compound plays a major part in the degree of sorption.

Following on from this, Zhou et al, (1995 b) qualified their earlier statements by reporting that desorption was dependent on temperature, pH, ionic strength and the type of DOC (dissolved organic carbon) involved. While modelling pesticide degradation rates, Lartiges and Garrigues (1995) found that pesticide removal was far greater in unfiltered river water than filtered water, suggesting that organic material of some kind was responsible for the sorption and removal of pesticides. In considering the length of time that a pesticide may contaminate an environment, and the degree to which it may affect biota, Gschwend and Wu (1985) questioned why predictive equations are assumed to be linear, since not all reactions are linear or

indeed, reversible. Such a consideration is difficu lt to include in most models however, as the shape or trendline o f predictive equations depends on the concentration range considered. At low environmental concentrations, predictive equations may appear to be linear. However, at higher concentrations, they may deviate from the prediction as the sorbent material becomes saturated, or as the sorbent

material begins to react with the compounds it is sorbing. Such deviations w ill also

be affected by the bioavailability of sorbent materials. 1 15

Figure 4 .1

Molecular structures of triazine herbicides used in this study

Molecular Weight

Simazine

C k .N NHCH2CH3

NHCH 2 CH3 100 201.7

Atrazine

C k TJNHCH 2 CH 3 NHCH(CH3)2 363 215.7

Propazine

C k .N NHCH(CH3)2

NHCH(CH3)2 933 229.7

Desmetryn

CH3S. /N . .NHCH(CH3)2

NHCH 3 Unknown 213.3 I 16

Figure 4.2

Molecular structures of triazine herbicides used in this study

Molecular Weight

Prometryn

C H jS ^ ^ N n HCH(CH3)2 Y y f NHCH(CH3)2 2570 241.4

Terbutryn

CHjS^ ,NHC(CH 3>3 ' ■ V ' Y N. f NHCH2CH3 3890 241.4

Cyanazine 1N C k .CHC(CH3)2

NHCH2CH3

54 240.7 I 17

Figure 4.3

Molecular structures of organophosphate insecticides used in this study

Molecular Weight

Fenitrothion

CH3 S

N O r X ^ op(OCH3)2 2512 277.2

Malathion

f « (CH3 0 )2PSCHCH2C0CH2CH3 CO

o

CH2CH3 776 330.3

Parathion

^0P(0CH2CH3)2 2570 291.3 Sorption models are currently an oversimplification of pesticide behaviour, and are based on materials whose forms do not exist in the environment. For example, soils or sediments that have been washed free of the organic coatings that normally surround them. Such models are also based on a limited range of concentrations that may not be indicative of the behaviour of pesticides at higher or lower concentrations.

4.1.4 Pesticide affinity for organic material produced by invertebrates.

A number of factors influence the affinity of a particular pesticide for sorption onto the surface of a given material. Two in particular are worth consideration: the hydrophobic nature o f each pesticide, which is in part described by the and its chemical structure. The structures of those used in this study are shown in Figures

4.1, 4.2 and 4.3; triazine herbicides and organophosphate insecticides. The shape and arrangement of chemical functional groups will lend specific charges (attractions or repulsions) between the compound and substrate (Leake and Gatzweiler, 1995). For these and other reasons, pesticide affinity (even to model minerals that have been cleaned and refined) cannot be accurately predicted at present. Chemical modelling techniques are primarily directed at the interactions of pesticide compounds under vacuum conditions, although some developments have been made in aqueous systems, modelling hydrogen bonding interactions (Zhmud et al., 1997).

Sorption can also affect the toxicity o f a compound. Stewart (1982) looked at the interactions of organic toxicants and dissolved humic materials, and noted that toxicity can increase or decrease depending on environmental conditions, the polluting chemical, and the configuration of its functional groups. He concluded that there are no absolute rules concerning pesticide sorption.

4.1.5 The aims of this study

The experiments described in this chapter are an attempt to quantify the affinity of

pesticides for representative examples of two types of organic material found on

freshwater sediments, or in the water column: snail trail mucus (STM) and blackfly 1 19 silk. Snail trail mucus and silk are both capable of consolidating dissolved and particulate matter from the water column. Wotton et al., (1996) observed that sand grains and organic matter in slow sand filter beds are bound by chironomid silk.

The aims of this study were:

1) To calculate distribution coefficients values) for a range of pesticides onto

STM of two species of freshwater snail (Lymnaea peregra and Potamopyrgus

jenkinsi).

2) To calculate distribution coefficients (K^ values) for a range of pesticides onto

silk threads produced by blackfly larvae.

3) To determine the means by which pesticides sorb onto such materials by

examination of their values with respect to their values. To attempt

to define the primary means of sorption (chemical structure of the pesticide,

hydrophobicity of the pesticide, sticky nature of the silk or mucus).

4.2 Materials and Methods

4.2.1 Experimental Protocols - Mucus

Two species of snails, L. peregra, a pond snail commonly found in rivers and slow water (Armitage, 1978, W right et al., 1984), and P. jenkinsi, a river snail, were used to coat clean sediment with mucus. Snails were collected from an experimental channel at East Stoke, Dorset (Nat. Grid Ref: SY 867 868 ). The sediment used was

BDH fine sifted sand, 0.1-0.3 mm (Product No. 33093-7E). Five grams of sediment were placed in a crystallising dish with a flat base (66 mm high, 79 mm diameter, 175 ml volume) in 50 ml o f distilled water. Snails were placed on the sand and left for

24 hours to move over the surface. A t approximately 2 hour intervals the dish was agitated to present a fresh sand surface, and snails that were moving up the side of the dish away from the sand were returned to its surface. 50 ml of difitüled vx.'at

Known wet weigjit of snails

Dish swirled around every few hours over 24 h to present Flat b o tto m s glass Suite of pesticides at known concentration new sediment surface for snails to coat in mucus 5 g of sediment (defllT ^d) crystallising dish

Pftranim

Polyethylene tube Incubated and shaken at 10° C for 24 h. Pestiddes should bind to mucus coating the sand C18 extraction column K) o

20 ml of solution containing remaining pesticides, i. e. those not bound to mucus coating sediment grains.

Gas chromatography unit

Remairung pesticides extracted Known weight of ethyl acetate containing from watei, eluted with ethyl — unbound pesticides acetate

Injection vial

GC analyses samples for remaining amounts of pestiade. These are subtracted from those in original solution, allowing calculation o f pesticide sorption by mucus

Figure 4.4 Schematic diagram of the preparation of mucus samples 121

After 24 hours, all snails were removed, the water was decanted, and the sediment with mucus coating was scooped into a low density polyethylene tube (28 ml). The quantity of mucus could not be determined non-destructively. Instead, the wet weight of the snails used to produce the mucus coating was recorded (attempts to quantify snail mucus production are described in section 4.3.3). Each tube was filled with a stock pesticide solution containing a suite of 10 pesticides, a mixture of triazines and organophosphates at a concentration of either 5 or 10 p,g 1‘, and sealed. The tubes were then agitated at 125 rpm to facilitate mixing of the mucus-coated sand with the pesticide mixture, and incubated at 10°C for 24 hours. Following incubation, 20 ml of pesticide solution was extracted from the 28 ml tube containing sediment, and analysed for remaining pesticides. A schematic diagram of the protocol is presented in Figure 4.4.

4.2.2 Estimation of mucus mass

Five L. peregra snails were weighed individually as fresh wet mass and allowed to crawl over a piece of foil that had been dried, and weighed to six decimal places

(Perkin Elmer Autobalance AD-2). Individual snails were placed within a drop of water on pieces o f foil. After 30 minutes, the snails were removed, excess water removed, and the fo il re-weighed to measure the mass of wet mucus. Foil was then freeze-dried and again weighed to determine the dry weight of mucus, water content of mucus and amount of mucus laid per unit mass of live snail per unit time. Foil was chosen as a non-absorbent material, from which excess water could be removed.

4.2.3 Sample sizes - Mucus

P. jenkinsi mucus samples

Eighteen samples were prepared for analysis, using the mucus of P. jenkinsi, which was exposed to two different concentrations of the suite of pesticides (5 and 10 p.g l ').

Mucus produced by the live (wet) snail masses of 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 10.0,

15.0, 20.0 and 25.0 g, on 5 g aliquots of sand, was exposed to a concentration o f 5

|lg r ' of the pesticide suite. Mucus produced by live snail masses of 1.0, 2.0, 2.4, 3.0, 122

4.0, 4.8, 5.0, and 9.6 g was exposed to 10 |lg l ' of the pesticide suite. An additional three samples comprising live snail masses of 2.4, 4.8 and 9.6 g were used to produce mucus for exposure to calcium chloride (CaCl 2), as a blank sample, allowing examination of pesticide deposition from snails or their mucus. A ll pesticide solutions and all blank solutions contained 0.002 M CaCl 2 to mimic the osmotic potential and pH of local river water.

L. peregra mucus samples

Sixteen samples were prepared using the mucus of L. peregra, exposed to two different concentrations of the pesticide suite. Live snail masses used in each sample were 1.0,

2.0, 3.0, 4.0, and 5.0 g at 5.0 g 1'. Live snail masses of 0.7, 0.8, 1.0, 1.4, 1.6, 2.0,

2.8, 3.0, 3.2, 4.0, and 5.0 g were also used to produce mucus for exposure to the pesticide suite at 10.0 g 1"'. An additional six samples comprising live weight masses of 0.7, 0.8, 1.4, 1.6, 2.8, and 3.2 g were used to produce mucus for exposure to CaCl 2, to be used as blank samples. In addition, five samples were prepared featuring neither mucus nor pesticides (CaClj only), to allow for examination of pesticide contamination or sorption onto any of the equipment used.

4.2.4 Experimental Protocols - Silk

Egg masses of blackflies on trailing vegetation were collected from the River Frome and a side channel, the M ill Stream, East Stoke, Dorset (Nat. Grid Ref: SY 867 868 ).

Pieces of vegetation with egg masses were removed, washed gently in mains water, rinsed in distilled water and placed in incubation jars of cold mains water with a vigorous air stream. Pirct mctoT eilV

Blackfly egg masses

Incubator jai of tap water

^eces of bank side vegetation 2 - 72 h for eggs to hatch and silk appear

Suite of pesticides at known concentration

Parafilm GF Filter or CN membrane used to gather fresh silk r o Pnlvethvlene tube (jO

Incubated and shaken at 10 C for 24 h. Pesticides should bind to the silk on the filter disc

20 ml of solution containing remaining pesticides,i.e. those not bound to silk or filter disc. C 18 extraction column

Remaining pesticides extracted from water, eluted with ethyl acetate

Known weight of ethyl acetate containing unbound pesticides lia,a GC analyses samples for remaining amounts of pesticide. These are subtracted from those in original solution, allowing calculation of pesticide sorption by silk

Figure 4.5 Schematic diagram of the preparation of silk samples 124

Masses of first instar silk were collected onto pre-weighed cellulose nitrate (CN) membranes or glass fibre (GF) filters. Silk masses were gathered using forceps holding CN membranes or GF filters, dipped into the incubation jar. Some egg masses were also unavoidably attached to the silk bundles, but were removed as far as was possible, using forceps. In order to minimise the attachment of DO M or coarse particulate organic matter (CPOM), the water within the incubation jar was changed every 12 hours.

Silk masses on membranes or filters were introduced singly into polyethylene tubes containing the pesticide suite (at either 5 or 10 |Xg l ') and incubated and extracted in the same way as mucus samples. Each membrane with attached silk was then removed, dried and weighed to calculate the dry weight o f silk. Such a procedure was not practical for the collection of mucus due to the minute quantities of mucus produced. Therefore, mucus calculations are based on the wet (live) weight of the snails that produced the mucus. A schematic diagram of the protocol is presented in

Figure 4.5.

4.2.5 Sample Sizes - Silk

O f the 12 samples on GF filters, 7 were exposed to 5 |ig l ' of the pesticide suite (0.2,

0.7, 0.7, 0.8, 1.2, 1.7 and 3.0 mg of silk), and 5 were exposed to 10 |ig l ' o f the pesticide suite (0.4, 0.7, 0.8, 1.2, and 4.8 mg of silk).

O f the 17 silk samples collected on CN membranes, 8 were exposed to 5 jLtg l ‘ o f the pesticide suite (0.6, 0.7, 0.7, 0.7, 1.3, 1.4, 1.5 and 2.2 mg o f silk), and 9 were exposed to 10 |ig r ‘ of the pesticide suite (0.1, 0.7, 0.9, 1.8, 1.9, 2.1, 2.4, 2.8 and 4.9 mg of silk). Twenty control samples were prepared; five with each filter/membrane type at each pesticide suite concentration, to account for pesticide sorption by the filter/membranes. Ten blanks were made, five at 5 |ig l ' and five at 10 |ig l ' o f the pesticide concentration, in order to assess pesticide sorption by equipment or pesticide contamination. 125

4.2.6 Extraction and analysis of the pesticides

A ll equipment, vessels and glassware were washed at each every stage of preparation.

Washing involved soaking for 24 hours in 5% Decon solution, 5 rinses in mains water,

5 rinses in distilled water, three rinses with HPLC grade acetone and three rinses with

HPLC grade ethyl acetate.

Twenty ml of the pesticide suite was extracted following incubation with either silk or mucus, and was drawn through an ISOLUTE SPE 6 ml C l8 solid phase extraction

(spe) column. Columns had previously been conditioned with 2 ml of methanol and

4 ml of ultra-pure distilled water (0.2 |im filtered, at 18 M Q resistance) under low vacuum (up to 0.2 bar). The column was then allowed to dry completely, for 30 minutes under high vacuum (0.2 - 0.6 bar), before elution with 2 ml of HPLC grade ethyl acetate under low vacuum into a pre-weighed crimp seal 3 ml glass vial. Each vial was weighed again, with crimp seal, prior to sealing, to calculate the volume of ethyl acetate extracted. One ml of each prepared sample was subsequently pipetted into a 4 ml screw cap vial into which 10 |xl o f ametryn (internal standard) had already been injected. After mixing, each sample was subdivided into three 0.3 ml injection vials, ready for GC analysis.

Samples were analyzed using a Perkin Elmer Gas Chromatograph 8700, with Nelson software for chromatograph interpretation and evaluation. Pesticide standards were produced from solids, supplied by Promochem Ltd. Herts, and checked for purity at

The Institute of Organic Industrial Chemistry, Warsaw, Poland. Pesticides were dissolved into a stock solution of ethyl acetate at 10 mg l ‘, and further diluted to 5 or 10 |ig r ‘ for sorption measurements in a background electrolyte of 0.002 M CaCl 2 solution.

Samples were analysed against the internal standard, ametryn, and calibrated to a quadratic equation derived from the pesticide suite multistandards of 0.05, 0.2 and 0.5

|Xg r ‘ in triplicate (pre, mid and post run). The need to calibrate each analytical run

(approximately every 25 samples) was necessitated by the extremely low 126 concentrations of pesticides involved. By developing quadratic equations to describe the multi standards rather than linear equations, errors due to deviation below the range of the standards concentration range were minimised.

Pesticide concentrations were then normalised with respect to the volume of ethyl acetate eluted and the volume o f the water sample originally used. Finally, values were calculated by averaging sorption onto filters (in the case of silk) or sand (in the case of mucus). These average sorption values were subtracted from the specific sorption value of each sample, leaving the sorption o f silk or mucus for each sample.

Finally, the sorbed pesticide (|ig mg ') was divided by the sorption concentration (jig ml '), to give a distribution coefficient, (ml mg ').

4.3 Results and discussion

A total of 34 samples of mucus were collected from different masses of snails of the two species and 29 samples o f silk were harvested. The resultant values are presented for each individual sample and for each individual pesticide (post correction for controls and blanks) in Tables 4.2 - 4.9. Figures 4.6 - 4.11 show values for each pesticide onto each of the three materials studied. K j values for mucus produced by a small group o f snails were found to be almost always higher than those for mucus produced by a larger group of snails (Figures 4.6 and 4.8). For this reason, values are presented for each pesticide for each sample, as well as a mean value for all samples. Table 4.2 Mucus Sample Kds 127

Individual values (ml mg ‘) for each sample, with mean and S.D.

Potamopyrgus jenkinsi

Snail Mass Starting Simazine Atrazine Propazine Desmetryn Prometryn (g) concentration (Mg I ') 1 5 0.00 0.00 0.00 3.64 4.00 2 5 &28 7.92 9.94 3.96 4.05 3 5 0.03 0.19 0.20 0.57 0.75 4 5 0.00 0.00 0.00 0.51 0.70 5 5 0.12 0.01 0.25 0.32 0.42 1 10 3.08 3.37 3.38 0.00 0.00 2 10 0.79 0.76 0.55 0.00 0.00 3 10 1.21 1.06 0.86 0.00 0.00 4 10 0.75 0.76 0.47 0.00 0.00 5 10 1.23 1.21 1.06 0.00 0.00

25 5 0.18 0.05 0.05 0.00 0.01 20 5 0.11 0.04 0.02 0.00 0.00 15 5 0.10 0.02 0.03 0.00 0.00 10 5 0.36 0.19 0.18 0.00 0.00 5 5 0.39 0.06 0.03 0.00 0.07

2.4 10 1.04 0.73 0.91 0.00 0.00 4.8 10 0.97 &88 0.90 0.00 0.00 9.6 10 0.48 0.50 0.51 0.00 0.00

Mean Kd 1.06 0.99 1.07 0.50 0.56

S.D. 1.95 .91 2.35 1.21 1.29 Table 4.3 Mucus Sample Kds 128

Individual values (ml mg ') for each sample, with mean and S.D.

Potamopyrgus jenkinsi

Snail Mass Starting Terbutryn Fenitrothion Malathion Cyanazine Parathion (g) concentration (Mg I ') 1 5 0.00 0.57 0.00 1.52 0.00 2 5 1.65 8.84 0.00 6.54 1.50 3 5 0.00 0.00 0.00 2.53 0.00 4 5 0.08 0.00 0.00 0.62 0.00 5 5 0.20 0.00 0.00 1.73 0.40 1 10 19.10 0.00 0.00 0.00 1.65 2 10 11.83 0.00 0.00 0.00 5.55 3 10 4.06 0.00 3.32 1.55 2.40 4 10 14.92 0.00 0.01 0.00 3.92 5 10 3.96 0.00 0.00 0.45 41.63

25 5 0.25 0.00 0.57 0.80 0.11 20 5 0.00 1.22 0.51 1.79 0.10 15 5 0.36 0.18 0.41 0.45 0.00 10 5 2.15 0.74 0.91 1.41 0.15 5 5 0.00 1.05 0.90 0.79 0.00

2.4 10 5.36 13.52 2.44 5.11 3.87 4.5 10 7.95 39.20 7.04 6.08 286 9.6 10 0.00 0.00 0.23 2.51 2.01

Mean 3 99 T63 0.91 3.73

S.D. 5.80 9.59 1.79 203 9.62 Table 4.4 Mucus Sample Kds 129

Individual values (ml mg ') for each sample, with mean and S.D.

Lymnaea peregra

Snail Ma.ss Starting

(g ) concentration Simazine Atrazine Propazine Desmetryn Prometryn (Mgr') 1 5 0.00 0.00 0.00 0.00 0.00 2 5 0.79 0.20 0.48 0.07 0.06 3 5 0.24 0.45 0.27 0.00 0.00 4 5 6.76 6.10 6.01 3J8 3.32 5 5 0.54 0.39 0.29 0.17 0.22 1 10 0.44 0.72 0.48 0.00 0.00 2 10 2.96 2.72 2.25 0.03 0.01 3 10 0.00 0.00 0.00 0.00 0.00 4 10 0.16 0.17 0.00 0.00 0.00 5 10 0.39 0.48 0.28 0.00 0.00

0.82 10 0.95 1.46 1.62 3.58 4.80 1.6 10 0.00 0.00 0.00 4.34 5.33 3.2 10 0.69 0.73 0.86 0.30 1.23 0.7 10 1.32 1.56 0.67 6.12 14.67 1.4 10 1.12 0.60 0.27 2.81 7.22 2.8 10 0.10 0.00 0.00 0.00 0.01

Mean K

S.D. 1.70 1.55 1.51 2.02 4.05 Table 4.5 Mucus Sample Kds 130

Individual values (ml mg ') for each sample, with mean and S.D.

Lymnaea peregra

Snail Mass Starting (g) concentration Terbutryn Fenitrothion Malathion Cyanazine Parathion (Mg I ') 5 4.09 0.00 2.66 1.29 0.00 5 3.21 0.00 12.81 4.83 1.15 5 4.26 0.00 0.00 0.68 0.72 5 7.93 4.90 3.64 6.92 2.76 5 1.33 0.00 0.00 1.74 1.73 10 0.00 0.00 0.00 7.35 8.44 10 2.62 2.30 0.00 9.17 14.45 10 0.32 0.00 0.00 3.02 1.32 10 3.20 0.00 0.00 3.25 4.21 10 1.18 0.00 3.55 3.19 4.22

0.82 10 0.00 0 0 0 0.00 1.6 10 6.89 2.64 0.00 0.00 0.00 3.2 10 31.16 5.58 0.52 0.64 0.21 0.7 10 21.14 200.92 6.36 14.52 41.69 1.4 10 1.76 50.64 8.81 8.95 19.79 2.8 10 2.07 20.30 3.12 3.61 8.00

Mean K

S.D. 8.49 50.50 3.81 4.08 10.91 Table 4.6 Silk Sample values ^ ^ ^ Individual K j values (ml mg ') for each sample, with data grouped for each membrane / filter type. Mean and S.D. calculated for each filter type and for all samples

Starting concentration (Mg I ') Simazine Atrazine Propazine CNGF CNGF CN GF 5 1705 30975 1096 7260 392 3745 5 52192 2561 36852 3648 38802 2218 5 11805 7299 5452 3988 1188 1492 5 3281 7369 1755 3746 100 1713 5 13016 3354 8844 2244 5104 447 5 4589 1954 2372 794 1509 No result 5 7710 No result 4225 No result 350 No result 5 427 528 165

10 6248 212668 19215 217418 27715 217299 10 722 43034 1829 39839 1798 35845 10 596 5165 1021 3094 370 2361 10 479 835 4882 417 725 393 10 No result No result No result No result 1332 No result 10 No result No result No result 10 No result No result No result 10 No result No result No result 10 No result No result No result

Mean 5 11840 8919 7640 3613 5951 1923 10 2011 65426 6737 65192 6388 63975

S.D. 5 16926 11058 12113 2158 13376 1206 10 2826 99975 8483 103065 11935 103503

Mean IQ [5 ]+ [10] 8564 31521 7339 28245 6119 29502

S.D. 14419 65200 10639 67488 12324 71327 CN GF CNGFCNGF

Simazine Atrazine Propazine

Mean (CN and GF samples) 18999 16842 15685 S.D. 45472 46095 46512

No result = non detectable Table 4.7 Silk Sample values ' ^2 Individual Kj values (ml mg ') for each sample, with data grouped for each membrane / filter type. Mean and S.D. calculated for each filter type and for all samples

Starting concentration (Mg 1 ) Fenitrothion Malthion Cyanazine CN GF CN GFCN GF 5 71681 602066 6823 No result 22426 162347 5 No result 57473 No result 10021 No result 4441 5 49135 18966 No result 2978 62811 65422 5 16192 284124 No result 202627 50831 9029 5 20011 378368 No result 1219725 45622 20600 5 11623 258753 No result No result 38579 23915 5 No result 32488 9126 No result 75 No result 5 18018 No result No result

10 No result 213386 No result No result 5275 629035 10 No result 14725 No result No result No result 40014 10 No result No result No result No result No result 27074 10 No result 41072 No result No result No result 4165 10 No result 102133 No result No result No result No result 10 No result No result No result 10 No result No result No result 10 No result No result No result 10 No result No result No result

Mean 5 31110 233177 7975 358838 36724 47626 10 No result 92829 No result No result 5275 175072

S.D. 5 23949 215036 1628 581331 22404.227 60207.825 10 No result 88317 No result No result No result 303004.49

Mean [5 ]+ [10] 31110 182141 7975 358838 32231 98604

S.D. 23949 187345 1628 581331 23655 192222 CN GFCNGFCN GF

Fenitrothion Malthion Cyanazine

Mean K<, (CN and GF samples) 128836 241883 71274 S.D . 166284 485383 148753

No result = non detectable 133 Table 4.8 Silk Sample K j values Individual Kd values (ml mg ') for each sample, with data grouped for each membrane / filter type. Mean and S.D. calculated for each filter type and for all samples

Starting concentration (Mg n Desmetryn Prometryn CNGF CNGF 5 82157 688 32 8011 5 14135 1956 76697 8464 5 2231 1019 15355 4491 5 9260 710 411 4047 5 2883 569 13002 2378 5 6657 No result 3986 No result 5 No result No result 5692 No result 5 No result 1079

10 12403 151868 71645 221490 10 1785 42501 5671 71666 10 215 1810 643 3143 10 537 247 4019 2001 10 No result No result 2264 No result 10 No result No result 10 No result No result 10 No result No result 10 No result No result

Mean 5 19554 988 14532 5478 10 3735 49107 16848 74575

S.D. 5 30980 566 25767 2644 10 5818 71246 30690 103219

Mean [5 ]+ [10] 13226 22374 15423 36188

S.D. 24723 50466 26507 72972 CN GFCNGF Desmetryn Prometryn

Mean K

No result = non detectable 134 Table 4.9 Silk Sample values Individual values (ml mg ') for each sample, with data grouped for each membrane / filter type. Mean and S.D. calculated for each filter type and for all samples

Starting concentration (Mg 1 ) Terbutryn Parathion CN GFCN GF 5 13070 96942 150964 694011 5 246514 28481 No result 41770 5 48377 851 1018249 9130 5 2632 43509 131334 No result 5 49460 18593 1071878 No result 5 22399 17443 453179 No result 5 22574 8689 279938 151166 5 7096 ■ 12926

10 194055 284433 No result 281968 10 10947 3387 No result 2729 10 195 64273 No result No result 10 12843 11029 No result 52021 10 5159 4428 No result No result 10 No result - No result 10 No result - No result 10 No result - No result 10 No result - No result

Mean 5 51515 30644 445495 224020 10 44640 73510 No result 112239

S.D. 5 80680 32287 432133 319161 10 83674 120589 No result 149041

Mean [5 ]+ [10] 48871 48505 445495 176114

S.D. 78377 79648 432133 248810 CN GFCNGF Terbutryn Parathion

Mean (CN and GF samples) 48695 310805 S.D. 77324 366465

No result = non detectable 450000 • 135

400000 t (430.000)

350000 •

.__. 300000 • E O) 250000 1 E

5 200000 f

150000 t

100000 r

50000 r

0 ^ I i 2 i

Figure 4.10 Mean association constants (Kd) for pesticides on blackfly larval silk attached to Cellulose Nitrate Membranes. Bars are one standard deviation, (upper limit bracketed where off scale).

500000 3

400000

E 300000 CT) E

200000 (192,000)

100000

Figure 4.11 Mean association constants (Kd) for pesticides on blackfly larval silk attached to Glass Fibre Filters. Bars are one standard deviation, (upper limit bracketed where off scale). 36 (60)

^ Mucus from groups of snails: Group mass < 3 g

H Mucus from groups of snails: Group mass > 3 g

Figure 4.6 Mean association constants (Kd) for pesticides on mucus produced by groups of different densities of Lymnaea peregra snails. Bars are one standard deviation, (upper limit bracketed where off scale).

25

( 50 ) 20

— 15 1 O) S J3 ^ 10

0 :

Figure 4.7 Mean association constants (Kd) for pesticides on mucus produced by Lymnaea peregra snails. Bars are one standard deviation, (upper limit bracketed where off scale). H Mucus from groups of snails: Group mass < 5 q

■ Mucus from groups of snails: Group mass > 5 g

□ Mucus from groups of snails: Group mass > 10 g

4 -

»3 -

2 -

1 -

0 -

Figure 4.8 Mean association constants ( K g ) for pesticides on mucus produced by groups of different densities of Potamopyrgus jenkinsi snails. Bars are one standard deviation, (upper limit bracketed where off scale).

5

4.5

4

3.5 -

- 3 E |>2.5

1.5

1

0.5

0 4. — Q) 0) 5 5

E < cn

Figure 4.9 Mean association constants (Kg) for pesticides on mucus produced by Potamopyrgus jenkinsi snails. Bars are one standard deviation, (upper limit bracketed where off scale). ( 362 ,000 )

300000

( 485,0 00 )

250000

200000 en E T3 150000

100000

50000

0 —

Figure 4.12 Mean association constants (Kd) for pesticides on blackfly silk. Bars are one standard deviation, (upper limit bracketed where off scale). 139

4.3.1 Comparison with previously published pesticide affinity

constants for various sediments and soils.

The results show considerable sorption o f pesticides to mucus and silk, especially when compared with the sediment distribution coefficients in the literature (Figure

4.12). Noble (1993) published a review detailing the distribution coefficients of 221 pesticides from as many different sources as were available, providing in some cases up to nine different published values of log for a single compound. An average value from each of the published results for all pesticides used in this study has been calculated and is presented in Table 4.1. Figure 4.13 is a comparison of part o f the published findings presented in Table 4.1, together with the findings of this study. K j and values are not directly comparable in that they refer to different materials.

However, Figure 4.13 gives an idea of where the results for mucus and silk fit in the

"league of pesticide sorption". Whilst refers to the affinity constant for any given material (in this case mucus and silk, but usually the term is used to describe a mixture of materials ie estuarine sediment), refers to a specific source of organic carbon. In this case, both mucus and silk can be considered to be organic carbon in that they consist only of carbon-based material of organic origin and water, so for these two materials, the descriptive terms can be considered interchangeable.

The pesticides examined in other studies, represented in Figure 4.13, are not specified

(due to a lack of sim ilarity between those pesticides used in this study and the very diverse range used in comparative studies). W hile this means that results from other studies are not directly comparable, it in no way detracts from the relevance o f the results presented by this study. It was for this reason that such an uncommonly large number of individual pesticides were used in my study, to provide a wide range of values for each of the organic materials examined. In addition, the results that my study presents are so different from those previously published or predicted (Figure

4.13 utilises a log scale), and based on such a wide range of pesticide compounds, that they are sufficiently distinct to prove that organic materials such as snail mucus and blackfly silk should be identified and examined separately from soils and sediments in future studies. K. for blackIIy silk K„ loi mucus ül

L. peregra " K,„ for mucus of L. peregni '' K„ for mucus of K „ for mucus of P. jenkinsi P. jenkinsi **

measured on soils and sediments''

for zeolite and organoclay'

■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■I Kj measured for soils and lake ::::::::::::::::::::::::::::::::::::::::::::::: sediments'*

• ■■■■■■ KI measured for estuarine sediments ^

based on all available isotherms’

K,^. predicted from equation^

predicted from equation'

10 100 1000 10000 100000 1000000 Log scale of and values, measured and predicted (ml mg ') Figure 4.13. Comparative studies presenting distribution coefficients for various materials. Key: ICi - distribution coefficient for soils and sediments; K^c - distributionn coefficient normalised with respect to organic content; Kn, Km and K^ are defined in Table 4.12 ' Brown and Flagg (1981) predicted K,K values from empirically derived equation Karichoff (1981) measured K,,^. values for soils and sediments ■’ Briggs (1973) predicted values from empirically derived equation ’ Kenaga and Gonng (1980) values based on review of all ’ Sujatha and Chacko ( 1992) measured values for estuarine sediments available isotherm equations * Gerstl and Mengelgrin ( 1984) measured ICi values for unwashed soils, lakesediments * This study, calculated on wet weight of snails producing pedal mucus ' Bottero er a! ( 1994) measured K,„. values on zeolite and organoclay respectively '' This study, calculated on dry weight of snail pedal mucus This study, calculated on dry weight of blackfly silk 141

4.3.2 Mucus sorption

Compared with values for sediments and measured values, mucus values are low. There are three possible reasons for this.

1. The values are not true values for mucus, but rather for the mucus produced

by a wet weight of snails. Quantifying the amount of mucus produced by a

snail presents many difficulties (see points A, B and C below).

2. Snails do not produce mucus at a uniform rate. Although mucus serves many

other functions, it is prim arily secreted as an aid to locomotion. If a snail is

not mobile, no mucus is produced. Therefore, mucus production may not be

continuous during the exposure time.

3. Snail mucus is a highly hydrated material. Conservative estimates place its

water content at 91% (Davies et ai, 1990a). Measurements within this study

place that figure at 95-96%. Only the carbon based polysaccharide material

(4-9 % of the hydrated mass) is capable of sorbing xenobiotics from water.

In addition, a point of great interest is that values are lower the greater the mass of snails involved. As the volume of the dish and sand in each case was standard, this, together with observations made during this study, suggests a few possibilities:

A. Snails may have produced mucus by crawling at a constant rate, but at greater

densities, there were more snails to consume the mucus trails produced

(Connor and Quinn 1984), achieving a net effect of less mucus. K j values for

the mucus o f P. jenkinsi are almost always lower than K j values for the

mucus of L. peregra. L .peregra is by far the larger snail, and so, accordingly,

lower numbers o f individual snails are required to achieve the same live mass.

B. A t higher densities, snails were not as mobile, due to space or oxygen

restrictions. Observations indicated that in such conditions, the preferred food

source of snails is the biofilm on conspecifics shells (Lopez and Levington

1978). A t higher densities therefore, snails did not need to move around the

sand as much, in search of food.

C. Snails may have been equally mobile at high densities as at lower densities,

but may not have needed to produce as much mucus. I f mucus is primarily to 142

assist locomotion, then it is reasonable to assume that once a surface is coated

m mucus, locomotion is possible as long as the mucus coating remains. It may 0^ be that a finite amount mucus is achievable per unit volume of sediment. (See 'V section 3.3.5)

4.3.3 The water content of mucus

By weighing the mass o f mucus produced by L. peregra of known weight, the water content, as well as the dry mass of mucus produced per unit mass of live snail per unit of time, was calculated. The water content of mucus was 98.8% (98.5%; 98.3%;

99.3%; 99.2%, with a standard deviation of 0.48%) for four samples. The unit mass of mucus produced per unit mass of L. peregra produced per unit time is 4.2 x 10 '^ g g (snail) ' s ' (± 4.5 x 10'*^S.D.). This is equivalent to 3.6 x 10"^ g (mucus) g '

(snail) d '. The problem is that the amount of mucus produced by a large group of snails over a long period of time will be variable and depend on a number of complex factors. The snails were allowed to coat sand with pedal mucus for 24 h and so the distribution coefficients produced are based on the weight of the snails producing the mucus, rather than the mass o f mucus or mass o f organic carbon. Hence an appropriate conversion factor for these distribution coefficients is to divide by a factor o f 3.6 X 10‘^ g (mucus) g ' (snail) d ' to convert the distribution coefficient to ml g '

(mucus) (Table 4.12). This factor produces distribution coefficients for mucus close to those found for silk (Figure 4.13).

4.3.4 Silk sorption

It is interesting to note that there are differences between values for each type of filter used, the higher values generally being with glass fibre filters (GF/F grade), which are recognised as having the least affinity for pesticides, compared with other materials (House and Ou 1992). There should, however, be no discernible differences as adsorption by filters, polyethylene incubation tubes and glass storage vials should all cancel because of the controls and blanks involved. As differences were detected unexpectedly, results for each type of filter have been presented separately (Figures 143

4.10 and 4.1 1) and in combination (Figure 4.12).

4.3.5 Individual pesticide sorption

Triazine pesticides

A wide range of ten pesticides from two broad groups (triazines and organophosphates) were chosen to provide information on pesticides representative of contaminants found globally. They were also chosen to exhibit a diverse range of solubility, atomic mass and structure. The triazine pesticides (simazine, atrazine, propazine, desmetryn, prometryn, terbutryn and cyanazine) share structural similarities, in that all are based around a triazine ring (see Figures 4.1 and 4.2). The organophosphate compounds are distinct from this group. Not only do they contain phosphate, but they also lack the distinct structure shared by the triazine group (see

Figure 4.3). Partly for these reasons, the first four compounds (simazine, atrazine, propazine and to a certain extent, desmetryn) are often sorbed to a sim ilar degree. Not only are these four compounds structurally similar, they are also of a similar weight class (see Figure 4.1) and are detected by the GC unit in very close succession

(meaning that chemically they are also very similar, as the GC column separates compounds according to a variety of criteria, including weight, structure, side ion groups, and importantly, solubility). Figures 4.6 - 4.12 illustrate that these four compounds are sorbed to a similar (comparatively low) degree. These four compounds are in fact the most reliably detected compounds of the suite of pesticides

used and are by far the most clearly distinguished in a chromatograph, despite their close proximity of emergence from the separating column. The fact that these compounds are sorbed to a lesser extent than others by the organic material tested here

is more an indication of the relative solubility of these compounds in water.

Generally, the order in which compounds are listed on each of Figures 4.6 - 4.12 (the

order in which they emerge from the separating column) is an indication of their

relative solubility or conversely, hydrophobicity, the most soluble being simazine, the

most hydrophobic being parathion. (See also values listed in Table 4.1, for exact

values, and exceptions to this rough guide). The fact that such compounds (simazine,

atrazine, propazine and desmetryn) are sorbed to this degree is an indication of the 144 high sorptive potential o f the material tested, and they should not be overlooked because the sorption o f other compounds may be higher. Other compounds within this suite would be expected to be sorbed to a far greater degree. To begin with, the other pesticides are more hydrophobic (and are therefore more likely to sorb onto anything rather than remain in solution), and they also have higher values, another indication of their preference for material less polar than water. Cyanazine is a notable exception to this trend. It has a relatively low (see Table 4.1) due to a side chain of a cyanide group which is hydrophilic. However, despite this relative affinity to remain in aqueous solution, cyanazine is still sorbed to a strong degree by blackfly silk and snail mucus, indicating that such materials are themselves hydrophobic, relative to water.

Organophosphate pesticides

Fenitrothion tends to dominate each figure (Figures 4.6 - 4.12) in the series, as do each of the other organophosphates (malathion and parathion). This is partly because o f the different structure and thereby, chemical nature o f these compounds, and also in part because of the higher sensitivity of the GC detector to fenitrothion in particular. For a demonstration of the relevance of these results, attention must be turned to Figure 4.13, which compares in diagrammatic form, the sorption of various materials, as well as the predicted sorption of materials, based on published, predictive equations. It is apparent that silk demonstrates a strong affinity for pesticides well beyond any other material either measured or postulated. Equally, snail mucus, when measured according to the wet weight o f the live snails, is comparable to measured

K j and values for sediments and soils. When measured using the correction factor described in section 4.3.3 where the amount of mucus (dry weight) produced per unit snail (wet weight) is used to calculate the for mucus, the resulting values are comparable to silk, and higher than those o f any other substance measured.

4.3.6 Are certain pesticides sorbed to a greater extent than others?

Sorption of different pesticides onto mucus and silk are statistically indistinct.

Analysis of a random subset of values (for all silk samples on CN membranes) 145

found that with the exception of parathion, pesticides did not differ statistically from

each other in their sorption onto the same material (Anova Fg^g = 1.94, P = 0.065).

Parathion is the most hydrophobic pesticide o f the suite examined, emerging last from

the GC column, and is therefore expected to sorb on to materials to a greater degree.

For a random subset of values based on mucus samples (all mucus samples for P. jenkinsi) no differences were found between pesticides in terms of sorption (Anova

Fg ,70 = 1.46, P = 0.166).

These findings imply that despite the considerable variation in hydrophobicity

exhibited by the diverse suite of pesticides chosen, and despite the considerable range

of molecular weight, chemical reactivity, side chain groups etc, sorption onto mucus

and silk is uniform ly high. This suggests that it is the material examined rather than

the hydrophobic nature of the pesticides that is causing sorption to this degree, and

that both snail mucus and blackfly silk may be considered to be strongly adsorptive.

4.3.7 Experimental constraints

Experimental design was dictated by the quantities of mucus and silk generated.

Attempts were therefore made to maximise sorption differences by reducing the

volume of sand on which snails crawled and also by reducing the concentration of

pesticides exposed to the mucus and sand mixture. Similarly, the low masses of silk

produced by larvae reared in laboratory conditions again necessitated low pesticide

concentrations in order to detect appreciable differences before, and after, exposure

due to sorption. A t 5 and 10 \ig l ‘, pesticide concentrations are close to the working

limit of detection. Micrograms per litre are equivalent to nanograms per ml, GC

injection samples prepared from each treatment were just 0.3 ml. For this reason,

certain pesticides were more reliably detected than others. This explains the rather

large standard deviation on Figures 4.6 - 4.12. That small quantities o f organic

material (mucus and silk) were produced in the laboratory does not indicate that such

material is limited in the environment. Ladle et ai, (1972) measured a density of up

to 300,000 Simuliidae larvae per square metre of vegetation in the area from which

egg masses were collected. Potamopyrgus spp. can exist at very high densities: up to 146

28,000 individuals per m ' of stream bed (Armitage pers. comm.). Lymnaea spp. are also able to exist at high densities in rivers, up to 965 (Extence, 1981). The organisms that produce the materials examined within this study can occur at high densities, producing considerable quantities of mucus and silk. However, in order to produce mucus and silk in the laboratory in a useable, fresh form, certain limitations are imposed upon production. For successful hatching of blackfly eggs in a glass jar incubator, most of the space available is required for aeration blocks. Similarly, the snails were observed to remain immobile in a dish o f sand, unless they have sufficient space in which to move around. The practical considerations associated with these experiments on snails and blackfly larvae tend to lim it production o f mucus and silk.

4.3.8 Mucus and silk as water purifiers

The examination of pesticide attachment to sand coated in snail mucus is analogous to the examination of slow sand filter beds as agents o f pesticide sorption. Slow sand filter beds are used by the water industry as a purification stage. Woudneh et al.,

(1996) reported the removal o f up to 17% of pesticides at optimum conditions using slow sand filter beds. Although they did not define the means o f removal, they presented their results as a means of bioremediation. By not defining the means of removal it can only be assumed that the pesticides were either photolytically degraded and their degradation products not detected, or that the pesticides were sorbed by schmutzdecke (the layer o f particles and organisms that forms on a filter bed).

Significantly, they found no removal of atrazine at all. If these results are compared with up to 54% removal by snail mucus and up to 98% removal by silk (see Table

4.10), the ability of the organic material (examined in this study) to sequester xenobiotics is apparent. Table 4.10. Percentage sorption of pesticides by blackfly silk and pedal mucus from two species of freshwater snail.

Pesticide Simazine Atrazine Propazine Desmetryn Prometryn Terbutryn Fenitrothion Malathion Cyanazine Parathion

"Blackfly silk 25 2 0 .6 15.3 2 1.2 32.8 58.0 94.9 88.0 16.9 96.9

^ P.Jenkinsi pedal mucus 1.8 3.3 2.6 54.1 50.3 0.1 2.7 — 0.1 9.3

' L p e re g ra pedal mucus 1.0 1.9 1.3 14.9 15.9 -- 0.1 0.3 7.1

“ Silk samples numbered 29, over the range 0.1 - 4.9 mg, exposed to 25 ml o f pesticide suspension o f either 5 or 10 pg -p^ P. je n k in s i mucus samples were produced using masses o f snails weighing 2.4 - 25 g. ,1 Eighteen samples were exposed to 25 ml of pesticide suspension of either 5 or 10 pg 1 ' L pe reg ra mucus samples were produced using masses o f snails weighing 0.7 - 5.0 g. Sixteen samples were exposed to 25 ml o f pesticide suspension of either 5 or 10 pg l ' 148

4.3.9 Placing blackfly silk and snail mucus in the context of other

materials studied.

W orking with pyrethroids which have exceptionally high values due to their extremely hydrophobic nature, Zhou et ai, (1995 c) found values o f 120,000 to

770,000 on a variety of organics coating clay minerals, most notably aromatic containing polyelectrolytes such as humic acids. Zhou et al., (1995 d) presented a table of organic compounds most likely to interact with pyrethroids: humic acids, fulvic acids, hydrophilic macromolecular acids, and then natural coatings on estuarine suspended particles. It is unfortunate that they limited themselves to pyrethroids which are expected to have exceptionally high values anyway, and that there is no overlap with the suite of compounds used in this study, to place macro in vertebrate organics such as silk and mucus into such a table. Their papers do illustrate however, the great potential of organic materials to sorb pesticides.

Some reviews state that pesticides are harmless, and that examination o f sorption onto materials other than sediments is futile. H ill (1989), stated that pyrethroids, despite very high LC^q values, would have no effect on freshwater ecosystems, and that such pesticides were in fact transitory and harmless. The basis for this claim is that, as pyrethroids have such high K j values, they will sorb onto almost any material, and it is possible that they may not undergo desorption. However, soils and sediments are not stable, non-dynamic media. Keilty et al., (1988) demonstrated that oligochaetes move pesticide contaminated sediments upwards, disturbing clean surface sediments and refuting the concept of bioremediation of contaminated water bodies by adding additional sediment to encase the pesticide (Isensee, 1983). The sorption of almost all pesticide compounds is pH dependent, due to the attachment o f hetero-atoms

(atoms other than carbon or hydrogen). The pH o f river water is unlikely to present a sufficient pH range to have any effect on sorption or desorption. The pH of some

invertebrate guts however, does present a pH range sufficiently broad as to affect the sorption of pesticides on DOM (Wotton 1996).

H ill (1989) concedes that zooplankton and aquatic stages of insects might be affected 149 by pyrethroid contamination. Furthermore, pesticides may be transferred to local predators via the food chain. Most important of all, is the consideration that organic material produced by macroinvertebrates (such as mucus and silk) which has a strong affinity for pesticides (far more so than soils and sediments), is also a food source for other organisms. It would seem therefore that if pesticides enter a freshwater system, they have the opportunities to attach and persist. The problem up to now has been in not identifying the correct component of sediments or soils to sample. A problem remains in trying to sample the appropriate fraction of sediments, the organic coatings around minerals that sorb pesticides.

4.3.10 The importance of accounting for pesticide affinity to biological

material

The last thirty years have seen many advances in pesticide technology, in their manufacture, detection and modelling of their persistence. However, pesticide technology has failed in forming cross-links between related disciplines. Clark et al.,

(1991), while examining pesticides in water from a chalk catchment area, pointed out that, historically, pesticides have been used for far longer than they have been monitored. In order to understand the behaviour of such contaminants, far greater information about aquifers is required. For example. Gomme et al., (1991), investigating the same catchment, noticed that factors such as season are important.

In spring-fed streams, summer flow w ill be low and winter flow w ill be fast, while aerial deposition and land run-off w ill be a series o f discrete events. A new research front (Spark and Swift, 1994) is pesticide interactions with humic acids. However, examination of materials other than sediments and soils or sub-lethal responses by

individual species has been limited.

In measuring sorption onto sediment, Karickhoff et ai, (1979), stated that values

can generally be predicted from values using the predictive equations already

available, since Kenanga and Goring (1980) had shown that there is essentially little

difference between them. As far as sediments and soils are concerned they are largely

correct. There seems to be little discernible difference between soil and sediment 150 types, with regard to sorption of individual pesticides (see Table 4.11). However, that is only the case if the minerals are washed. If the minerals are coated in organic material, then considerable variations are detected. Hence the importance o f isolating and defining sorption of individual organic materials (Zhou et al., 1995 a,b,c,d). In attempting to predict pesticide sorption, desorption and persistence in rivers and streams, it is no longer sufficient to examine pesticide sorption onto soils or bed sediments in isolation. Biological material exists w ithin freshwater systems, which is capable of sorbing xenobiotics to a high degree. Indeed, many biological materials such as mucopolysaccharide, silk and biofilm communities, due to their chemical structure and physical design, are particularly suited to sorbing micro-organic compounds such as pesticides (Bishop et al., 1995). Furthermore, not only are these materials ubiquitous and often present in large quantities over almost every surface

(mucus and biofilm exist on sediment, stones, roots etc), but they are also an essential food source for macroinvertebrates, and ultimately all consumers within freshwater systems.

These results show that organic materials such as snail mucus and silk have a high affinity for a range o f pesticides, and by sorbing pesticides from the water column they provide access for pesticides into the food chain. 51

Table 4.11 Comparison of distribution coefficients for blackfly larval silk with other distribution coefficients found in the literature for the pesticides used in this study (ml mg ')

R e fe re n c e a b b c d e f g

Pesticide K„ K.... K.; K . K,. K K,.

Simazine 135 135 1.9x10" 130 Atrazine - - 550/3000 148 149 1.7x10" 100 Propazine --- 158 160 1.6x10" 154 Desmetryn ---- 1.7x10" - Prometryn - - - - 810 2.4x10" 400 Terbutryn -- 700 4.9x10" 2000 Fenitrothion ----- 13x10" 2000 Malathion 0 57 - 0.72 --- 1778 24x10" 1800 Cyanazine -- 200 200 7.1x10" 190 Parathion 0 29-0.39 0.78 ■64.9 351 - 972 - 6457 4800 31x10" 5000

a Sujatha and Chacko (1992) on three unwashed estuarine sediments, b Get S t I and Mengelgrin (1984) on 11 unwashed soils and 4 unwashed lake sediments c Bottero ei ul (1994) on zeolite and organoclay respectively, d Karickhoff (1981) on 17 soils and sediments from across the USA e Kcnaga and Goring (1980) A general review o f all available predictive equations, f This study, distribution coefficients for blackfly silk g Hornsby ct al (1996), estimated values based on the diverse range o f K j values available. 152

4.4 Conclusions

1. Values are presented for sorption of the pesticides simazine, atrazine,

propazine, desmetryn, prometryn, terbutryn, fenitrothion, malathion, cyanazine

and parathion onto blackfly larval silk and the pedal mucus of two freshwater

snails.

2. Pesticide contamination studies are traditionally limited largely to materials

(soils and sediments) that are inappropriate (in isolation) to environmental

studies, in that these materials do not exist in isolation, but are often coated

with organic material.

3. Organic materials produced by invertebrates, are a rich food source, and are

an important, yet neglected, class of materials in terms of sorption studies and

for models relating to pesticide contamination and retention in the

environment.

4. Organic materials produced by invertebrates have a high affinity for pesticides,

capable of sorbing such compounds to a far greater degree than soils or

sediments alone.

5. No statistical differences were found between the sorption of pesticide

compounds. Coupled with the high sorption of hydrophilic as well as

hydrophobic compounds, this suggests that the mechanism o f pesticide sorption

onto mucus and silk is determined by the nature of the organic materials, rather

than by the chemical nature, atomic weight or structure of the pesticide

compounds. Characteristics such as pesticide atomic weight or structure

cannot, however, be assumed to have no influence on their sorption on to

materials within the water column.

6. By sorbing onto organic materials of such high food value, pesticides are

accessible to the food chain, leading to implications of bio-accumulation. 153

Table 4.12

Definition of parameters used in this study. The distribution coefficient for mucus produced by a known wet weight of snails:

(Amount o f pesticide sorbed onto mucus) |ig = (mass o f wet snails that produced the mucus) g ° \ (concentration of pesticide e solution after 24 h equalihration)

Hence, K„ has units of:

ml {wet weight of snail)

Using the conversion factor of 3.6 x 10^ g (mucus) g * (snail) d

(Amount o f pesticide sorbed onto mucus) ^ I ______5______(mass o f mucus) ______g [______[concentration of pesticide e solution after 24 h equalibration)

So that has units of:

= ml gr-i {mucus)

Similarly, the distribution coefficient for silk is defined as:

(Amount of pesticide sorbed onto silk) \ig K. = ______(mass of s ilk ) g ______\ (concentration of pesticide € solution after 24 h equal ibration) jig m l'^^

giving in units of :

= m l ( s i l k ) 154

Chapter 5 Sediment stability

5.1 Introduction

In looking at invertebrate distribution in shallow lakes in relation to sediment stability,

Moss and Timms (1989) found greater invertebrate colonisation in stable sediments.

By offering such stable areas to invertebrates (with sediment, free of macroinvertebrates, allowed to settle in plastic bowls, covered in protective netting and buried such that it was level with the surrounding sediment), they concluded that structure of the sediment, rather than food content, was the primary attraction for oligochaetes and chironomids. It is possible that organisms such as these, in secreting mucus and silk, w ill also contribute to the stability of sediments. Moss and Timms did not, however, venture any hypotheses on the means by which sediments in bowls become more stable in the first place. W ork on microaggregates o f picoplankton by

K lut and Stockner (1991) may provide some clue as to how this process, or rather cycle, begins. They describe small aggregates o f planktonic cells that seasonally form in order to reduce the risk of herbivory. O f specific interest to my study is the observation that, as nutrient availability declines seasonally, greater quantities of unspecified "non diffusible cell exudates" are produced. It is conceivable that such exudates are polysaccharide-based, and that, following senescence of such microaggregates, they might sink. In so doing, they will settle upon and blanket benthic sediments, so producing the stable areas described by Moss and Timms

(1989), that might favour invertebrate colonisation.

It is only recently however, that such material as TEP and microaggregates (albeit in a different form, ie colloidal organic carbon aggregates (Kepkay, 1994); estuarine TEP

(Syvitski et al., 1995); suspended solid's aggregates, (Maldiney and Mouchel, 1995);

CEP (Wotton, 1996); particle aggregates (Gregory, 1997)), have been noted to exist in lotie systems. Carlough (1994) looked at particulate amorphous seston in a blackwater river, composed of "clay, organic debris and microorganisms within a matrix of mucopolysaccharide fibrils". Examining biofilm on wood in the same river.

Couch and Meyer (1992) noted that microbial extracellular polysaccharide may be 155 assimilated by detritivores. However, it was Wotton (1996) who first made the connection that the recently categorised TEP also existed as a similar material (as yet unnamed), in rivers as well as oceans. In reviewing colloids, bubbles and aggregates with regard to their role in suspension feeding, he noted that colloidal exopolymer particles (CEP) act as a vehicle for the aggregation of dissolved organic matter.

Others were certainly aware o f such suspended aggregates and Maldiney and Mouchel

(1995) developed a new means of studying them in situ. Whilst they noted that aggregation accounts for the "biogeochemical fate" (via sedimentation) of a proportion of certain contaminants via sticky polysaccharides, their main aim was to observe suspended particles rather than speculate on the effect, or source, of such floes. It was thought that most aggregates would settle on to sediment, where, due to greater turbulence, shear stresses would erode floes, so depositing pollutants onto sediments.

It is not unreasonable to assume that remnants o f sticky polysaccharide floes w ill also settle upon sediments, possibly sealing in, or encapsulating whatever particles / pollutants they have transported. This assumption is particularly plausible when one considers the action of macroinvertebrates such as snails which coat sediments in trails of polysaccharide. Additionally, tube builders utilise particulate matter, while burrowing organisms drag organic material below the surface of sediments (Dudgeon,

1990).

5.1.1 The role of macroinvertebrates in sediment stabilisation and

disturbance

A ll the studies examining sediment consolidation cited in Chapters One and Five, have looked largely at bacterial mucopolysaccharide. Only Moss and Timms (1989) hinted that something other than bacteria may be responsible for the initial primary cohesion of sediments that bacteria subsequently stabilise. Scheffer et al., (1993) suggested that lake sediments undergo a cycle, such that lake waters are alternately turbid and clear.

W hilst this is probably due in part, to algal or bacterial blooms, there is a gap in the theory as to what provides an initial foothold for the stabilisation of sediments in lakes. Macroinvertebrates may provide the answer via the bioturbation they cause and possible stability they lend to benthic sediments. Blauchard et ai, (1997) used snails 156 as agents of bioturbation, while burrowing organisms are known to stabilise the walls of their burrows with polysaccharide (de Vaugelas and Buscail, 1990). Furthermore,

Chapter Two illustrates the sustained attachment of sediment particles to STM. There is then a gap in the literature concerning the contribution made to sediment stability by freshwater macroinvertebrates, or indeed, macroinvertebrates of any aquatic environment.

The following experiments are an attempt to investigate whether macroinvertebrates,

(in this case, river snails) promote sediment stability. Whilst tubificids or chironomids may work sediment, coating discrete packages with organic material, snails coat greater areas with polysaccharide simply through greater daily mobility. Such areas may then hold particles that impact upon a surface, or may serve to bind lose sediment and fine particles long enough to allow for bacteria to produce further quantities of polysaccharide interstitially. Gastropods are known to actively farm the bacteria that impinge upon their mucus trails (Connor and Quinn 1984), and I have shown that snail trails persist over a number of days (Chapter Two). Each of the four experiments was an attempt to quantify the cohesive properties of polysaccharide, or other organic material, within a lotie system. Organic material, bacterial mucopolysaccharide and snail trail mucopolysaccharide are the three basic ingredients under trial, in various combinations.

5.1.2 Experimental objectives

The main objective was to design, construct and calibrate a "low cost - low tech" procedure that would measure accurately, the cohesion of sediments. Using a number of different sediment preparation procedures, additional objectives were the quantification of the degree of cohesion offered to sediment by:

1) Undefined natural organic, and inorganic, fractions (that provide stability to

sediments);

2) Snail mucus with undefined natural organic, and inorganic, fractions;

3) Snail mucus alone;

4) Snail mucus with bacterial EPS that may be present as a result of snail mucus; 157

5) Bacterial EPS, algal exudates and other materials that exist, or are swept up,

in the water column rather than being bound to sediments, and;

6) The impact of macroinvertebrate sediment dwellers;

5.2 Materials and Methods

Preparation of dried sediment

Wet sediment was removed from the Botany Pond, fed by the M ill Stream leat of the

River Frome, East Stoke, Dorset (NGR: SY 876 868). Material was collected from the surface of the pond sediment, using a pond net, up to a depth o f 20 cm. Sediment was allowed to settle, was decanted, then sieved as a slurry through a 2.0 mm sieve to remove coarse matter. Sediment was further allowed to settle overnight, before being decanted, placed in metal baking trays and dried at 60®C. Pieces of dried sediment were ground in a mortar and pestle and sieved, the fraction between 250 |im and 500 |im being retained. This size fraction was placed in ceramic crucibles and burned, using methanol, to remove excess organic material (an attempt to reduce noxious smoke emissions within the laboratory). The remaining sediment was ashed in a muffle furnace at 550°C for at least 12 hours, to remove all organic material, leaving only dry mineral sediment (Figure 5.1).

Fresh Sediment

Wet sediment was collected from the Botany Pond as above, and wet sieved, retaining the fraction between 250 |Xm and 500 jlm (Figure 5.1) and therefore retaining all organic matter of this size. Ilic Hv)tan> I’ixul. I ,:isl Stoke Dorset. \(!K:SY X67 S(>X

Sediment prqjaraticMi D 1 Glass tank of dried prepared sedimait and snails.

Sediment sampled from top 20 cm Sediment preparation D 2 oily, sieved at 2 mm and allowed to settle

Allowed to settle, water decanted off, cooked for 48 hours at 1 ^ 60®C to remove pore water. Sieved (250-500 pm), flamed and ashed at 550°C for 12 hours to ranove all organic material. Ln Sediment preparation B 1 00 Sediment preparation A 1 Sedimmt preparation A 2 Sediment preparalic® B 2 ▼ ▼ Sediment preparatiai C 1 / Sediment preparation C 2

Tanks ofwel unwashed sediment, covered with riva wata and left for 7 days. Tanks of dried organic free sediment, one left in riva wata with snails for 7 days, the otha left ovalaid by an antibiotic solution.

Figure 5.1 Mesh bag of sediment, suspended in flowing riva water Schematic diagram to illustrate the preparation o f each o f the four sediment types with associated controls. 159

Experimental design

Four experiments were designed, with controls for each (Figure 5.1). These experiments allow comparison of the effect of L. peregra STM on three types of sediment; Fully conditioned wet sediment, coated in unidentified background organic material (Al); clean dried sediment, free of organic material of any kind (Bl); and sediment subject only to organic material of a bacterial origin (Cl). In addition, further comparisons can be made, determining the degree o f cohesion offered by bacteria only (C2 with B2), and all organic material (A2 with B2). D1 and D2

(sediment free of organic matter, and fresh, wet sediment respectively) define the parameters within which all other treatments w ill be measured, whilst also offering comparisons to quantify organic components, i.e. the stability conferred by snails can be measured by comparing treatment D2 to A l.

5.2.1 Experimental Protocols

5.2.1 A Cohesion from snail mucus with natural background organic

material (wet sediment).

A 1) This treatment was an attempt to determine the degree of cohesion conferred by freshwater snails, (L. peregra) in addition to naturally-occurring materials that lend cohesion. Wet sediment was placed in a large glass tank filled with river water.

Snails were allowed to crawl over the sediment for seven days.

A 2) The control for this treatment was also wet sediment, left for 7 days in a glass tank of river water, but without snails. No washing, or rinsing, of sediment took place so as to minimise disturbance of organic coating on sediment particles.

5.2.1 B Cohesion from Snail Mucus without natural background organic

material (dry sediment).

B 1) The second treatment was also designed to examine the degree of cohesion conferred to sediment by snails, but in isolation from other factors that lend stability.

Dried prepared sediment (free of organic material) was placed in a large glass tank, and snails were allowed to coat the particles for seven days.

B 2) The control in this case was dried prepared sediment left in a glass tank for 7 160 days with river water, with an antibiotic (chloramphenicol (Fisher C/4322/47) 1 g 1‘, as described in Chapter Three), added to prevent bacterial growth.

5.2.1 C Cohesion from bacterial EPS resulting from bacterial

entrapment on STM.

C 1 ) The third treatment was designed to measure cohesion offered by bacterial EPS arising from entrapment due to STM on sediment. Dried, prepared sediment (free of organic material) was exposed to snails for seven days, then placed in mesh bags, sewn from nylon mesh of 250 |Lim (small enough to retain the prepared sediment fraction of 250-500 |im, large enough to allow stream water and bacterial cells through) and suspended in the flow o f the M ill Stream.

C 2) The control was dried prepared sediment, placed in mesh bags and suspended in the flow of the M ill Stream for 7 days. It was expected that bacteria, DOM , POM etc would become trapped by the dried sediment, and would lend cohesion to the sediment. The aim of this trail was to assess the additional trapping potential of STM on sediment.

5.2.1 D Cohesion conferred by natural background organic material (wet

versus dry sediment).

D l) The fourth treatment was designed to set the parameters within which all other treatments were viewed, a blank and a control. Acting as a blank, dried prepared sediment was left in mains water to settle for 24 hours.

D2) The control in this case was designed to define the maximum degree of cohesion (while D l should define lack of cohesion). Treatment D2 was wet sediment, removed from the Botany pond, unwashed, allowed to settle for 24 hours, and used directly.

(See Figure 5.1). 151

Paddle Motor

Water in glass jar Light Detector Light Beam

Paddle

Prepared Paddle Motor Control sediment

C - Ring Light Meter

Data Logger and converter

Figure 5 .2 Diagram illustrating measurement of turbidity achieved within a jar o f water containing prepared sediment that has been allowed to settle for 24 hours. At each o f seven set speeds o f the paddle, turbidity is measured by the amount o f light that penetrates the turbid water. 200

150 y = 242.41x- 313.; R^ = 0.9911 100 P > 0,995

I 0) ■a 0.2 0.4 0.6 0.8 -50 0 O) -100 c

1 -150 I -200 Ch CO

-250

-300 T

-350 ^

Optical density

Figure 5.3 Calibration curve of light detector using a series of optical density filters. Errors bars are one standard deviation, based on 5 replicate readings with varying intensities of background light

Optical density units relate to the amount of light allowed to pass through, based on a log to the base 10 scale. For example, at zero, all light is allowed to reach the detector, at 0.3, 50 % of light is allowed to pass through 1, 10% of light is allowed through, and at 2, 1 % of light is allowed through. 163

5.2.2 Equipment design

Experimental equipment used is depicted in Figure 5.2. Each glass jar was 205 mm tall and 95 mm in diameter. The paddle was made o f Teflon® coated plastic and was

45 mm in diameter, consisting of 4 blades of equal dimensions on a stem o f 6 mm diameter. Both the paddle motor and the C-ring light meter were of an unspecified make or model number. The rheostat paddle motor control was an Andeman and Co.

Ltd. Multi speed fine control unit, and the data logger and converter was a Husky

Hunter 16 (1.6 MB).

5.2.3 Calibration of light meter

The light meter was calibrated using a series of five glass discs of known optical density, (ranging from translucent (0), to almost opaque (2), allowing only 1% of light through), (Figure 5.3). The calibration was performed five times at varying levels of background light intensity. The minimal variation (bars at each point are one standard deviation of the 5 readings) between such calibrations and the operation o f the light meter as a UV detector showed that ambient light was not a consideration ie background light played no part in UV light scatter and detection. The resulting equation (Figure 5.3) relating light meter reading to optical density filter allowed calculation of turbidity with each treatment Jar.

5.2.4 Calibration of speed o f water in Jars at each paddle setting.

Two methods were employed to determine the speed of the water at various locations within the Jar. Using a Kent Miniflow electric current meter (propeller 10 mm diameter) (used by Armitage and Davies 1989) the speed was generally too low to cause any movement of the propeller at all. The only registered speeds were at paddle speed settings 6 and 7 at paddle height (1 and 1.5 cm/s respectively). A ll lower settings (1-5) at paddle height, and all settings (1-7) at positions above the paddle, mid water column and directly above the sediment surface were un-measurable. The second method of determining the speed of the water at each paddle setting was using 164

Fluorescein dye, the time taken for drops to make a circuit at paddle height, and at the surface of the water column, being recorded.

5.2.5 Sampling

For each of the eight experimental preparations (See Figure 5.1), 5 aliquots of 100 g of sediment were used. Each aliquot was placed in an identical glass cylinder and allowed to settle in distilled water (which offers consistent, negligible turbidity) for

24 hours. Following this period, the rotating paddle was inserted into the cylinder and fixed at 5 cm above the surface of the sediment. A t each o f 7 set speeds of rotation, the turbidity was measured using the C ring light meter attached to the Husky Hunter data logger and converter. The mean of 5 readings was taken at each speed for each cylinder. Upon reaching each speed setting, a period of 15 seconds elapsed to allow

"disturbance equilibria" to be reached (time to allow excess disturbance caused by the increase in paddle speed to dissipate, leaving only the increased turbidity due to the increased paddle speed). Twenty-four hours after the first reading had been made, a second series of readings were taken to determine whether any changes were detectable over this time period.

5.2.6 Data manipulation

The mean of the five turbidity measurements at speed setting zero was calculated and subtracted from every subsequent raw data point for each replicate jar. Thereafter, the mean and standard deviation of each set o f five turbidity measurements was calculated.

These were used to calculate the coefficient of variation for each treatment. In addition, mean readings for each Jar at each speed within each treatment were also averaged, and the mean turbidity for the five replicate jars plotted against paddle speed.

Student's t-tests were used to determine differences between treatments and appropriate controls, using mean turbidity readings for each treatment {ie. mean readings of all 5

readings of all 5 replicate jars within each treatment). Lastly, ANOVA was performed 165 on the raw data (post standardisation around the mean turbidity reading at paddle speed zero). This served to compare differences between jars at each speed and over time (readings were taken 24 hours after preparation, and again, 24 hours after the first reading to assess the effect of induced bioturbation) within each treatment.

5.3 Results and Discussion

5.3.1 Water speed generated by paddle speed

Increase in the paddle speed generated an exponential, rather than a linear increase in water speed, (Figure 5.4). That water speeds generated at paddle height are all slightly higher than those at the water surface implies that the water speed below the paddle was greater still. This does not account for the boundary layer effect, but does give an indication o f the relative change in water speed above the sediment as paddle speed increases. Measurement o f water speed below the paddle proved impossible due to dispersal o f the dye by the paddle. This suggests that the sediment surface was subject to a certain degree o f turbulent disturbance, mimicking the flow of a stream.

5.3.2 Light meter readings at each paddle speed

An internal test of reproducibility was applied to each treatment, whereby the coefficient of variation (cv) was calculated for each set of five replicate readings for each jar at each speed. A large cv value (above 5%) suggests that variation within results is due to inconsistencies within the experimental system, i.e. glass treatment jars, light meter etc. Such values vary widely for each treatment jar, but are generally under 5%. The mean o f all treatments at paddle speed zero is 3.5%. This suggests that data are usable, despite the wide variation in light meter readings, noted during experimental readings. 1.8

1.6

Water surface Paddle Height

I I « 0.8 - I

0.6 4

0.4 I

0.2 +

0 1 2 3 4 5 6 7 Paddle Speed settings

Figure 5.4 Water speed generated at paddle height and at water surface by each paddle speed setting. 167 1800

1600

1400 ■ - A2 1200

o 1000 : s 800 g 600

400

200

-200

-400 0 1 2 34 5 6

Paddle speed setting

Figure 5.5

1600

1400

1200 - A2 1000

g 800 0 600

1 400 x:O) □ 200

-200

-400

-600 0 1 2 3 4 5 6 Paddle speed setting

Figure 5.6

Progression of light restriction due to turbidity as paddle speed increases. Sediment preparation A, A l - wet sediment, in tank of snails in river water for 7 days A2 - wet sediment, in tank of river water for 7 days.

First reading (24 hours after sediment placed in observation jars) - Figure 5.5 Second reading (24 hours after first reading) - Figure 5.6 Average light restriction at each speed setting o f five replicates, error bars are one SD. 168 3000

2500 *

■ ■ B2 2000 ; I 0 1500 ' 1 S 1000 • O) _i 500 T

0 #

-500 - t 2 3 4

Paddle speed setting

Figure 5.7

6000

5000

4000 ■ - B2

c 3000 o 5 2000

I 1000 O) _l

-1000

-2000

+ H 2 3

Paddle speed setting

Figure 5.8

Progression of light restriction due to turbidity as paddle speed increases. Sediment preparation B, Bl - dried organic free sediment in tank with snails for 7 days B2 - dried organic free sediment overlaid by an antibiotic solution for 7 days

First reading (24 hours after sediment placed in observation jars) - Figure 5.7 Second reading (24 hours after first reading) - Figure 5.8 Average light restriction at each speed setting o f five replicates, error bars are one SD. 69

100

80

60 ■ " C2 40 c o I 20 -20 -I -40

-60

-80

-100 i -H-- 2 3 4

Paddle speed setting

Figure 5.9

1200 ; 1000 +

800 - ■ - C2

c 600 - o t 400 r s 200 sO) -I

-200

-400

-600 J 4 t 4- 2 3 4

Paddle speed setting

Figure 5.10

Progression of light restriction due to turbidity as paddle speed increases. Sediment preparation C, C l - dried organic free sediment in tank with snails for 7 days, then placed in mesh bags in river for 7 days - C2 - dried organic free sediment in mesh bag, suspended in river.

First reading (24 hours after sediment placed in observation jars) - Figure 5.9 Second reading (24 hours after first reading) - Figure 5.10 Average light restriction at each speed setting o f five replicates, error bars are one SD. 70 25000

20000 Ds

c 15000 o 4-«0 1 10000 O) 5000

0 »

-5000 0 2 3 4 5 6

Paddle speed setting

Figure 5.1 I

20000

Dl 15000 ■ - Ds

c o u 10000 1 Z en 5000

-5000 -4------2 6

Paddle speed setting

Figure 5.12

Progression of light restriction due to turbidity as paddle speed increases. Sediment preparation D, D l - Dry Sediment, D2 - Wet Sediment First reading (24 hours after sediment placed in observation jars) - Figure 5.11 Second reading (24 hours after first reading) - Figure 5.12 Average light restriction at each speed setting of five replicates, error bars are one SD. 171

The progressions in turbidity, or light restriction, for each treatment are presented in

Figures 5.5 - 5.12 Each figure has two progressions, one for the experimental treatment, one for the appropriate control. In almost all of these figures there is a steady progressive increase in turbidity up to paddle speed 5, thereafter, the turbidity, with increasing water velocity (Figure 5.4), escalates rapidly. This pattern highlights the first problem encountered by such an experimental design, the non-graduated increase in paddle speed afforded by the rheostat paddle control. It was observed that for all readings, relative clarity was maintained above the surface of each replicate sediment layer, just prior to paddle speed setting 5, thereafter, a cumulative water speed approaching vortex conditions appeared to stir up loose surface sediment, often resulting in total turbidity.

In addition, each data point has bars. These are standard deviations around the mean for each treatment {ie of the five replicate readings of the five replicate jars). In almost all cases, the error bars for the experimental treatment overlap with those of the control (described in section 5.2). Indeed, Student's t-test's between treatments and controls (Table 5.1 A) show no significant differences for any of the four experimental groups on either measurement (24 or 48 hours after preparation of each jar), excepting treatment C l against C2 on the first reading (sediment suspended in flow ing river water, with (C l) and without (C2) exposure to STM). That no difference was observed on the second reading suggests that the statistical significance was lessened by the effect of induced bioturbation (taking a set of readings 24 hours after the first set). 172

Table 5.1A

Comparisons between treatments and controls using Student's t-test

Treatment (hours) Variance t P

A1-A2 (24) unequal -1.31 0.25

B1 - B2 (24) unequal -1.00 0.36

C1-C2 (24) equal 5.26 P «0.001

Dl - D2 (24) equal -0.52 0.61

A l - A2 (48) equal 1.02 0.33

B1-B2 (48) unequal -1.48 0.20

C1-C2 (48) unequal -0.92 0.40

Dl - D2 (48) equal -0.33 0.75

The effect of disturbance (or artificially induced bioturbation, and subsequent re­

settlement) was examined by the comparison o f data from each treatment and control

set of five replicate jars, against those same jars, examined 24 hours later. Using

Student's t-test demonstrates (Table 5.1 B) that disturbance had an effect upon the

cohesion of re-settled sediment in only two cases; treatments A l and Cl. That

differences are noted following disturbance due to bioturbation involving snails

confirms the findings of Blauchard et al., (1997). However, similar differences would

also therefore be expected between examination days for treatment B l which also

features STM. That no differences are detected suggests that the data exhibit far too

great a variance due to errors introduced by the factors already mentioned,

(inconsistencies in light meter readings and jars), to allow meaningful statistical

analyses. 173

Table 5.IB

Comparisons between jars against time (hours in brackets), examining the effect of disturbance using Student's t-test

Treatment variance t P

A l (24 - 48) unequal 2.76 0.03

A2 (24 - 48) unequal -0.45 0.67

B l (24 - 48) unequal 1.70 0.15

B2 (24 - 48) equal 0.36 0.72

C l (24 - 48) equal 2.73 0.02

C2 (24 - 48) unequal 1.17 0.29

Dl (24 - 48) unequal 0.40 0.70

D2 (24 - 48) equal -0.48 0.64

As noted above, few treatments exhibited a difference to the appropriate control (one

out of eight. Table 5.1.A). Few differences between treatments were noted post

bioturbation (two out of eight comparisons. Table 5.I B). With this in mind, raw data

were once again examined in order to determine whether such a lack of significant

differences was due to the immeasurable nature o f the material / effects studied, or due

to flaws in experimental design. Consequently, analysis of variance was performed,

in order to examine the amount of variation between replicate jars due to sampling

time (first and second readings, pre and post bioturbation), individual jars and error

due to other aspects o f experimental design such as the light meter. The results of this

analysis are presented in Table 5.2, and illustrate that a very large proportion of the

within treatment variation is due to unaccountable variables such as the light meter

(multiway analysis o f variance, Sokal and Rohlf, 1981). 174

Table 5.2 A N O V A (using balanced designs) for turbidity, using four

randomly selected treatments o f the eight prepared:

A l Wet, fresh botany pond sediment, in river water for 7 days, exposed to snails.

B l Dried, sieved sediment, free of organic material, exposed to snails for 7 days.

C2 Dried, sieved sediment, free of organic material, suspended in flowing river

water for 7 days

D2 Wet, fresh botany pond sediment.

A l

Source DF S3 MS FP

Hours 1 4.335x10^ 4.335x10" 7.95 0.030

Jar 6 4.772x10^ 7.953x10' 1.46 0.329

Hours and Jars 6 3.270x10' 5.450x10' 7.67 0.000

Error 336 2.387x10" 7.105x10"

Total 349 3.625x10" Variance component due to jars is 13.2%, error due to light meter and other errors is

65.8%

B l

Source DF SS MS FP

Hours 1 2.565x10' 2.565x10" 9.06 0.024

Jar 6 2.173x10' 3.623x10' 1.28 0.386

Hours and Jar 6 1.698x10' 2.830x10' 2.53 0.021

Error 336 3.753x10" 1.117x10'

Total 349 4.397x10" Variance component due to Jars is 4.9%, error due to light meter and other errors is

85.4% 175

C2

Source DP SS MS F P

Hours 1 6.006x10' 6.006x10' 1.03 0.349

Jar 6 2.061x10" 3.434x10' 0.59 0.731

Hours and Jar 6 3.490x10" 5.817x10' 6.52 0.000

Error 336 2.998x10? 8.924x10"

Total 349 3.614x10? Variance component due to jars is 5.7%, error due to light meter and other er

82.9%

D2 Wet, fresh botany pond sediment

Source DF SS MS F P

Hours 1 6.628x10"’ 6.628x10"’ 1.02 0.352

Jar 6 3.823x10" 6.372x10"’ 0.98 0.511

Hours and Jar 6 3.912x10" 6.520x10"’ 1.09 0.367

Error 336 2.007x10" 5.973x10"’

Total 349 2.091x10" Variance component due to jars is 1. 8 %, error due to light meter and other errors is

95.9%

The analysis o f variance detailed in Table 5.2 illustrates that the explanation for such a lack of discernable difference between treatment and controls is largely due to random noise. Such noise could be a result of inconsistencies in the glass Jars coupled with the sensitivity of the light meter. As described in the data manipulation section

(5.2.1), for each set of 5 replicate readings at each o f the 7 paddle speeds for each individual replicate jar, the mean light meter reading at the lowest speed was calculated and subtracted from every reading at every speed for each jar. This was an attempt to reduce the variation in light meter readings at speed zero, ie a standardising, across still, clear settled water. However, considerable variance between replicate jar light meter readings at individual speed settings remain. Analysis of variance of a random selection of 5 treatment jars at a particular speed reveals that for treatment A l, at paddle speed setting five, 27% of the variance found between jars was due to the jars themselves. 176

For this reason, treatments are not directly comparable to each other, nor indeed is one replicate jar to another. Hence for the sake of this study, comparisons have been limited to treatments against controls, and no attempt made to define the stabilising effect of each individual organic fraction within the sediment, as per the original objective.

Lastly, sensitivity of the light meter caused additional problems. It seems that each cylindrical glass treatment column acted as a light reflector or lens. This would explain the fact that detector readings for experimental readings were beyond the scale used to calibrate the light meter from zero to almost total light obstruction.

Because of these difficulties, the data generated within this study are insufficient to provide evidence for, or against, the experimental aims. The data are subject to too much noise, as well as being incomparable between replicates due to differences in the scale of the light meter response.

Due to the difficulties and design failings described, it is not possible to describe, or compare, results for each treatment. However, visual observations when preparing sediments did back up expected findings. It is assumed that wet, untreated pond sediment would exhibit the greatest cohesion, or the greatest resistance to disturbance.

Such an assumption is based on the unknown organic inputs of various natural sources, such as colloidal matter, bacterial EPS, algal polysaccharide material, macroinvertebrate secretions, fish mucus, algal and macrophyte exudates etc. Quite whether sediment containing such unknown fractions would be made even more cohesive by the known addition of snail mucus remains open to speculation. It must also be considered that storage of wet sediment in a tank at room temperature for a week may have caused sediment cohesion to decrease by allowing such organic material to degrade, or even be consumed by the snails.

Preparation of dry sediment as described above is a destructive process, not only removing all organic material, but also altering the structure of the inorganic material, oxidising minerals and thermally altering certain fractions such as expandable clays. 177

Dry sediment, prepared and sieved for this study resembled a friable dust containing larger composite granules. These were observed to swell as they took up water which suggests that analysis of comparative mineral size, and composition might be appropriate in order to assess differences between the dried prepared sediment, and natural wet sediments used. Once treatments based on dry sediment preparations were placed within treatment jars and under water, they were more prone to disturbance by physical movement than were treatments based on wet sediment. Indeed, such was the settling time after movement of such a treatment jar from one bench to another, that all treatments were allowed to settle for 24 hours following introduction of water to the jar. In practice, wet sediment treatments needed only an hour or two to settle.

Similarly, dried sediments that had been allowed to condition within the river (C l and

C2) took an intermediate amount of time to settle within the treatment jars. This is also partly due to the fact that suspension within flowing river water had allowed the removal of the finer fractions of dried sediment.

By way of confirmation of these observations, the order in which sediments were most prone to disturbance by paddle speeds, or movement of a prepared treatment jar, was;

Dried sediment. > Dried sediments that had > Wet sediments.

been subsequently

conditioned in flowing river water.

5.3.3 Experimental improvements and suggestions

The following suggested improvements could not have been made until the system used within this study had been tested. A ll glass vessels must be of uniform thickness, curvature, opacity and density. Glass treatment jars should also be constructed of flat glass to reduce any light magnification or reflective properties that might result from the use of circular treatment jars. The rheostat control unit for the paddle stirrer must be designed for graduated, repeatable, accurate increments of output. Standardisation o f sediments used would minimise differences in particle size 178 distributions. For example, the use of an artificial substrate of standard sized particles, compared to identical material that has been conditioned should eliminate concern over particle preparation procedures. Lastly, the light meter must either be desensitised, or preferably, replaced by a scanning laser particle detector, which would not only measure tiirbidity, but also particle size and number.

Despite the problems faced by this study, and the apparent cost required to meet the recommendations for improvement, this study is well worth repeating. It has been noted that as water treatment process control increases, the need to measure the concentration of particles in water is ever more apparent (Urrutikoetxea et al., 1993).

This study was an attempt at a "low-tech" alternative to the detailed, and often complicated, equipment required for similar studies. For example, in order to measure particle size composition after the removal of organic fractions and subsequent chemical dispersal. Stone and W alling (1997) utilised a Coulter L S I30 laser granulometer. The possibility of using a modified coulter counter to detect particles disturbed from the surface of a settled sediment by sample removal was rejected for being overly complicated, with an excessive reliance on custom-built automated equipment. W hile W alling and Woodward (1993) and Nicholas and W alling (1996) used an impressively simple water élutriation system to quantify the suspended sediment size fractions using a peristaltic pump coupled to a sequential series of filters, it would be extremely difficu lt to scale down such apparatus to a level appropriate to the aims o f this study.

However, the use of a modified coulter counter, or at least a means of taking water samples immediately above the surface of disturbed sediment could be a more desirable means o f assessing sediment stability than using turbidity measurements.

However, Coulter counters are problematic pieces of equipment. In his review of turbidity, Gregory (1998) recommends particle counters as being superior to light meters, depending upon the particle size fraction of interest. Equipment must therefore be carefully chosen or designed for each type of study. Farr and Clarke (1984 and unpublished data) noted that as discharge increases, so too does turbidity as "worked" fine particulate matter is swept upwards. However, once that relatively thin surface 179 layer is depleted, turbidity measurements then decrease. If discharge continues to increase as in a spate, bank erosion occurs, and to a lesser extent the unworked material that underlies the worked surface layer is also swept into the water column.

Such material tends to be of a smaller physical size (Farr and Clarke, 1984) eg clay particles, and so produces greater light scatter than does particulate floe material (Farr and Clarke, 1984). Sim ilarly, as particle size increases, due to flocculation, so density of individual particles decreases (Gregory, 1997). In this way it is possible to achieve turbidity measurements that belie the suspended solids load. Depending on the scale of assessment, turbidity measurements can vary in terms o f efficacy.

The cost of appropriate equipment to measure particle size distribution of suspended sediments was noted by Phillips and Walling (1995 a). They argued that both cost and adverse field conditions not only favour laboratory-based simulations of sediment behaviour, but also encourage simple alternative strategies. Despite these considerations, they were obliged to use a costly, "high-tech" field portable, laser- based backscatter particle analyser in order to place laboratory and field samples into context (Phillips and W alling, 1995 a, b).

Many designs and attempts had previously been rejected prior to the design of the approach used in this study. Such designs included the monitoring of sediment retention within plexiglass channels of sediment, worked by macroinvertebrates while river water was run continually over the surface. This scheme was rejected for having too many uncontrollable factors such as water flow rate, or macroinvertebrate husbandry. Similarly, the design involving the monitoring of sediment within the re­ circulating paddle channel described in chapters 2 and 3 (sim ilar to the system described by Blauchard et al., 1997) was rejected for being too artificial a system in terms of sediment maintenance, as well as being unable to provide sufficiently detailed data. Alternative concepts were also designed within the method described. The use of a magnetic stirrer bar within each treatment jar to agitate sediment was rejected for requiring too small a sediment sample size; being unpredictable and chaotic in terms of sediment agitation; equally inaccurate in terms of precision speed settings; creating and maintaining a vortex (the main problem caused by the paddle that was used, at 180 high speeds); and lastly for providing a means o f sediment agitation that was not likely to occur in natural conditions.

The main problem in designing such equipment as that needed for this study is the scale on which observations need to be made. A ll previous studies, and all papers cited within this chapter, have examined sediment stability or suspension on a grand scale. Yet this study was an attempt to examine the minute detail of cohesion afforded by the application of small quantities of material that is laid over the surface o f sediments rather than worked in, and which may subsequently attract agents of further consolidation. W orking at such a scale provides unique problems of measurement and observation. My study used jars of sediment with a depth (around

3-4 cm) considerably less than most lotie benthic sediments, which may influence the boundary layer effect, as detailed by Hynes (1970). Therefore it is comforting to note that in auditing data collected on a nationwide survey of suspended sediment concentration and flow, Webb et al., (1997) found that gross inconsistencies were apparent between methods of turbidity monitoring. Their considered findings included acknowledgement of the need to develop new, and improved, methods of turbidity measurement.

While the newly reported material TEP (algal, phytoplanktonic, bacterial and diatomaceous in origin), and its (exclusively) bacterial equivalent EPS have been rapidly examined for all sorts of physical, chemical, and possible financially exploitable properties (Labare et al., 1989), there has been little or no examination of the effect of such potentially cohesive material to physical processes. It has been acknowledged that polysaccharide floes (such as TEP) in general have some effect on their surroundings, if only because of the vast scale on which they occasionally appear, (Logan et a i, 1995). It has also been recognised that bacteria, the producers of EPS, play a role in sediment stability via the formation of biofilm (Lock, 1993).

Yet the role of such material upon sediments, ion availability and DOM availability have all been overlooked. 181

5.4 Conclusions

This study was an attempt to provide an inexpensive and accessible alternative to high cost custom designed equipment. It would also have allowed access to processes that exist on a scale often overlooked by most studies and their respective experimental apparatus. The equipment required to pursue the aims of this study would otherwise be costly, requiring as it does, large, purpose built glassware in large quantities, a laser based turbidity meter with associated particle sizing unit, and attached automated coulter counter sampling unit, together with an adequate reliable paddle stirrer.

W hile a great deal of extremely useful work has been performed over the last thirty years on suspended sediment loads and movement, such studies tend to be on a grand scale of tonnes rather than the grams examined in my study. Such a scale is often necessitated by the practical implications of collecting a data set as well as by the need to explain a visually perceptible issue. However, this has meant that studies of smaller scale processes are not as common as they might be, and that problematic though they m ight be to examine, small scale processes have been overlooked in recent years.

Lastly, the effect o f macroinvertebrates has also been neglected. Their effect may very well be minor, or simply so slight as to be unmeasurable. However, this study has proved the durability and strength of material such as snail trail mucus (Chapter

Three). Its effect upon the substrate on which it is laid should be assessed. In addition, the effect of bacterial EPS, natural organic fractions and macroinvertebrates other than snails should be assessed and quantified, both in isolation and combination. 182

Chapter 6. Biofilm growth and the role of snailmucus

6.1 Introduction

Various theories describe how colonising cells attach to surfaces. These include electrostatic forces (Flemming et al., 1997) or via alginate production triggered by a gene-switching mechanism (Hoyle et al., 1993; Costerton et al., 1995). The concept of seed inoculum (a fragment of established biofilm lifted free of the community) is another possibility. In looking at biofilm scour during storm events, Blenkinsopp and Lock

(1994) found that most biofilm cells are swept away, except cells of Cocconeis which will shelter other biofilm cells, forming microcosms that act as inoculum in re-colonisation.

Similarly, in the marine environment, Szewzyk et al., (1991) found that biofilm acts as an incubation unit or "nursery" to larval ascidians, which on migration may carry biofilm inoculum to new surfaces. Once the pioneers have established themselves on a surface and released sufficient polysaccharide, other cells may impact and stick, thus initiating the complex structure of a biofilm community.

6.1.1 The potential advantage offered by snail mucus to biofilm

development

The arrival of bacteria at surfaces within flowing, and non-flowing systems was discussed by Gilbert et ai, (1993). They noted that fluid dynamics disperse microorganisms evenly throughout a liquid, and concentrate suspended organisms close to a viscous boundary

layer above a surface on which biofilm might develop. They further noted that at such

surfaces, frictional drag and turbulent downsweeps w ill tend to direct organisms close to

that surface. Thereafter, roughness of such surfaces presents "niches" within which

microorganisms will be protected from fluid dynamic shear. The thickness of such a layer

(which a cell must penetrate in order to attach to a surface) is dependent on the magnitude

of the fluid shear rate (Marshall, 1985). Such fluid dynamics can also act reversibly,

forcing downswept cells upwards, and generally maintaining a state of turbulence 183

(Lacoursiere, 1992, Craig, 1993). Ultimately, however, cell attachment is dependent upon a number of variable factors, including the condition o f the bacterial cell surface, and that of the solid substratum (McEldowney, 1984).

McEldowney (1984) examined the attachment o f freshwater bacteria to solid surfaces, noting the various factors that enable cellular attachment, proliferation and subsequent surface film development. The contributory factor of established surface film was noted, and McEldowney states that "exopolymer such as pectin and polygalacturonic acid, is shown by Arlauskas and Burchard (1982) to exhibit the properties of temporary adhesives to Flexibacter FS-1 ". The possible contributory effect o f exopolymer from abraded or damaged macrophyte source (detailed by Bronmark, 1985; Zeng and Gabius, 1992) to cellular attachment was not explored.

However, how much faster would succession take place if an otherwise clean surface was already coated with adhesive polysaccharide material such as snail trail mucus (STM)?

In the same way that Korte and Blinn (1983) placed aluminium stubs in rivers to examine bacterial succession, my experiments studied bacterial and particle accretion and succession on clean aluminium surfaces. This progression was observed using aluminium stubs coated in the mucus trails of Lymnaea peregra, allowing an assessment of the assistance that such trails may provide in biofilm community formation and the accretion of particulate organic matter (POM). (See chapters 2 and 3 for examination of particle attachment to STM and the examination of STM using marker particles).

6.1.2 Experimental objectives

1 To determine whether STM accelerated the accumulation of particles from the

water column using Scanning Electron Microscopy, (SEM).

2 To determine whether STM accelerated the development of a biofilm community

using SEM.

3 To identify any interactions between specific bacterial groups and snail mucus by 184

identification of microorganisms using microbiological techniques.

4 To determine whether STM accelerated cellular accumulation and / or expedited

the development of a biofilm community using microbiological techniques.

6.2 Materials and methods

In order to determine whether STM accelerated biofilm development, as well as facilitating particle and cell attachment, two forms of analysis were employed. The first method was direct observation. A Scanning Electron Microscope (SEM) was used to monitor the daily build up of POM. The second method was a more detailed analysis of microbial cell accrual using microbiological plating techniques. (Techniques utilised to identify microorganisms are detailed Section 6.5).

The SEM stubs that I used were solid cylinders of aluminium, 10 mm in diameter, 10 mm high, with an upper surface available for mucus-coating of 79 mm^ (471 mm^ total surface area). Stubs were placed in a holding tray which consisted of a sheet o f aluminium with

50 holes, in which stubs could be held. Beneath this holding sheet was another aluminium sheet with smaller holes drilled in the same places such that each stub surface would be flush with the first sheet, whilst allowing removal of a stub without touching the stub upper surface (wire pushed through the hole in the second sheet forced the stub upwards, such that it could be gripped by sterile forceps at its sides). The two aluminium sheets were spaced apart with small blocks of aluminium and bolted together. The whole structure was bolted on to sections of iron railway line which acted as anchors to prevent displacement. 185

Plate 6. Aluminium stub holding tray with two stubs in foreground.

A ll stubs were pre-polished with metal polish, cleaned in acetone, and rinsed 5 times in distilled water. They were then soaked in 70% industrial methylated spirit before being rinsed in distilled water and numbered on their underside. Experimental stubs were placed in a dish of distilled water with Lymnaea peregra, which were allowed to crawl over the upper surface of the stubs for up to thirty minutes to ensure total coverage of the upper surface of the stub, prior to random placement in the holding tray. Distilled water was used to minimise the incorporation of cells or particles to the STM and also as an attempt to stress the snails toward copious mucus production. Snails had previously been acclimated at room temperature in dishes of tap water for two hours. This minimised transfer of organisms and particles from the surface that the snails had been gathered from. An equal number of stubs without a mucus coating were randomly placed in the

holding tray, having been subject to the same preparation as experimental stubs, but

without exposure to snails, to act as controls. 186

The full holding tray was then placed in an experimental channel, or artificial river of controllable flow, at the Institute of Freshwater Ecology, fed by the M ill Stream at East

Stoke, Dorset (Nat Grid Ref: SY 867 868 ) where flow and depth were controllable.

August was chosen as a suitable month for maximum biofilm development, as there were warm temperatures, low flow and high nutrient inputs (Hartley, 1997).

At four time intervals (zero, 1,3,5 days), five experimental stubs (coated with mucus,

M ) and five control stubs (without mucus, W M ) were removed from the holding tray for microbiological analysis. An additional two stubs (one with, and one without, mucus) were removed, examined and photographed using SEM.

6.2.1 Experimental protocols - SEM

Following removal from the river, each stub was air dried for at least 24 hours, and thereafter stored in a desiccator to minimise degradation of material on its surface. Prior to examination, each stub was sputter coated in gold and examined in a JEOL JSM-T20 scanning electron microscope. The whole surface of each stub was examined at a magnification of approximately x 750. Representative pictures were taken, the negatives developed and scanned into a computer using the package "Adobe 4.0".

6.2.2 Experimental protocols - Microbiological analysis

Stubs were removed from the holding tray using sterile forceps, and placed in sterile

Ringer's solution (Oxoid, BR52). Stubs were refrigerated at 4°C until analysis took place to prevent the proliferation of cells. At analysis, each vial containing a single stub was agitated in a w hirlim ixer to ensure removal o f cells and POM from the stub. Ringers solution surrounding each stub was then subjected to a serial dilution, plating and incubation. The types of agar used were selected for the detection of microorganisms expected to be found in the locality (Baker and Farr, 1977; Austin and Baker 1988; Sleigh et al., 1992). 187

Pseudomonas Agar (Oxoid, CM559) containing C-F-C supplement (Oxoid, SRI03) was used to selectively isolate Pseudomonas species in general ("slime formers"); plates were incubated at 15°C and 25°C.

Yeast Extract Agar (YEA, Oxoid, CM 19) was used for total aerobic counts at 15°C and

25°C; this is a general purpose plate count agar for waterborne bacteria.

Yeast and Mould Agar (Oxoid, CM920) was used for the isolation o f yeasts and moulds at 15°C and 25°C.

MacConkey Agar (Oxoid, CM 115) was used for the isolation and enumeration of coliforms and other enteric bacteria; plates were incubated at 37°C.

Tryptone Soya Agar (TSA, Oxoid, CM 131) is a general purpose medium, which was used to perform total anaerobic counts at 20®C. Plates were incubated anaerobically in desiccator jars, and Oxoid AnaeroGen sachets (Oxoid, AN025A) were used to create an anaerobic environment.

Nutrient Agar (Oxoid, CM 3) is a general purpose medium, which was used to obtain pure cultures of selected colonies for identification purposes.

Two incubation temperatures were used for the YEA, Yeast and M ould and Pseudomonas agars, to evaluate any difference in microbial numbers due to the likely presence of psychrophiles ("cold loving" organisms with an optimum growth temperature below 20°C

(Stanier et al., 1976)), in the river water. It is recognised that many bacteria in fresh waters are viable but non-culturable (due to stress, damage etc, or because suitable culture media has not yet been identified, (Roszak and Colwell, 1987; Head et al., 1996; Head et al., 1998)). Such non-culturable organisms w ill still make a contribution to biofilm development and POM accrual (Davies and Evison, 1991, Arana et ol., 1997). This study serves however to compare culturable microbial numbers found between an experimental 188 treatment and its control. Ringer's solution was used for all dilutions for plate counts, where 0.1 ml of each dilution was spread (using a sterile glass rod) on to the following media to evaluate microbial numbers;

6.2.3 M icrobial identification.

A selection of colony types, common to most, if not all, samples, and a number of colony types unique to specific samples (e.g. control stub 2, day 3, Pénicillium) were chosen from the isolation media. Nutrient agar was used to obtain pure cultures o f the selected colonies, prior to identification. Methods used for the identification of bacterial types included colony and cell morphology. Gram staining, pigment production, oxygen requirements, cell motility and glucose utilisation (Figures 6.1 and 6.2), (as described in

Gibbs and Shapton, 1968; Cowan and Liston, 1974; Stanier et al., 1976). Yeasts and moulds were identified using microscopic techniques (Onions et al, 1981).

Microorganisms were identified to genus level, and the distribution of organisms among mucus-covered and control stubs determined. An ad hoc scale was used to indicate relative numbers of organisms, allowing comparison to be made between the microflora of the experimental and control stubs (Table 6.1). Gram Negative 2 Cocci Rods

i Straight Curved / Spiral Neisseria

Diffusible Pigment Non-diffusible Pi^m Vwrio on Nutrient Agar on Nutrient Agar Cytophaga

Pseudomonas No Pigment on Nutrient Agar Oxidase Red Negative Yellow/Orange Purple i Oxidase Coliforms Positive Oxidative Fermentative C hromobacteriu m Respiration Respiration Aeromonas

Oxidase Oxidase Coliforms Positive Negative Oxidative Fermentative Respiration Respiration

Flavobacterium Xanthomonas I Pseudomonas Serratia Key to Identification Methods 1 Gram Stain 2 Microscopy - Cell Shape 3 Growth on Nutrient Agar 4 Oxidative / Fermentative respiration 5 Oxidase Test

Figure 6.1 This guide applies only to true bacteria (unicellular organisms). Identification of mycelial bacteria such as Actinomycetes Identification of Gram negative bacteria as well as Yeasts and Moulds are based on microscopic investigation.

V o ' ^ ^ o ^ ^ Gram Positive 2

Cocci Rods 7 Obligately \ Anaerobic Facultatively Non-Spore- I Anaerobic _ Former Peptococcus I Aerobic Cells divide to form Strict Catalase Catalase irregular clusters Anaerobe

Cells divide to form Staphylococcus Clostridium irregular clusters Cells divide to form or tetrads pairs, chains or tetrads Cells divide to form r pairs, chains or tetrads i ‘ Aerobic or Facultatively anaerobic Micrococcus Streptococcus 8

Flanococcus Catalase Catalase Positive Negative ; Bacillus Sporolac^obacillus Key to Identification Methods 1 Gram Stain 2 Microscopy - Cell Shape 4 Oxidative / Fermentative respiration 6 Microscopy - arrangement of cells 7 Microscopy - presence / absence of endospores 8 Catalase Test

Figure 6.2 This guide applies only to true bacteria (unicellular organisms). Identification of mycelial bacteria such as Actinomycetes Identification of Gram positive bacteria as well as Yeasts and Moulds are based on microscopic investigation. 191

6.3 Results and Discussion

6.3.1 Analysis of treatments using SEM

SEM indicated the relative quantities of POM or "debris" that accumulate on a mucus- coated surface as opposed to a "clean" surface. Unfortunately, such debris is rarely identifiable. Photomicrographs of the four stubs (days zero, 1, 3 and 5) for each treatment are presented as Figures 6.3 and 6.4. Identification was to genus level and was based on visible characteristics only. It is interesting however that diatoms were the most noticeable additions to the stub surfaces, and were present in greater quantities at each comparable stage on mucus-coated stubs than on the control stubs. Thissuggests that diatoms (which are good primary colonisers anyway, as they produce their own polysaccharide) may be entrapped by snail mucus. Many diatoms are also large enough to have cells already attached to their surfaces. Diatom mucus production not only serves to anchor the individual diatom, but also to cement the attachment o f those cells in their immediate vicinity (Crocker and Passow, 1995).

Progressive accrual of material on to stubs is shown with mucus (M ) (Figure 6.3), and without mucus (W M ), (Figure 6.4). Stubs dried on time zero show dried, cracked mucus and a clean metal surface respectively. Stubs that were dried on days one and three for the control series also showed a dried film that may be depositional or may be evidence o f a snail having crawled over the stub in question. Snails were known to be present in the locality of the stub holding tray, despite attempts at physical removal of all snails from the area. However, it is not until day five that any noticeable POM appears in the form of diatom frustules. By comparison, the mucus-coated series have trapped frustules and assorted debris within one day, and indeed by day three are capable of trapping large particles such as that shown in Figure 6.3. In this way, the presence o f mucus from a snail trail can be viewed as the primer for accretion by a "snow-ball" effect, for the components for biofilm development. Î r Ï 1 k

Figure 6.3 A 1 Figure 6.3 A 2

i â

Figure 6.3 A 3 Figure 6.3 A 4

Figure 6.3 A 1 Mucus Day zero x 750 Mucus film has air dried and fissured. Figure 6.3 A 2 Mucus Day One x 750 General Iruslule fragments trapped in, or under, wet mucus film, including Navicula, Diatoma and Svnedra. Figure 6.3 A 2 Mucus Day Three x 750 Shot avoiding frustule fragments to show structure embedded in mucus film, possibly a piece of chitin. Figure 6.3 A 4 Mucus Day Five x 750 Diatom frustule debris, including Synedra or M erid ian and Diatom a. M ■ ■ . a ' i j

ÆÏ Figure 6.3 B 1 Figure 6.3 B 2

o % ' T

Figure 6.3 B 3 Figure 6.3.B 4

Figure 6.3 B 1 Control Day Zero x 750 Unknown, featureless object at bottom right was only reference. Figure 6.3 B 2 Control Day One x 750 Slight cracking of unknown surface film. Figure 6.3 8 3 Control Day Three x 750 Cracking of unknown surface film. Thicker than Day one, suggesting that film is depositional. Figure 6.3 B 4 Control Day Five x 750 Diatom frustules, including Diatoma, Cocconeis, Navicula and Synedra. 194

6.3.2 Distribution of Microorganisms

Throughout the remainder of this study, various references are made to ithe potential that snails themselves offer to the development of biofilm from their STM, via the inclusion o f viable cells from the digestive tract. Extensive and detailed studies on the excretory systems of gastropods (such as Martin and Harrison, 1966; Martin, 11983; McMahon,

1983) reveal no information on the fate of faecal pellets, or even the means o f exit from the mantle cavity. Observations within this study allow me to state that the faecal pellets of L. peregra (and P. jenkinsi) are often found on STM rather than to the side o f the

STM, particularly when an individual snail executes a change in direction. In addition, wherever snails exist in close proxim ity, faecal pellets are incorporated (under) STM, faecal pellet production being copious in laboratory conditions. The inclusion, or close proximity of faecal material (containing viable cells from the digestive tract) to STM, may explain a number o f observations w ithin this section.

The distribution of microbial genera on mucus-coated (M ) and control (W M ) stubs is shown in Table 6.1. Diagnostic photographs of a selection of identified organisms from

Table 6.1 are included in Section 6.5 to illustrate the identification techniques used. It is interesting to note that certain genera are more commonly found on the mucus-coated stubs, many being totally absent from the control stubs. These are notably the moulds

Cladosporium and Fusarium, the yeasts Saccharomyces and Rhodotorula and the "slime formers" Flavobacterium, Xanthomonas a.nd Aeromonas. Data presented in Table 6.1 are of a qualitative rather than quantitative nature. However, certain differences are apparent between the genera o f microorganisms that w ill settle upon, and develop on, a given surface. It is reasonable to assume for instance, that if moulds are present in greater numbers on the mucus-coated stubs, it is because they have been laid down on, or within, the mucus trail by the snail (see section 3.3.8), having either survived the gastropod digestive system (Cummins, 1973; Adrian, 1987; Wotton, 1990; King et ai, 1991), or having been present on the pedal surface. Moulds are capable of producing robust spores, designed to survive extended periods of extreme conditions while dormant (Onions et ai, 195

1981). Indeed, of the numbers of moulds found on mucus-coated stubs, the greatest numbers of these genera are found on the time zero stubs. This suggests that the source of such organisms is the snail. The same cannot be assumed for yeasts and those "slime formers" that illustrate a preference for mucus-coated stubs. Rhodotorula only appears on day three implying that the mucus-coated stubs offer a more suitable environment on which to attach and develop, either because of the shelter afforded by the now accumulated POM, or because of the STM in which a single planktonic cell may embed.

W hilst "slime formers" such as Flavobacterium, Xanthomonas and Aeromonas are capable of producing the mucopolysaccharide matrix that is the basis o f biofilm communities, they may not necessarily arrive ready encapsulated in a suitable cellular coating (Decho, 1990).

Cells arriving at a surface "naked" of a slime coating, may use the ready supply of STM to attach, which may also act as a suitable food source for slime-producing bacteria.

O f the four categories presented in Table 6.1, the first, Gram Negative Bacteria, are all

"slime formers", that is, all bacteria within the genera Pseudomonas, Flavobacterium,

Xanthomonas and Aeromonas, are capable o f producing considerable quantities of mucus.

This category also includes coliform bacteria which, whilst not recognised as being slime producers in the same way as Xanthomonas, are quite capable of producing copious quantities of exopolysaccharide and often exist encapsulated w ithin exopolymer secretions

(EPS), (Takeda et ai, 1994; Yokoi et ai, 1997). Coliforms are members o f the family

Enterobacteriaceae, which, due to their habitat, require a thick protective EPS at certain, if not all, stages of their life cycle (digestive tracts are hostile environments). Whether, like those genera previously discussed, such cells arrive already encapsulated and so are able to stick to any surface, depends on the individual species and the ambient conditions that the individual cells experience. However, as such cells are capable of producing mucus, it is reasonable to assume that they arrive ready encapsulated in mucus, and therefore that there would be no difference between the occurrence of these genera on mucus-coated and control stubs. Indeed, little discernable difference is observed for any of the Gram negative genera apart from Xanthomonas which is on, or in, the STM at day zero. Xanthomonas is a plant pathogen (Azad et ai, 1996). Xanthomonas was not found 196 on any control stub, suggesting that it is not present in the water in sufficiently high numbers to make an impact. Its presence on mucus coated stubs suggests that is likely to have passed through the digestive tract of the snail unharmed and been subsequently attached to the mucus trail. The increase of Xanthomonas colonies over days three to five is therefore most likely to have resulted from reproduction within the biofilm developing on, or within, the snail mucus. In this way, snail trails may not only assist in the development of biofilm , but may also "sow the seeds" with primary colonisers from the snail's own digestive tract. Xanthomonas spp. are prodigious producers of extracellular polysaccharides and gums (Roserio et al., 1992) and so, where present, can be considered important in consolidating material in the early stages o f biofilm development (dosSantos et al., 1997; Reij et al., 1997).

Other categories within Table 6.1, such as moulds and yeasts, while capable o f producing extracellular polysaccharides in copious quantities {e.g. within fermentation processes), rarely do so as individual planktonic cells (Petersen et al., 1989; Rees lev et al., 1997).

They do, however, have polysaccharides within their cell walls, which may provide some means of temporary attachment to an existing source of polysaccharide in order to stick to a surface (Herrera and Axcell, 1991). Whether initial attachment is due to bacterial mucus or snail mucus is immaterial. Whether snail mucus is of the correct consistency to be incorporated into biofilm is, as yet, unknown. However, due to the adhesive, polysaccharide basis of snail mucus, temporary attachment is conceivable for such cells.

Once attached, however temporarily, bacterial mucus from other sources may provide a more permanent means of attachment. Table 6.1

Comparison of Identified colonies on mucus coated and control stubs Totals for each treatment of 5 stubs Mucus coated stubs (M ) Control Stubs (W M)

Days Days Gram Negative Bacteria Pseudomonas spp. + 4-++ + + + + + + ++•+- 4-4- Flavobacterium spp. + + + + . + Xanthomonas spp. -t- + + + Aeromonas spp. + + Coliforms + + + + + + + + +4- 4-4-4-

Gram Positive Bacteria Micrococcus spp. 4-4- 4-4-4 4 4 4 +++ + ++ + ++ +++ Anaerobes {Bacillus . Clostridium ) 4-4- 4 4 4 4 4 +++ ++ ++ + ++ + +++ Aerobic Bacillus spp. 4- 4 4 + + + Actinomyces spp. 4-4- 4 4 4 + +

Yeasts Saccharomyces and related yeasts 4- 4 Rhodotorula spp. . . 4 Other Yeasts 4- 4

Moulds A lternaria spp. 4-4- 4 4 4 4 Fusarium spp. 4-4- 4 4 Cladosporium spp. 4- 4 4 Pénicillium spp. ..•

= absent + = I - 100 cfu/ml ++ = 100- 1000 cfu/ml +++ =>1000 cfu/ml 198

No such differences were observed between treatments for Gram positive species, suggesting that the availability of mucus is immaterial to the attachment of such cells.

Bacillus spp. certainly produce polysaccharides of their own (Gorshkova et al., 1992), while Clostridium spp. indicate a strategic ability toward adherence to mucus

(GomezTrevino et al., 1996). Gram positive species also often have a thick, external polysaccharide peptidoglycan layer coating their cell wall, as well as the ability to form endospores. As small dispersal units, coated in polysaccharide, they are less reliant on a mucus layer o f another source to attach to a surface than a larger "naked" cell would be.

6.3.3 Analysis o f microbial cells attached to stubs

Variation o f microbial numbers for each treatment per sampling day are shown in Figures

6.5 - 6.12. Figures are presented for each of the five types of agar used, at each temperature at which incubation took place. M icrobial numbers have been expressed as colony form ing units per ml (cfu ml ') of sample tested. Standard deviations are given for each sample.

Pseudomonas spp.

Pseudomonas spp are generally considered to be important primary colonisers (Szewzyk et al., 1991; Matsuda et al., 1992), partly because they are "slime formers" and partly because they can exist in the planktonic state with a copious EPS coating (Titus et al.,

1995). This means that not only can they provide mucus to allow other organisms to attach, but that they can attach themselves to an otherwise clean surface without the need for precursors.

As expected, no significant differences were found between mucus-coated stubs and control stubs at either incubation temperature (A N O V A F,jg = 0.26 P = 0.611 at 15°C;

AN O VA F,3g= 0.20 P = 0.657 at 25°C). Much lower numbers were found at 25°C, as

Pseudomonas spp. are prim arily psychrophiles (Stanier et ai, 1976) and are therefore 199 more likely to be isolated at lower incubation temperatures. (Figures 6.5 and 6.6).

Bacterial numbers increased between time zero and day three to a significant degree at

15°C and close to a significant degree at 25°C, (AN O VA F 227 = 9.49 P = 0.001 at 15°C;

A N O V A F227 = 2.72, P = 0.084 at 25°C), suggesting successional accrual (or reproduction) o f cells (beginning with zero counts on the control stubs at time zero; a few cells were however laid down within the snail mucus). However, by day five, microbial numbers had decreased. W hile the differences between days three and five at either temperature are not significant (A N O V A F, ,g = 1.73, P = 0.204 at 15°C; A N O V A F, ,g

= 0.03, P = 0.871 at 25°C), the decrease suggests sloughing o f assorted colonies (as described by Blenkinsopp and Lock, 1994), but may be due to water current scour, or the selective grazing of mucus by grazing macroinvertebrates, specifically snails.

Coliforms

Most coliforms have an optimum growth temperature of 37°C. However, they are capable of growth at temperatures as low as 10°C (Stanier et al., 1976). Many species within the coliform group are capable of producing EPS (Yokoi et al., 1997) and they may have a role to play in benthic biofilm development. Coliforms are primarily indicators of vertebrate faecal pollution, therefore the presence of high numbers would indicate a pollution event. This would also suggest that an effect may be experienced by existing benthic biofilm (high nutrient input, increased turbidity, greater biological and chemical oxygen demands etc). This is of particular interest to this study as the section o f the

River Frome used is subject to inputs of sewage and agricultural waste. However, low coliform numbers were isolated from all samples, indicating the good quality of the river water at the time of sampling.

Time zero control (W M ) stubs contained no organisms, indicating good laboratory procedure. The presence of low microbial numbers on the mucus-coated stubs (M ) at time zero suggested that these organisms were contained within the mucus, possibly from snail faecal material, or pedal mucus that has come into contact with coliforms. At time 200 zero, mue us-coated (M ) stub microbial numbers are significantly greater than microbial numbers found on the control stubs (WM) (ANOVA F, g = 5.80, P = 0.043). Microbial numbers were however, higher on control stubs (W M ) for days one and three (AN O VA

F, ,g = 4.36, P = 0.051).

The above result raises the possibility that, whilst snail mucus clearly contains some coliforms, either picked up from whatever surface the snail has previously explored, or because coliform organisms are present in the snail gut (faecal pellets are deposited in the snail trail), snail mucus may also contain antibacterial agents to prevent the development of such organisms. Further, while there is not yet any supporting evidence, it may be suggested that snail mucus attracts and supports specific types of bacteria that produce bacteriocins (antimicrobial agents), effective against coliforms (Padilla et ai, 1996).

Bacteriocins have only recently been described by Padilla et al., (1996). Indeed, as microbial numbers changed from being significantly greater on mucus-coated stubs (time zero) to significantly greater on control stubs (days one and three) this suggests that such an antimicrobial agent may be of finite lifespan (Padilla et al., 1996), (Figure 6.7).

Total anaerobic count

A total count of anaerobic bacteria was performed to compare colony numbers isolated from mucus (M ) and control (W M ) stubs. Anaerobic organisms would only survive in the depths of an established biofilm, in the absence of oxygen, protected within an island of cells in the glycocalyx. Vegetative anaerobic cells would have developed from dormant spores, which may have also been present on the surface o f the biofilm . Indeed, the two most common anaerobes found in soil and water are sporeformers, namely

Bacillus and Clostridium spp. (Buchanan and Gibbons, 1974). Therefore, such species would not contribute greatly to biofilm development or structure. No significant differences were found between mucus-coated and control stubs (A N O V A F, 3 g = 0.08,

P = 0.777), (Figure 6 .8 ).

Total aerobic count 20 i

Yeast extract agar is a general purpose agar used for total aerobic counts. A t time zero at both 15 and 25*^0, the mucus-coated stub contained a significantly greater number of microbial cells than the control (A N O V A F, g = 23.42, P « 0.001 at 15°C; AN O V A F, g

= 28.76, P « 0.001 at 25°C), showing that snail mucus contained more aerobic bacteria than did a clean sterile metal surface. This indicated not only that snails bring cells to every surface they traverse, but also provided an indication of the type of bacteria that the snails had picked up from the last surface with which they came into contact. Those colonies may alternatively be representative of an indigenous microflora, specific to each snail. Once the control stubs were immersed in river water however (days 1, 3 and 5), there was no significant difference between mucus and the control stubs (A N O V A F, 2 g

= 0.49, P = 0.489 at 15°C; A N O V A F. ^g = 5.34 x 10'-'*, P = 0.948 at 25®C). This was possibly due to the small sample size (5). (Figures 6.9 and 6.10)

* This F value (based on the division of the mean square of treatments by the mean square of the error), despite being less than one, is valid for a one tail test. It simply indicates that there is no difference between treatments for this subset o f organisms.

Yeasts and Moulds

No significant differences for yeasts and moulds were detected between mucus-coated stubs and control stubs at any sampling stage at 15®C (A N O V A F, 3 g = 3.38 x 10'^*, P =

0.953) and only at time zero (A N O V A F, g = 69.73, P « 0.001) at 25°C. The fact that microbial numbers on control stubs were not significantly different from those found on mucus-coated stubs refutes the hypothesis that snail mucus w ill accelerate the accumulation of yeasts and moulds at these temperatures and conditions. This suggests that STM does not accelerate the accrual of yeast and mould colonies. However, such a finding could be due to rapid "farming" or grazing of mucus and attached cells as described in section 3.1. In addition, the fact that a significantly greater number of cells were not found on the control stubs conflicts with the observation by Allison and

Sutherland (1987) that the presence of mucus inhibits the growth of cells (Figures 6.11 and 6.12). * See Previous note. 202 14000

12000

10000

8000 t l Mucus B Control

6000 ^

4000

2000

0 4 Day 0 Day 1 Day 3 Day 5

Figure 6.5 Comparison of Pseudomonas counts (Pseudomonas agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 15°C. Bars are one standard deviation.

1400

1200 -

1000 -- □ Mucus B Control '^00 --

^00

400 --

200 --

Day 0 Day 1 Day 3 Day 5

Figure 6.6 Comparison of Pseudomonas counts (Pseudomonas agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 25°C. Bars are one standard deviation. 203

1400

1200

1000 -

_ 800 El Mucus Ë ES Control '^600

400 *

200 I

Day 0 Day 1 Day 5

Figure 6.7 Comparison of Coliform counts (MacConkey agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 37°C. Bars are one standard deviation.

9000

8000 i

7000 t

E3 Mucus 6000 r Q Control

7^000 : ^ I - I *^4000 f

3000 +

2000

1000

Day 0 Day 1 Day 3 Day 5

Figure 6.8 Comparison of Total Anaerobic counts (Tryptone Soya agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 20°C. Bars are one standard deviation. 204

140000

120000 □ Mucus B Control

100000

T_ 80000 E =3

60000

40000 I

20000

Day 3 Day 5

Figure 6.9 Comparison of Total Aerobic counts (Yeast Extract agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 15°C. Bars are one standard deviation.

70000

60000 I

□ Mucus 50000 B Control

40000

30000

20000

10000

Day 0 Day 1 Day 3 Day 5

Figure 6.10 Comparison of Total Aerobic counts (Yeast Extract agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 25°C. Bars are one standard deviation. 205

8000

7000 • □ Mucus B Control

6000 '

-^_5000 - E 2 ; U4000 -■

3000

2000 --

1000 --

DayO Day 1 Days Day 5

Figure 6.11 Comparison of yeast and mould counts (Yeast + Mould agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 15°C. Bars are one standard deviation.

18000 j-

16000 E3 Mucus B Control 14000

12000

10000 E 3 o 8000

6000

4000

2000

-I Day 0 Day 1 Days

Figure 6.12 Comparison of yeast and mould counts (Yeast + Mould agar) isolated from mucus coated and control stubs (5 replicates of each), where plates were stored at 25°C. Bars are one standard deviation. 206

6.3.4 Mucus availability

The overall lack o f significant differences between mucus-coated and control stubs may

not only be due to too small a sample size. The small amount of mucus available on each mucus-coated stub may also help explain the similarities between the two treatments.

Each stub had a total surface area of 471 mm^ (2 x area at end of each cylinder (2 x 7tr^) plus the height of the cylinder (height x circumference (10 mm x 27t:r) where r is 5 mm),

while the single upper surface that was coated in mucus had an area o f 78.5 mm^. In other words, for the mucus-coated stubs, only 16% of the surface area was coated with

mucus. Therefore, 84% o f the surface area of each mucus-coated stub was without a

mucus coating. In effect then, 84% o f the surface area o f each mucus-coated stub was

identical to the control stubs. In order to overcome this sim ilarity between (M ) and (W M )

stubs, (M ) stubs should ideally have been completely coated in STM, achieving 100%

surface area cover. However, in order to achieve close to total cover, snails would have

had to have been individually manipulated about each stub, rather than allowed to move,

unimpeded upon a bed of stub surfaces. Such manipulation would have induced stress

that may have affected the deposition, content or consistency of STM.

Variation among stubs sampled on different days may be affected by disturbance of river

bed sediment upstream, or by invertebrate grazing on suspended and attached bacteria.

The experiment took place in August over five rain-free days, following on from fourteen

rain free days, in a spring-fed, spate-free stream, so the former argument can be

dismissed. Efforts were also made to minimise grazing disturbance by removal of all

snails from the small, dammed area in which the stub holding tray was placed.

The role of snail mucus in the formation and development of biofilms cannot be

dismissed simply because total microbial numbers between treatments were found to be

similar. The fact that differences are observed at all (see Table 6.1 where identification

of colonies on each type of agar is listed) is an indication of the potential that snail mucus

has in attracting and facilitating the growth not of greater numbers of all microbial cells. 207 but of greater numbers of certain types of cells.

The vast majority of microorganisms in rivers are natural inhabitants of the surrounding land (soil, allochthonous material etc). Microorganisms are an important food source for suspension-feeding invertebrates which may in turn affect the availability of such microorganisms, as filter feeders are more numerous and active in summer (Baker and

Farr, 1977). Filter feeders pelletise particles and viable microorganisms. Pellets may subsequently drift to the appropriate environment or surface and act as a seed inoculum for the development of a benthic biofilm.

M icrobial species found within a biofilm w ill depend on a number of factors, such as the density of exopolysaccharide matrix (Decho, 1990), the velocity of flow ing water (Dade et ai, 1990), and the action of grazing organisms. In addition, the smoothness of the surface on which the biofilm develops w ill have some bearing on the type of

microorganisms which attach and are able to remain attached.

The presence of polysaccharide may, alternatively, inhibit biofilm development, physically

rather than chemically. Allison and Sutherland (1987) argue that, while

exopolysaccharide is involved in the development of benthic biofilms, it does not play a

role in initial adhesion, suggesting therefore that something else must be there first. It

is known that cells attaching to a surface will initially do so using weak van der Waal's

forces or electrostatic forces before eventually becoming irreversibly chemically attached

vm polysaccharide (Fletcher and Loeb, 1979; Armstrong and Barlocher, 1989). However,

those experiments took place in vitro, in a shake flask, where an individual cell is subject

to chaotic turbulence. My experiments took place within a natural stream, where a

planktonic cell is subject to the natural flow of a stream. Allison and Sutherland (1987)

further argue that excess polymer would inhibit attachment of a cell to a surface as it

would saturate binding surfaces o f the cell. If, however, a cell was able to utilise the

polymer as a food source, sinking as it consumed its polysaccharide surroundings until

it reached, and attached to, a solid surface beneath, the presence of polysaccharide would 20K be of benefit. Certain Pseudomonas species are capable of surviving on a vast range of organic substrates as their sole food source, including mucate and saccharate among 24 carbohydrates and carbohydrate derivatives (Stanier et al., 1976), suggesting that STM provides sufficient nutrients for certain bacteria.

According to the hypotheses tested in my study, it is now recognised that STM may not encourage biofilm growth, or accelerate biofilm development. Yet, STM does seem to cause the accumulation of cells that are able to utilise STM as a food source and then begin to develop as a biofilm community. In addition, snails also "prime" their own trails with cells of specific organisms such as Xanthomonas, picked up from their food source or from a surface previously crawled over, which can act as biofilm primers. Such inclusions may well be fortuitous for those species o f gastropod known to graze their own mucus trails for attached, proliferating bacteria (Connor and Quinn, 1984). Whether EPS is involved in cellular attachment or not, some surface coating must provide initial shelter from bulk liquid currents to allow unattached cells to enter the lesser flow o f the boundary layer, preventing unattached cells from being swept downstream.

6.3.5 Suggestions for further work

My study suggests a great opportunity for further work and some possible improvements.

Increasing the sample size would remove any doubt about differences between treatments,

although logistically this would be difficult (my experiments generated some 1,400 agar

plates for colony counts alone, exclusive of colony identification). If a greater proportion

of the stub surface was coated with mucus, this would also help confirm differences

between treatments, although difficulties in handling the stubs would arise. A purpose

built operating area within a stream from which snails and other grazers were excluded

would also diminish doubt regarding biofilm harvesting by macroinvertebrates. Such an

experimental set up would however raise doubts as to the validity of the field conditions.

Identification of all colonies to species level, whilst being logistically problematic,

requiring possibly years of work, might provide a definitive guide to differences between 209 organisms that are suited to settling and developing on a mucus-coated surface as opposed

to a "clean" surface, thus answering the original question o f whether or not STM assists

the development of biofilms.

6.4 Conclusions

1) SEM methods indicate that the accretion of POM occurs at a greater rate on

surfaces coated with STM than on clean surfaces.

2) Qualitative microbiological methods, using colony identification techniques,

indicate that STM does accelerate microbial accretion for certain genera, based on

the physical characteristics of those genera. In this way, STM can play a role in

the development of benthic biofilm.

3) Quantitative microbiological methods illustrate the accretion of microorganisms

over time, but do not illustrate a difference between STM-coated surfaces and

clean surfaces. 210

6.5 Microbial Identification

]. Pure culture.

A Nichrome wire loop was sterilised in a Bunsen flame and allowed to cool, before picking up a portion o f an isolated bacterial colony. The tip o f the loop was then streaked

across the surface of a fresh agar plate (Nutrient agar, Oxoid CM003). A single streak

was made along one edge o f the plate, the loop was re-sterilised, and a second streak was

made at right angles to the first, ensuring the loop crossed the first streak. The process

was repeated twice more, with each successive streak diluting the number of cells present.

Plates were incubated at 25°C for three to five days, and follow ing incubation, an isolated colony was selected and streaked on to a second nutrient agar plate, thus ensuring the purity of the culture prior to identification work commencing.

2. Gram stain.

An isolated colony was selected from a Nutrient agar purity plate. A drop o f sterile water

was placed on a microscope slide, and a suspension made with a portion of the colony

selected. The cell suspension was heat-fixed by passing the slide quickly through a

Bunsen flame many times, until the suspension had dried to form a smear.

The Gram stain kit was obtained from bioMerieux U K Ltd. (Color Gram 2, product code

55542), and contained oxalate crystal violet, Lugol's iodine, decoloriser and safranine.

Each reagent was placed on the smear for 60 seconds, then washed o ff with slowly

running water before the next reagent was applied. Finally, the slide was blotted dry and

examined microscopically, using lOOOx magnification (oil immersion). Gram positive

cells retain the crystal violet-iodine complex in the cell wall after staining, and appear

purple. The crystal violet-iodine complex is washed out of Gram negative cells which

therefore take up the pink colour of the safranine counterstain (Bridson, 1990). 21 1

3. Pigment production.

Many Gram negative rods may be identified to genus level on the basis of the production of pigments on Nutrient agar (Oxoid, CM003). Colonies of Gram negative rods were selected from Nutrient agar purity plates, and identified using the key in Figure 6.1.

4. Oxidative/Fermentative metabolism.

OF medium (Oxoid, CM883) was used as a means of identifying bacteria based on their

ability to utilise specific carbohydrates in the presence and absence of oxygen. Two tubes of OF medium containing glucose were used for each organism, with the inoculum being

stabbed into the agar to within 5mm of the base of the tube. One tube was then overlaid

with sterile mineral oil, and both tubes were then incubated aerobically at 30°C for 48

hours. Growth only at the surface of the tube without oil indicated oxidative metabolism,

while growth in both tubes indicated fermentative metabolism (Bridson 1990).

5. Oxidase test.

Oxidase Identification Sticks (Oxoid, BR64) were used to detect the presence of the

enzyme cytochrome oxidase, which is present in many Gram negative bacteria. The

oxidase reaction is based on the ability of certain bacteria to produce indophenol blue

from the oxidation of dimethyl-p-phenylenediamine and a-naphthol, both of which are

impregnated into the oxidase sticks.

A colony to be identified was touched with the impregnated end o f the stick, and the stick

rotated to ensure that a small mass of cells was picked up. The stick was placed between

the lid and base of the Petri dish, and examined after three minutes. A positive reaction

was shown by the development of a blue-purple colour, while no colour change was

observed in oxidase negative organisms (Bridson 1990). 212

6. Catalase test.

10 mis of hydrogen peroxide (100 volumes) was made up to 100 ml with deionised water.

A Pasteur pipette was used to transfer one drop of diluted hydrogen peroxide on to a glass slide. A portion of a pure bacterial colony was immersed in the solution on the slide, using a Pasteur pipette, and a coverslip was then applied. The suspension was examined for the evolution of gas bubbles, indicating the presence o f the catalase enzyme, which converts hydrogen peroxide into water and oxygen. 213

/ .

- ; -V

À PSeuclOiviOriaï X 1 ijOU

Plate 6.2 Pseudomonas sp. x 1000, a pure bacterial culture (Gram negative).

1 ,

_ ' Ï-V à Flavobacterium SP xlOOO

Plate 6.3 Flavobacterium sp. x 1000, a pure bacterial culture (Gram negative). 214

**> • ^ r. » X

? il

« r *

MicrococouS SP. X 1000

Plate 6.4 Micrococcus sp. x 1000, a pure bacterial culture (Gram positive). p s i

- 2'/: Y - ^ P v 'c\ Baci. I lus SP X

Plate 6.5 Bacillus sp. x 1000, a pure anaerobic bacterial culture (Gram positive). 215

Plate 6.6 Actinomyces sp. x 1000, a pure bacterial culture (Gram positive).

O

O

Rhodotorula SPP

Plate 6.7 Rhodotorula sp. x 1000, a pure yeast culture. 216

% #

Plate 6.8 Cladosporium sp. x 1000, a pure mould culture

Plate 6.9 Pénicillium sp. x 1000, a pure mould culture 217

Chapter 7 General Discussion.

7.1 Introduction

Relevant studies in the literature agree that marine gastropod mucus trails and larval

blackfly silk threads w ill trap bacteria, and by implication, other particles as well

(Conner and Quinn, 1984; Davies, et al., 1992b; Kiel, et al., 1998). M y study

confirms that, freshwater snail mucus trails will trap bacteria, POM (including

diatoms), marker particles etc, while both snail trail mucus (STM) and silk threads w ill

sorb xenobiotic DOM. Such straightforward results present considerable implications

for our understanding of freshwater processes, particularly in light of the concept of

"re-cycling of sites of attachment", introduced in Chapter One. Mucus and silk are

therefore important components of the freshwater environment.

7.1 Mucus rich environments

Mucus is ubiquitous in aquatic environments. Mucus sources include the invertebrates

described within this study, as well as all other Mollusca, bacteria (Decho, 1990;

Decho and Lopez, 1993), filamentous algae (Santelices & Varela 1993; Jackson, 1995;

Heissenberger et al., 1996), diatoms (Crocker and Passow, 1995), zooxanthelle within

corals (Coffroth, 1984; Denny, 1989; Vacelet and Thomassin, 1991), macrophytes

(Sutfeld et al., 1996; Delgobo et al., 1998; Kroer et al., 1998) as well as fish

(Downing et al., 1981; Davies, 1992). Mucus as a particulate material, with DO M and

POM attached is also to be found in all aquatic environments, e.g. TEP in oceans

(Aldredge et al., 1993, etc), CEP in fresh waters (Wotton, 1996) and also estuarine

environments (Syvitski et al., 1995). A large number o f references within this study

have already noted the enormous range of functions that mucus fu lfils for various

organisms, generally within, or, on, the organism in question. However, there is also

a vast reserve of mucus and mucus-like material that remains in the environment,

discarded by, or released from, its producer. 218

The recent proliferation of studies concerning TEP has been examined in Chapter One, highlighting the growing interest in the functions and fate of mucus based material in the aquatic environment. Most of those early studies identified TEP as being of mucopolysaccharide origin, by the uptake of stains such as Alcian Blue (Tandavanitj et al., 1989; Andrews, 1991; Beninger and Le Pennec, 1993; Passow and Aldredge,

1994; Compere and Goffinet, 1995; Wetzel et al., 1997), Coomassie Blue (Long and

Azam, 1996), or Ruthenium Red (K lut and Stockner 1991 ; Olianas et al., 1996). The uptake of such dyes is merely an indication of negatively charged carbohydrate groups

(Wilson, 1968; Logan et al., 1994). Using such dyes (that effectively highlight any

"mucus-like" material), new classes o f particles or mucus are continually being identified. For example, a new class of particles, Coomassie Stained Particles (CSP), was identified by Long and Azam (1996). These are invisible, globular, sheet or string-like particles in coastal sea waters, similar in size and shape to TEP, that take up the protein stain Coomassie Blue. They noted (using both Alcian Blue and

Coomassie Blue stains) that while CSP and TEP coexist with, and may be mistaken for, other particle aggregates, they are separate substances, with CSP enjoying abundances two orders of magnitude greater than TEP. CSP particles were also noted

(using DAPI staining technique) to be colonised by bacteria, suggesting that such particles represent a whole new cyclical interaction of proteinaceous material and bacteria (Long and Azam, 1996).

Similarly, established materials are also being re-classified as new methods of

separation are developed. Chin et al., (1998) note that it has been suggested that colloids, TEP and large aggregates of marine "snow" may all be regarded as polymer

gels. They suggest that DOM polymers such as the above, can assemble to form gel­

like structures, highly hydrated polymers similar to polysaccharide. Such an

observation can offer new insight into the processes o f exchange between DOM and

POM and the cycling of organic materials in the marine environment. It seems

therefore that detailed re-examination of known substances can lead to new ideas and

a greater understanding of nutrient cycling processes. 219

With reference to nutrient cycling, or in fresh waters, spiralling, there appears to be a continual turnover of organic carbon from bacteria to invertebrates to plants to vertebrates and back again, with many combinations in between (Allan, 1995). W hile many studies have shown (see Chapter One) that the production of invertebrate mucus represents a high proportion o f an organism's energy budget, mucus may be considered an energetically inexpensive material to manufacture, when considered on a cost-to- volume ratio. Polysaccharide may essentially, despite all its myriad functions and the secondary benefits it offers, be considered as a waste product. Smetacek and Pollehne

(1986) hypothesise that for certain bacteria and plants, excess carbohydrates are produced, utilised and released as mucus in the drive to gain and maintain nutrients, leading to a continual release o f polysaccharide.

Certainly, there exists a large volume of carbon based DOM in the form of TEP alone

(Alldredge et al., 1993). O f enormous importance to the utilisation or study of polysaccharide in the environment, and hence the cycling o f organic carbon, is the achievement of Logan et al., (1995) in predicting the half-life and (hence) sedimentation rates of phytoplanktonic TEP. Not only does such a prediction offer further understanding of the cycling of organic carbon via polysaccharide (as particles on mucus particles), but it also raises the opportunity for commercial consideration by allowing predictive models to be constructed for a vastly abundant material. In addition, there are a number of other points that are raised by the work of Logan et al., (1995) and by my study also. As materials such as mucus (and to a lesser extent, silk), previously considered unimportant invertebrate secretions, are quantified in terms

of behaviour and their role within different ecosystems, they become predictable. This

leads to the possibility of their being manipulated and ultimately, being harnessed.

If such ubiquitous materials are known to play such important roles in the cycling of

nutrients essential to all life, what other materials, which are currently overlooked,

are also involved in fundamental processes within the environment? These materials

offer fresh opportunities to drive and manage natural processes in aquatic systems. 220

7.2 Physical properties of mucus and silk, characterised by this

study

While this study is an attempt to answer a number of questions about the physical and biological characteristics of STM, it raises a greater number of questions. Denny states that superficially, at least, "all molluscan mucins are very much alike". The conclusions of section 3.3.1 concur with Denny, suggesting that all molluscan mucins behave, or rather respond to physical and environmental stimuli, in a sim ilar manner.

This implies that they are indeed essentially similar materials. The two snail species described in Chapter Three represent different extremes of freshwater snail habitat in terms of population densities, current velocity, life cycle etc, and yet their mucus trails are very similar when compared using 22 different tests. This suggests that all freshwater mucus trails may behave in a similar way, and that all aquatic mucus trails would (within environmental limitations) respond in a predictable manner. The ability to forecast the behaviour of a material in its natural environment allows a certain degree of predictive modelling, if such a material were deemed to be o f commercial interest.

The monosaccharide sub-units of the pedal STM polysaccharide of L. peregra and P. jenkinsi have yet to be identified. In the light of the results discussed in Chapter Four

(pesticide sorption), it could yet prove valuable, to identify those monosaccharides and estimate the quantity o f each, in those environments subject to pesticide contamination.

This would allow the calculation of pesticide sorption to specific monomers, which

may be artificially produced on filters, as a means of waste / fresh - water processing

/ clean-up. Equally, by identifying the protein sub-units of blackfly silk, their

individual ability to sorb pesticides may be quantified.

The small, non-aqueous portion of mucus (the remaining 0.3 - 9.9%, Denny, 1983) has

been characterised for a number o f different species, in a number of different

situations. However, for the purposes o f this study, there was little point in attempting

to characterise the pedal mucus o f either snail species used. This is because mucus

secretions vary in composition seasonally (ash, protein and carbohydrate, Davies et ai. 221

1990a), according to stress (Davies, 1992) and according to diet, environment (Davies et ai, 1992 a and b) and population density (Chapter Four). In order to gain a sufficient understanding of the composition of mucus, contemporary studies list the basic constituents {eg. Hunt, 1970; Denny, 1980; Denny, 1983; Livingstone and De

Zwaan, 1983; Denny, 1989), which prim arily are, long chain carbohydrates, with small quantities of inorganic salts and protein. However, for the purposes o f environmental management, such as the control of nutrient availability, biological considerations such as season are reduced in importance. Production of highly sorbative, synthetically produced, mucus or silk polymer sub-units does not need to consider the environmental factors that influence natural abundance of mucus or silk.

7.3 Bioturbation

Despite the volume of literature published and regularly reviewed, (see Chapters One and Five), there remains a considerable lack of understanding o f the effects of invertebrates on bioturbation and sediment stability. A review of papers published in recent years reveals that little work has been conducted on bioturbation caused by invertebrates. These few existing papers, do however indicate, the role that invertebrates play in benthic processes. For example, Parkyn et al., (1997) suggested that freshwater crayfish play a key role in sediment bioturbation, and thereby increase organic matter processing rates. That invertebrates alter local turbidity is of great significance to the processes o f particle-attachment-site availability. The binding of sediments using organic invertebrate secretions offers further sites of particle attachment, while lim iting the m obility and downstream processing of those particles present. The disturbance of sediments offers an increase in the number of mobile particles, thus decreasing the availability of attachment sites, as those disturbed particles settle. That is a rather simplistic overview, and the reality is far more complex.

The interactions of amphipods, oligochaetes and chironomids were studied by

Vandebund et al., (1994). They found that the bioturbation caused by each of the three organisms resulted in an increased oxygen penetration of sediments, which led 222 to an increase in the bacterial population (dependant on bacterial feeding rates of organisms studied). No difference was noted in sub-surface layers. Once more, invertebrates have a direct effect on sediment conditions, influencing the proliferation of particles (bacteria), that w ill in turn affect the accrual o f particles and subsequent particle sorption, as biofilms develop. Interactions between bacterial communities and freshwater invertebrates are beginning to be studied. The interactions between freshwater nematodes and bacterial abundance indicate that sediment grazing by nematodes stimulates bacterial activity, and does so, to a greater extent than bioturbation or excretion by nematodes (Traunspurger et al., 1997). In this instance, invertebrates are again indirectly responsible for the increase in the availability of particles and the provision of sites of particle attachment within fresh waters.

An example of invertebrates causing the direct release of particles from sediment is also available. In a direct contradiction o f Isensee's (1983) rather short sighted vision of bioremediation of rivers by the casing of benthic sediments, Reible et at., (1996) have shown that the burrowing and benthic surface defecation o f tubificids can result in the release of hydrophobic xenobiotic compounds by desorption into the water column following chemical and physical changes due to exposure. Such compounds would otherwise be sorbed to sediment-trapped particles, or sediments, as bound organic matter.

Invertebrates also influence sediment stability via their role in the attachment of bacteria to sediments. The implications o f carbohydrate concentration in cohesive sediments is both reviewed and examined by Taylor and Paterson (1998). They noted the considerable variation within estuarine sediments as well as the importance of EPS in sediment stability. STM has been shown to enable the attachment of bacteria and diatoms to substrata, (see Chapters Three and Six).

Finally, the influence that invertebrates have upon sediment stability is perhaps best demonstrated by Blauchard et ai, (1997). They note that the re-suspension of estuarine sediments enhances planktonic organisms (diatoms and bacteria), a process controlled by many factors, including tidal shear stress, sediment cohesion, and 223 bioturbation by snails. O f particular interest, they noted that critical shear velocity of diatoms and bacteria in the presence of STM was decreased. They suggested that such an observation is due to the attachment of such particles to a more easily erodible material (STM erodes more easily than the estuarine mud they studied). Not only does their study indicate the attachment of particles to invertebrate secretions, it also highlights part of the continual process of particle adhesion and removal, due to the action o f invertebrates, and in particular, invertebrate secretions, such as STM.

7.4 Mucus, biofilm , particles and pollutants

Two very important new findings have been made within Chapters Four and Six.

Firstly, that invertebrate secretions such as STM and blackfly silk exhibit extremely high partition coefficients for hydrophobic xenobiotics. Secondly, that STM will accelerate the accumulation o f POM and DOM, leading to the formation of potentially long-lived biofilms, seeded with specific microbial types. Kiel et al., (1998) have forecast the same property for blackfly silk. The implications of such findings have barely been explored. A key paper linking these two discoveries is that of Leppard

(1997), who indicated the degree to which polysaccharide, fibrils and colloids, contribute toward biofilm, both from within, and via capture from the planktonic state.

In addition, polysaccharide exopolymer is known to scavenge metals from surrounding

waters (Labare et ai, 1989).

Considering the degree to which mucus sorbs xenobiotics, and its subsequent potential

incorporation into biofilm (either from the attachment of cells and POM, or due to

capture, having eroded from its site of secretion), this suggests the incorporation of

pollutants into biofilm communities. The inclusion of metal ions, nutrients, DOM,

particles, and by inference, xenobiotics into biofilm and other benthic slimes was

explored by Winterbourne (1986), who found that all were trapped and processed by

benthic layer "slimes". Colloids, which are known to be entrapped by biofilm, and

so by implication, may be assumed to attach to STM and silk, are also known to sorb

DOM such as xenobiotics (Liljestrand and Lee, 1991 ). The partitioning of polycyclic

aromatic hydrocarbons to marine organic colloids was detailed by Chin and Gschwend 2 2 4

(1992), who reported high levels of sorption. This was to be expected as they did examine compounds with high partition coefficients to inorganic soils. Sorption of such compounds (fenvalerate, a pesticide) to (non-specified) DOM was found by Fan et al., (1997), to be 2 x 10\ considerably lower than for STM or silk, yet considerably higher than to mineral fractions and soils previously measured. By not specifying the source or type o f DOM, one may assume, that it is a TEP or CEP-like material. In the first paper o f its kind. Means and Wijayaratne (1982) examined the role of colloids in the transport of xenobiotics, stating that the partition coefficient of atrazine onto colloids is 1850. This was remarkably high at that time, but has been placed into context by my results (See Table 4.9) e.g. 49,000 for terbutryn sorption on to blackfly silk).

Of even greater concern is the confirmation that it is not just hydrophobic pollutants

(i.e. pesticides) that colloids w ill sequester. The transport of trace elements and radionuclides are also influenced in ground waters by colloids (Lieser et al., 1990).

With colloidal material often being incorporated either biofilm (Leppard, 1997), or for example STM or silk strands, with toxic compounds already attached, a considerable proportion of pollutants find their way into the cycle o f sites of attachment. This is in addition to the sorption of pollutants directly by biofilm

(Decho, 1990; Lau, 1990; Costerton, 1992; Bishop et al., 1995; White, 1995; Leppard,

1997; ReiJ et ai, 1997), STM and silk (Chapter Four). When such considerations are placed within the context of spiralling, it is apparent, that rivers may become and

remain polluted at sites of individual features such as pools or backwaters. This

potentially leads to localised pollution sites within a water body.

Once attached, a pollutant particle's existence is a long series o f attachment,

detachment and re-attachment events (Chapter One), continually available to the food

chain. Biofilm communities are favoured food stuffs for invertebrates such as snails

(Lopez and Levinton, 1978) and Gammarus sp. (Barlocher and Murdoch, 1989).

B iofilm surfaces are also sites of attachment for particles (McLachlan et al., 1978).

Particles are also used by invertebrates such as Ephemeroptera, Trichoptera, Diptera

and Chironomidae (M erritt and Wallace 1980; Alstad, 1987). In addition, faecal 2 2 5 pellets are largely comprised of compacted particles of various types which are further utilised by other organisms (Ladle et al., 1972). Particles used by these organisms, are capable of attachment and incorporation into biofilm , sediments and on to bacterial cells. They include all types of DOM as well as humic acids, fulvic acids etc (Baxter et al., 1990; Deschauer and Kogel-Knabner 1992). Chapter Four has revealed that pollutants have access to the food chain (as well as remaining in freshwater systems longer than previously thought). By the same pathway, DO M may also access the food chain, without being "packaged" by filte r feeders.

Mucus and STM in particular however, have been found to enable the development of specific biofilm communities, dependent on the cells deposited upon the STM by the snail. The EPS surrounding the bacterial cell is of a similar consistency to STM

(99% water) and is known to be used in biofilm development by acting as an adhesin or adhesive (Weiner et al., 1995). Three factors in conjunction indicate that biofilm and STM may be considered a sink for pollutants. They are 1) the potential for biofilm to develop wherever snails have traversed in fresh waters, 2) the ability of both STM and biofilm to sorb xenobiotics and, 3) the recruitment by biofilm of potentially xenobiotic laden DOM. W hile there are no studies yet published on the topic of silk as a substrate for biofilm, as mentioned by Kiel et al., (1998), it is reasonable to assume that silk w ill act as a sink for pollutants in the same way that

STM does. Indeed, results in Table 4.9 suggest that silk will sorb pollutants to a far higher degree. Coupled with Wotton's observations (1987) on the densities o f blackfly larvae at certain locations, it is apparent that freshwater silk is indeed a potential sink for xenobiotics.

7.5 Designing biofilm

Certain pesticides are known to be degraded by specific bacteria. For example, mixed pesticide degradation by biofilm in column reactors, (Gisi et al., 1997); fenitrothion

by batch culture, Nishihara et al., (1997); atrazine by Streptomyces, Fadullon et al.,

(1998); and cyanazine and others by batch culture in sewage (Liu et al., 1998).

Biofilm, of identifiable bacterial types, results from STM (pending snail diet and 2 2 6 previous areas of contact / contamination, Chapter Six). As snails are capable of egesting pellets that include viable bacterial cells, which subsequently proliferate on the STM substrate (Chapter Six), it should be possible to feed, or "prime" snails with bacterial cultures, that result in specified, desirable biofilm communities. By priming snails with bacterial cells that, for example, degrade certain pesticides, it may be possible to engineer specific biofilm communities of direct value to freshwater management. Such biofilms could, depending on environmental considerations, be utilised to bioremediate contaminated waters.

Naturally, when utilising invertebrate populations in polluted environments, the effects of the pollutants need to be taken into account. Fortunately, there exists a considerable literature examining the effects of specific compounds on specific organisms, e.g. atrazine on Lymnaea spp. (Baturo et al., 1995). Mucus is a durable material. In addition to the studies conducted within Chapter Three examining the stability of mucus, others have highlighted the persistence o f STM. The study by

Bretz and Dimock (1983) found that snails were unable to detect their own trails, only after the combined action of temperature 80°C, alcohol (95% for 30 minutes) or the action of a digestive enzyme. Even following such action, total destruction was not

achieved. Such resilience indicates the potential of STM as a basis for

bioremediation processes, whereby a physically resilient material is used in water

treatment to sorb xenobiotic compounds.

The engineering of single cells that could be fed to snails such that they are introduced

to STM where they will come into contact with biodegradable pollutants (most

pesticides currently licensed in this country are biodegradable (Walker et al., 1996)

either by direct sorption, or by indirect carriers such as DOM or colloidal particles is

perfectly feasible. Various teams are looking to identify strains and specifically genes

that w ill degrade mixed suites of pesticides in various locations (Kochetkov et a i,

1997). In the same way, biofilm structure, density, longevity and secondary functions

could be designed by priming snails with specific bacterial types. In this way, the

removal of STM by grazing macroinvertebrates may be avoided (within limits) until

the act of clean up is complete, by designing biofilm density to resist grazers. W hile 227 the attachment of non-useful bacterial cells may be discouraged by the inclusion of cell types that actively restrict the growth of other colonies (Padilla et al., 1996;

Vachée et al., 1997). Molluscan mucus is already well adapted to preventing the attachment or development of certain bacteria. Within vertebrates, mucociliary mechanisms are the primary defence against pathogenic microbial colonisation. It is thought that molluscan reliance on mucus secretion as a means o f defence is even greater (Bayne, 1983). Furthermore, by engineering the production of mucus to include factors that prevent consumption by grazers, the pathway of pollutants sorbed to mucus into the food chain may be diminished. Such factors that prevent consumption, have been detected within diatom mucus by Malej and Harris (1993).

The potential that STM offers in terms of placing specific bacterial populations, within a primed biofilm , is considerable. Fresh research is continually being published detailing highly specific uses of certain strains of bacteria. For example. Pseudomonas spp. are reported to produce antimicrobial compounds that prevent the growth of food poisoning bacteria and moulds, stimulate plant growth and suppress plant diseases

(Laine et al., 1996).

7.6 Existing applications of polysaccharide

The previously suggested applications of polysaccharide would not be difficu lt to either produce or implement. Within the biotechnology industry, polysaccharide production is widely understood and utilised. Polysaccharides account for many foodstuffs, generally via bacterial fermentation. For example, bacteria such as

Xanthomonas campestris are fermented for commercial use of xanthan (for use in tomato ketchup and chewing gum), (Roseiro et al., 1992). However, there are many considerations other than those relating to the food industry. Some o f these relate directly to the presence of polysaccharides, and other materials, that w ill offer sites of adsorption to DOM and POM in freshwater systems. For example, Porschmann et al.

(1991) reported the use of microbial exopolymers as flocculating agents within the waste water treatment industry. They also stated that there exists an urgent need for effective natural flocculants to replace or optimise mechanical separation methods. 228

It would seem to be appropriate therefore, to utilise mucus producing invertebrates within waste water treatment, in the same way that bacterial beds currently act as filters. Polysaccharides offer the double advantage of being both effective flocculants and natural materials that can be easily removed and are totally, naturally, degradable.

Interactions between mucus and fish are also o f commercial concern. In the first instance, it was noted by Yano et at., (1991) that intraperitoneally injected polysaccharides activate the alternative complement pathway in carp, so inducing protection against bacterial infection. The source o f the ten polysaccharides used was yeast. In the second instance. The Environment Agency (1988) reported that fish in the River Kennet, Avon canal and nearby fish farms had been killed en masse by excess polysaccharide coating their gills. The source of the polysaccharide was thought to be a spring algal bloom. These two examples imply that greater understanding of the role o f polysaccharides within fresh waters is required for effective management strategies.

Mucus offers commercial potential in the most unusual of circumstances. Chapters

One and Two included a brief review of the variety of uses that organisms, specifically invertebrates, produce and utilise mucus for. It is understood that mammalian life depends on mucus for various essential functions such as breathing, reproduction, defence system etc. Chapter Seven has already described how various dyes can be used to highlight mucus. In addition to Alcian Blue attaching to negatively charged carbohydrate groups, so ruthenium red (ruthenium oxychloride), attaches to a specific ligand associated with acidic glycoproteins. Olianas et al.,

(1996), have shown that ruthenium red is trapped by mucus aggregates (benthic, marine, mainly diatoms) both chemically and physically. Attachment was consistent with the Langmuir ligand binding isotherm, (i.e. the classical isotherm equation which assumes the "adsorbate to be localised on the surface without lateral interactions", as described in House, 1983). They further stated that a "mucus matrix of acidic binding sites acts as an intracellular glue, providing a molecular sieve-like capacity to the aggregates dispersed in seawater". This suggests the utilisation of mucus (or a synthesised polysaccharide containing acidic binding sites) as a separation material / 229 stage for fine or delicate biological or chemical fermentation products such as enzymes. The use of mucus as a means of sequestering ions in water transport is a further possibility (Gupta, 1989). The effective removal of colloidal materials by silk or STM presents an alternative means of chemical filtration o f either waste waters, fresh waters or, fine industrial processes. The detailed modelling o f colloidal binding

{e.g. Gregory, 1993), coupled with the ability o f molluscan mucus to recognise specific compounds via lectins (Bayne, 1983), suggests that the ground work for the commercial utilisation of invertebrate secretions is already available.

Simply by examining these few recent research fronts, it is apparent that polysaccharide, and natural materials in general {eg. silk, mucus, chitin, proteins, fibre-

resin composites etc) offer tremendous potential for commercial application (Viney,

1993). The behaviour, production and movement o f mucus alone must be understood

in order to safeguard the viability of our fresh waters. Commercial aspects of mucus and silk relevant to this study include the use of those materials as agents of

bioremediation of dissolved pollutants in waste water treatment, as well as the engineering of specific biofilm communities that w ill further act as agents of

bioremediation. The importance of natural materials as being "ready-made" substitutes

for highly specific manufacturing process requirements is detailed by Viney (1993).

Simply by characterising natural materials, especially invertebrate secretions, because

of their vast abundance and physical range, Viney argues that novel, renewable,

resources w ill become available for developing technologies.

7.7 Further work, identified by this study

As with all scientific research, this study raises as many questions as it answers. In

addition to a number of important findings, it has also served to highlight areas of

further research. Primary among such further needs is a study of the physical

properties o f STM in situ rather than artificial conditions. Besides ease of

manipulation, the main reason this study used an artificial system, was to avoid the

effect of invertebrate grazing. That is not to imply that my study has not revealed a

great deal about the physical responses of STM. An investigation such as my study 2 30 provides consistent conditions, where levels of starvation, season etc can all be considered constant, and therefore discounted. This indicates that the use of artificial systems to study freshwater processes is valid. By way of context, the variability of

STM in natural conditions has been discussed by Peck et al., (1993) who noted that limpet mucus production is reduced by up to 40% when individuals are starved, while m obility is not restricted in any way. In addition, they also stated that mucus production in limpets has been shown to vary by factors of up to 1.5 and up to 5 with site and season respectively. Furthermore, by pre-conditioning the snails in the laboratory, the practical problems of faecal pellets or particulate matter on the mucus trails, are removed. However, it is essential that the factor of laboratory handling remains foremost when making conclusive statements about the behaviour o f snail trail mucus (A loi, 1990).

As well as examining STM in its natural habitat, it is also important that mucus is examined on its natural substrate. Considering that a magnification o f 200 is required to examine marker particles, this is somewhat impractical for materials such as bedrock or unconsolidated silt. Less problematic, and equally interesting would be the examination of STM on a micro-scale, particularly with regard to the inclusion of bacteria, for example, using an oxygen probe.

The mechanism of particle attachment is an interesting topic that has been raised by this study. Adm ittedly this is a huge area of study, where potentially a different means of attachment w ill be employed for each particle type. However, Heissenberger et ai, (1996) have demonstrated the attachment and embedding o f bacteria and inorganic particles within marine snow, so, theoretically the same should be possible for freshwater snail mucus. Whether particles stick to the surface of the hydrated

mucus trail, become embedded, or attach to a number of sites o f specific chemical attraction remains unknown. Each possibility suggest different mechanisms of attachment, physical structure and ultimately, a different definition of saturation.

Unfortunately, despite trials, no methodology was devised that might adequately explore this aspect of snail mucus. 231

Characterisation of the particles and dissolved material that attaches to the mucus trail is an important topic that seems to have been overlooked by the literature. W hile

Chapter Four of this study examines pesticide attachment to snail mucus material, and

Chapter Six investigates bacterial cell attachment, it is also important to examine material such as metals, radio-nuclides etc. Fisher et al., (1991) has demonstrated the considerable ability of mucus-bound-zooplanktonic-faecal-pellets and marine snow to scavenge metals from surrounding sea water. Such a study also serves to highlight the importance of freshwater snail faecal pellets, bound in mucus and hypothesised by this study to contain viable bacterial cells. As such they are a food source and an important site of chemical binding.

A further unstudied aspect identified by this study, is the examination of the physical dimensions of the mucus trail. W hile this study has successfully determined the rate of production of STM, and population densities of freshwater snails, we remain unaware of the physical volume of STM within freshwater. Attempts were made to measure the dimensions of snail trails, leading to highly variable results. Under hydrated conditions, trails are prone to folding in on themselves. On the other hand, while using SEM, the dehydration process resulted in a distorted remnant o f a trail.

Examination by microscopy in the hydrated state, using reverse interference

microscopy was found to be inappropriate for the measurement of vertical (rather than

horizontal distances) from a glass slide.

In addition to the few areas requiring further examination highlighted by this study,

there remains a vast new area awaiting fresh research. Aquatic, invertebrate secretions

such as mucus and silk, remain under-studied materials. This study has successfully

profiled various aspects of freshwater snail mucus trails and blackfly silk with respect

to particle attachment. Davies and his co-workers have already described the physical

properties of limpet mucus in the rocky intertidal zone. There remain however, many

other sources of invertebrate secretions yet to be examined such as marine snow, the

TEP o f the oceans and the CEP of freshwaters among the polysaccharides alone. 232

This discussion has also drawn attention to the potential that mucus and silk offer within commercial processes, as well as within water management. A greater understanding of these materials is required in order to better comprehend processes such as particle availability, allowing better management of our freshwaters. 233

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