Ecology of Mediterranean snails in Southern Australian ......1.4 UNDERSTANDING THE BIOLOGY AND...

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ECOLOGY OF MEDITERRANEAN SNAILS IN SOUTHERN

AUSTRALIAN AGRICULTURE: A STUDY OF CERNUELLA

WRGATA AND COCHLICELLA ACUTA ON THE

YORKE PENINSULA

VANESSA L. CARNE

Thesis submitted for the degree of

Doctor ofPhilosoPhY

in

The University of Adelaide

Faculty of Sciences

School of Agriculture and Wine

The [Jniversity of Adelaide

South Australia

AUGUST 2OO3

TABLE OF CONTENTS

TABLE OF CONTENTS

TABLE OF CONTENTS ll

LIST OF FIGURES

LIST OF TABLES

vvrtlSUMMARY

DECLARATION xxvll

ACKNOWLEDGEMENTS

CHAPTER I: MEDITERRANEAN SNAILS IN SOUTHERN AUSTRALIAN

AGRICULTURE

I.1 INTRODUCTION I

1

1.1.1 The snail specie s 2

1. 1. 1.1 Cernuella virgata

1.1.1.2 Theba pisana

1.1.1.3 Cochlicella acuta 5

J

aJ

1.1. L4 Cochlicella barbara 5

6

7

1.1.1.5 Breeding

1 .1.1.6 Response to heat

1.2 SIGNIFICANCE 9

ll

l01.2. I Economic significance

TABLE OF CONTENTS

1.2.2 Medical signif,rcance l2

1.3 CONTROL 12

1.3.1 Chemical control 13

1.3.2 Cultural control 15

1 .3.3 Biological control l6

1.4 UNDERSTANDING THE BIOLOGY AND ECOLOGY OF MEDITERRANEAN

SNAILS t7

1.4.1 Population ecolo gy of Cernuella virgata, Cochlicella acuta and Theba pisana -18

l. .2Breeding behaviour of Cernuella virgata 19

1.4.3 Dispersal 21

1.5 AIMS

CHAPTER II: FIELD SITE DESCRIPTION & SNAIL SPECIES USED

2.1 GENERAL FIELD SITE

2.2 SNAIL COLLECTION SITES

2.2.1 W arooka field site

2.2.2 AS field site

2.3 SNAILS

2.4 MAINTENANCE OF LABORATORY SNAIL CULTURE

23

)<

25

26

25

26

30

31

312.5 STATISTICAL ANALYSß

ul

TABLE OF CONTENTS

CHAPTER III: FACTORS THAT INFLUENCE THE POPULATION DYNAMICS

OF CEÀ¡|/UELLA VIRGATA, TIIEBA PISANA AND COCHLICELLA ACUTA-3Z

3.l INTRODUCTION 32

3.1.1 Climatic data 3t

3. 1.2 Statistical models 38

3.2 MATERIALS AND METHODS

3.2. 1 Statistical analysis

3.3 RESULTS

3.3.I Cernuella virgata

3.3.2 Cochlicella acuta

3.3.3 Theba pßana

3.4 DISCUSSION

BREEDING BEHAVIOUR Oß CERNUELLA VIRGATA

4.1 INTRODUCTION


4.2.1 Soil moisture retention curves

4.2.2 Snail collection and short-term maintenance of the culture 73

4.2.3 Exp erimental set-up 73

40

4T

46

53

58

60

62

CHAPTER IV: THE EFFECT OF SOIL MOISTURE AND SOIL TYPE ON THE

68

68

7l

7l

4.2.4 Statistical analysis 7 5

IV

TABLE OF CONTENTS

4.3 RESULTS

4.3.1 Soil type 76

5 . L2. I Mark-releas e-recapture 93


5.2.1 Mark-release-recapture: optimalrelease size 96

5.2.2Dispersal trials 99

5.2.2.I Mass-mark-release-recapture dispersal trials 1 00

5.2.2.2 Individual -mark-release-recapture dispersal trials 101

5.3 RESULTS 105

76

4.3.3 Total egg production 79

4.4 DISCUSSION 84

CHAPTER V: DISPERSAL OF ADULT AND JUVENILE CERNUELLA VIRGATA

AND COCHLICELLA ACUTA ON THE YORKE PENINSULA 88

5.1 INTRODUCTION

4.3.2 Soil moisture 76

5.1.1 Dispersal 88

5.1.2 Studying dispersal 90

88

96

5.3. 1 Mark-release-recapture: optimal release slze

5.3.2 Mass-mark-release-recapture dispersal trials

105

110

5.3.3 Individual -mark-release-recapture dispersal trials 127

5.3.3.1 Adult snails 127

1465.3.3.2 Juvenile snails

TABLE OF CONTENTS

5.4 DISCUSSION 155

5.4.1 Density release 155

5. 4.2 Mass-mark-release-recapture 156

5.4.3 Individual-mark-release-recapture dispersal 162

CHAPTER VI: FACTORS THAT INFLUENCE INDIVIDUAL MOVEMENT OF

CERNUELLA VIRGATA AND COCHLICELLA ACUTA: WITH PARTICULAR

FOCUS ON ADULT CERNUELLA VIRGAIA IN BARLEY 172

6.1 INTRODUCTION t72

6.2 MATERIALS AND METHODS t75

6.2.1 Identification of factors that influence movement 175

6.2.2 Simulation model t77

6.3 RESULTS 191

6.3.1 Identification of factors that influence movement 191

6.3.2 Simulation model 198

6.4 DISCUSSION

6.4.1 Factors that are associated with dispersal 205

6.4.2 The simulation model 209

6.4.3 Wider implications 2tr

CHAPTER VII: CONCLUSIONS AND FUTURE RESEARCH 216

7.1 INTRODUCTION 216

211

205

7.2 PROJECT OVERVIE\ilvl

TABLE OF CONTENTS

Stage 1 Population ecology of Cernuella virgata Cochlicella acuta and Theba pisana -217

Stage 2

Stage 3

Breeding behaviour of Cernuella virgata 219

Dispersal

7.3 FUTURE RESEARCH

7.4 CIJALLENGES OF SNAIL MANAGEMENT

APPENDIX 1. Descriptive statistics for climatic and non-climatic variables, which relate

to the population densities of C. virgata over 20 years at Balgowan South Australia.

Climatic data from Maitland, South Australia (Commonwealth Bureau of Meteorology).

230

APPENDIX 2. Descriptive statistics for climatic and non-climatic variables that affect the

population densities of C. virgata over 20 years at Weetulta, South Australia. Climatic data

from Maitland, South Australia (Commonwealth Bureau of Meteorology).N: 'Number of

days' 231

APPENDIX 3. Descriptive statistics for climatic and non-climatic variables that affect the

population densities of C. virgata, T. pisana and C. acuta over 20 years at Hardwicke Bay.

Climatic data from Warooka, South Australia (Commonwealth Bureau of Meteorology). N

: 'Number of days' 232

APPENDIX 4. Climatic data measured at the release site (Minlaton, South Australia) for

each release in the 2001 (2 days) and2002 (5 days) field seasons. 234

vii

220

222

228

TABLE OF CONTENTS

APPENDIX 5. Descriptive statistics of dispersal over two days for adult C. virgata and C.

acuta in 2001 relating to Chapter 5 241

APPENDIX 6. Descriptive statistics of dispersal over fìve days for individual adult and

juvenile C. virgata and C. acuta in2002 relating to Chapter 5 26l

APPENDIX 7. MATLAB Code defining functions used in calculating the extinction time

cumulative distribution function and its confidence limits. From Box 3.3 (Morris and

Doak,2003). pp 80 289

APPENDIX 8. A MATLAB m-file defining the function stretchbetaval which returns

stretched beta-distributed values. Note that this procedures uses betaval, defined in

Appendix 4. From Box 8.5 (Monis and Doak, 2003). pp283 290

APPENDIX 9. A second MATLAB function to make beta-distributed random numbers

(See Appendix 4). 'betaval' returns a beta-distributed value with the specified CDF

(cumulative distribution function) value.From Box 8.3 (Morris and Doak, 2003) pp. 277.

292

REFERENCES 294

vlll

LIST OF FIGURES

LIST OF FIGURES

Figure 2.1. Map of Australia showing the location of Minlaton and Warooka on the Yorke

Peninsula (Biolink 1.5 CSIRO Entomology, 2001)

Figure 2.2. FtanfaLl data from a. Warooka Field site and b. SYP Field Site at Minlaton

meteorological station for 2000 ..; 2001 I and 2002 and the long-term average ---

(Commonwealth Bureau of Meteorolo gy, 2003

Figure 4.L. 'Water retention curve for the calcareous - and the non-calcareous -- soils'

Matric suction for saturation (S) is 0.3 m; field-capacity (FC) is 1 m; mid point (MP) is 10

m; and permanent wilting-point (P!VP) is 150 72

29

Figure 4.2. Effect of soil tlpe on the time taken until the first egg cluster was laid by C.

virgata irrespective of soil moisture treatment. Relationship calculated using Kaplan-Meier

analysis. n : 100. MNS -; YPS -. Log-rank test, f: 10.12;ldf, P : 0.0015. wilcoxon

f : tl.02,I dt p : 0.0009. NB. Data from the no-moisture treatment were excluded from

the analysis since no eggs were laid in this treatment. 78

lX

LIST OF FIGI]RES

Figure 4.3. Effect of soil moisture treatments on the MNS on time taken until the first egg

cluster was laid by c' virgata' sattxation * field-c apacity r 11 : 20; Mid-point - n : 10;

Wilting-point - n: 10. Relationship calculated using Kaplan-Meier analysis. Log-rank

f:37.3g,2 dfp < 0.0001. Wilcoxon f :Zt.zl,2 df,P < 0.0001. NB. Data fromthe no-

moisture treatment were excluded from the analysis since no eggs were laid in this

80

Figure 4.4. Effect of soil moisture on the YPS on the time taken until the first egg cluster

was laid by c' virgata' saturation - Field-capaclty - Mid-point -' Relationship

calculatedusingKaplan-Meieranalysis.n:50.Log-rankt:ZZ'I3,2df,P<0.0001;

Wilcoxon f : ZZ.tl,2 df,P < 0.0001. NB. Data from the wilting point and no-moisture

treatments were excluded from the analysis since no eggs were laid in these treatments-81

Figure 4.5. Total number of egg clusters laid over the course of the experiment in each soil

moisture treatment for MNS - and YPS -, Values are means -|/- standard errors.-83

Figure 5.1. Triangulation with measuring tape. A: Release point; B: Reference point; C

: Location of snail at time of observation. The baseline AB should be approximately as

long as the linear dimensions of the areathat includes all the flags marking out the path of

the snails. The n-th distance is measured by stretching one tape measure from A to C, and

the other from B to C to achieve distances AC and BC respectively. This procedure is

repeated for all stopping points, always using A and B as fxed points. Figure adapted from

Turchin (1998)

x

LIST OF FIGURES

Figure 5.2. Distance travelled by adult r. C. virgata andb. C. acuta by day two at release

densities of 8, 16, 40 and. 100 snails in June 2001.Values are means t +/- standard

deviations. Forecasted distance - derived from parameter estimate from generalised linear

model. N.B. means for each release s:r:e are offset to clariff standard deviations for each

replicate 109

Figure 5.3. Example of displacement of adult C. virgata in unburnt Canola in a. June, and

b. October 200I, over two days. Day I r; Day 2 t.Each point represents an individual

snail. Mean angle day 1 o; day 2 . n: 40. Distances are shown in cm. 111

Figure 5.4. Frequency of the net distance moved by adult C. virgata in unbumt canola in

a. June and b. October 2001 over two days. Day I r; Day 2 t n: 40. Populations are the

same as those in Figure 5.3 a. and b. 112

Figure 5.5. Mean displacement +l- standard error of adult a. C. acuta and b. C' virgata at

day two after release in each of the five treatments for July r; September r and October l.

126

Figure 5.6. Movement paths over five days of two individual adult C. virgata, released in

barley in July 2})2.Distances moved in cm. 128

X1

LIST OF FIGURES

Figure 5.7. Mean displacement +l- standard error of adult a. C. virgata and b. C. acuta at

day five after release in barley and medic habitats in June r; July r and October r NB

No data available for C. acuta in July 2002. 137

Figure 5.8. Frequency of the distribution of the directional headings of adult C. virgata

released in barley, in July 2002 - at a. Day 4 and b. Day 5. Mean angle of directional

heading --. Rayleigh's test of bias (z) shows significant bias in directional heading'

Headings are grouped in 30o categories. n:40 39

Figure 5.9. Frequency of distances moved by adult C. virgata in barley in July 2002 fot

dayl4day2t,day3 tday4 anddaY5 r 140

Figure 5.10. Observed mean squared displacement r and expected MSD - as a function

of the number of steps for C. virgata in a. barley b. medic and C. acuta in c. barley, d.

medic in June. For C. virgata in e. barley and f. medic in July; and C. virgata in g. barley,

h. medic, and C. acuta in i. barley and j. medic in September' n : 120. 142

Figure 5.11. Mean displacement +l- standard error of juvenile C, virgata r and C. acuta t

at day five after release in barley and medic, September 2002' 150

Figure 5.L2. Frequency of distances moved by juvenile C. virgata in medic in September

512002forday 1 r, day2 t, day3 t day 4 andday5 r'n: 40

xll

LIST OF FIGURES


of the number of steps for juvenile C. virgata in a. barley b. medic; and juvenile C' acuta

in c. barley, d. medic in September 2000. n: 153

Figure 6.1. A flow diagram representing how the simulation model forecasts the

movement length of adult C. virgata in barley, and how the parameters in the model are

included' 184

Figure 6.2. Forecasted proportion of individual adult C. virgata in barley, within a given

distance atday I-day2-day3 - day4 andday5-'n: 10000. 199

Figure 6.3. Forecasted proportion of observed displacement in June 2002 ; July -; and

September 2002 -; and forecasted - individual adult C. virgata in barley, at day 5. 203

Figure 6.4. Forecasted proportion of observed - and forecasted - individual adult C.

virgata in barley, at day 5. Observed data from June, July and September 2002 releases

combined

x111

LIST OF TABLES

LIST OF TABLES

Table 2.1. Summary of soil chemical and physical characteristics from the Southern Yorke

Peninsula Alkaline Soils Field Trial Site, South Australia. 30

Tabte 3.1. Sources of population data for C. virgata, C. acuta and T. pisana where

applicable, collected at three sites on the Yorke Peninsula, South Australia. 40

Table 3.2. Non-climatic variables that were investigated in the mixed model analysis to

43determine if they affect seasonal snail population densit

Table 3.3. Temperature ("C) variables that were investigated in the mixed model analysis

to determine if they affect seasonal snail population densities. 'N.' refers to 'number of.

NB: Summer: December 01 previous year - February 28129; Autumn: March 01 - May 31;

Winter: June 01 -August 31;Spring: September 01-November 30. 44

Table 3.4. Rainfall (mm) and relative humidity (o/o) variables that were investigated in the

mixed analysis to determine if they affect season snail population densities. NB: Summer:

December. 01 previous year - February 28129; Autumn: March 01 - May 31; Winter: June

01 - August 31; Spring: September 01 - November 30. 45

Table 3.5. Southern Oscillation Index variables that were investigated in mixed model

analysis to determine if they affect seasonal snail population densities. 46

XIV

LIST OF TABLES

Table 3.6. Mean population counts (snails /m2; of C. virgata (> 6 mm in maximum shell

diameter) at Balgowan, South Australia, for autumn and spring fiom 1984 through to 2001.

Data collected by G. Baker 47

Table 3.7. Mean population counts (snails tn:2¡ of C. virgata (> 6 mm in maximum shell

diameter) at Weetulta, South Australia, for autumn and spring from 1984 through to 2001.

All counts were conducted in a crop. Data collected by G. Baker' 48

Table 3.8. Mean population counts (snails lrÊ¡ of C. virgata (> 6 mm in maximum shell

diameter) at Hardwicke Bay, South Australia, for autumn and spring from 1984 through to

2O0l. Data collected by G. Baker. 49

2001. Data collected by G. Baker. 50

Tabte 3.9. Mean population counts (snails trÊ¡ of T. pisana (> 6 mm in maximum shell

diameter) at HardwickeBay, South Australia, for autumn and spring from 1984 through to

Table 3.10. Mean population counts (snails trÊ¡ of C. acuta (> 6 mm in maximum shell

height) at Hardwicke Bay, South Australia, for autumn and spring from 1985 through to

2001. NB. No data available for 1984. Data collected by G. Baker I

Table 3.11. Variables that were associated with C. virgata populations (> 6 mm rn

maximum shell diameter), in a crop in autumn at three sites on the Yorke Peninsula, South

54Australia from 1 984-200 I

XV

LIST OF TABLES

Table 3.12. Yariables that were associated wiht C. virgata populations (> Ó mm rn

maximum shell diameter), in a crop in spring at three sites on the Yorke Peninsula, South

Australia from 1 984-2001 5

Table 3.13. Variables that were associated with C. virgata populations (> ó mm tn

maximum shell diameter), in a pasture at autumn and spring at Balgowan and Hardwick

Bay on the Yorke Peninsula, South Australia from 1984-2001 7

Table 3.14. Comparison of the variables that were associated with C. acuta populations (>

6 mm in maximum shell height) populations in a crop and a pasture in spring and in

autumn at Hardwicke Bay South Australia from 1984-2001

Table 3.L5. Comparison of the variables that were associated with Z. pisana populations (>

6 mm in maximum shell diameter) in a crop and a pasture for spring and autumn at

Hardwicke Bay South Australia. From 1984-2001 6l

Table 4.1. Preparation of the soil moisture treatments for the calcareous and non-

calcareous soil. Water content calculated from Soil Moisture Retention Curve. 74

Table 4.2. One-way ANOVA table showing the effect of soil moisture and soil type on the

total number of eggs laid over the duration of the experiment. There was no two-way

interaction between soil moisture and soil type on total number of egg clusters laid.-82

Table 5.1. Recapture rate of adult C. virgata and C. acuta at different release slzes over

two days, June 2001. Values are means * / - standard error. n: 3. 105

xvi

5 9

LIST OF TABLES

Table 5.2. Pearson's Chi-square test to compare headings (grouped at 90') for adult C.

virgata within and between release sizes 8,16, 40 and 100 snails, at day 2 at 0.05 level,

June 2001 106

Table 5.3. Pearson's Chi-square test to compare headings (grouped at 90") for adult C.

acutawithin and betweenrelease densities 8,16,40 and 100 snails, atday 2 at 0.05 level,

June 2001 . 107

cumulative of days one and two. 115

Table 5.4. Slope of lines for regression of distances moved versus release numbers for

distances moved by adult C. virgata and C. acuta at release sizes 8,16, 40 and 100 in June

2001, derived from generalised linear model. 108

Table 5.5. Solution for fixed effects from mixed model analysis on the effect of crop type

on displacement of adult C. virgatø in July 2001. Separate models shown for days one and

for the cumulative of days one and two. ll4


on dispersal of adult C. acuta in July 2001. Separate models for days one and for the

Table 5.7. Solution for frxed effects from mixed model analysis on the effect of crop type

on dispersal of adult C. virgata in September 2001. Separate models shown for days one

116and for the cumulative of days one and two

XVII

LIST OF TABLES


on dispersal of adult C. acttta in September 2001. Separate models shown for days one and

for the cumulative of days one and two. I 18


on dispersal of adult C. virgata in October 2001. Separate models shown for days one and

for the cumulative of days one and two. 119

Table 5.10. Solution for hxed effects from mixed model analysis on the effect of crop tlpe

on dispersal of adult C. acuta in October 2001. Separate models shown for days one and

for the cumulative of days one and rzl

Table 5.11. Summary of directional bias (Fisher's omnibus test) across all treatments, over

two days for adult C. virgata and C. acuta in October 2001. n: 3' 122

Table 5.12. Tests of fixed effects; factors that affected dispersal distance of adult C.

virgata on days one and two during the 2001 field season. 123

Table 5.13. Tests of fixed effects; factors that affected the dispersal distance of adult C.

acuta ondays one and two during the 2001 field r23

Table 5.14. Summary of heading directional bias (Fisher's omnibus test) in barley and

medic over five days for adult C. virgata and C. acuta inJune. n :3ltreatment.-l28

xvlll

LIST OF TABLES

Table 5.15. Summary of turning angle bias (Fisher's omnibus test) in barley and medic

over five days for aú;Jt C. virgata and C. acuta in June. n: 3/treatment. 130

Table 5.16. Solution for fixed effects from mixed model analysis to investigate the effect

of crop tlpe on the daily dispersal of adult C. virgata in June 2002 131

Table 5.17. Solution for fixed effects from mixed model analysis investigating the effect

of crop tlpe on the daily dispersal of adult C. acuta in June 2002 131

Tabte 5.18. Solution for fixed effects from mixed model analysis investigating the effect

of crop type on the daily dispersal of adult C. virgata inJúy 2002 132


medic over five days for adult C. virgata and C. acuta in September. n: 3lfieatment 133


over five days for adult C. virgata and C. acuta in September. n: 3lfteatment'-t34

Table 5.21. Effect of crop type on the dispersal of adult C. virgata in September 2002.-134

Table 5.22. Solution for fixed effects from the mixed models investigating the effect of

crop type on the daily dispersal of adult C. acuta in September 2 35

x1x

LIST OF TABLES


medic over five days in September 2002 for juvenile C. virgata and C. acuta. n :

3/treatment. 146


over five days in September 2002, for juvenile C. virgata and C. acuta. n: 3/treatment.

r47

Table 5.25. Solution for fixed effect from mixed model analysis investigating the effect of

crop type on the daily dispersal ofjuvenile C. virgala in September 2002 48


of crop type on the daily dispersal ofjuvenile C. acuta in Septembet 2002 148

Table 6.1. Daily climatic and non-climatic variables that were measured (Chapter 5) and

tested to determine the factors that influence movement length of adult and juvenile C.

virgata and C. acuta in barley and medic. 177

Table 6.2. Solution for fixed effects from mixed model analysis on the factors that were

associated with the movement length of adult C. virgata in a barley crop in 2002 at

Minlaton, Yorke Peninsula, South Australia. 193


associated with the movement length of adult C. virgata in medic in 2002 at Minlaton,

t94Yorke Peninsula, South

XX

LIST OF TABLES


associated with the movement length of adult C. acuta in a barley crop in 2002 at



associated with the movement length of adult C. acuta in medic in 2002 at Minlaton,

Yorke Peninsula, South 195


associated with the movement length of juvenile C. virgata in a barley crop in 2002 at

Minlaton, Yorke Peninsula, South A 195


associated with the movement length of juvenile C. virgata in medic in 2002 at Minlaton,

Yorke Peninsula, South Australia. 196


associated with the movement length of juvenile C. acuta in a barley crop in 2002 aT



associated with the movement length of juvenile C. acuta in medic Ln2002 at Minlaton,

r96Yorke Peninsula, South

XXI

LIST OF TABLES

Table 6.10. Forecasted movement length based on the variation of previous movement

length, minimum temperature and rainfall. 197

Table 6.11. Forecasted proportion of adút C. virgata, in barley, forecasted to be within

given distances from origin. n: 10 000. 200

Table 6.12. Descriptive statistics for the forecasted displacement for adult C' virgata in

barley over five days obtained from simulation model' 201

Table 6.13. Forecasted mean, median and maximum displacement of adult C. virgata in

barley at days I0,20,30, 60, 90 and 120. Forecasts based on a regression analysis from the

descriptive statistics derived from the simulation model. 213

XXII

STIMMARY

SUMMARY

This study reports on the ecology of exotic Mediterranean snails in southern Australia with

the aim to improve control measures against these agricultural pests. Particular emphasis

was placed on Cernuella virgata (da Costa) and Cochlicella acuta (Müller) for thìs study

because they are the most abundant and damaging species. Mediterranean snails are

introduced pests of pastures, grain crops and vineyards in southern Australia. The

abundance ofthese snails, and hence their pest status, has increased recently, probably as a

result of a shift in agricultural practices towards soil conservation. Mediterranean snails

cause significant feeding damage to crops in winter and spring, and contaminate harvests

in summer due to their aestivation on the ears of cereals and pods of legumes. Snails

damage harvest machinery, and grain shipments have been rejected overseas due to snail

contamination.

In particular, the aim of the work presented in this thesis was to increase our understanding

of the population ecology, breeding behaviour and factors that influencc movcmcnt of

adult and juvenile Mediterranean snails in southern Australia.

Long-term population data were combined with climatic data and used to develop

statistical models in order to indicate the factors that affect snail population densities on the

Yorke Peninsula. Autumn and spring populations were analysed separately for both crops

and pastures. The analyses showed temperature and rainfall to be useful predictors of snail

abundance on the Yorke Peninsula. 'While the models could forecast snail population

numbers, there were limitations that had to be considered which were investigated and

discussed. Longer-term forecasts of snail populations could improve pest management.

XXIII

SUMMARY

The integration of population models with climatic data, as presented in this thesis,

provided indicators of seasonal risks. However, as there were no consistent predictors

across sites, additional work is needed to obtain a more appropriate data set for this

analysis.

In order to better control these snails and develop optimal management strategies, it is

important to understand how their breeding behaviour is influenced by soil moisture and

soil type. Pairs of adult C. virgatawele placed into vials containing either a calcareous or a

non-calcareous soil at five moisture levels: no-water; permanent wilting-point; mid-point;

flreld-capacity and saturation. Survival analysis was used to estimate the tendency of C.

virgata to lay an egg cluster. This study has shown thal C. virgata breed more frequently in

moist soils. These results help to predict egg-laying behaviour during breeding seasons

(autumn through winter) with different weather patterns, and therefore the risk of crop

contamination in spring that follows.

Determining the factors that influence the dispersal of adult and juvenile Mediterranean

snails is important in devising appropriate control methods. Movement of individual adult

and juvenile C. virgata and C. acuta were measured in crops and pastures on the southern

Yorke Peninsula, South Australia. Preliminary mark-release-recapture field experiments

were conducted in 2000, with displacement being measured at one and seven days after

release. Whilst the data showed that the snails moved in a biased direction, it provided

little information on how far the snails were moving each day, and what factors,

particularly climatic, were driving their dispersal. Further displacement trials were

conducted in 2001 measuring snail movement over two consecutive days. This provided a

more of an insight into the factors that influenced movement of these snails. To more

XXIV

SUMMARY

precisely determine which factors were driving individual movement, individual mark-

release-recapture dispersal trials were conducted over five consecutive days in 2002.

Turning angles, heading direction and distance moved were measured each day. Based on

the results of these studies, a simulation model of dispersal was developed. Comparing

theoretical and actual displacement, using mean squared displacement, showed that the

correlated random walk model was inappropriate to describe the dispersal pattem for C.

virgata and C. acuta.

Factors that were identified as important for snail movement were analysed using climatic

data and data collected from dispersal trials conducted in 2002 to build a simulation model.

This model can be used to forecast dispersion at chosen time intervals using parameters

deiived from statistical models. Separate models were necessary to describe dispersal for

C. virgata and C. acuta, and for crops and pastures. Statistical models have shown that

snail behaviour differs significantly between snail species, plant types, and stages of snail

development. Information derived from the models to look for patterns of snail dispersal.

Understanding the key factors that drive snail population dynamics are essential to

optimise pest management strategies. The work in this thesis shows that snail behaviour

differs significantly between species, age and plant type; which suggests that control

measures may need to be adjusted to target individual snail populations. By combining

field studies with a modeling approach, rainfall and minimum temperature were identified

as the most signiftcant environmental factors that influenced the breeding behaviour,

population dynamics and movement of Mediterranean snails. Consequently, the risk of

grain contamination in spring is predicted to be greater following a relatively warm wet

autumn and winter.

XXV

SLrl\4MARY

This research contributes new and original information on the behaviour and ecology of

Mediterranean snails, which could lead to optimal control of these agriculturally important

pests.

XXVI

DECLARATION

DECLARATION

I declare that this work contains no materiat that has been accepted for the award

of any other degree or diplomn in any university or other tertiary institution. To the best of

my knowledge and belief, this thesis contains no material previously published or written

by another person, eJccept where due reþrence has been mnde in the text.

I consent to this copy of my thesis, when deposited in the University Library, being

made available for loan or photocopying.

September 2004 Signed

Vanessa L Carne

xxvll

AKNOWLEDGEMENTS

ACKNOWLEDGEMENTS

I was extremely fortunate to work under the supervision of Mike Keller and Geoff Baker.

Their wealth of knowledge and enthusiasm was greatly appreciated. They have taught me far

more than I could have hoped. Their encouragement, support and friendship will always be

appreciated.

Mike, thank you for always having your door open for 'quick' questions, you knowledge of

biology, behaviour, statistics and modeling is inspiring, and you have taught me ecology in a

new light.

Geoff, thank you for your support, and always making the time to catch up when in Adelaide.

Your vast knowledge Mediterranean snails has allowed me to learn much from you, and I have

always enjoyed our visits.

I would also like to thank:

Past and present members of EnTales and the Department of Applied and Molecular Ecology

for many valuable discussions and their friendship.

I parlicularly want to thank Danyl Jackman, Kaye Ferguson, Angela Lush, Ana Lilia (Lily)

Alfaro Lemus, Lucy Thompson, Samantha Scarratt, Louis Maritos, Gitta Siekaman and Anna

Treager, for many thought-provoking discussions. Thank you to Nancy Schellhorn for valuable

discussions on all things SAS.

A big thank you to Teny Feckner, Heather Fraser and Gary Taylol for all of their behind-the-

scene but VERY appreciated support.

Thank you to Pat Doak. I thoroughly enjoyed my visit to your lab, and learnt much from our

valuable discussions. A.P. Patricia Doak wrote the simulation model in Chapter 6'

Thank you to Katriona Shea, for hosting me at Penn State, and for many valuable discussions.

XXVIII

AKNOWLEDGEMENTS

Thank you to Liz Drew for your assistance with the soil-retention curves, and for your valuable

friendship

My field assistants, in particular, Samantha Scarrett, Lisa Carne and Tim Cavagnaro were

wonderful! Thank you for your hard work, dependability and long hours through the cold,

windy and very wet Yorke Peninsula days!

Thank you to the SARDI Entomology group, in particular Dennis Hopkins, Megan Leyson,

Kerrin Bell and Nathan Luke. Your support, help and friendship have been appreciated'

Megan, thank you for your many valuable discussions.

The Snail Management Advisory Group, in particular Michael Richards, Graham Hayes, Bill

Long. Members from GRDC who had direct involvement, including Terry Bowditch, Allan

Umbers, Jim Fortune, and John Sando for making those meetings so valuable and fun.

A special thank you must certainly go to Michael Richards. Your incredible knowledge,

enthusiasm and interest in snail management have been great. I learnt so much about

agriculture and southern Australian farming systems through you. I always looked forward to

catching up with you in a paddock or in town. The field trips just wouldn't have been the same

without you.

This project would not have been possible without the financial supporl of Grains Research

and D eve lopment Corporation Postgraduate S cholarship.

Thank you to Joan and Richard for your support and encouragement.

Mom and Dad, thank you for your support and help over the years, I would never have made it

this far without you.

Finally, Timothy, thank you for all those hours of valuable discussions and countless hours in

the field. Most of all, thank you for your unconditional love and support.

XXIX

"The rapidiÍy of change and the speed with which new

situations are created follow the impetuous ond heedless

pace of man rather than the deliberate pace of nature"

Rachel Carson,1962

The most exciting phrase to hear in science, the one that

heralds new discoveries, is not "Eureka!" (I found it) but

"That's funny..."

Isaac Asimov

XXX

To The Three People'Who Have Influenced Me The Most:

Mom, Dad and Timothy

XXXI

CHAPTER 1 : INTRODUCTION

CHAPTER I

MEDITERRANEAN SNAILS IN SOUTHERN AUSTRALIAN

AGRICULTURE

1.1 INTRODUCTION

Mediterranean snails are introduced pests of pastures, grain crops and vineyards in

southern Australia (Cotton, 1937; Rimes, 1968; Hawthorn et al,1984; Baker and Hawke,

1991; Hopkins and Baker, 1993; Coupland and Baker, 1995; Kidd, 1995; Coupland,

1996a, b; Carter and Baker, 1997a, b). They cause significant feeding damage jn winter

and spring, and contaminate harvests in summer due to their aestivation on the ears and

pods of cereals and legumes, and amongst bunches of grapes (Baker, 1992;1998). Snails

damage harvest machinery, and grain shipments have been rejected overseas due to snail

contamination (Smith and Kershaw, 1979 Baker, 1986; Hopkins and Baker, 1993).

Similar problems have been reported in South Africa (Joubert and Walters, 1951, D.

Herbert, pers com). The abundance of these snails, and hence their pest status, has

increased recently as a result of a shift in agricultural practices away from tillage and

burning towards soil conservation (Smith, 1981; Baker, 1992). Successful control of these

snails, whether by chemical, cultural or biological means, will require an understanding of

their ecology and population dynamics (Baker, 1988c). Therefore, determining the factors

that influencs movement, dispersal and reproduction of Mediterranean snails is important

in developing appropriate control methods.

I


1.1.1 The snail species

There are four introduced species of Mediterranean snails, two round species, Theba

pisana (Müller) (Helicidae), Cernuella virgata (da Costa) (Hygromiidae), and two species

of conical snails, Cochlicella acuta (}y'rüIler) (Hygromiidae) and Cochlicella barhara L.

(Hygromiidae) (Butler and Murphy, 1977). Polymorphism including shell shape, banding

patterns, denticulation of the mandible and the radula, and the shape of reproductive organs

is highly variable in C. virgata, T. pisana (Cabaret 1983; Baker, 1986) and C. acuta

(Lewis, lg75). Additionally, polymorphism has been shown in shell colour (Lewis, 1975;

Johnson, 1980; 1981; Heller, 1981; Cain, 1984; Heller and Gadot, 1984; Cowie' 1990;

Hazel and Johnson, 1990) and foot size (Tattersfield, 19S9). While mantle colour varies

within populations, the variation between populations is significantly related to mean daily

temperature of the hottest month (Cowie, 1990; 1992). Populations in hotter regions tend

to have paler mantle colours than those in cooler climates (Cowie, 1990).

Land snails typically live in discrete populations, often isolated from one another. Because

of their sedentary nature and high cost of locomotion, snails and slugs are characterised by

low dispersal ability (Denny, 1980a, b). Thus, land snails are prone to the effects of

population subdivision with reduced gene exchanges between cohorts, leading to strong

local differentiation (Schilthuizen and Lombaerts, 1994). Extinction and re-colonisation

dynamics in local populations may also modifu the distribution of genetic variability,

leading to morphological variation among populations (Heller, 1981; Cain, 1984; Cowie,

1990; Schilthuizen and Lombaerts, 1994).

2

CHAPTER 1: INTRODUCTION

1.1.1.1 Cernuellu virgøta

The common white snail, C. virgala, is endemic to Mediterranean and western Europe

(Baker, 1991). Since its introduction into South Australia in I92l (Pomeroy, 1969; Baker,

1986; 1988b), C. virgatahas become a widespread pest of pastures, crops and vineyards

(Baker, 1991; Coupland and Baker, 1995; Baker,1996) throughout the temperate regions

of South Australia, western Victoria and south-west Western Australia (Baker, 1986;

1988b). The distribution of C. virgata is patchy. This might be attributed to the availability

of food, calcium, moisture and aestivation sites (Butler, 19'72;P.aker, 1988b), but remains

to be resolved.

High mortality of C. virgata occurs during sunìmer in South Australia, especially if the

snails are unable to climb off the ground. This mortality is most likely caused by starvation

or high temperature stress (Baker, 1986). Pomeroy (1969) found in laboratory experiments

that death in dormant snails was caused by starvation rather than desiccation. The

temperature experienced by aestivating snails decreases rapidly as they increase their

height above the ground (Pomeroy, 1969). By climbing to one metre above ground, the

temperature is cooler, (Pomeroy, 1969, Pomeroy, and Laws, 1967), thus decreasing the

risk of summer mortality.

l.l.l.2 Thebø pisanø

T. pisana was first recorded in South Australia at Port Adelaide in 1928 and is now

common along the coastal areas throughout the state. It occurs in large numbers in the

South East of South Australia, near the Mouth of the Murray River in South Australia,

-t

CHAPTER I: INTRODUCTION

throughout the Yorke Peninsula and on the Eyre Peninsula (Baker, 1986). In'Western

Australia, T. pisana occurs along the coast (Rimes, 1968; Baker, 1986). T. pisana has also

been recorded in Victoria, New South Wales and Tasmania (Baker, 1986; Baker and

Hawke, 1991).

T. pisana is native to western Europe and the Mediterranean. It is widely distributed in

coastal regions of countries bordering the Mediterranean (Bar and Nevo, 1976; Heller,

1982;Heller and Gadot,1984;Baker, 1986;Moran, 1989) and along the coasts of western

Europe, the Atlantic coast of North Africa and some Atlantic Islands. It is most abundant

in coastal areas, but can also be found far inland in Spain (Baker, 1986). T. pisana is a

significant pest of lucerne in southern France, especially around the edges of fields (Baker,

1986). In some Mediterranean countries (Portugal, France, Italy, Algeria and Israel), 7.

pisana is a popular food in the summer (Bat, 1977; Baker, 1986)' In 1914, T. pisana was

introduced into California (USA) (Basinger, 1923, 1927; Roth et al, 1987), where it was

eradicated in 1949. However, in 1985, T. pisana was again detected in California (Roth et

al,1987; Miller et al, 1988). In 1986, T. pisana was found in abundance at two San Diego

county sites on fennel stalks, wild radish, wild mustard and curly dock (Roth et al,1987)'

T. pisana was introduced to Cape Town (South Africa) in 1881, and is now widespread

(Joubert and Walter, 1951; Quick, 1952; McQuaid et aL,7976 Baker, 1986)' In Israel Z'

pisana is the most prevalent land snail along the coast (Nevo and Bar, 1976) and is

considered to be the most damaging species of economically important snails (Harpaz and

Oseri, 1961).

4


1.1.1.3 Cochlicella øcutu

C. acuta is endemic to the coastal areas of the Mediterranean and western Europe

(Aubertin, et al, 1930; Lewis, 1977; Kerney and Cameron, 1979)' It was accidentally

introduced into South Australia in 1953 (Baker and Hawke, l99l). C. acuta is typically an

inhabitant of dunes, turff cliffs and hedge banks within a few hundred meters of the sea

(Aubertin, et al, 1930). However, C. acuta is now also found considerable distances from

the sea (Aubertin, et al, 1930).

C. acuta is an introduced agricultural pest in south-eastern Australia (Baker et al, 1991).

Large numbers of C. acuta aestivate on the ears and stalks of cereals, clogging machinery

and contaminating grain during harvest (Baker et al, 1991). Significant feeding on

agricultural plants (e.g. Lolium perenne, Brassica napus, Trifolum spp. and Medicago spp.)

has not been reported, but has been observed in the laboratory (Baker, 1 989)'

The life-cycle of C. acuta in a pasture-cereal rotation is primarily biennial (tsaker, 1991).

The one-year-old snails that infest crops in winter are slightly smaller in size (mostly 10-14

mm in height) than the two-year-old snails that infest pastures at the same time (12-17

mm), but both groups have mature albumen glands suggesting they are both capable of

breeding (Baker and Hawke, 1991).

l.l.l.4 Cochlicellu børbarø

C. barbara was first reported in South Australia in Mt Gambier in 1921 and is now

widespread throughout south-eastern Australia, Western Australia and through to the

5


Northern Territory (Baker, 1936). C. barbara has posed an economic threat in the United

States of America being detected at US naval stations (Eversole,l97l).

1.1.1.5 Breeding

The breeding season for these Mediterranean snails in Australia is from autumn through

spring with most of the eggs and clutches laid in autumn (Baker, 1986; 1991). There is a

significant positive correlation between shell size and the total number of eggs produced,

the number of clutches and clutch sizes in C. virgata andT. pisana (Baker, 1986; 1991).

With C. virgata, the number of young produced, their rates of feeding and growth and their

adult longevity all decrease with increasing density (Baker, 1986). C. virgata and T. pisana

that are one-year-old are slightly smaller than two-year-old snails, however both groups

can have mature albumen glands, which suggests that both age groups are capable of

reproduction (Baker and Hawke, 1991).

Mediterranean snails are hermaphroditic, and during mating each individual transfers

spermatophores to its partner (Avidov andHarpaz, 1969). The spermatophores are stored

in the spermathecae, from which the spermatozoa pass via the oviducts to fertilise the eggs

(Avidov andHarpaz, 1969). On completing oviposition in the soil, the snail seals the hole

with a mixture of slime and soil. Eggs absorb moisture from the soil, swell, and 2-3 weeks

later they hatch (Avidov and Harpaz,1969).

6


1.1.1.6 Response to heøt

Dehydration is one of the main threats terrestrial molluscs have to deal with in their natural

environment (Vorhaben et al, 1984; Biannic et al, 1994). Mediterranean snails are

ectothermic and use morphological, physiological and behavioural adaptations to control

their internal temperatures, and to avoid or withstand both high environmental

temperatures and dry conditions (Cain, 1984; Cowie, 1985; 1990). Land snails are mainly

nocturnal (Bailey, 1975; Cowie, 1985; Bailey andLazaridou-Dimitriadou, 1986). When

the sun shines on sparsely vegetated ground, the ground surface and adjacent air reach

higher temperatures than the air above (Cowie, 1985). Cowie (1985) suggested evaporative

cooling as a mechanism of enhancing tolerance to high temperature. In relatively dry air,

evaporation takes place when the shell aperture is not sealed; the snail is thus cooler than

the ambient air (Cowie, 1985).

In Mediterranean habitats, both adults and juveniles are forced off the ground in summer

since ground temperature can exceed the upper lethal temperature. There is considerable

mortality in extremely hot summers, even in snails off the ground (Cowie, 1985). Water is

also of significance to these snails as a resource. In addition, the ability of snails to find

food is important (Pomeroy, 1969). Snails can feed by scraping the soil surface, and in

doing so, they ingest a great quantity of organic matter (Pomeroy, 1969)' The length of

available feeding time is more important for juveniles than for adults. During summer, or

in a prolonged dry spell in winter, the soil becomes dry and decomposition of vegetation

virtually ceases, which affects the quality of food available to snails. Even when food is

present, it is not available to snails unless the ground is sufficiently moist to permit activity

7


(Pomeroy, 1969). Patchy distributions of C. virgata might be attributed to the availability

of food, calcium, moisture and aestivation sites (Baker, 1988b).

In summer, Mediterranean snails leave their food plants and settle on dried plants, on

posts, wire fences and walls (Avidov and Harpaz, 1969). These snails seal their shell

aperture and aestivate (Avidov and Harpaz, 1969; McQuaid et al, 1979). During

aestivation, the snails may lose half or more of their body weight, but with the first rains,

they break dormancy and resume feeding again (Avidov and Harpaz, 1969). During long

periods of thermal and desiccation stress, little evaporation takes place through the shell,

and therefore water loss is low (Cowie, 1985). Active and aestivating snails differ in high

temperature tolerance since aestivating snails do not use 'evaporative cooling' (Cowie,

1985). The desiccating effects of dry air are further enhanced by greater wind speeds. Z.

pisana in Spain is more tolerant of higher temperatures (46"C - 50'C) fhan those in Wales

(42'C - 46'C), and aestivating Spanish snails are more tolerant than are active ones

(Cowie, 1985).

Some land snails can exist in a semi-dormant state during dry periods for as long as five

years (Baker, 1958). They are able to do this because they have their reserve supplies of

CaCO¡ (calcite or aragonite) in their shells, to which they can add, or from which they can

subtract relatively large quantities. To prevent asphyxiation during the dry periods, they

dissolve CaCO:, even to the extent of making holes in their shells in order to buffer the

CO2 content of their blood (Baker, 1958).

Juvenile snails are more tolerant of heat than adults due to their greater ability to use

evaporative cooling for short periods of time (Cowie, 1985). They have a higher aperture

8


surface area to shell volume ratio and are therefore more prone to desiccation than adults in

the longer term (Cowie, 1985), which may result in a preference for higher humidity in low

vegetation. While juvenile snails can withstand higher temperature better than adults, they

are more likely to die of starvation than adults (Pomeroy, 1968; 1969)'

1.2 SIGNIF'ICANCE

Snails native to Australia never seem to have reached plague proportions, whereas several

introduced snails have become serious pests (Young, 1996a, b). The distribution,

abundance and economic importance of snails can vary greatly over a geographical region

(Smith, 1989). Mediterranean snails are serious agricultural pests in southern Australia and

have emerged as an increased problem in western Victoria and southern NSW (Hopkins,

I990a,b;1996,2000; Hopkins and Baker, 1993; Coupland and Baker, 1995; Baker,2002).

For example, Helix aspersa (Müller), C. virgata, C. barbara, C. acuta and T. pisana

(Smith, 1989) are now found at damaging levels in many places around the world. Because

of the greater ecological flexibility and success of many of these species, and because of

the lack of the natural checks on population growth in their new localities, many of these

species of introduced snails have become pest species in their new environments, quickly

reaching a dominant position in these areas (Smith, 1989). They can cause many problems

including contamination and herbivory.

Problems for grain producers arise in several ways including potentially downgrading

grain through contamination (Baker, 1988a, b, c; 1991; Coupland and Baker, 1995; Cartet

and Baker, I997a, b). When snails are abundant, substantial areas of a farm may not be

9


harvested because of the potential for fouled grain (Baker, 1986; 1989; Young,1996a,b).

Snails cause severe damage and occasionally total destruction to legume-based pastures

(annuals, medics, lucernes and clover) and seedling crops (wheat and barley) (Coupland

and Baker, 1995). T. pisana artd C. virgata cause significant feeding damage to these crops

in southern Australia (Baker, lg92). A loss of 83 % of herbage in a pasture on the Yorke

Peninsula during a two-month period was attributed to T. pisana (Baker, 1992)' Squashed

snails clog harvesting machinery and a farmer can spend considerable time cleaning away

blockages (Baker, 1989). The abundance of these snails, and hence their pest status has

increased recently as a result of a shift in agricultural practices towards methods that

enhance soil conservation (Baker, 1992).

Slugs and snails form an important part of the herbivore fauna in different vegetation tlpes

(Scheidel and Bruelheidi, 1999). Land molluscs are harmful pests to many crops

worldwide (Godan, 19S3). Invertebrate herbivory can influence pasture species richness,

plant cover and seedling establishment as well as affecting plant growth, survival and

reproduction (Rees and Brown, 1992). Mollusc herbivores are known to show preference

to plants that are palatable and in relative abundance (Grime et al, 1968; Cottam, 1985).

Mollusc grazing in grasslands can exert long-term influences on community composition

and the reproductive potential of the plant community (Kelly and Martin, 1989; Hanley et

al, 1995). These can negatively affect cropping systems'

1.2.1 Economic significance

In 1984, a shipment of barley from South Australia was rejected by quarantine in Chile

because live C. virgata were found in the grain (Baker, 1986; 1989; Hopkins, 1990a;

10

CIIAPTER 1 : INTRODUCTION

Hopkins and Baker, 1993). This one rejection cost the Australian Barley Board AUS1.3

million in compensation payments. Foreign markets for grain are difficult to secure and

maintain, therefore, Australia cannot afford to develop a reputation for poor quality

products (Baker, 1989; Hopkins and Baker, 1993). Livestock may also reject stock-feed

that is contaminated with snail slime (Baker, 1988a, b;2002; Hopkins and Baker, 1993;

Coupland and Baker, 1995; Carter and Baker, 1997a,b). C. acuta are hard to remove from

infested grain because they are approximately the same size (when young) as a grain of

wheat or barley (Baker, 1989; Young, 1996a). An estimated 918 million snails were

delivered in barley to each of the 116 silo complexes operating in South Australia in 1983-

1984 (Baker, 1989). However, only a small number of deliveries were downgraded or

rejected (Baker, 19S9). Of the 1.51 million tonnes of barley delivered in South Australia in

1986-1987, 1630 tonnes were downgraded because snail contamination (Baker, 1989).

Therefore, the cost to the barley industry is small, but the cost to individual farmers can be

significant if their farms are broadly infested with snails (Baker, 1989; Hopkins and Baker,

1ee3).

The snail problem is not only restricted to broadacre cropping. Some fruit has been

quarantined and fumigated because of snail contamination, jeopardising export markets

(Carter and Baker, 1997a,b). T. pisana feeds on flowers and its slime inhibits pollination

of undamaged flowers (Baker, 1986). These snails are reported to feed on ornamental and

vegetable gardens in Israel, and on fruit and young foliage of citrus trees, and on grape

vine leaves, thus exposing the leaves to excessive solar radiation (Haryaz and Oseri, 1961).

This is an increasing economic problem in southern Australia.

11


T. pisana aîd, C. virgata have invaded some conservation areas and caused considerable

damage to native vegetation. The land bordering the Coorong in south-eastern South

Australia has a high-density infestation of T. pisana (Baker, 1988b; I99I;2002; Young,

l996a,b).

1.2.2 Medical significance

In many areas of the world, diseases caused by trematodes affect millions of people and

much damage to livestock (Levy et al,1973; Berg and Knutson, 1978). Because a specific

mollusc, often a snail, is necessary for the trematode to complete its life-cycle, control of

the host is an important step in the control of diseases (Levy et al,1973). C. virgata is an

intermediate host of several parasites of veterinarian importance, such as lancet fluke

Dicricoelium dendrititum andthe lung-worm Muellerius capillarls in Europe (Cabaret and

Vendroux, 1986; Cabaret, 1987; Baker, 1988b). Mediterranean snails are aî intermediate

host for the trematode Brachylaima sp. (a parasitic fluke worm) that in recent years has

infected several South Australians (Baker, 1991; Ptìster et al, 1994; Butcher et al, 1996;

1998; Carter and Baker, 1997a).

1.3 CONTROL

Ecological studies of agro-ecosystems have demonstrated both signihcant environmental

problems associated with intensive cultural and chemical control of pests within simple

crop production systems, and the largely unexplored opportunities for management based

on information of bio-ecological design of complex systems (Hill et al, 1999). Current

control measures against snails in southern Australia are not always satisfactory. Control

I2


methods involve chemical, cultural and biological methods (Baker, 1986; Young, 1996b)

or a combination of two or more of them.

1.3.1 Chemical control

Baits are effective in controlling snails (Crowell, 1977;Baker 1986; 1988b; Baker and

Hawke, 1990; Bailey and Wedgwood,1997; Hopkins and Baker, 1993). The use of snail

baits for the control of C. virgata, C. acuta, T. pisana, and C. barbara in cereal crops has

become increasingly prevalent (Mutze and Hubbard, 2000). The toxicity and attractiveness

of baits varies between species of snails and with size, age, nutritional and physiological

status of the individual (Godan, 1983). Strategic strip baiting (directed placement) may

prevent movement between adjacent fields of cereal crop and pasture in autumn, winter

and spring (Baker, 1993). A greater understanding of the factors that control snail

movement will facilitate the efficient use of strip baiting (Baker, 1992;1998).

Most commercial products for snail control contain metaldehyde (Avidov and Harpaz,

1969; Godan, 1983; GlenandOrsman, 1986; Bourneetal, 1988;Mills etal,1990;Bailey

and Wedgwood, l99l ; Glen et al, l99I; Martin, 1991 ; Davis et al, 1996; Carter and Baker,

7997a, b; Heim, 2000; Bailey, 2002). Metaldehyde, when applied in dry conditions, is

usually more effective than under moist conditions (Baker, 1986; Miller et aL,1988; Mills

et al, 1990; Young, I996a). It is an irritant that causes excess mucus secretion and

desiccation, inhibits mobility, and is a nerve poison at high concentrations. Symptoms after

poisoning with metaldehyde / acetaldehyde include increased mucus secretion, muscle

spasms, undirected mouthing movements, and uncoordinated locomotion followed by a

period of immobility (Mills et al, 1990). Therefore under very wet conditions snails avoid

13


dehydration and negate toxic effects within a few days. Additionally, an increase tn

concentration of metaldehyde causes a decrease in meal length (Baker, 1998).

Methiocarb is another commonly used bait (Godan, 1983; Baker, 1986; Bailey and

Wedgwood, \99I; Glen et al, l99l; Martin, 1991; Arad et al, 1993; Bowen and Antoine,

1996; Glen and Orsman, 1996; Perrett and Whitfield, 1996). It inhibits the nervous system

of the snails. Methiocarb is more effective under damp conditions when the snails are most

likely to be active (Baker, 1986). However, methiocarb is an insecticide and acaricide, and

is consequently more toxic to non-target organisms such as beneficial insects and

earthworms than is metaldehyde (Young, 1996a), thus its use needs to be considered

carefully.

Alternative chemicals used for control of pest snails include iron EDTA, which acts as a

stomach poison in some snail baits. Additionally, solutions of caffeine are effective in

killing or repelling slugs and snails when applied to foliage or the growing medium of

plants (Hollingworth et al, 2002). However, the mode of action of how caffeine works to

kill snails is yet to be fully understood. Snails that contaminate stored grains in silos could

be killed with fumigants (e.g CO2, phosphine), however, the dosages required for an

efficient kill are higher than those recommended for insect control (Baker, 2002).

Additionally, fumigants would only kill the snails, thus decreasing quarantine risk, that is,

of live snails being introduced to other susceptible countries. Fumigating stored grain will

not prevent contamination of snails in the grains therefore, the grain cannot be sold locally

or internationally.

t4

CHAPTER I : INTRODUCTION

1.3.2 Cultural control

Different cultural methods of control are used to target snail populations at different times

of the year. Cultivation can remove or make less attractive the habitat of the mollusc and is

the least expensive of the control measures (Young, 1996b). Stubble management

techniques, such as cabling, burning, grazing and heavy rollers are used prior to seeding,

whereas rakes and windrowing (cutting the stalks before the grain is fully ripe, raking the

fallen crops into rows across the field, leaving the crop to mature on the ground for around

a week, and then harvesting it) are used prior to harvest. Heavy rollers crush the snails, and

are only effective if the soil is hard and flat, therefore, rolling is not often effective on the

sandy soils where the Mediterranean snails are most abundant in South Australia.

Additionally, the effects of soil compaction on beneficial organisms and on plant growth

must be considered. Windrowing crops can reduce contamination as many snails aestivate

on the stubble between rows and hence do not contaminate the grain when harvested,

however, there is no published data to support this as an effective control method (Baker,

1989; Carter and Baker, 1997a, b). Windrowing is more effective on round than on

conicals snails, however, the reasons for this are unknown (Baker, 2002). Burning in

summer is effective, however, it leads to an increase in soil erosion (Baker, 1996), and is

not consistent with farming practices where the seed bank is retained to sustain the pasture

in the farming system (Hopkins and Baker, 1993; Baker, 1996). When there is damp

weather, or the soil is prone to wind erosion and the vegetation is sparse, burning is seen as

undesirable or inefficient in killing snails (Baker, 1988a, b, d; 1989; Baker and Hawke,

1990a, b; Baker et al, l99I; Cartq and Baker, 1997a). Additionally, many C. acuta escape

the fire by sheltering beneath loose rocks.

15


Traditional cultural control included the use of outriggers attached to the harvesting

machinery; however, these are now rarely used as they dislodge heads of grain, particularly

barley, in addition to the snails (Rimes, 1968). Cabling acts in a similar way, but acts as

stubble management, and thus is used prior to seeding. Large chains are attached between

two tractors, the chains dislodge the snails fromthe stubble and many of these snails then

die.

1.3.3 Biological control

Sciomyzid flies have been shown to be effective natural enemies against Mediterranean

snails in Europe (Aubertin et al, 1930; Berg, 1953; Berg and Knutson,1978; Reidenbach et

al, 1989; Hopkins and Baker, 1993; Coupland et al' 1994). Some Sarcophagidae flies

(Sarcophaga spp.), including Sarcophaga penicitlata (Yilleneuve), parasitise snails by

depositing larvae into the snail shell opening (Berg and Knutson, 1978; Baker, 1986,

1988b; Coupland and Baker, 1994; Coupland et al, 1994; Coupland, I996a; Carter and

Baker, 1997a;Hopkins and Baker, 1gg3). A larva moves towards the body of the snail and

attacks it, causing the snail to contract violently, pulling the larva deep inside its shell. The

larva then feeds on the body, consuming all of the snail's flesh before pupating (Carter and

Baker, 1997a). These flies are active in summer when the snails are aestivating, making the

snails less likely to defend themselves and thus they are an easier target (Carter and Baker,

I997a). S. penicillata was frst released at several sites on the Yorke Peninsula in April

2000. The full impact of this parasitiod will not be realised for 5-10 years (Leysonet al' in

press).

T6


A local rhabiditid nematode (Phasmarhabditis hermaphrodita) from the Yorke Peninsula,

is highly pathogenic to C. virgata, T. pisana and C. acuta (Charwat et al, 1999; 2000;

Charwat and Davies,1999;2001). However, alarge number of these nematodes are needed

to kill non-breeding individuals of C. virgata and T. pisana and thus they are not

economically viable pest suppression agents (Charwat et al, 1999; Charwat and Davies,

1999;2001).

The degree of snail control, whether by biological, chemical or cultural means, may vary

with soil t1pe, vegetation, (Baker, 1986; Barker, 1990) and prevailing weather conditions

such as temperature and humidity (Baker, 1986). Suppression can also vary with soil

moisture content and solar radiation (Baker, 1986). Seasonal behaviour of the snails such

as when and where they are active and feed, and how far they travel will also influence the

control of the snails (Baker, 1986).

1.4 UNDERSTANDING THE BIOLOGY AND ECOLOGY OF MEDITERRANEAN

SNAILS

An understanding of the basic biological and ecological requirements of Mediteffanean

snails is essential if the snails are to be properly considered in farming decisions (Murphy,

2002). Furthermore, it is important to understand not only their lifecycle, but also the

factors that drive their population ecology, breeding behaviour, and movement. Integrating

the knowledge gained from such studies should provide an increased understanding of

these pests and thus enable the development of more improved control methods.

17


1.4.1 Population ecology of Cernuellø virgata, Cochlicellø acuts and Thebø pisana

The abundance and diversity of snails are influenced by a wide range of agricultural and

other land use practices (Baker, 1998). These include variations in tillage. Many farmers

are changing to minimum- or no-tillage, but this leads to increased snail densities'

Treatment of pasture and crop residue, crop rotation, stocking rate and type, application of

pesticides and fertilisers, sewerage, soil ameliorates (clay, lime), drainage, vehicle damage

(soil compaction), fire, habitat patch size and the plant species used in land reclamation can

influence snail abundance (Baker, 1993). Pomeroy (1969) found that the spatial

distribution of C. virgata in southern Australia, showed a marked degree of clumping,

which is a characteristic of animals that feed on litter (Atkins and Leebour, 1923). The

overall distribution of C. virgata is closely related to the availability of calcium (for

example, the alkaline soils of the Yorke Peninsula) and is strongly correlated with the

amount of organic matter in the soil and the moisture content of the soil (Pomeroy,1967).

Snail densities are generally lower in crops than pastures (Baker, 1989, Carter and Baker,

I997a). Highest densities in crops are usually found at the edges; this may result from

invasions from adjacent habitat, where control measures were less efficient (Baker, 1989;

Baker et al, 1991). Snail densities may also vary depending on the different treatments by

farmers at the edges of paddocks. Snail densities in crops may be high if they were

abundant in the particular field the previous year, if the summer temperatures were mild

(cooler than average), or if the field was not burnt prior to sowing (Baker, 1989)' Baker

(198Sb) found that the abundance of adult snails in crops during the breeding season was

half that of pastures. Scarcity of mates, and therefore decreased fertilisation are considered

unlikelyto be driving factors (Baker, 1988b). Howevet, lack of food for the young due to

18


burning, harrowing and herbicide use might be contributing to decreased snail numbers.

Physical characteristics that make the soil inappropriate for oviposition or survival of

young may also limit snail abundance in crops. Tattersfield (1981) found that the shell size

of C. acuta was negatively correlated with density, however, De Smet (1983 cited in Baker

et al, 1991) found the reverse.

Mediterranean snails aggregate on fence posts, stubble and summer weeds to aestivate.

They are also often found aggregated in crops and pastures. Aggregation is known to occur

in several gastropod species (Potts, 1975; Cook, 1979;1981; Baur and Baur, 1988; Bailey,

1989), but its adaptive significance does not appeat to be the same in every case (Baur and

Baur, 1988; 1990). In some species aggregative behaviour may be part of reproductive

activities (Kupfermann and Carew, 1974), while in others it may protect snails from

predation and reduce net water loss by decreasing the total surface area: volume ratio

(Chase et al, 1980).

l.4.2Breeding behaviour of Cernuellø virgata

While it is essential to understand the factors that drive population dynamics between

seasons and years, anunderstanding of the breeding behaviour of these snails will help us

to understand more intricate details as to why populations are responding to particular

variables. The courtship and mating behaviour of snails are controlled at least in part by

environmental factors (Runham, 1 983).

Climatic conditions are almost certainly the most important factors in determining the

lifecycle of the introduced snails (Cowie,1984 a, b, c). The snails mate immediately after

19


the first heavy autumn rains, and the breeding season is autumn through spring (April-

September) (Baker, 1989; 1992; 1998; Baker et al, 1991). Temperature is an important

factor in many species, with courtship not taking place above or below a certain

temperature range (Runham, 1983). Baker and Hawke (1990) suggested physical

characteristics of soils under crops might be inappropriate for oviposition or the survival of

the young.

Mating behaviour in snails is not affected by crowding (Fearnley,1996). Search costs for

mates may be low within populations (due to aggregation), however, may be considerable

between populations (Fearnley, 1996). Random mating should occur where there is little

variance in mate quality and / or search costs for mates are high (Parker, 1983). The energy

costs of searching for a mate, and avoiding predators during courtship and mating arc all

important features of the reproductive strategy of any species (Runham, 1983). During

their long lasting courtship, terrestrial gastropods produce huge amounts of mucus, an

energetically expensive behaviour (Calow, 1977 Davies et al, 1990). Searching involves

purposeful movement until a receptive partner is encountered and is more effective when

aggregation occurs in the breeding season (Runham, 1983).

Snails from different sites differ in their mating tendency (Fearnley, 1996). Hermaphroditic

land snails are known for their elaborate courtship. This includes circling, touching, lip-lip

and lip-genital contact, biting and sequential eversion of the genital apparatus (Adamo and

Chase, 1987; Pomiankowski and Reguera,2001).

20


1.4.3 Dispersal

Mobility is an important feature of the life-history of most invertebrates (Kareiva, 1982),

and dispersal plays a central role in population biology of many herbivorous invertebrates

(Kareiva, 1982). Dispersal in land snails has been shown to be affected by type and height

of vegetation (Cain and Currey, 1968; Cowie, 1980a, b;1984; Baker and Hawke,1990;

Baur and Baur, 1993), local population density (Greenwood,1974; Baur and Baur, 1993),

snail size (Baur and Baur, 1988; Baur and Baur, 1993), homing tendency (Cain and

Currey, 1968; Greenwood, 1974; Pollard, 1975; Oosterhoff, 1977 Cook, 1979; 1980;

Rollo and Wellington, 1981;Baker and Hawke,1990; Baur and Baur, 1993) and time of

year (Cameron and Williamson,1977, Baur, 1984;Baur and Baur, 1986).

Information on the movement of snails is critical to understanding the spatial spread,

dynamics, and genetic structure of their populations, as well as their interactions with other

species (Cronin et al, 200I). Pest management decisions should take into consideration

quantitative information on dispersal of invertebrate pests, but such information is often

lacking (Turchin and Thoeny,1993).It is well understood that dispersal by pest snails is a

phenomenon that impacts crop production. Dispersal is, however, often omitted as a factor

of IPM programs at the local level, for two main reasons. First, there is little known about

the factors that influence dispersal by a particular snail. Second, testing the impact of this

phenomenon on pest populations in agricultural settings is notoriously diff,rcult (Byrne et

aL,2002).

One of the most fundamental tasks to better controlling Mediterranean snails in Australia is

an in-depthknowledge of the factors that drive dispersal (Baker, 1988c). This needs to be

21


investigated at not only a population level, but more importantly at an individual level

(Turchin, 1998). In addition, it is essential that snail species and snails of different life-

stages be investigated separately. Furthermore, a comparison of how the snails behave in

crops and in pastures, and at different times of the year, as a response to crop height,

temperature, rainfall, and thus, changing microclimates needs to be undertaken. This is

necessary because the locomotion of terrestrial gastropods relies on alarge portion of their

body surfac e areato be in direct contact with the substrate and separated from the substrate

only by a thin (10 pm) layer of pedal mucus (Dawson et al,1996). Although largely water,

(> g5%) pedal mucus is essential for locomotion, coupling the foot to the substrate (Denny,

1980a, b) and protecting the epidermis (Dawson et al,1996).

Spatial behaviour influences the distribution of snails, and is a key component in

understanding population d¡mamics (Turchin, 1991). Spatial variation will depend on the

location of food and/or mates. Population distribution, metapopulation dynamics, predator-

prey interactions or community composition may then be determined by how individual

movement behaviour is influenced by environmental features (Wiens, et al, 1993b)'

Terrestrial snails disperse by three main methods: these are natural dispersal, and

accidental and intentional movement by humans. Accidental dispersal occurs when the

snails become hidden in the tools, plant stocks, or vehicles of modern travel, and are

transported unknowingly by humans to another region (Burch, 1956; Smith, 1989).

Intentional dispersal can be either through illegal import of live snails, or the official

introduction under scientifically controlled conditions for biological control purposes

(Smith, 1989).

22


1.5 AIMS

This research contributed to a larger snail management research group set up to develop

optimal control methods against pest snails in southern Australia. Understanding the key

factors that drive snail population dynamics are essential to optimise pest management

strategies. Snail behaviour differs significantly between species, age and plant type' This

research contributes new and original information on the behaviour and ecology of

Mediterranean snails, which could assist in the development of optimal control of these

agriculturally important Pests.

The aim of the work presented in this thesis was to undertake a detailed study of the

ecology of the Mediterranean snails, with particular focus on C. virgata and C. aaúa' This

was done using a number of different approaches including examining the relationship

between snail population density data and climate, breeding behavioural studies and

detailed dispersal studies of adult and juvenile snails.

23


The specific aims of the work presented in this thesis were therefore

L To identiff environmental factors that affect f,reld populations of C.

virgata, T. pisana and C. acuta, on the Yorke Peninsula, based on 18

years of population data.

II. To determine whether soil type and / or soil moisture effect on the egg

laying of C. virgata,

ilI. To determine an optimal release size of C. virgata and C. acuta for mass-

mark-release-recapture and individual-mass-mark-release-recapture

studies, and from this, conduct dispersal trials in different habitats at

different times of the snails' active season to determine the factors that

stimulate movement of adult and juvenile C. virgata and C. acuta, and

IV. To use the above information to build and test a simulation model that

predicts the net displacement of adult C. virgata in barley.

24

CHAPTER 2: FIELD SITE & SNAIL SPECIES

CHAPTER II

F'IELD SITE DESCRIPTION AND SNAIL SPECIES USED

This chapter describes the field sites and general materials and methods routinely used in

this study. Any modif,rcations of these materials and methods are outlined in the relevant

chapters.

2.1 GENERAL FIELD SITE

All field studies, unless otherwise specified, were conducted at locations on the southern

Yorke Peninsula, South Australia. The southern Yorke Peninsula (SYP) is an area

substantially affected by the four species of exotic Mediterranean snails that affect crops

(Baker, 1988a; b, d, 1991; 1992; and others).

2.2 SNAIL COLLECTION SITES

Snails were collected from two field sites on the SYP (Figure 2.1). Site 1, located at

Warooka (Latitude -35o 03' 36.2" S; Longitude l37o 24'00.3" E; Elevation: 53 m), was

chosen because of the abundance of the four species of Mediterranean snails at the site.

Site 2 was the SYP Alkaline Soils Field Trial Site (AS), near Minlaton, (Latitude -34o 47'

37.9" S; Longitude I37" 33' 43.9" E; Elevation:32 m). This site was also used for the

majority of field experiments (see section2.2.2).

25


2.2.1 W arooka field site

The climate at Warooka is considered Mediterranean (Commonwealth Bureau of

Meteorology, 2002) and is characterised by moderately dry winters and warm summers'

Climatic data for Warooka were recorded at the Warooka Meteorological Weather Station.

Temperatures range from an average maximum of 27.3'C and a minimum of 15.9'C in

January, to lowest monthly averages of 14.9"C maximum and7.5oC minimum in July' The

highest recorded temperature for the region was 44.1oC and the lowest was 0'6oC. Rainfall

averages 447 mm, and varies from 328 mm to 593 mm per annum. Total rainfall in 2000,

2001 and 2002was 559.1 mm, 494.1 mmand 318.6 mm, respectively (Figure 2'2a).

Snails were collected from 2000-2002 at Warooka, from the roadside adjacent to a

paddock, unless otherwise stated. This site was dedicated as a snail collection site by the

owner of the property. It provided the large snail numbers needed for all lab cultures,

breeding studies and dispersal work.

2.2.2 ^S

field site

The soil atthe AS Field Site is a calcareous clay - loamwith apH of 7.7 (Table 2.1). All

experiments conducted at the AS freld site were in the same paddock. The paddock history

was: 1998 Durham wheat; 1999 canola; 2000 trial plots of barley, chickpea and canola;

2001trialplots of medic barley and canola; 2002barley. A no-tillage management strategy

had been employed on this properly since 1995.

26

CHAPTER LFTELD SITE & SNAIL SPECIES

The nearest meteorological station to the SYP field site until March 2001, was situated at

Warooka. However, all weather data from March 2001 onwards, were recorded at

Minlaton weather station. The climatic temperature description for this site is similar to

that for Warooka. Rainfall data for Minlaton were recorded at the field trial site. Rainfall

averages 432.8 mm and varies from 265 mm to 758.7 mm per annum. Total rainfall in

2000,200I and2002 was 498.7 mm, 430.8 mm and 292.2 mm, respectively (Figure 2.2b)'

Snails were collected throughout the year. However, the majority of snails, were collected

between the break of the season, ca. April (when the amount of rainfall received equals or

exceeds the effective rainfall Tow, l99I); and the end of the growing season, ca.

November (when the amount of rainfall received is less than the effective rainfall; Tow,

1991). This was because the snails are active during this time, and therefore was when all

field-based and most laboratory-based studies were conducted'

27


../..:

.: !

ADELAIDE

c

Figure 2.l.}dap of Australia showing the location of Minlaton and Warooka on the Yorke

Peninsula (Biolink 1.5 CSIRO Entomology, 2001).

28

\/

EE

t!tr(úÉ,

a. 120

100

80

60

40

20

0

b. 100

0


\I

JFMAM

JFMAM

JJMonth

ASOND

\/,

a

80

Ê560(o

Ë40'õÉ,

20

¡

JJMonth

I I

\I

ASOND

-

Figure 2.2. Rainfall data from a. Warooka Field site and b. SYP Field Site at Minlaton

meteorological station for 2000 ;2001 I and 2002 and the long-term average ---

(Commonwealth Bureau of Meteorology, 2003).

I

29


Table 2.1. Summary of soil chemical and physical characteristics from the Southern Yorke

Peninsula Alkaline Soils Field Trial Site, South Australia*.

Depth

(cm)

Texture Colour pH (Calcium

Chloride)

Calcium

(ppm)

0-10

10-30

30-60

Clay Loam

Clay Loam

Clay Loam

Grey

Yellow / Orange

Brown

7.7 5800

7.7

8.0

N/A

N/A

*Table produced by Pivot Ltd, South Australia (2001)

2.3 SNAILS

Of the four species of Mediterranean snails that affect the grain industry on the YP, C.

virgata and C. acuta were considered to be the greatest pests by the Snail Management

Advisory Group. Therefore, these two species were the subjects of the majority of

experimental work in this study.

Adult round snails, i.e. C. virgata and T. pisana and conical snails, C. acuta and C.

barbara were defined as those snails with a minimum greatest shell dimension of 12 mm'

Snails whose largest shell diameter was less than 5 mm were considered to be juvenile

snails, and snails whose largest shell dimension was between 5 mm and 12 mm were

excluded from experimental work to eliminate any ambiguity between adults and juveniles.

30


2.4 MAINTENANCE OF LABORATORY SNAIL CULTURE

C. virgata, C. acuta, T. pisana and C. barbara were collected in the flreld and transported

to the laboratory in 31 cm x22 cm x 9.5 cm plastic containers. A 20 cm x 12 cm rectangle

was cut out of the lids and replaced with 2 mm synthetic nylon mesh to allow airflow into

the container. During transportation, moist paper towelling was added to the plastic

containers to prevent the snails from desiccating.

Once in the laboratory, snails were kept in a container (as above) containing a 50 mm deep

layer of a calcareous sand-loam soil mix composed of Mt Compass Grey sand with

Calcium hydroxide and Agriculture Lime, with a pH of 8.0. Twenty to thirty snails of the

same species were kept in each plastic container, with a layer of wet paper towel covering

the soil, and three slices of carrot. Snails were kept in a constant temperature room at 16oC

with a photoperiod of l2 h light - 12 h dark. The snails were sprayed daily with water, and

food was replaced every three to four days, as required'

Snails used for field-based studies conducted on the YP were collected immediately before

each experiment and were therefore not kept under laboratory conditions.

2.5 STATISTICAL ANALYSIS

All statistical analysis, were conducted using either JMP version4.02, (SAS Institute Inc,

Cary, North Carolina) or SAS for Windows, version 5.0.2195, release 8.02 TS level 02M

unless otherwise specified.

31

CHAPTER 3: POPULATION D\.NAMICS

CHAPTER III

FACTORS THAT INFLUENCE THE POPULATION

DYI{AMICS OF CERNUELLA WRGATA, THEBA PISANA

AND COCHLICELLA ACUTA

3.1 INTRODUCTION

Invertebrates impact on humans through their effects on crops and diseases. Predicting pest

activity in crops is one of the most practical applications of population dynamics modelling

(Shirley et al, 2001). There has been considerable effort to identify the most effective time

to apply control measures to obtain the maximum reduction in slug populations (Shirley et

al, 2001). For most farmers, this means identifying the season or the stage in the cropping

cycle when control will be most effective and economically viable. From the pest

management point of view, timing needs to be linked to optimal phases in the population

cycle of the pest (Shirley et aL,2001).

The distribution and abundance of many species of land snails are related to both biotic

and abiotic factors in the environment (Tattersfield, 1981; Schrag and Read, 1992; Schrag

et al, 1994a. b). This includes the availability of microhabitats that provide the snails with

food, shelter and a temperature-moisture regime within their tolerance limits (Boycott,

1943, Burch,l956;Gleich and Gilbert,l976). Additional factors that are important in snail

population ecology are thought to be rainfall (Carter and Baker, 1997a, b; Shirley et al,

32

CHAPTER 3: POPULATION DYNAMICS

200I; Labaune and Magnin, 2001), relative humidity (Rosenberg et al, 1983; Shirley et al,

2001; Labaune and Magnin, 2001), temperature (Baker, 1988b; Shirley et al,200Ii.

Labaune and Magnin,200I), season (Baker, 1989; Baker et aL,1991), plant type (Cameron

et al, 1980a, b; Baker, 1989; 1992; Sternberg, 2000; Labaune and Magnin, 2001), the

presence of other snail species and previous season's / year's snail count (Baker, 1989).

The suitability of a habitat depends in part on the level of resources (Southwood, 1977).

Despite this, it is difficult to precisely define determinant environmental factors that

explain snail distribution and abundance, and most variables are often inter-related

(Labaune and Magnin, 2001).

It has been suggested that climatic conditions can influence the life-cycle of snails in

Mediterranean climates (Cowie, 7984a, b, c, d; Cain, 1984). Terrestrial molluscs are

extremely sensitive to microclimate (Rollo, 1989). Temperature impacts directly on their

growth rate, movement, incubation period and time to sexual maturity of slugs (Shirley et

al,200l).It is therefore expected that snails would also respond similarly given that both

snails and slugs aÍe exothermic. Temperature can influence the reproduction and

maturation of the snails Bulinus truncates (Bayomy and Joosse, 1987) and Helix aspersa

(Gomot et al, 1989a, b; Jess and Marks, 1998), and the slugs Arion ater (Lewis, 1969b)

and Cepaea nemoralis, C. hortensis, and Arianta arbustorum (Cameron, 1970a)'

Additionally, photoperiod has been shown to affect breeding and egg laying in H. aspersa

(stephens and Stephens, 1966; Bailey, 1981; Enee et al, 1982; Gomot, et al, 1989a, b;

Shrag eT al,1994a, b) B. truncates (Bayomy and Joosse, 1987), Deroceras reticulatum and

Arion distinctus (Hommay et al, 1998) and A. ater (Lewis, 1969b).

JJ


Biological rhyhms of snails have been demonstrated to follow tidal and lunar cycles,

photoperiod and annual seasonal changes (Lewis, 1969a, b; Block et al,1994; Hommay et

al, 1998). Such rhythms provide snails with an internal time reference that allows for the

appropriate amalgamaTion of physiology and behaviour to environmental cycles. (Block et

al, 7994). Abundance of Mediterranean snails may vary greatly from one year to another in

Australian agro-ecosystems. Reasons for this include the availability of food, climatic

extremes (Baker, 1988a), and density dependent interactions such as those mediated

through slime (Butler,1976; Bull et al,1992).

Humidity and rainfall levels have been demonstrated to be important influences on

geographical distribution of land snails (Tattersfield, 1981). For all terestrial molluscs,

water balance is a determinant of population process, as are soil moisture and temperature

(Cook, 1981; Shirley et aL,2001).

Mediterranean habitats are defined as warm to hot, with dry summers and mild, wet

winters with rainfall occurring almost exclusively during the winter months (Nahal, 1981).

In these habitats, both adult and juvenile snails are forced off the ground during summer

since ground temperature can exceed the upper lethal temperature (Cowie, 1985). There

are high rates of mortality in extremely hot summers, even amongst aestivating snails

(Cowie, 1985).

C. virgaÍa produce fewer young per reproducing adult, when at higher densities (Baker,

1996). This same pattern was observed in Cepea nemoralis (Williamson et al, 1977). This

reduced reproduction in dense populations may in part be explained by the smaller size of

adults due to resource limitation and hence decreased fecundity, as suggested for other

34


snails (Baker, 1996). However, the relationship between adult size and fecundity in C.

virgata is at best weak, and not always across the range of adult sizes commonly found in

the field (Baker, 1996). Interference competition for food between adults or the young, or

cannibalism amongst young may help explain the poorer reproduction in dense populations

(Baker, 1996). Density-dependent regulation of fecundity through control of shell growth

rate is considered an important component of the populationdynamics of some species of

snails (Cameron and Carter, 1979; Baker and Hawke, 1991). Regulation may operate

through chemical or behavioural interactions (e.g. in the mucus trails) (Cameron and

Carler, 1979;Danand Bailey, 1982; Bull et al, 1992) and be independent of food supply

(Baker and Hawke, 1991). Laboratory studies of terrestrial gastropods have shown that

populátion density can have an important influence on juvenile growth rate, adult shell size

and fecundity even when excess food is available (Baur, 1988a, b, c; Cameron and Carter,

1979; Reichardt et al, 1985). T. pisana have been observed eating C. virgata under

optimum food availability (Smallridge and Kirby, 1988). Wäreborn (1970) suggested that

carnivory in snails was a means of increasing calcium intake where this is limiting. The

effects have been ascribed to the density of mucus trails, which depresses the activity, and

hence food intake and growth rate, of snails (Cameron and Cafter,7979;Dan and Bailey,

1982).

Certain patch types may disproporlionally influence populations. Therefore, examining the

impacts of these different patches on distribution, abundance and dynamics will highlight

the effects of patchiness (Doak, 2000a). Highest densities in crops are usually found at the

edges as a result of invasions from adjacent habitats (Baker, 1989; Baker et aL,1991). Snail

densities in crops may be high if they were abundant in the particular field the previous

year, if the summer temperatures were mild, or if the field was not burnt prior to sowing

35

CHAPTER 3: POPIILATION DYNAMICS

(Baker, 1939). C. virgata can disperse in autumn and winter fiom relatively sheltered

habitat in roadside vegetation into more exposed agricultural land where they feed and

reproduce. In spring and early summer, the snails may disperse back to roadside vegetation

in search of cool, above-ground sites for aestivation (Baker, 198Sb). Scarcity of mates, and

therefore, decreased fertilisation are considered unlikely to be important factors in

dispersal (Baker, 1988a, d). However, lack of food for the young, due to burning,

harrowing and herbicide use in preparation for planting crops, might be a limiting factor'

physical characteristics that make the soil inappropriate for oviposition or juvenile survival

may also be an ongoing reason for lower adult numbers in crops during the breeding

season.

Heavy autumn rainfalls may enhance oviposition and lead to heavy snail infestations in

spring (Baker, 1989; Carter and Baker,1997a, b). Spring rains encourage invasion of snails

from pastures into adjacent crops (Carter and Baker, 1997a, b). In spring, young snails

from adjacent habitats in which snail numbers are high invade edges of crops. This may be

due to more favourable conditions for reproduction and survival, or a reflection of invasion

from adjacent habitats where the snail numbers are higher or the vegetation is less

favourable (Baker etal,1991; Baker, 1992).In a permanent pasture, the numbers of large

juvenile and adult T. pisana C. acuta and C. virgata are greatest in spring following the

breeding season (Baker and Vogelzang, 1988; Baker, 1989; Carter and Baker, 1997a, b). In

a well-grazed pasture with few tall shady weeds where snails aestivate, population

numbers decrease in summer (Baker, 1989) leaving fewer breeding snails in autumn.

36


3.1.1 Climatic data

Ecologists often think primarily about the mean and variance of a distribution. But many

problems of biological interest concern the extremes in a variable (eg. highest temperature)

rather than its central tendency (Gaines and Denny, 1993). Extreme-value theory (Gaines

and Denny, Igg3) assumes that samples used to empirically generate the estimates of

population density are statistically independent and identically distributed. Yet for many

environmental variables, such as temperature and rainfall, the samples are temporally

correlated, and there are commonly seasonal and long-term trends in the data (Gaines and

Denny, 1993).

The Southern Oscillation Index (SOD is an index of the air mass to the north of Australia

that is highly correlated with rainfall in eastern and northern Australia, as well as countries

around the Pacific and Indian Oceans (McBride and Nicholls, 1983, Maelzer and Zalucki,

2000). The SOI is the difference in atmospheric pressure between Tahiti and Darwin. It has

been measured in Australia since 1852 and is usually expressed in Australia as a mean

monthly value ranging from - 40 to + 40. When the mean is strongly positive, much of

eastern Australia is likely to receive above average rainfall. When strongly negative,

rainfall in the same regions is usually well below average and drought may ensue (Maelzer

and Zaltcki, 2000). The SOI has been used for seasonal climate forecasting around the

world (Allan et al, 1996) and in Australia to forecast weather events which influence

agricultural processes, especially rainfall, the date of the last frost, the number of frosts in a

season, and mean temperatures (Nicholls, 1986;Nicholls et al,1996), and therefore may be

an important tool in forecasting snail population densities. In Australia, the SOI has proven

a useful indicator of crop yields (Hammer et al, l99l; Rosenberg et al, 1983).

JI


Relationships between the SOI and agricultural processes have led to seasonal forecasts

being quantified as climatic risk in models for better production management in a number

of crops (Hammer eT al,I99l; Maelzer andZaÍtcki, 2000).

3.1.2 Statistical models

Forecasting pest abundance, or 'pressure and its timing' is considered central to aspects of

successful integrated pest managernent (Dent, 1991). Phenological models based on insect

physiological time scales have been relatively successful at forecasting the timing of

population peaks (Maelzer and Zahrcki, 2000), and are therefore useful for timing control

measures and sampling snail populations. Forecasting pest pressure is more problematic

because many factors influence abundance (Maelzer and Zahtcki, 2000)' Such predictions

would be useful to determine control measures for the following season. Statistical

regression models can be used to analyse the existing data, and to model population

dynamics. Statistical regression models also highlight gaps in the existing data that can be

used to direct further studies.

There are a number of methods available to build models of pest population ecology' In

recent years, Bayesian methods have been widely used in statistical analyses of agricultural

data (Datta and Smith, 2003). Generalised linear models have been used to model multiple

fixed and random effects and to identify and quantify their existence (Vyn and Hooker,

2002). Linear mixed models are increasingly used to take into account all available

information and deal with correlations between variables (Datta and Smith, 2003; Thiébaut

et aL,2002; Vyn and Hooker, 2002).

38

CHAPTER 3: POPIJLATION DYNAMICS

Aims

Dr. Geoff Baker collected population data for C. virgata, T. pisana and C' acuta from the

yorke Peninsula over l8 years. This data set provided an opportunity to examine a variety

of climatic and non-climatic factors that might be correlated with snail population

densities. The implications of this may be that population densities at given times of the

year may be predicted, based on climate and crop t1pe, thus aiding in better management

ofthese pests.

Specifically, the aims of this chapter were

I. To identi$z the climatic and non-climatic variables that affect the densities of

field populations of C. virgata, T. pisana and C. acuta, and to compare the

variables that influence snail population densities across three field sites on the

Yorke Peninsula, in spring and autumn, and between crops and pastures, based

on 18 years of population data collected by G. Baker'

il. To determine whether the abundance of one species impacts on the abundance

ofanother, and

ilI. To provide an indication of the factors that affect snail population ecology to

farmers to help optimise control measures'

39



Population data were collected for snail species at three sites on the Southern Yorke

Peninsula (SYP) between 1984-2001 by Dr. Geoff Baker (Table 3.1). Raw data were

recorded as snails per 0.25 ri.Datuwere analysed as mean snails p", m'. Snail counts for

each field were analysed separately. Snails 6 mm (greatest shell dimension) and larger

were included in population counts. At the Balgowan (Latitude: S 34'19' 60" Longitude: E

l37o 28'60"; Elevation 1 m) and .Weetulta (Latitude: S 34o 15' 05" Longitude: E I37o 37'

60"; Elevation 116 m) field sites, C. virgata was present. At the Hardwicke Bay field site

(Latitude: S 34"54' 26" Longitude: E I37o27' 18"; Elevation 1 m), C. virgata, T. pisana

and C. acuta were present.

Table 3.1. Sources of population data for C. virgata, C. acuta and T. pisana where

applicable, collected at three sites on the Yorke Peninsula, South Australia.

Site Snail species Years of data Fields Plots / Field

Balgowan

Weetulta

Hardwicke Bay

C. virgata

C. virgata

C. virgata

T. pisana

C. acuta

1984 - 2001

t984 - 2001

1984 - 200r

1984 - 2001

1985 - 2001

5

5

5

5

5

4

4

2

2

2

At the Balgowan site, measurements were taken for both crop and pasture, across four

fields, in autumn and spring. At Weetulta, snail counts were taken across four plots, in

40


autumn and spring, with crop treatments only. Crops at this site'were canola, barley, wheat,

bean, lentils, oats, and peas. Data were analysed by combining all crops. Snails at

Hardwicke Bay were counted in autumn and spring. There was a crop / pasture rotation at

this site. All population counts for each of the sites were taken within two days of each

other.

Long-term reliable climatic data were required to integrate with long-term population data.

Two weather stations provided the weather data for the three sites based on their proximity

to the collection site. The weather station closest to Balgowan and Weetulta is the Maitland

weather station (Latitude: S 34o 22' 60" Longitude: E 137" 40' 0"; Elevation 185 m).

Climatic data collected from the Warooka weather station (Latitude -35" 03'36.2" S;

Longitude I37o 24' 00.3" E; Elevation: 53 m) were used to model Hardwicke Bay data'

Descriptive statistics of the climatic variables found to influence snail populations from the

analyses are provided for Balgowan (Appendix 1), Weetulta (Appendix 2) and Hardwicke

Bay (Appendix 3).

3.2.1 Statistical analysis

Snail population densities and climatic variables were analysed using PROC MIXED (SAS

for Windows; version 5.0.2195 release 8.02 TS level 02M0, SAS Institute, Cary, North

Carolina), which estimates the unknown parameters using normal theory maximum

likelihood or restricted maximum likelihood (Mazumdar et al, 1999). The collected data

can be unbalanced at any level, and higher levels can be added without limit (Suzuki and

Sheu, 1999; Kowalchuk and Keselman, 2001). This procedure offers repeated measure

analysis that accounts for within-subject co-variability (Suzuki and Sheu, 1999i-

4l


Kowalchuk and Keselman,2007; Wolfinger and Chang,2003).It analyses all available

data, and instead of ignoring subjects with missing data, it uses a likelihood-based

estimation method for them (Kowalchuk and Keselman, 2001; SAS Institute, Cùry, North

Carolina). The effects of year were treated as random because inferences were not made

for specific years. The models were fitted using stepwise reduction and Akaike's

Information Criterion (AIC) (Akaike, 1969; Judge et al, 1980; Thiébaut et aL,2002; Doak,

pers comm). AIC can be used to compare models with the same fixed effects, but different

variance structures (Akaike, 1974). The model having the smallest AIC is deemed best'

Terms were progressively dropped from the model and their importance was determined

using the AIC value. The non-significant terms were dropped from the full model. The

remaining significant terms demonstrated those variables that influenced snail population

densities (Kowalchuk and Keselman, 2001).

The MIXED procedure of SAS fits a variety of mixed linear models to data and enables

these fitted models to make statistical inferences about the data (SAS Institute Inc, Cary,

North Carolina, U.S.A). A mixed linear model is a generalization of the standard linear

model used in the generalised linear model (GLM) procedure, the generalization being that

the data are permitted to exhibit correlation and no constant variability (SAS Institute Inc,

Cary, North Carolina, U.S.A). Therefore, the mixed linear model provides the flexibility of

modelling not only the means of the data (as in the standard linear model) but their

variances and covariance's as well (SAS Institute Inc,Cary,North Carolina, U.S'A). There

are two primary assumptions underlying the analyses performed by PROC MIXED. The

data arc normally distributed (Gaussian) and the means (expected values) of the data ate

linear in terms of a certain set of parameters (SAS Institute Inc, Cary, North Carolina,

u.s.A).

42


Non-climatic, temperature and rainfall data were grouped based on their means and

extremes. The SOI was examined as it has been shown to be a useful predictor of insect

numbers in eastern Australia (Maelzer and Zahtcki, 2000). A total of 105 variables were

investigated as factors that could affect the population density of the three snail species.

These variables were classified as non-climatic variables (Table 3.2),temperature variables

(Table 3.3), precipitation and relative humidity variables (Table 3.4), and SOI variables

(Table 3.5). All variables were measured daily with the exception of relative humidity,

which was measured at 9 am and 3 pm (Commonwealth Bureau of Meteorology) and

therefore was analysed as two separate variables. In addition, interactions between most of

the variables were analysed. The snail counts were log transformed (ln (snail count + 1)) to

stabilise variances and satisfu the PROC MIXED assumption of normality'

Table 3.2. Non-climatic variables that were investigated in the mixed model analysis to

determine if they affect seasonal snail population densities'

SiteÏ Snail speciesÏ

SeasonÏ Other snail species I count (ifpresent) (mean / m2)

FieldÏ Other snail species 2 count (if present) (mean I rr?)

Transectl Previous season (same species) snail count (mean / m2)

Plant typel Previous year (same season) snail count (mean / m2)

t categorical or class variables.

43

CHAPTER 3: POPI]LATION DYNAMICS

Table 3.3. Temperature ('C) variables that were investigated in the mixed model analysis

to determine if they affect seasonal snail population densities. 'N.'refers to 'number of .

NB: Summer: December 0l previous yeff - February 28 I 29 Autumn: March 01 - May

3l; Winter: June 0l - August 31; Spring: September 01 - November 30.

Mean maximum annualtemperature

Mean minimum annualtemperature

N. days maximum years

temperature under 15oC

N. days maximum an years

temperature over 25oC

N. days maximum yearstemperature over 35oC

N. days minimum yearstemperature over 3OoC

N. days minimum years

temperature over 20oC

N. days minimum yearstemperature under 20oC

N. days minimum years

temperature under 15oC

N. days minimum yearstemperature under 5oC

Mean maximum summertemperature

N. days in spring maxlmumtemperature 15 "C - 25 "C

Mean minimum summertemperature

N. days in summer maxtemperature over 30

oC

N. days in summermaximum temperature under20"c

N. days in summer mlnlmumtemperature under 15oC

N. days in summermaximum temperatureunder 10oC

Mean maximum autumntemperature

Mean minimum autumntemperature

N. days in autumn maximumtemperature over 30

oC

N. days in autumn maximumtemperature over 20

oC

N. days in autumn maxlmumtemperature under 15

oC

N. days in autumn mintmumtemperature under 15

oC

N. days in spring maxlmumtemperature under 15

oC

N. days in autumn mintmumtemperature under 5

oC

Mean maximum wintertemperature

Mean minimumwintertemperature

N. days in winter maxlmumtemperature over 20

oC

N. days in winter maxlmumtemperature lsoc - 25oC

N. days in winter maxlmumtemperature under 10

oC

N. days in winter minlmumtemperature under 10

oC

N. days in winter mintmumtemperature under 5

oC

Mean maximum springtemperature

Mean minimum sprlngtemperature

N. days in spring maxlmumtemperature over 25

oC

N. days in spring mintmumtemperature over 15

oC

44

CI{APTER 3: POPULATION D\1{AMICS

Table 3.4. Rainfall (mm) and relative humidity (o/o) variables that were investigated in the

mixed model analysis to determine if they affect season snail population densities. NB:

Summer: December 01 previous year - February 28 129 Autumn: March 01 - May 31;

Winter: June 0l - August 3 1; Spring: September 01 - November 30.

Mean monthly rainfall N. days in spring with no December rainfallraln

Total annual rainfall January rainfall Mean annual relative

humidity af 9 am

Previous years total annual February rainfallrainfall

N. days in a given year with March rainfallno precipitation

N. days in a given year with April rainfallover 20 ml precipitation

Summer rainfall May rainfall

Autumn rainfall June rainfall

Winter rainfall July rainfall

Spring rainfall August rainfall

N. days in summer with no September rainfallrainfall

N. days in autumn with norainfall

N. days in winter with norainfall

October rainfall

Mean annual relativehumidity at 3 pm

Mean summer relativehumidity at9 am

Mean summer relativehumidity at 3 pm

Mean autumn relativehumidity at9 am

Mean autumn relativehumidity at 3 pm

Mean winter relativehumidity at9 am

Mean winter relativehumidity at 3 pm

Mean spring relative

humidity at9 am

Mean spring relativehumidity at 3 pm

November rainfall

45


Table 3.5. Southern Oscillation Index variables that were investigated in mixed model

analysis to determine if they affect seasonal snail population densities'

January SOI

February SOI

March SOI

April SOI

May SOI

June SOI

July SOI

August SOI

September SOI

October SOI

November SOI

December SOI

Previous January SOI

Previous February SOI

Previous March SOI

Previous April SOI

Previous May SOI

Previous June SOI

Previous July SOI

Previous August SOI

Previous September SOI

Previous October SOI

Previous November SOI

Previous December SOI

3.3 RESULTS

Population counts collected by G.Baker from 1983-200I are presented for C. virgata at

Balgowan (Table 3.6), Weetulta (Table 3.7) and Hardwicke Bay (Table 3.8). Counts for Z.

pisana (Table 3.9) and C. acuta (Table 3.10) at Hardwicke Bay are also presented.

46


Table 3.6. Mean population counts (snails / m2; of C. virgata (> 6 mm in maximum shell

diameter) at Balgowan, South Australia, for autumn and spring from 1984 through to 2001.

Data collected by G. Baker.

Field A B c

Year Autumn Spring Autumn Spring Autumn spring Autumn Spring

D

1984

1985

1986

1987

1988

1989

1990

t99t

1992

1993

1994

1995

r996

L997

1998

1999

2000

2001

16.80*

0.1 6*

0.1 67

|.72*

o. l6T

1.72*

7.041

4.48*

64.32ï

26.40*

0.64*

2.08t

6.56*

0.167

0.3 *

2e.8ï

24.96*

7.68*

25.28

0.96

5.60

0.48

25.60

2.88

269.92

46.72

645.28

8.50

t.44

47.20

1.92

43.04

3s.70

176.80

90.80

89.92

28.001

2.08*

0.1 6f

7.20*

0.e67

4.64*

8.487

8.00*

t8.24ï

30.08*

e.44ï

r0.24*

r.28*

1.t2ï

1.20*

s2.60I

27.68*

46.24*

203.52

0.64

14.08

r.44

47.36

t2.32

12r.28

28.96

297.12

13.83

2t.76

12.96

r.28

82.24

16.00

t96.40

78.90

234.72

4.48*

0.321

4.80*

0.e6t

a a/l*

10.087

4.48*

6.881

64.00*

2.72ï

0.48*

8.647

27.52*

8.001

21.60*

5.61 x

22.08*

130.08

4.48

74.24

0.16

99.52

7.68

79.52

83.68

102.83

3.04

47.52

t3.28

17 5.84

21.6

6.20

249.1

28.64

Missing data

2.08 e.761

2r.76 2.56*

t.44 6.241

49.28 0.32*

1 1.36 3.s2ï

64.48 6.24*

42.56 0.64*

424.96 14.72*

r4.t7 77.44Ï

5.7 6 7 .84*

13.28 1.44ï

287.84 18.72*

12.32 8.967

163.50 19.00x

13.60 1.80*

477.10 5.28*

32.00 23.36*

* Crop t Pasture. Note. Spring crop is same as autumn crop for each field.

47

CHAPTER 3: POPT]LATION DYNAMICS

Table 3.7. Mean population counts (snails I m2¡ of C. virgata (> 6 mm in maximum shell

diameter) at Weetulta, South Australia, for autumn and spring from 1984 through to 2001.

All counts were conducted in a crop. Data collected by G. Baker'

Field

Year

1987

1989

1992

1995

1997

ABCI)

Autumn Spring Autumn Spring Autumn Spring Autumn Spring

1984 2r.44 s 1.36 3.52 40.32

1985 0.00 6.56 0.00 4.32 9.76

1986 0.00 36.32 0.00 8.64 0.80

Missing data

99.36 0.00

76.80 0.64

3.36 i.60

0.00 0.00

0.00 0.00

0.64 0.00

rt.s2 0.00

r38.24 0.64

t7.28 19.84

42.72 0.64

37 .60 1.76

7 .04 1.12

8.96 2.24

76.30 2.30

4.80 2.20

94.70 0.64

9.92 2.24

t0.72

28.t6

3.52

0.48

1.12

2,40

0.32

4t.12

26.24

s.76

s.60

78.24

0.48

35.20

r 6.80

127.80

13.76

1988 0.48 0.64 0.00 r.28 0.00

0.96 3.04 0.16 3.20 0.48

0.16 6.40 0.00 l.r2 0.16

0.00 8.16 0.00 2.72 2.72

0.32 1.60 0.00 t.r2 3.52

0.96 1.28 2.40 8.64 r.92

0.96 4.12 3.20 8.32 1r.52

1990 0.32 2.24 0.00 5.76 0.00

t99r 0.00 0.48 0.16 0.96 0.00

1993 0.80 12.00 1.92 0.80 63.20

1994 0.00 3.20 0.00 2.56 0.32

1996 0.48 39.52 0.48 r.92 2.56

1998 |.20 9.60 1.00 8.80 1.80

r999 0.30 49.20 1 .00 2r.60 37.80

2000 5.61 132.6 5.28 ll7.90 2.56

2001

48


Tabte 3.8. Mean population counts (snails I m2¡ of C. virgata (> 6 mm in maximum shell

diameter) at Hardwicke Bay, South Australia for autumn and spring from 1984 through to

2001. Data collected by G. Baker.

Field

Year Autumn Spring Autumn Spring

BA

1984

1985

1986

1987

1988

1989

1990

t99r

1992

1993

\994

r 995

1996

1997

1998

1999

2000

2001

2.48*

0.807

0.32*

3.687

2.96*

4.087

18.88*

0.64ï

10.00*

87.847

0.08*

0.481

2.16*

7.28ï

5.20*

e.30f

16.60*

s.681

1.92

54.64

2.72

16.32

2.16

50.96

t2.72

43.s2

rr9.44

2.08

0.08

9.60

4.24

223.52

24.30

70.20

10.80

tt2.40

3.68r

0.00*

0.721

0.244

2.s61

rt.7 6*

o.s6l

1.04*

14.88t

27.20*

o.e6t

3.68*

1r.44ï

3.44*

s.407

10.60*

23.601

2.08*

54.08

0.08

48.32

1.52

s5.68

t6.96

48.80

4.96

274.08

t2.32

5.12

r0.24

30.72

12.16

180.s0

10.40

i 65.30

* Crop t Pasture. Note. Spring crop is same as autumn crop for each field

23.04

49


Table 3.9. Mean population counts (snails t rrf¡ of T. pisana (> 6 mm in maximum shell

diameter) at Hardwicke Bay, South Australia, for autumn and spring from 1984 through to

200I. Data collected by G. Baker.

Field


BA

1984

1985

1986

1987

1988

1989

1990

t99r

1992

1993

r994

1995

1996

1997

1998

1999

2000

2001

3.36*

0.241

0.16*

0.641

12.96*

0.s6t

1.28*

0.007

0.40*

11.68I

10.48*

0.007

0.32+

r.e2ï

1.70*

10.80f

9.40*

0.72ï

3.44

13.44

0.72

24.t6

L44

3.92

1.84

1.60

5.76

169.36

0.40

7.20

2.48

39.92

4.00

180.20

1 8.10

6.80

t.44ï

0.00*

0.641

0.08x

0.321

0.80*

0.087

0.00*

o.e6t

3.60*

r.e2ï

1.04*

r.r2ï

2.16*

2.401

2.70*

18.007

0.48*

68.56

0.00

17.76

0.48

t9.04

4.40

5.36

L36

24.24

47.76

9.60

0.80

28.56

6.r6

114.10

48.40

50.00

* Crop t Pasture. Note. Spring crop is same as autumn crop for each f,ield.

2.00

50


Table 3.10. Mean population counts (snails t rrÎ¡ of C. acuta (> 6 mm in maximum shell

height) at Hardwicke Bay, South Australia, for autumn and spring from 1985 through to

2001 . NB. No data available for 1984. Data collected by G' Baker.

Field


BA

1985

1986

1987

1988

1989

1990

1991

1992

1993

r994

1995

1996

1997

1998

1999

2000

2001

4.48*

o.o8t

4.56*

2.721

1.92*

0.007

r.76*

13.441

27.t2*

0.e67

0.24*

0.321

0.80+

0.607

19.40*

1e4.807

18.08*

76.32

4.24

39.68

0.08

3.r2

0.48

14.64

t2.00

r7.76

0.08

0.80

0.08

6.40

10.10

25.40

51.60

41.12

0.007

7.52+

0.087

r.92*

s.367

0.00*

0.007

70.32*

7.36ï

0.08*

0.241

l.r2*

t.t2ï

1.00*

1.401

5 5.60*

2.087

0.48

1s.44

0.64

9.20

0.24

r.28

0.08

24.08

2.08

0.88

0.40

2.80

0.08

13.90

1 .80

23.8

6.00

* Crop t Pasture. Note. Spring crop is same as autumn crop for each field

51


A global analysis was performed incorporating snail counts from each of the three sites,

Balgowan, Weetulta and Hardwicke Bay. This analysis yielded no significant factors that

influenced snail populations; therefore, separate analyses were performed for each of the

three sites.

Comparisons of the variables that affected snail populations were investigated combining

all field sites. The large variation in the value of the intercept across sites and seasons is

due to the variable population densities at each of these sites. The factors that affected C.

virgata at the Balgowan site were investigated separately in crop and pasture, and in spring

and autumn. The factors that affected C. virgala in crops at the Weetulta site were

investigated separately in autumn and spring. Factors that affecte d C. virgata, C' acuta and

T. pisana at Hardwicke Bay were investigated separately in crop and pasture, for autumn

and spring.

Results shown are variables that were related to snail population numbers for each of the

three sites, for autumn and spring counts, and for crop and pasture counts. Models shown

are derived from the PROC MIXED analysis. Where appropriate, comparisons were made

between species, between sites and across seasons. The models showing fixed effects are

presented in the form:

Log transformed snail count: intercept + fixed effects (variable).

That is, equations show the impact of each variable on the snail count for each treatment

52


3.3.1Cemuella virgøta

Although each model was different, a number of common themes emerged. Pooled across

sites, C. virgata population densities in an autumn crop were associated with current year's

rainfall, previous year's rainfall, the previous year's SOI, and temperatures in summer and

autumn (Table 3.1i). Previous year's rainfall had the greatest influence on the population

densities of C. virgata in a crop at Balgowan in autumn. The number of days in summer

with no rainfall had the greatest association with the snail population densities in Weetulta

in an autumn crop, and March rainfall had the greatest association with C. virgata

population densities at Hardwicke Bay.

No parameters were found to be predictors of C. virgata population densities in an autumn

crop across all sites. There are many inconsistencies in the predictors of population

densities between sites. For example, the impact of the previous spring count was an order

of magnitude higher at Balgowan than at Weetulta. Additionally, previous year's rainfall

was ten times greater at Balgowan that at Hardwicke Bay, and was not a predictor for

Weetulta C. virgata population densities. Previous March SOI had a positive effect on C.

virgata population densities at Balgowan, but a negative association with population at

Weetulta, and no influence on populations at Hardwicke Bay. There were no other

parameters that were predictors of C. virgata population densities shared among sites.

53


Table 3.11. Variables that were associated with C. virgata populations (> 6 mm m

maximum shell diameter), in a crop in autumn at three sites on the Yorke Peninsula, South

Australia from 1984-2001.

Estimate

VariableBalgowan Weetulta Hardwicke Bay

Intercept

Previous spring snail count

Previous year's rainfall

Days in summer with no rain

Mean min autumn temp

Days in summer over 30oC

Days in autumn over 30oC

March rain

Previous February SOI

Previous March SOI

Previous April SOI

- 18.03

0.004

0.1

-0.5

0.03

3.98

0.01

-0.04

-0.1

0.04

-0.03

-136.42

0.01

0.1

0.03

0.03

There \Mere no parameters that were found to be consistent predictors of C. virgata

population densities in a spring crop across the three sites (Table 3.12). However, rainfall

and non-extreme temperatures \Mere associated with these populations in spring. The mean

monthly rainfall had the greatest association with population densities in Balgowan,

however, at Weetulta, the number of days where the minimum temperature was less than

10"C had the greatest positive association with population densities of C. virgata- For C.

54


virgata at Hardwicke Bay, the number of days in winter where the maximum temperature

was between 1OoC and 15oC was had the greatest effect.

Table 3.12. Yariables that were associated with C. virgata populations (> 6 mm m

maximum shell diameter), in a crop in spring at three sites on the Yorke Peninsula, South

Australia from 1 984-2001.

Estimate

VariableBalgowan Weetulta Hardwicke Bay

-3t9Intercept

Mean monthly rainfall

Previous year's rainfall

January rain

April rain

Summer x Autumn rain

-299.8

0.1

0.03

0.02

-0.1

-180.2

0.02

0.1

0.9

0.002

0.04

Days inmaximumunder 20oC

summer wheretemperature was

Days in winter where minimumtemperature was under 10

oC

Days in winter where maximumtemperature was between 10-

150C

Days in spring where maxlmumtemperature was between 15-25OC

C. acuta numbers N/A N/A 0.01

55


There were no common predictors of C. virgata pop:ulation densities across the two sites

(Balgowan and Hardwicke Bay) of autumn or spring populations in pasture (Table 3.13).

C. virgata populations in pasture at Balgowan were most associated with previous year's

spring counts in the autumn, however, by spring, the number of days in winter between

lQoC and 15"C had the biggest effect on the same population. For C. virgata at Hardwicke

Bay in a spring pasture, the number of days in autumn where the maximum temperature

was less thanl5oC was most determining, having a negative association with the

population density for autumn and spring populations. Autumn rain was associated with

this same population the greatest in spring. Taken together the same pattern emerges, as

was seen for C. virgata in crops, with temperature and rainfall shown to be associated with

the densities of C. virgata on the Yorke Peninsula.

56


Table 3.13. Variables that were associated with C. virgata populations (> 6 mm tn

maximum shell diameter), in a pasture at autumn and spring at Balgowan and Hardwicke

Bay on the Yorke Peninsula, South Australia fiom 1984-2001.

Estimate

VariableBalgowan Hardwicke BaY

Autumn Spring Autumn SPring

Intercept -16t.4 -117.8 t04.7 401.5

Previous spring snail count 0.04

Days in summer with no rain -0.08

Days in autumn where maxlmumtemperature was under 15

oC

Days in autumn where maxlmutrltemperature was above 30

oC

Days in winter where maxlmumtemperature was between l0-150C.

March rain

June rain

Autumn rain

Winter x Spring rain

Previous July SOI

0.03

0.05

-0.3

-0.3

-0.02

0.01

0.01

0.0004

0.1

57


3.3.2 Cochlicella acuta

No parameters were found to be consistent predictors of C. acuta populations between

autumn and spring, and between crop and pasture (Table 3.I4). C. acuta in an autumn crop

was most strongly related to the densities of T. pisana. The number of days in summer with

no rain had the greatest association with the same population in spring. The number of

days in summer that had a minimum temperature less than 15oC were associated with the

C. acuta population in a pasture the greatest, whereas it was June rain that affected this

population the most in a spring pasture.

58

CHAPTER 3: POPTILATION DYNAMICS

Table 3.14. Comparison of the variables that were associated with C. acuta (> 6 mm in

maximum shell height) populations in a crop and a pasture in spring and in autumn at

Hardwicke Bay South Australia from 1984-2001.

Estimate

Variable

Autumn

Crop

Spring

Pasture

Autumn Spring

Intercept

February rain

March rain

June rain

September rain


Autumn rain


Days in summer where minimumtemperature was under l5oC

Days in autumn where mlnlmumtemperature was under l5oC

Density of C. virgata

Density of T. pisana

-126.0 -528.5 428.9 76.8

-0.02 0.008

-0.02

-0.03 -0.03

0.01

0.0003 0.0001

-0.01

0.03

-0.03

0.08

0.01

0.05

59


3.3.3 Theba pisanø

No parameters were found to be consistent predictors of T. pisana popula|ions at

Hardwicke Bay across autumn and spring, and in a crop and a pasture (Table 3.15).

However, this is expected as plant habitat varied between crop and pasture, and between

seasons. Additionally, different life-stages of populations would be influenced by different

climatic variables. The number of days in summer where the minimum temperature was

less than 15'C had the greatest (negative) association with autumn crop populations'

Temperature (the number of days in summer where the minimum temperature was less

than 20'C) was still the greatest determinant for the same population densities in the

following spring. For pasture populations of T. pisana, the variable that was associated

with densities the greatest in both autumn and spring was again the number of days in

summer with no rain. It can be seen that T. pisana at Hardwicke Bay was most associated

with temperature and the number of days with no rainfall.

60


Table 3.15. Comparison of the variables that were associated with Z. pisana populations (>

6 mm in maximum shell diameter) in a crop and a pasture for spring and autumn at

Hardwicke Bay South Australia from 1984-2001.

Estimate

Variable

Intercept

March rain

April rain

June rain

July rain



Days in summer where maxlmumtemperature was under 20oC

Days in summer where maxtmumtemperature was over 30

oC

Days in summer where the

minimum temperature was underI 50C

Density of C. virgata

Density of C. acuta

Previous March SOI

Previous December SOI

-14.8 -29.9

-0.02

0.0003 -0.0001

0.12

0.06

-0.96

0.03

0.05

Pasture

Autumn Spring

-209.2 167.0

-0.01 0.02

-0.04

-0.02

0.02 -0.12

0.01

-0.0055

0.05

-0.01

Autumn

Crop

Spring

61


3.4 DISCUSSION

The use of PROC MIXED to investigate the effects of climatic and non-climatic variables

on snail population dynamics had the potential to provide an insight into the factors that

influence snail populations on the Yorke Peninsula, and therefore aid the farmer to

implement control measures against these pest snails based on predicted densities.

However, no consistent predictors of C. virgata population densities at Balgowan,

Weetulta and Hardwick Bay across sites were identified. 'When population densities were

analysed for all sites combined, no parameters were found that could explain the

population densities of C. virga¡a. Additionally, there were many inconsistencies with the

predictors across sites, with some having no shared parameters consistent across sites, and

for others, shared parameters had an effect that were either an order of magnitude different

from another site, or had the opposite affect, i.e. a positive effect at one site, and a negative

effect at another. The parameters that were found to be predictors of snail population

densities at each site were site specific, and therefore were not useful predictors of snail

population densities across the Yorke Peninsula.

There were some factors that complicated the data, and therefore no sensible predictor of

snail population densities can be ascertained from the parameters used:

Firstly, weather data varied between sites and population size may be affected by climate

(yom-Tov, 1970; 1983). Climatic data used were collected from weather stations at some

distance from the collection sites. The distance from the weather stations varied between

sites, and while temperature did not vary greatly, rainfall measurements were site specific,

therefore, climatic data collected ftom weather stations did not give precise conditions for

62


local sites. In addition, the interactions between climate and physical features of a site are

complex and need to be examined at a more local level. Maximum daily temperature and

recent total rainfall and their interaction explained the number of Cepea nemoralis that

climbed trees (Jaremovic and Rollo, 1979). Additionally, the life cycle and activity

patterns of T. pisana arc largely determined by climatic factors including temperature,

relative air humidity and rainfall (Nevo and Bar, 1976).

There have been many investigations into the effect of photoperiod and temperature on

snail reproduction activity (Lüsis, 1966; Price,1979; Sokolove et al, 1983; Gomot et al,

1989a, b). Courtship of many molluscs occurs at night, and it is likely that light may affect

courtship behaviour (Runham, 1983). A lowering of temperature, dew formation and

diurnal activity rhythms may interact with low light intensity to stimulate courtship and

mating (Runham, 1983). Low temperatures (below 16"C) inhibit reproduction in Helix

aspersa,however, the simulation of a long day (18 hr light: 6 hr dark) can compensate for

the inhibitory effects of low temperature (Stephens and Stephens, 1966; Bailey, 1981;

Bride and Gomot, 1989; GomoI et al,l989b; Jess and Marks, 1998).

The SOI has been found to be of limited use in southern Australia for pest forecasting in

the April to October cereal growing season (Maelzer and Zalr¡cki, 2000), which coincides

with the breeding season of C. virgata, T. pisana and C. acuta. However, the SOI tended

to be correlated with snail densities and in cropping systems these forecasts would be

useful for control measures in the next season, such as determining molluscicide budgets,

or making strategic decisions on which crops to plant (Maelzer and Zal'tcki,2000)' The

reason for the previous year's SOI being a predictor of snail population numbers may be

that it is reflecting the previous year's winter temperature and rainfall.

63


Soil types, and the direction that a slope faces, even a slope with a small angle could

influence soil moisture and would interact with rainfall and evaporation, and thus, snail

population densities. Soil moisture has been shown to influence population densities of the

snails D¡sc an cronkhitei and Ettconulus fulvus observed above and below litter surface,

more than temperature or light have (Boag, 1985). Growth rates and mortality of these

snails are greatly affected by temperature (South, 1982). Furthermore, extreme

temperatures and rainfall also influence survival of aestivating snails (Baker, 1988a, c).

Perhaps a weather station at each of the sites would allow for a more robust model to

highlight predictors of snail population densities across sites, and therefore could be used

to develop a better model to predict snail population densities across the southern Yorke

Peninsula.

Secondly,the problems of estimating the abundance of snails are numerous, as no sampling

method is without bias (Bishop, 1977). Population counts were conducted in autumn and

spring. These counts were collected at a calendar time, and not at a biologically meaningful

time, such as a particular time after the first rains, or after the break of the season (See

Section 2.2.2).In order to use snail counts to help predict population densities, counts

could perhaps be conducted after the f,irst significant rainfall event, or at either side of a

management strategy such as burning, baiting or a cultural control. Snail counts could

(time permitting) be collected more frequently and incorporate all age I size-classes'

Ideally, snail counts would be conducted several times a year, however, this would be very

labour intensive and was therefore not practical.

Assumptions in many sampling estimates of snail populations include that all life stages

are equally represented, that there is no differential visibility either because of size or

64


fragility (Boag, Ig82). Juvenile snails can contribute alarge component of the spring snail

population (Baker, 1986; 1988b; 1989; 2002). However, in the current population data set,

juvenile snails are excluded, and therefore not all life stages were represented' Snails that

hatch late in the breeding season may not be picked up in snail counts until the following

autumn. These snails may not breed until later in the following year (if at all), and their

offspring may not be included in snail counts until two years after they hatch. The effects

of control measures used against the snails, such as burning, baiting and tilling are inherent

in the data on which the models were based. Only snails that hatched at the beginning of

the breeding season would be included in the data for the following spring, as the other

juveniles were unlikely to have grown to greater than 6 mm by this time. Other factors

such as soil moisture, soil nutrient content and soil texture (see Chapter 4) that were not

measured may also have been correlated with the population dynamics of C. virgata, C.

acuta and T. pisana.

Thirdly, there are many variables that were not possible to include in the analysis that

would effect snail population densities. It was not possible to include management

practices, such practices may influence snail population densities (many of the

management practices either directly or indirectly alter the snails' habitat and resources).

The interaction between species may also be affected by land management practices. Inter-

and intra-specific snail densities may be regulated through mucus trails (Baker and Hawke,

1991). In addition, food (abundance and quality) is an important component in the

environment of a snail (Butler, 1976). Field distributions of C. virgata and T. pisana are

suggestive that these species compete for resources (Pomeroy and Laws, 1967;Lim and

Jenkins, 1972; Butler and Murphy, 1977; Bull et al, 1992). V/hen studying the

relationships between resources and the snails. it is valuable to identify the nature of any

65

CHAPTER 3: POPIILATION DYNAMICS

resource shortage or limitation that may occur (Butler, 1976). However, the analysis

performed in this chapter was not planned when the data was collected, and therefore the

above mentioned limitations were not identified at the time.

Intensive grazingcan also reduce snail numbers, however, grazing in pastures adjacent to

crops encourages the invasion of the snails into the crops (Baket, 2002)' Continuous

cropping reduces the population density of Mediterranean snails. However, many farmers

include a legume-based pasture in rotations to diversify their income, and also to limit the

development of herbicide resistance in weed species, improve soil structure, increase soil

organic matter and replenish soil nutrients, such as nitrogen (Baker, 2002).

Not only would management practices need to be included in the model, but also the

timing of the snail counts relative to particular management practices. Additionally, the

number and combination of management practices would need to be included. Ideally,

population counts would be taken at a site that had either none or consistent management

practices from year to year. This of course would need to be replicated at various sites

across the Yorke Peninsula in order to have a model that is useful at a broader level that

farmers could use.

Fourthly, Mediterranean snails tend to migrate from pasture (where the population

densities are high) to crop (where the population densities are lower) (Baker, 1988a, c),

and this will confound the analysis. The migration rate between any two populations of the

same species may differ depending on the distances between populations and a number of

population specific characteristics including the type of habitat and the density of the

source population (Akçakaya and Baur, 1996). Dispersal may lead to recolonisation of

66


empty patches by immigration from another population (Akçakaya and Baur, 1996).

Migration factors may confound the analysis, consequently, it is important to consider

whether this migration in influencing the results.

While the limitations in the analysis presented in this chapter are inherent in the statistical

models, the analysis was potentially worthwhile. Had the parameters in the statistical

models beenpredictors of population densities across sites, they could be usedby farmers

to aid in more strategic control measures. However, this was not the case for the reasons

discussed above. Forecasts of high populations may indicate the need for precise and

careful in the management of these snails, while forecasts of low populations may allow

for softer control measures. In addition, suppliers of snail bait could use these models to

predict the demand for future bait, which is beneficial to the supplier as baits have a

limited shelf life, and baits that remain unused would result in a f,rnancial loss to the bait

suppliers. Short to medium term predictions may not be useful for pest management,

because the predictions are made at a local level and cannot substitute for sampling for

decisio n-based control within spec ifi c fields.

67

CHAPTER 4: EFFECT OF SOIL MOISTURE ON BREEDING

CHAPTER IV

THE EFFECT OF'SOIL MOISTURE AND SOIL TYPE ON

THE BREEDING BEHAVIOUR OF CERNUELLA WRGATA

4.1 INTRODUCTION

Although Mollusca originally evolved in a marine environment, the order Pulmonata is

abundant on land, including arid and semi-arid zones (Arad and Avivi, 1998). The

distribution pattern of each species and its microhabitat is related to its ability to cope with

desiccating conditions (Arad and Avivi, 1998). In fact, terrestrial molluscan diversity and

abundance are correlated with soil moisture (Macintosh et al, 2002). Water conservation is

essential for adaptation of land snails to the terrestrial environment (Asami, 1993a, b),

including their breeding behaviour.

Godan (1983) described five distinguishable phases in the reproductive cycle of terrestrial

gastropods: courtship and copulation, nest building, egg-laying, and the development of

embryos prior to hatching, and the development of embryos into adults. Nest building, egg-

laying, the development of the embryos and the hatching of juvenile snails can all take

place in the soil. All snails require calcium for egg development and snail hatchlings

require available calcium for their shell development (Burch, 1960). The physical

properties of different soil types are important in soil moisture retention (Leeper and Uren,

68

CHAPTER4: EFFECT OF SOIL MOISTURE ON BREEDING

1995). Thus, not only are the ftequency and intensity of rainfall events important, but the

soil type and its ability to hold water affect the breeding behaviour of snails.

The role of environment is central for sexual reproduction (Schrag and Read, 1992).

Mediterranean snails in southern Australia mate after late summer I early autumn rains

(Baker, 1936). In Mediterranean climates including Israel and southern Australia, egg-

laying begins several days after mating providing that the rain continues (Avidov and

Harpaz,1969; Baker, 1986). Wet weather in early autumn allows earlier breeding by adult

snails. This may lead to greater oviposition and I or enhanced survival of hatchlings

(Baker, 1996). Development to maturitytakes about one year on irrigated land, while on

non-irrigated land development takes about two years, suggesting that population increase

is largely dependent upon moisture (Avidov and Harpaz, 1969). In very wet winters,

particularly at the beginning of the winter season, most eggs develop normally in the soil

and the resulting population increase is considerable. The eggs absorb moisture from the

soil, swell, and hatch 2-3 weeks later (Avidov and Harpaz, 1969). Conversely, when there

is little precipitation and the upper soil horizons dry out, oviposition activity is low, and

eggs desiccate and die (Avidov andHarpaz,1969).

It is well established that moisture affects the breeding, development and survival of

terrestrial molluscs. However, the relationship between breeding behaviour of C. virgata

and soil type and soil moisture has not been investigated. A laboratory experiment was

conducted in which the breeding behaviour of C. virgata was studied in two soil types at

five different soil moisture levels, ranging from dry to saturation.

69

CI{APTER 4: EFFECT OF SOIL MOISTURE ON BREEDING

Specifically, the aims of this chapter were

I. To determine whether soil type has an affect on the egg laying of C. virgata,

and

To determine the effect of soil moisture on egg deposition by C. virgata.il.

70

CHAPTER 4I EFFECT OF SOIL MOISTURE ON BREEDING


4.2.1 Soil moisture retention culryes

Two soils were used in this experiment, a calcareous soil and a non-calcareous soil. The

calcareous soil (YPS) was collected from Minlaton on the Yorke Peninsula, South

Australia (Latitude: -34o 47' 37.9" S;Longitude: l37o 33' 43.9" E; Elevation: 32 m)' It had

a pH of 8.3 and a calcium content level (total calcium) of 5800 ppm. Calcium content was

measured with the following procedure: 100mg of soil was digested with 7 ml of t nittic I

perchloric acid mixture (6:1) at 150oC. At the end of the digest the sample was diluted to

50 ml with water. The calcium was then measured by atomic absorption. The non-

calcareous soil (MNS) was collected from Georgetown in the mid-north of South Australia

(Latitude: -33o 36',0.8" S; Longitude: 138" 39' 50" E,; Elevation: 273 m). It was a red-

brown earth, had a pH of 6.4 and no measurable calcium was detected.

Soil water retention curves show the relationship between soil water content and soil water

availability (matric suction potential) for soil during a drying phase, and are useful

indicators of water retention by soil (Topp et al, 1993). Water retention curves (Figure 4.1)

for the two soils were measured in the laboratory under well-controlled conditions, using

the pressure plate technique (Klute, 1986). The water contents for each soil type used in

this experiment were calculated according to the measured retention curves.

'11

FC

S

I0.5

0.4

Etctt

Ë 0'3oÊoob 0.2G

=

CHAPTER4: EFFECT OF SOIL MOISTURE ON BREEDING

MP

PWP

10tUatric suction (m)

1000

0.1

0.0

0.1

Figure 4.1. Water retention curve for the calcareous - and the non-calcareous --

soils. Matric suction for saturation (S) is 0.3 m; field-capacity (FC) is 1 m; mid point

(MP) is 10 m; and permanent wilting-point (PWP) is 150 m.

1 100

72

CHAPTER4:EFFECT OF SOIL MOISTLIRE ON BREEDING

4.2.2 Snail collection and short-term maintenance of the culture

Adult C. virgata were collected from the roadside adjacent to a field at Warooka, South

Australia (Section 2.2.I). The soil at the Warooka field site where the snails were collected

was an alkaline, calcareous, sandy loam.

Snails were collected and transported according to Section 2.4. Prior to use in the

experiments, snails were kept in the laboratory in these plastic containers. A 20 cm x 12

cm rectangle was cut out of the lids and replaced with 2 mm nylon mesh to allow air

exchange. A calcareous sand-loam soil mix, with apH of 8.0, composed of Mt Compass

Grey Sand with Calcium Hydroxide and Agriculture Lime, was placed into the bottom of

each of the containers to a depth of approximately 50 mm and kept moist. Twenty to thirty

snails were then added to each container, with a layer of wet paper towel covering the soil

and three slices of carrot per container. Snails were kept in a constant temperature room at

16"C with a photoperiod of 12 h light - 12 h dark for fourteen days. The snails were

sprayed with water daily and carrot was replaced every three to four days as required, as

starvation has been shown to inhibit egg laying in other snails (Ter Maat et al,1982).

4.2.3 Exp erimental set-u P

plastic 200 ml vials (75 mm x 80 mm) were used as experimental arenas in this

experiment. The lids of the vials had a 5 mm diameter hole lightly packed with cotton wool

to allow airflow. Vials contained either the YPS or MNS t1pes. There were five soil

moisture treatments: 1. No-water; 2. Permanent wilting-point; 3. Mid-point;4. Field-

capac\ty; and 5. Saturation (Table 4.l). Each treatment was replicated 10 times.

t)

CHAPTER4:EFFECT OF SOIL MOISTURE ON BREEDING

Table 4.1. Preparation of the soil moisture treatments for the calcareous and non-

calcareous soil. Water content calculated from Soil Moisture Retention Curve'

YPS

Dry soil

weight:

150 g

MNS

Dry soil

weight:

r20 g

Saturation

Field-capacity

Mid-point

Wilting-point

No water

Water content

0.40

0.30

0.20

0.14

0.00

Moisture

treatment (e/e)

Vy'ater added (g) Final weight (g)

of soil

Saturation 0.40

Field-capacity 0.31

Mid-point 0.21

Wilting-point 0.15

No water 0.00

60.00

45.00

30.00

21.00

0.00

48.00

37.20

25.20

18.00

0.00

210

t95

180

t7t

150

168

157.2

145.2

138

120

74

CHAPTER 4: EFFECT OF SOIL MOISTLIRE ON BREEDING

Two adult snails (greatest shell dimension ranged ftom 12-15 mm) were randomly

assigned to each vial. The vials were arranged randomly in a growth cabinet under

controlled light and temperature conditions with temperature range of 8"C (night) to 16oC

(day), and a 12 hr light - 12l.Í dark photoperiod. Relative humidity in the growth cabinet

was set at 80 o/o. Soil moisture treatments were maintained daily by weighing and adding

water as required. Snails were fed a fresh piece of carrot every three to four days.

Vials were searched for new egg clusters daily. Fine forceps were used to search for egg

clusters. Egg clusters were not removed, but their positions were recorded. The experiment

concluded 59 days after the first egg cluster was laid: this was 72 days from when the

snails were added to the vials.

4.2.4 Statistical analysis

Data were analysed using Analysis of Variance and survival analysis (JMP version 4.02

SAS Institute Inc, Cary, North Carolina, U.S.A).

Kaplan-Meier survival analysis was used to determine if there were significant differences

between treatments in time to first egg cluster being laid. A steep slope in this analysis

indicated a greater tendency for snail pairs to lay an egg cluster. Survival curves that did

not touch the time axis were a result of snail pairs in a treatment not laying egg clusters

during the course of the experiment, i.e. the curves had 'censored' data points. The analysis

included a Log-rank and a Wilcoxon test, which examined the differences between the

culves for longer and shorter egg laying times, respectively. One-way ANOVA was used

for analysis of total egg cluster numbers.

75


4.3 RESULTS

The soil moisture retention curves (Figure 4.1) for the YPS and MNS were very similar.

The two soils therefore, have similar abilities to hold water. This provided an opportunity

to determine factors that affect C. virgafa's breeding behaviour across different soil types,

but with similar water holding capacities. Across soil type and moisture treatments, there

'was no mortality among snail pairs.

4.3.1 Soil type

The tendency of C. virgara to lay their first egg cluster was higher in the MNS than the

YPS (Figure 4.2). No snails laid an egg cluster in the no-water treatment, and therefore

these data were not included in Figure 4.2. At the conclusion of the experiment, 80 o/o of

the snail pairs in the MNS had laid an egg cluster, compared to 52.5 % of snail pairs in the

YPS. (Figure 4.2). The overall mean number of days that it took the snails in the MNS to

lay their first egg cluster was 19.5 days, compared to 31.3 days for the snails in the YPS.

4.3.2 Soil moisture

In the MNS, soil moisture treatment had a significant effect on the number of snail pairs

that laid egg clusters (Figure 4.3).Data from all soil moistures were analysed separately'

However, there was no significant difference between the time taken and number of snail

pairs that laid their first egg cluster between the saturation treatment and the field-capacity

treatment (data not shown), therefore, these two treatments were combined for this

analysis. All snail pairs in the saturation + field-capacity treatment laid eggs by the

76

CHAPTER 4: EFFECT OF SOIL MOISTLIRE ON BREEDING

conclusion of the experiment, v/ith a mean time to the first egg cluster of 7.4 days.

Similarly, all snail pairs in the mid-point treatment laid eggs by the end of the experiment,

but the mean time to the first egg cluster was nearly 27 days.In the wilting-point treatment,

only 20 o/o of the snail pairs laid any eggs over the course of the experiment.

77

1

I

CTIAPTER4: EFFECT OF SOIL MOISTURE ON BREEDING

Mean time tofirst cluster

ËooCL

oo

othL'õct

otr.t,

otrooIE

lL

0.

0

0.7

.8

0.6

0.5

.4

.3

.2

.1

0

0

0

0

0

1Mean time tofirst cluster

200 10 30

Time (days)

40 50 60

Figure 4.2. Effect of soil type on the time taken until the first egg cluster was laid by C.

virgata irrespective of soil moisture treatment. Relationship calculated using Kaplan-Meier

analysis. n : 100. MNS -; YPS -. Log-rank test, f: 10.12;ldf, P : 0.0015. Wilcoxon

f : t1.02, I df, p : 0.0009. NB. Data from the no-water treatment were excluded from

the analysis since no eggs were laid in this treatment.

78

CIIAPTER4: EFFECT OF SOIL MOISTTJRE ON BREEDING

In the YPS, snails in the saturation, field-capacity and mid-point treatments laid egg

clusters (Figure a.$.By the end of the experiment, irrespective of water treatment, not all

snail pairs had laid an egg cluster. In the YPS there were significant differences in time to

first egg cluster among the treatments, with decreased moisture associated with longer

times for egg deposition.

4.3.3 Total egg production

There was a significant effect of soil moisture level (P < 0.0001), irrespective of soil t1pe,

and a significant effect of soil type (P : 0.0004), irrespective of soil moisture (Figure 4.5),

on the total number of egg clusters laid over the course of the experiment. However, there

\ilas no two-way interaction between soil moisturo and soil type (Table 4'2) on total

oviposition.

79


0.9

0 10 20 40 50 60

Figure 4.3. Effect of soil moisture treatments on the MNS on time taken until the fnst egg

cluster was laid by C. virgata. Saturation * f,reld-capaclty - ll: 20; Mid-point - n: 10;

Wilting-point - n: 10. Relationship calculated using Kaplan-Meier analysis' Log-rank

f: ll.lO, 2 dfP < 0.0001. Wilcoxon f : Zt.ZZ, 2 df,P < 0.0001. NB. Data from the no-

water treatment were excluded from the analysis since no eggs were laid in this treatment.

0Ët,oCL'too

ooGct

IEtrØ

otroIJ(E

lr

1

.8

0.7

0.6

.5

.4

0

0

0

0

0.3

.2

1

0

30

Time (days)

1Mean timeto firstcluster

1Meantime tofirstcluster

80

1


Mean timeto firstcluster

I0.

ËI os.go 0.7o

E 0.6o'õ 0.5CL

=E o.¿Ø

3 oto

2 o.zl¡.

Meantimeto firstcluster

10

Mean timeto firstcluster

20

I

I

0 1

0

0 30

Time (days)

40 50 60

Figure 4.4. Effect of soil moisture on the YPS on the time taken until the first egg cluster

was laid by c. virgata' saturation - Field-capacity - Mid-point -' Relationship

calculated using Kaplan-Meier analysis. n:50. Log-rank f : ZZ.l3,2 df, P < 0.0001;

Wilcoxon "f : ZZ.ZI,2 df, P < 0.0001. NB. Data from the wilting point and no-water

treatments were excluded from the analysis since no eggs were laid in these treatments.

81

CIIAPTER4: EFFECT OF SOIL MOISTURE ON BREEDING

Table 4.2. One-way ANOVA table showing the effect of soil moisture and soil type on the

total number of eggs laid over the duration of the experiment. There was no two-way

interaction between soil moisture and soil type on total number of egg clusters laid.

Source DF Sum of Mean F-ratio P>F

Squares Square

Model

Soil moisture

Soil type

Error

185.08

167.44

17.64

94 r27.96

37.02 27.195

4

1

<0.0001

30.75

t2.96

<0.0001

0.0004

1.36

Regardless of soil moisture content, C. virgata snail pairs in the MNS laid a significantly

greater total number of egg clusters over the duration of the experiment than those snail

pairs in the YPS treatment (Figure 4.5), except the no-water treatment in which no egg

clusters were laid.

82

CTIAPTER4: EFFECT OF SOIL MOISTTIRE ON BREEDING

5

0

No water Wilting point Mid point Field capacity Saturation

Soil moisture

Figure 4.5. Total number of egg clusters laid over the course of the experiment in each soil

moisture treatment for MNS - and YPS -. Values are means */- standard errors.

pga!ooEE)Etorú

ot-

4

3

2

1

83

CHAPTER4:EFFECT OF SOIL MOISTURE ON BREEDING

4.4 DISCUSSION

The overall distribution of C. virgara is closely related to the availability of calcium (for

example, the alkaline soils of the Yorke Peninsula) and is strongly corelated with the

amount of organic matter and moisture in the soil (Pomeroy, 1967). The breeding

behaviour of C. virgata was significantly affected by both soil type and moisture content.

Soil type had a significant effect on both the total number of eggs laid, and the tendency to

lay the first egg. Hatchling snails emerged from each of the egg clusters. Given the

requirement for calcium (Burch, i960; Pomeroy, 1967; Thomas et al, 1975), the survival

of snail hatchlings on the YPS would potentially be greater than on the MNS, especially as

the MNS had no measurable calcium. Presumably C. virgata adults had sufficient calcium

reserves for egg development and deposition, given that the snails were collected from an

area with calcareous soils. However, it is not known whether this would have had an effect

on the breeding behaviour of C. virgata. Calcittm was found to be the most important

factor on the distribution of Cochlicopa lubrica, Vertigo pygmaea, and Carychium

tridentatum (Ondina et al, 1998). Tolerance to acidic soils has been reported for other snail

species (Bishop, 1977; Cameron et al, 1980; Hermida et al, 1995). Furthermore, the role of

other soil parameters such as soil physical properties (Outerio et al, 1993; Hermida et al,

1995) and availabilities of nutrients such as calcium (Atkins and Leebour 7923, Boycott,

1934; Camercn, 7973; Outerio eT al, 1993; Baur et al, 1994; Hermida et al, 1995; Ondina et

al, 1998), aluminium (Ondina et al, 1998), nitrogen (Locher and Baur, 2000a, b) and

magnesium (Gomot et al, 1989a, b; Graveland and van der Wal, 1996; Ondina et al, 1998),

or water (see below) (Hermida et al, 1995; Atkins and Leebour, 1923; Boycott, 1934;

Cameron, 1973) on the breeding behaviour of C. virgata should be the focus of further

research. The preference for the Mid-north soil type for egg laying by C. virgata is

84

CHAPTER4:EFFECT OF SOIL MOISTLIRE ON BREEDING

especially intriguing as the snails were collected from a soil type similar to the YPS, and

not the MNS. C. virgata is abundant on the Yorke Peninsula, but is scarce in the Mid-north

of South Australia,

Soil type is clearly an important factor in the breeding behaviour of C. virgata; however, it

remains unclear which soil characteristics are important. As the soil retention curves of the

two test soils were virtually the same, soil moisture per se does not explain the differing

copulation and egg laying of the snails on the two soil t1pes. If the important factor were

available calcium, it would be expected that more egg clusters would be laid on the YPS,

but this was not the case. Other soil type variables that could affect the breeding behaviour

of C. virgata might include soil texture (Outerio et al, 1993; Hermida et al, 1995; Leeper

and Uren, 1995) or soil chemistry (Atkins and Leebour 1923, Boycott, 1934; Cameron,

1973; Gomot et al, 1989a, b; Outerio et aL,7993; Baur et al, 1994; Hermida et aL,7995;

Graveland and van der Wal, 1996; Ondina eT al, 1998; Locher and Baur, 2000a, b)' Baker

and Hawke (1990) suggested that physical characteristics of soils under crops might be

inappropriate for oviposition or the survival of the young. Pomeroy (1966) found that C'

virgata was more abundant where the soils contained considerable organic matter, but it is

not known if this affected either egg deposition and juvenile survival, or both' Oviposition

behaviour of C. virgata appears to be influenced by the nature of the organic matter in the

soil since snails would not deposit eggs in soil from the Yorke Peninsula that was heat

sterilised (autoclaved for 40 minutes aT I20oC), but did so in the non-heat sterilised soil

fromthe same site (S. Charwat and K. Daviespers comm). Furtherresearch is necessaryto

identi$r the soil characteristics that influence egg-laying.

85


Water balance is a determinant of population processes for terrestrial molluscs (Shirley et

al, 2001). In this study, it was shown that soil moisture influenced the total number of egg

clusters laid and the time taken to the first egg-laying event. Across all soil moisture levels,

the mean time for the first egg deposited in the MNS was approximately 66 o/o of that in the

ypS. FurtheÍnore, the snails laid their egg clusters at a higher rate as the soil moisture

level increased. It is likely that if the soil flooded, no eggs would be deposited (Carne,

unpublished results). As expected, there was no difference between the no-water treatment

and the wilting point treatment, as snails require water to be active (Cowie, 1985; Arad,

1990), and there was insufficient moisture in these treatments to initiate breeding.

Egg clusters are resistant to a degree of desiccation. In dry conditions, embryos in the

centre of the cluster would have a better chance of survival than those on the outside.

Bayne (1969) showed that embryos of Deroceras reticulatum survived 60-80 %

desiccation. Since embryos may take several months to develop, it is possible that some

would be able to survive exposure to drying conditions. Therefore the delay in egg laying

by those snails in the mid-point treatment could result from an inhibition of egg-laying by

lowered soil moisture.

Snails in the treatment with no-water in both soil types began aestivation, on the side of the

vials, almost immediately after being placed into the vial. This is a survival strategy against

desiccation, because even when food is present, it is not available to snails unless the

ground is sufhciently moist to permit activity (Pomeroy, 1969, Cowie, 1984b, c)'

This study has shown That C. virgata lay eggs more frequently in moist soils. Knowledge

of how these snails behave in different soil types and moisture levels is essential to

86


determine and implement more appropriate control methods. This study may also help to

predict egg-laying behaviour in a wet season compared with a dry season, and therefore the

risk of crop contamination in spring. Knowledge of the factors that stimulate and

encourage egg-laying could be used to optimise the timing of baiting in order to control the

snails before egg laying.

87

CHAPTER 5: DISPERSAL

CHAPTER V

DISPERSAL OF ADULT AND JUVENILE CERNUELLA

WRGATA AND COCHLICELLA AC(TTA ON THE YORKE

PENINSULA

5.1 INTRODUCTION

5.1.1 Dispersal

Dispersal is the redistribution of individuals in a population that leads to the spatial spread

of organisms (Turchin, 1997; Nathan, 2001). It is a fundamental biological process that

operates at multiple temporal and spatial scales. Dispersal has implications for the survival'

growth and reproduction of individuals, and the composition, structure and dynamics of

populations and communities (Kareiva, 1990; Reeve, 1990; Taylor, 1990; Harrison, 1991;

Doak et al, 1992; Kuussaari eI al, l996,Ims and Yoccoz,1997, Stacey eI aL,1997; Nathan'

2001). It affects the genetic structure of a population (through immigration and emigration)

and influences demographic processes within the population (Kleewein, 1999). Dispersal is

also important for the colonisation of new habitats. Movement determines how individuals

encounter features of their environments (Wiens et aI,7993a). The most fundamental task

in studying dispersal is describing the distribution that it generates (Clark et al, 2001l'

Nathan, 2001). The ability of an organism to move through a landscape is determined by

the interaction between its innate movement behaviour and the landscape structure

88


(Goodwin and Fahrig, 2002). Dispersal behaviours of organisms have been the subject of

extensive ecological investigation from both the theoretical and experimental perspectives'

Short-range dispersal is certainly as important biologically as long-range dispersal (Byrne

et al, 2002). Studying diffusion and dispersal behaviour requires actively tracking the

movements of individuals (Fagan, 1997).

The dispersal behaviour of pest invertebrates is an important aspect of their life cycle and

has implications for where populations will be exerting pressure on crop production (Byrne

et aI,2002). However, the importance of dispersal in invertebrate population dlmamics has

been largely ignored when formulating integrated pest management (IPM) plograms

(Byrne et al, 2002). Invertebrate dispersal is often in response to both biotic and abiotic

factors that promote migratory behaviour (Byrne et aI,2002)'

Because of their sedentary nature and high cost of locomotion, snails are characterised by

low dispersal ability (Arnaud et al, 1999). Factors that influence snail movement may

include season and weather including temperature and rainfall, habitat preference,

anthropomorphic activities including agricultural practices, and competition for resources

(Baker, 1986; 1988d;2002). Land snails typically live in discrete populations, often

isolated fiom one another. Snails can move between patches by active or passive dispersal

(Akçakaya and Baur, 1996) and are more likely to be active and move greater distances on

rainy nights than dry nights (Murphy, 2002).Increased activity has also been associated

with humid conditions or darkness (Bailey, 1989; Murphy,2002). Movement may also be

initiated by changes in physical conditions, such as temperature, relative humidity and

precipitation (Dainton, 1954a, b; Karlin, 1961; Welby, 1964; Dainton and Wright, 1985;

Bailey, 1989; Staikou et al, 1989; Rollo, l99I). Dispersal is likely to be a general

89


behavioural pattern in many land snails species, assisting to minimise evaporative loss.

Furthermore, olfactory cues may be involved in homing (Edelstam and Palmer, 1950), or

orientationto a variety of stimuli (Chase and Croll, 1981) such as food (Croll and Chase,

t977;1980).

5.1.2 Studying dispersal

There are limitations to laboratory data, which are collected under artificial conditions

where many external factors have been reduced or eliminated, and therefore are easier to

interpret than field data. Laboratory conditions impose limits on an organism's natural

movement and behaviour (Turchin, 1991). Therefore the collection of field data reported

here provided information on the movement and behaviour of the snails in their natural

environment.

Central to dispersal studies is the selection of an optimal release size (number of

individuals released). An optimal release size in this thesis refers to the smallest release

size that best represents the dispersal of C. virgala. Evidence from several studies suggests

that interference is common amongst land snails (Cain and Currey, 1968, Ooosterhoff,

1977; Cameron and Carter, 7979:Dan and Bailey,1982; Baur, 1988b)' However, these

studies have conflicting results, with interference being shown to affect snail activity

negatively (Cameron and Catlet, 1979; Dan and Bailey, 1982; Baur, 1988b) or positively

(Cain and Curey, 1968, Ooosterhofl 1977)'

There are two types of interference competition in molluscs: direct aggression among

individuals and indirect interference through mucous deposition (Baur, 1992). An example

90


of indirect interference is that both pheromones in the snail's mucus and mucous trails

themselves can make food unpalatable (Cameron and Carter,7979 Dan and Bailey,1982i'

Bull et al,1992).

The density of a snail population can influence the rate of dispersal. In land snail

populations of the genera Arianta and. Cepaea, dispersal has been found to be density

dependent (Greenwood, 1974; Baur, 1988a, b; Baur and Baur, 1993)' Crowding has been

shown to increase the dispersalrate of land snails (Cain and Curey, 1968; Oosterhoff,

1977), decrease it (Greenwood, I974) or have no effect (Cameron and Williamson,1977;

Baker 1988b; Ba.çrr,1992), so the impact of densityremains unclear. Interactions between

biotic and abiotic factors influence the rate of dispersal (Baker, 1988b).

A path is defined as the complete spatio-temporal record of a followed organism, from the

beginning to the end of observations (Turchin, 1998). Eachpath is represented by a series

of straight-line moves. A move is defined as the displacement between two consecutive

stopping points. The usual method for digitising such paths is to record the spatial

coordinates of the organism(s) at regular time intervals and to connect the successive

positions with straight lines (Kareiva and Shigesada, 1983). Such displacements are

referred to as 'steps' (Turchin, 1997).

Tracking the movement of snails in their natural habitat is essential for understanding their

basic biolo gy and demography (Hagler and Jackson, 2001). Methods to track the

movement of snails include mark-release-recapture, cardboard trapping and soil sampling

(Oggier et al, 1998) among others. In order to track a known individual or population of

snails, they need to be marked.

9l


Animal marking dates back to at least 218 8.C., when ornithologists distinguished

ownership by banding (Hagler and Jackson, 2001). Inveftebrate marking for scientific

studies began around 1920, when researchers used paints, dye and stains (Hagler and

Jackson, 2001). A wide variety of markers have since been used to assess invertebrate

population dynamics and dispersal (Edelstam and Palmer, 1950). Ideally, markers should

be environmentally safe (Mclntosh, 1999; Hagler and Jackson,2001), cost effective, easy

to apply, quick drying (if applicable), available in several highly visible colours (Mclntosh,

l99g), and easy to use. Above all, they should minimise interference with the

invertebrate's 'normal' biology (Mclntosh, 1999; Hagler and Jackson, 2001). Although

using paints or inks for marking individual snails is often tedious and time consuming

(Hagler and Jackson, 2001), it provides the best method for mark-release-recapture studies

of terrestrial snails. Baker (1988b) found that dispersal of C. virgata and T. pisana was not

influenced by the paint he used for marking, nor was displacement or crowding at the

release point. Oggier et al, (1998) found that marking Helix itala with car lacquer did not

affect their dispersal behaviour.

Marking methods differ in the extent of disturbance to the snails, damage to the vegetation,

weather dependence and in the spatial scale at which they can be applied (Oggier et al,

1998). An alternative method fortracking the movement of individual snails is to use the

spool-and-line tracking technique, in which a spool of thread is attached to the snail, and

unwinds from the inside as the snail moves around, leaving a trail of thread which can be

followed (Murphy, 2002). This method however may affect movement patterns of the

snail. Radio transmitters have been used to study the foraging range of Helix aspersa

92


(Bailey, 1989). Harmonic radars attached to land snails, have been used to study snail

movement in New Zealand (Lovei eI al, 1997)'

5.1.2.1 M ark-release-recapture

Mark-release-recapture (MRR) has been used extensively in dispersal studies (Turchin and

Thoeny, 1993; Jones et al, 1980; Rudd and McEvoy, 1996; Oggier et a1,1998; Cronin et al,

200I; Goodwin and Fahrig, 2002 and others). MRR can be extended to the marking of

individuals. The advantage of individual MRR (IMRR) is the ability to obtain a time

sequence of spatial positions of an individual (Turchin, 1997) rather than only the

population as a whole. Spatial behaviour of individuals is a key component to

understanding the population dynamics of organisms (Turchin, 1991). IMRR may be most

suitable for snails of medium to large size as these snails are easier to find than small

individuals (Oggier et al, 1998). However, additional handling can occur with IMRR,

which may significantly affect snail dispersal at the release point (Paul,1978)'

93


The aims of this chapter were

I. To establish and test mass-mark-release-recapture and individual-mark-release-

recapture methods for C. virgata and C. acuta, and from this, determine an optimal

release size for C. virgata and C. acula for MRR studies,

il. To conduct MMRR trials to determine how snail displacement changes at different

times of the year in different crops with fire treatments,

ilI. To compare individual dispersal behaviour of C. virgata and C. acuta in crops and

medic,

IV. To determine whether the movement of C. virgata and C. acuta can be explained by

simple diffusion, or whether their movement is biased, and

V. To compare individual movements of adult and juvenile C. vìrgata and C. acuta

using IMRR.

Preliminary MRR field experiments using 100 C. virgata and 100 C. acuta were conducted

with displacement being measured one and seven days after release (data not shown).

While the data showed that the snails moved in a biased direction, it provided little

information on how far the snails were moving each day, and what factors, particularly

climatic, were driving the dispersal.

Displacement trials using mass-mark-release-recapture (MMRR) were conducted the

following season (2001), which measured snail movement on two consecutive days on

either burnt or unburnt fields. Burning is a common agricultural practice on the Yorke

Peninsula to decrease snail populations. When fields are not burnt, then it is referred to as

94


stubble retention. The two land preparation practices, burning and stubble retentton were

compared, as in some years, the soil is not burnt, but when snail numbers are high, fields

are often burnt prior to seeding. This comparison of movement on the two land preparation

practices provided more of an insight into the factors that influence the movement of snails

and is discussed in this chapter.

In the 2002 field season, individual-mark-release-recapture (IMRR) dispersal trials were

conducted over five days to derive information on the factors that drive individual

movement. Turning angles, heading direction and distance moved were measured, and are

the focus of this chapter. Mean net squared displacement (R2,) aftet n moves was

calculated as it provides a convenient and theoretically sound parameter with which to

quantify dispersal (Skellam, 1973; Kareiva and Shigesada, 19S3). Comparing theoretical

and actual displacement provides an overall test of appropriateness of the Correlated

Random Walk model (Turchin, 1998). A random walk is a mathematical description of the

probabilistic movement process underlying trajectories of individual organisms (Turchin,

1998). It is assumed that movement is driven by both stochastic and deterministic factors.

95



5.2.1 Mark-release-recapture: optimal release size

The following experiment was conducted in order to determine an appropriate release size

for further MMRR and IMRR studies.

Adult C. virgata and C. acuta were collected from the Warooka field site (Section 2'2.I).

Snails of each species were sorted into three groups of eight, 16,40 and 100. Groups of C.

virgata were marked with yellow, blue, pink or orange spray paint (White Knite@,

Australia). Groups of C. acuta were hand painted with either red, pink or orange nail

lacquer (Catwalk@, Australia) as the umbilicus of C. acuta was easily sealed when using

spray paint. All snails were transported in plastic boxes to the release site (Section2.4).

The groups were released at the Minlaton field site, into barley Qlordeum vulgare L.,

Sloop variety) seeded in unburnt soil at distances of greater than 10 m from each other.

The barley plants were 4 cm high, and planted in rows at a distance of 24 cm from each

other. For all releases, the local snail density was lower than eight snails / m2. There were

three replicates of each release size treatment. Snails were released within eight hours of

being collected. Release points were randomly chosen throughout the treatment plots, and

marked with survey flags. Snails were released within a 40 m x 60 m area, within twenty

minutes between 5:00 pm and 5:20 pm on June 20, 2001.

Displacement for each snail was measured daily for two days after release. A survey flag

was placed into the ground at the location where each snail was found. The displacement

96

CIIAPTER 5: DISPERSAL

of each recaptured snail was measured using triangulation with a measuring tape (Figure

5.1). The data consisted of two measurements, AC and BC. These were translated into

spatial coordinates specifiiing landing points, using trigonometric relationships (Turchin,

1998). Movement lengths can describe movement paths for set time intervals. The

directions of heading from the release point, were determined from the sequential positions

of individual snails using triangulation. At the conclusion of each experiment, all located

snails were removed fromthe site. This prevented a build up of these snails at the release

site and avoided contamination from 'old release' snails with 'new release' snails in

subsequent releases.

97

n+2


n J

1 N

n 1

nIl

Heading

a\\

n n- 2

Tutningangle /

a \Tap ,

Ia

\aTape

\\

\a\t\a-\

^

¿.......¡r.rrrrrrrrrr¡r..r¡ :........................ì B

Figure 5.L. Triangulation with measuring tape. A : Release point; B: Reference point; C

: Location of snail at time of observation. The baseline AB should be approximately as

long as the linear dimensions of the areathat includes all the flags marking out the path of

the snails. The n-thdistance is measured by stretching one tape measure from A to C, and

the other from B to C to achieve distances AC and BC respectively. This procedure is

repeated for all stopping points, always using A and B as flxed points. Figure adapted from

Turchin (1998).

\a

98


5.2.2 Dispersal trials

Collection and release

Adult C. virgata and C. acuta were collected from the Warooka field site (Section 2.2'I)

Release size of 40 snails was determined (see below) to be optimal for C. virgata and C.

acLtta, and therefore \Mas used for all further MRR studies. For each trial, three replicate

groups of marked snails were released. C. virgata were laid out on the ground in groups,

with their umbilicus down, and marked with either blue, pink or orange fluorescent spray

paint (White Knite@, Australia). C. acuta were hand painted with red, pink or orange nail

lacquer. Each group in each treatment was marked with a different colour to prevent any

ambiguity if there was overlap of groups. Experimental releases were separated by 20 m -

30 m. Snails were released within eight hours of being collected. Release points were

randomly chosen throughout the field plot at the Minlaton field trial site'

Air temperature, relative humidity and soil temperature were measured at the field site at

five minute intervals using Hastings Tinytalk@ data loggers (Hastings Data Loggers Pty

Ltd, UK). The data loggers were placed in a weather screen at a height of 1.5 m. A probe

from the soil temperature data logger was inserted 1 cm into the soil. Data loggers were

programmed and their data were downloaded using OTLM version 1.51 (Gemini Logger

Manager (UK) Ltd, 1994-1998).

Recording disp I acement

Displacement of individual snails was measured one and two days after release in the 2001

field season, and on days one, two, three, four and f,tve after release in the 2002 fteld

99


season (Figure 5.1). Searching was conducted for up to 30 minutes per release group each

day.

5.2.2,1 Mass-mark-release-recaplure dispersal trials

Before seeding commenced, two field plots, one for future canola and the other for future

barley crops were divided in halves. One half of each of these plots was burnt seven days

before seeding the other half was left as barley stubble. Groups of snails were released into

burnt and unburnt treatments in barley (seeding rate: 80 kg I ha), canola (Brassica napus L'

Mystic variety) (seeding rate: 5 kg I ha) and grazed pasture, which was predominantly

medic (refe6ed to as medic: seeding rate: 15 kg / ha). For simplicity, medic is defined as a

crop for all dispersal studies conducted in this thesis. These crops were adjacent to each

other. Releases were conducted in June (June 20-22,2001), July (July 18-20, 2001),

September (September 04-06,2001) and October (October 26-28,2001).

Climatic data for each of the releases are summarised in Appendix 4' During the June

release, there was rainfall on the release day and through to day two. Minimum

temperatures remained mild (around 11"C) with maximum temperatures around 18oC. In

this release, snails were only released into canola as part of the optimal size release. The

canola at this stage was 3 cm high. During the July release, the soil remained moist from

moderate rainfall on the day of the release and subsequent light rain. Air temperature

ranged from 4oC to 20oC, and soil temperature was similar. The canola crop at this release

was 32 cm high; the barley crop was 12 cmhigh, and The grazed medic was 5 cm high. The

September release had heavy rainfall throughout the release, and air temperature ranged

fiom 2oC to 20oC. Soil temperatures ranged from 5oC to 22oC. At this release, the canola

100


was 112 cm high; the barley crop was 98 cm high and the medic was 4 cm high. During the

October release, there was moderate rainfall on the day of the release and on day one.

There \Mas no rainfall on day two. Air temperature ranged from loC to 23oC, whereas the

soil temperature remained warmer at between 9oC and 30oC. The canola crop was 140 cm

high; the barley was 120 cm high and the grazed medic was 6 cm high'

5.2.2.2 Individual-murk-release-recapture dispersal triøls

For IMRR trials, individual snails had to be uniquely marked. Following collection and

marking (Section 5.2.2), each adult snail was individually identified by being numbered

with a felt pen on two sides of the shell. This replicated marking helped ensure against a

marked snail losing its identity. IMRR allowed tracking the paths of individual snails.

Three replicates per treatment were released into a barley crop and a medic pasture in June,

July and September 2002. There was a late break to this season, and therefore seeding

occurred later in the year than was expected.

The June release was conducted from Jtne 27 - July 02 2002. The barley crop was 3 cm

high, with barley rows plante d 24 cm from each other, and a seeding rate of 80 kg I ha. kt

the grazedmedic treatment, the medic was 4 cm high, with rows planted 24 cm from each

other with a seeding rate of 15 kg / ha. During this release there was heavy rainfall, air

temperatures ranged between 3oC and 25oC, and soil temperature ranged between 4oC and

28"C. The July release was July 28 - August 02,2002. At this time the barley crop was 11

cm high. The grazed medic was 4 cm high. Rainfall during the release ranged from light to

heavy. Air temperatures ranged between 5oC and 20oC, and soil temperatures from 8oC to

19"C. The September release was Septemb er 28 - October 03, 2002. At this time the barley

101


crop was 48 cm high. The grazed medic was 5 cm high. There was moderate rainfall

during this release. Air temperature ranged from 6oC To 23oC, while soil temperature

ranged from 12'C to2loC.

Spray paint could not be applied to juvenile snails without killing them, therefore, juvenile

snails were put into groups, and hand painted with nail lacquer (Catwalk@, Australia). Each

snail was numbered with an Artline 725 superfine point (Artline@, Australia) felt pen on

two sides of the shell. Juvenile snails were released in September 2002, as spring

populations are mostly juveniles (Baker, 1986; 1988b; 1989), and this was the only time

when juvenile snails were abundant enough to conduct an experiment.

Statistical analysis

Release-size

Chi-square tests were used to compare headings within and between release-size

treatments. For the purpose of chi-square tests, the headings were classified into groups of

90" (i.e. 0o - 90o; 91o - 180o; 181" - 270o and 27I'- 360). chi-square analysis was

performed using JMP version 4.02 (SAS Institute Inc, Cary, North Carolina, U.S.A).

Generalised linear models (GLM) were used to determine whether there were differences

in distances moved by day two among release densities'

Descriptive statistics were compiled for the dispersalof C. virgata and C. acuta from the

release point. Mean distances and the standard deviation's around the means were

determined. Mean angles, circular variance; angular variance and angular deviation were

calculated (Zar, 1999} Circular variance (1-r) is a measure of dispersion (spread of the

population). Lack of dispersion would be indicatedby I-r:0, and a maximum dispersion

r02


by l-r: 1.0. Angular deviation is analogous to the linear standard deviation. It has a finite

upper limit and is therefore a more appropriate measure of dispersion than circular

deviation, which has a range of 0-1.41 radians (0 - 31.03"). Rayleigh's test for circular

uniformity (Zar, 1999) was performed to determine circular uniformity in heading

direction and turning angles. In this test, the null hypothesis is that the sampled population

is uniformly distributed around a circle. The critical value for Rayleigh's z is zo.os,qo:2,97 '

In other words, values less than 2.97 indicale that the distribution of displacement from the

release point cannot be distinguished from random. Circular uniformity implies that there

is no mean direction (Zar,1999).

Fisher's omnibus tests (f : 2 x (1og" + logu + log") compared the Rayleigh's z factor

between treatments for biased heading directions. This test was used to compare replicates

in the size-dependent dispersal trials.

Mass-mark-rele ase-recapture (200 1 field season)

Descriptive statistics were compiled for mass-mark-release-recapture experiment as for the

release-size experiment.

Mixed models were used to determine the effects of release and treatment for C. virgata

and C. actúa on total displacement at day two among treatments. These analyses were

performed using PROC MIXED (SAS Institute, Cary, North Carolina). The distribution of

net displacement during the field trials was visualised using a histogram expressing

frequencies.

103


Fisher's omnibus tests were used to compare Rayleigh's z factor for biased heading

directions in the MMRR field trials. Histograms of the frequencies of distance moved

within populations, and the mean net distance moved for each treatment are shown.

Individual-mark-release-recapture (2002 field season)

Descriptive statistics were compiled for individual-mark-release-recapture experiments as

for previous experiments. Turning angles were calculated from the IMRR studies using the

data collected by triangulation. Chi-square analysis was performed to compare the

distribution of headings and turning angles using JMP version 4.02 (SAS Institute Inc,

Cary, North Carolina, U.S.A). Fisher's omnibus tests were used to compare replicates in

the IMRR studies. Circular histograms provide graphical presentation of heading directions

and turning angles (Zar,1999) and representative graphs are provided for IMRR'

Mixed models were used to determine the effect of release and crop type for adult and

juvenile C. virgata and C. acutct on total displacement over days one through five during

Ihe 2002 field season. These analyses were performed using PROC MIXED (SAS Institute,

Cary, North Carolina). The distribution distances moved each day during the 2002 field

trials were assessed using histogram expressing frequencies'

Mean squared displacement (see Turchin, 1998, Box 5.1, ppl39) is related to the rate of

population spread. It can be used to compare theoretical and actual displacement, providing

an overall test of appropriateness of the correlated random walk model (CRW) pattern

(Turchin, 1998). Observed mean-squared displacement was tested against expected mean

square displacement (Turchin, 1998) to test for applicability of a CRW for the dispersal of

104


individual adult and juvenile C. vìrgata and C. acuta in barley and medic, in June, July and

September 2002.

5.3 RESULTS

5.3.1 Mark-release-recapture: Optimal release size

Recapture rates for C. virgata were between 91.3 %o and96.7 o/o, and for C. acutawere

between 81.3 % and 93.8 % (Table 5.1).

Table 5.1. Recapture rate of adult C. virgata and C. acuta at different release sizes over

two days, June 2001. Values are means * / - standard error. n : 3.

Number of C. virgata C. acutø

snails released Day 1 Day 2 Day I Day2

8 95.7 +l- 4.3 91.3 +l- 4.3 91.3 +l- 4.3 91.3 +l- 4.3

16

100

40

gl.8+l-2.2 93.8+l-3.7 93.8+l-3.6 81.3 +/- 9.5

95.0 +l- 1.4 96.7 +l- 0.3 87.7 +l- 4.8 87.4 +l- 2.8

95.0 +l-2.6 94.3+l- 0.9 86.0 +/- 5.5 92.0 +l- 5.5

Descriptive statistics for the release-size trials are given in Appendix 5. There were

differences in the mean angle of dispersal among release groups of eight, 16, 40 and 100 C.

virgata 03o.or,1e: 19.02). However, there was no difference in the mean angle of dispersal

among release groups of eight, 16, 40 and 100 C. acuta 03o1t, rc: 6.39), indicating that

105


movement was biased across the treatments. While there was no difference in distribution

of headings (angle of dispersal) among replicates for C. virgata at release sizes 40 andat

16 (Table 5.2), there were differences among replicates at release size 100 and eight.

Replicates were combined for release densities 40 and 16, and the two release densities

were compared (Table 5.2) showing a difference in the distribution of headings over two

days. Therefore, while dispersal was non-random among treatments, the direction of bias

was not consistent among treatments.

Table 5.2. Pearson's Chi-square test to compare headings (grouped at 90) for adult C.

virgata within, and between release sizes 8,16, 40 and 100 snails, at day two at 0.05 level,

June 2001

Treatment DF Chi-Square P>Chi-sq.

Among reps: Release size 8




Between release densities 40 and 16

6

6

6

6

aJ

12.850 0.0455

4.477 0.6t24

5.009 0.2864

13.497 0.0358

r 6.1 81 0.0010

There were differences in the distribution of headings over two days for C. acuta at release

densities eight, 16 and 100 and snails (Table 5.3). Therefore, dispersal differed among

replicates. There were no differences in the distribution of headings among replicates for

release size 40 snails indicating that dispersal was consistent at this release size.

106


Table 5.3. Pearson's Chi-square test to compare headings (grouped at 90") for adult C'

acutawithin, and between release sizes 8,16, 40 and 100 snails, at day two at 0.05 level,

June 2001.

Treatment DF Chi-Square P>Chi-sq





6

6

6

6

t6.074 0.0134

13.468 0.0362

4.531 0.6052

40.t67 <0.0001

There was a positive increase in distance displaced from the release point with increasing

release-size when analysing all C. virgata release size treatments (Table 5.4). However,

there was no difference in displacement among release-sizes of eight, 16 and 40 C. virgara.

When comparing across all C. acuta release-size treatments, there was a positive increase

in distance displaced from the release point with increasing size (Table 5.4)' Additionally,

GLM showed that there were differences in mean displacement among each of the release-

SIZES

t07


Table 5.4. Slopes of lines for regression of distance moved versus release numbers for

distance moved by adult C. virgata and C. acuta aL release densities 8,16,40 and 100 in

June 2001 derived from a generalised linear model analysis.

Parameter Estimate (cm) Standard Error t P>ltl

C. virgata all release densities

C. virgata at release densities

eight, 16 and 40

C. acuta all release densities

C. acula at release densities eight,

16 and 40

0.7717971 0.r867s252 4.t3 <0.0001

-1.2319515 0.57157262 -1.4r 0.1592

0.53010507 0.12002003 4.42 <0.0001

0.34623235 0.632421132 4.12 <0.0001

The parameter estimate from the GLM showed that the distance moved increased with

increasing snail densities (Figure 5.2a). There were very large standard deviations within

replicates. The data indicate that the increase in movement is largely due to the release size

of 100 snails. Taken together, the data show that release sizes of forty snails are consistent

among replicates, and were more representative of snail movement, and were therefore

chosen as the release densities to be used in further release studies.

Distance moved did increase with increasing release-size of C. acuta. (Figure 5 '2b)' There

was no difference in the distribution of headings in C. acuta at release size 40' The

distance moved increased with increasing release sizes, however, there were large standard

deviations associated with the means. As with the results for C. virgata, taken together, the

release size of 40 C. acuta was justified on the need for repetition balanced against a

relatively small increase in movement based on distance moved, thus were chosen as the

optimal release size for further experiments.

108

i.450

400

350

300

250

200

150

100

50

0

CTIAPTER 5: DISPERSAL

80 1000

EoN(uît-oît-gõ.E

ootro.9o

20 40 60

b"300

250

150

100

200

50

0

o 20 40 60 80 100

Number of snails released

Figure 5.2. Distance travelled by adult z. C. virgata andb. C. acuta by day two at release

densities of 8, 16, 40 and 100 snails in June 2001.Values are means I +/- standard

deviations. predicted distance - derived from parameter estimate from generalised linear

model. N.B. means for each release size are offset to clariff standard deviations for each

replicate.

109


5.3.2 Mass-mark-release-recapture

All work in this section was fiom the 2001 field season. Separate analyses were performed

for days one and two. Reasons for this separation of days were that day one displacement

may have been affected by handling, and day two displacements were less likely to be

affected by this. In addition, climatic variables changed and therefore would influence

dispersal (Appendix 4). Descriptive statistics for each release are presented in Appendix 5.

Results from mixed model analysis describe the effect of crop type and treatment on

distance moved on days one and two. The estimate for Medic is given as zero because this

category is fitted by the intercept. The degrees of freedom vary according to the data

collected, i.e. the number of snails that were found on each day. Fisher's omnibus test

results are presented for each month. At the conclusion of this section, the outputs from

mixed model analysis for the effect of crop type and the month in which snails were

released are presented for C. virgata and C. acuta.

Snails moved in a non-uniform direction at the beginning of the season when crops were

small. This was seen among replicates, but was different between snail species. As crops

became larger, snails moved smaller distances, and movement was less directional.

Representative graphs for canola are shown for the beginning and end of the season

(Figure 5.3a and b). However, the data from each release (June, July, September and

October) and treatment (canola and barley sown in burnt and unburnt soil, and medic) are

shown in Appendix 5. Frequency data shown (Figure 5.4a and b) are from the same

populations as shown in Figure 5.3a and b. The distribution of distances moved by C.

virgaÍa in June (Figure 5.4a) was twice that of the distance moved by snails in October

(Figure 5.4b).

110


^,

b.

500

400

300

200

I

ANI

t

¡¡

tr¡¡ - t

.t'1ooT

t

-600 -500 -400 -300 -200 -100 100 '1200 300

60

-100

50

40

30

10I

I

¡r! ¡

Ia

-60 -40

l¡

¡r¡l

¡r rÜt

fI

h

¡-30

-20

I

4020I

¡l¡

III

,¡I

¡¡I

I

-40

Figure 5.3. Example of displacement of adult C. virgata in unburnt Canola in a. June' and

b. October 2001, ovef two days. Day 1 r; Day 2 t Each point fepresents an individual

snail. Mean angle day I o; day 2 . n: 40. Distances afe shown in cm'

111

L.

b

16

14

12

10

I6

4

2

0

otroEol¡.


10 20 50 70 100 150 200 250 300 400

25

20

I

1

oc,o5EoLlJ.

5

0

5

0

10 20 50 70 100 150

Distance (cm)

200 250 300

Figure 5.4. Frequency of the net distance moved by adult C. virgata in unburnt canola in

a. June and b. October 2001 over two days. Day 1 r; Day 2 t n:40. Populations are the

same as those in Figure 5.3 a. and b.

-l- i

t12


Adult C. vtrgatareleased in July 2001

Mixed model analysis show that crop type had an effect on the displacement of C' virgata

in July (P : < 0.0001). Movement of C. virgata in July (Table 5.5) was greatest in barley

grown on burnt soil followed by canola grown on burnt soil. C. virgata released in barley

sown in unburnt soil moved the next greatest distance, and C. virgata released in canola

grown in unburnt soil dispersed the smallest distances on days one and two' C. virgata

moved in a non-uniform direction (Fishers P < 0.001) in each of the canola, barley and

medic treatments in July.

113



on displacement of adult C. virgata in July 2001. Separate models shown for days one and

for the cumulative of days one and two.

Crop Estimate (cm) Standard error DF t P>t

2 8.80 0.0127

>ìcú

â

Intercept

Barley in burnt soil

Barley in unburnt soil

Canola in burnt soil

Canola in unburnt soil

Medic

Intercept





Medic

29.09

20.76

10.33

TT.22

-8.7 5

42.22

49.99

9.38

s.59

-16.48

3.31

4.76

4.70

4.70

4.69

6.16

8.68

8.66

8.72

8.64

525 4.36 <0.0001

s25 2.20 0.0281

52s 2.39 0.0172

s25 -1.87 0.0622

2 6.8s 0.0207

577 5.76 <0.0001

577 l.08 0.279r

s77 0.64 0.52ts

577 -1.91 0.0571

0

c.l

l.t

0

Adult C. acuta released in July 2001

The crop type into which C. acttla was released had an effect on displacement from release

site (p < 0.0001). Mixed model analysis showed that in July, C. acuta teleased in canola

grown on burnt soil moved the greatest distance (Table 5.6), followed by snails released in

barley grown on burnt soil on day one. On day two, C. acuta dispersed the greatest

distance in barley grown on burnt soil.

rr4



on dispersal of adult C. acuta in July 2001. Separate models for day one and the

cumulation of days one and two.

Crop Estimate Standard error DF t P>t

(cm)

t-l

Intercept





Medic

Intercept





Medic

1s.44

16.24

14.21

27.62

9.3 8

22.46

31.66

14.85

29.47

4.91

2.38

2.6s

2.66

2.64

2.64

5.43

6.25

6.25

6.24

6.1 8

2 6.s0 0.0229

540 6.12 <0.0001

540 5.34 <0.0001

540 10.46 <0.0001

540 3.ss 0.0004

2 4.13 0.0538

552 5.06 <0.0001

s52 2.38 0.0179

552 4.72 <0.0001

s52 0.79 0.4279

0

ôl>\(d

Ê

0

Adult C. virgata released in September 2001

There was an effect of crop type on the displacement of adult C. virgata in September

2001 (P : 0.0004). Analyses of the effect of crop type on displacement of C. virgata in

September show that C. virgata were displaced the greatest distance when released in

barley grown on unburnt soil (Table 5.7) on days one and two. On day one, snails released

in the barley grown in unburnt soil treatment displaced the greatest distance from the

115


release point, and there was no distinguishable difference between distance moved in the

other treatments. On day two, C. virgata moved the greatest distance in barley grown on

unburnt soil, followed by snails released in barley sown on burnt soil.


on dispersal of adult C. virgata in September 2001. . Separate models for day one and the

cumulation of days one and two.


2 4.97 0.0382

>.(Ë

t-l

Intercept





Medic

Intercept





Medic

16.7 |

0.967

11.00

2.77

2,07

26.21

6.52

11.92

2.72

-0.15

3.37

1.94

|.94

1.95

t.94

5.06

3.16

3.15

3.13

3.t2

s86 0.50 0.6193

5 86 5.67 <0.0001

s86 t.42 0.1s52

586 1.06 0.2874

2 5.18 0.0352

s70 2.06 0.0394

s70 3.79 0.0002

s70 0.87 0.3846

570 -0.05 0.924

0

c.ì

Ê

0

Adult C. acuta released in September 2001

The crop type into which adult C. acuta were released in September 2001 affected the

displacement of the snails on days one and two (P < 0.0001). Mixed model analysis

116

C}IAPTER 5: DISPERSAL

showed that C. acuta released into barley grown on burnt soil moved the greatest distance

on days one and two (Table 5.8). On day one, C. acuta released into canola grown on burnt

soil moved the next greatest distance, with those snails released into the medic treatment

dispersing the least distance. On day two, C. acuta released into barley grown on unburnt

soil dispersed the second greatest distance from the release point, and those snails that

were released into medic dispersed the least distance from the release point (Table 5'8).

tr7



on dispersal of adult C. acuÍa in September 2001. Separate models shown for days one and

for the cumulative of days one and two'


CË

â

Intercept





Medic

Intercept





Medic

1 1.82

6.69

2.39

s.66

1 .18

t3.24

18.23

10.40

9.17

2.r3

1.53

1.37

1.39

1.39

r.37

2.39

1.91

1.90

1 .88

1 .89

2 7.75 0.0163

584 4.87 <0.0001

s84 |.72 0.0858

584 4.09 <0.0001

s84 0.86 0.3893

2 5.54 0.031 I

273 9.56 <0.0001

273 5.47 <0.0001

273 4.87 <0.0001

273 1.13 0.2604

0

c-ì

(d

,-.{

0

Adult C. vtrgaTa released in October 2001

Crop type had an effect on the displacement of adult C. virgata in October 2001 (P <

0.0001). Mixed model analysis showed that on both days one and two, C' virgata released

into canola grown on unburnt soil moved the greatest distance, followed by those snails

released onto barley also grown on unburnt soil (Table 5.9). Snails released in barley

grown on burnt soil dispersed the least distance from the release point on day one,

118


however, those snails that were released in canola grown on burnt soil were displaced the

least distance from the release point by day two.


on dispersal of adult C. virgata in October 2001. Separate models shown for days one and


Crop Estimate Standard error DF r P>t

(cm)

2 16.06 0.0039

Ê>'cú

â

Intercept





Medic

Intercept





Medic

27.09 r.69

-0.88 2.42

tt.92 2.40

4.82 2.37

17.67 2.45

50.63 8.36

-s.68 4.40

0.87 4.s5

-7.39 4.42

13.84 4.59

561 -0.36 0.7180

s61 4.97 <0.0001

56t 2.03 0.0425

561 7.22 <0.0001

2 6.05 0.0262

583 -l.29 0.1971

s83 0.19 0.8492

583 -1.67 0.0948

583 3.02 0.0027

0

c\(Ë

t-l

0

119


Adult C. acuta released in October 2001

The crop type into which adult C. acuta were released in October 2001 affected snail

displacement (P < 0.0001). On day one, C. ctcLtta released in barley grown on unburnt soil

dispersed the greatest distance followed by those snails released onto barley grown on

burnt soil (Table 5.10). On day one, snails that were released into canola that was grown

on burnt soil dispersed the smallest distance from the release point' However, by day two,

C. acttta released into canola grown on unburnt soil dispersed the greatest distance,

followed by those snails that were released into barley that was grown on unburnt soil' C.

acuta released into barley that was gro\¡/n on burnt soil were displaced the smallest

distance by day two.

r20



on dispersal of adult C. acuta in October 2001. Separate models shown for days one and


Crop Estimate Standard error DF t P>t

(cm)

CË

t-.1

Intercept





Medic

Intercept





Medic

20.13 1.37

3.54 1.50

4.37 1.51

-t.74 1.50

-0.55 1.53

23.20 2.33

-1.10 2.25

9.12 2.30

5.26 2.26

15.89 2.33

2 14.66 0.0046

s80 2.35 0.0189

580 2.89 0.0040

580 -1.16 0.2466

580 -0.36 0.7 r97

2 9.96 0.0099

560 -0.49 <0.0001

s60 3.97 0.6237

s60 2.33 0.0200

560 6.82 <0.0001

0

c.l

(d

â

0

Fisher's omnibus test was used to determine whether or not the direction of movement was

biased when pooling data across all replicates. Directional bias rù/as seen in adult C. virgata

across the barley and medic treatments, and in the canola grown on unburnt soil treatment

across days one andtwo (Table 5.11). Adult C. virgata released in canola grown onburnt

soil showed directional bias on day two, but not day one. Directional bias was seen in C.

acuta in barley grown on burnt soil, canola grown on unburnt soil, and the medic

12l


treatments (Table 5.1 1) on days one and two. C. acttÍa released in barley grown on unburnt

soil showed directional bias on day two only. No directional bias was seen in C. acuta

released in canola grown on burnt soil (Table 5.11).

Table 5.11. Summary of directional bias (Fisher's omnibus test) across all replicates, over

two days for adult C. virgata and C. acuta inOctober 200I' n:3'

C. virgata C. øculø

TreatmentDay 1 Day2 Day I Day 2





Medic

P<0.001 P<0.001 P<0.001 P<0.001

P<0.001 P<0.001

NS P < 0.05

NS

NS

P < 0.001

NS

P<0.05 P<0.005 P<0.05 P<0.005

P<0.001 P<0.001 P<0.001 P<0'001

NS not biased

Mixed model analysis was used to determine the effect of the month in which C. virgata

and C. acuta were released and crop treatment (crop type, burnt or unburnt) in which the

snails were released. Additionally, the interaction between month released and crop

treatment on the distances C. virgata (Table 5.12) and C. acuta (Table 5.13) moved from

the release point by days one and two were analysed. The interaction between month and

treatment are significantly related to overall displacement of C. virgata and C. acuta on

both days one and two.

r22


Table 5.12. Tests of fixed effects; factors that affected dispersal distance of C. virgata on

days one and two during the 2001 field season.

Effect

Crop treatment

Month

Month*Crop treatment

Crop treatment

Month

l 839 469 0.0009

I 839 t47.07 <0.0001

I 839 7.07 <0.0001

1788 5.64 0.0002

Num DF Den DF F-value P>F

IJ

c.l

(d

IJ

4

J

8

4

-) 1788

1788

145.11 <0.0001

8.35 <0.0001Month*Crop treatment 8

Table 5.13. Tests of fixed effects; factors that affected the dispersal distance of C' acuta on

days one and two during the 2001 field season.

Effect Num DF Den DF F-value P > F

â

c.l>.

â

Crop treatment

Month

Month*Crop treatment

Crop treatment

Month

I 813 t2.04 <0.0001

1813 213.40 <0.0001

1 813 6.86 <0.0001

1794 12.16 <0.0001

r794 r45.62 <0.0001

4

J

8

4

t

Month*Crop treatment 8 1794 8.35 <0.0001

Rainfall during the September field trial was much greater than during the other releases

(Appendix 4). While rainfall was lower during the October and July releases, the soil

would have remained moist from rainfall on the previous days. The highest minimum air

123


temperature recorded was during the June release. The coldest minimum air temperature

was during the October release, however, the minimum soil temperature \Mas the warmest

after that measured during the June release. The interaction between rainfall and minimum

temperature are likely to have affected snail movement. Additionally, the height of the

vegetation in the habitat tlpe would have affected movement. From the dispersal data, it

would seem as though heavy rainfall inhibits movement, whereas lighter rainfall events

enhances it.

The mean distance moved over two days by C. virgata and C. acuta varied among

treatments and between snail species (Figure 5.5a and b). Data for day one were not

analysed as there are many factors such as handling, marking and crowding that would

have influenced the immediate displacement of the snails. For adult C. virgaîa, the highest

displacement in the barley in the burnt treatment was seen in the July release, and there

was no difference in mean displacement between September and October for the same

treatment (Figure 5.5a). There was no difference among releases in the canola sown in

burnt soil. C. virgata released canola gro\Mn on unburnt soil dispersed the greatest distance

in October. Adult C. virgata released in barley sown in unburnt soil dispersed further in

July than those released in September, and C. virgata released into medic dispersed further

in October than those released in September.

For C. acLtta,the mean displacement at day two was highest in barley and canola in burnt

soil, and barley in unburnt soil in July (Figure 5.5b). During this release there was light

rainfall, however moderate rain fell on the day of the release. Additionally the minimum

soil temperature was cool (approximately 5"C). The interactions between temperature and

moisture are the most likely factors that influenced movement of C. acuta. For these

124


treatments (barley and canola in burnt soil, and barley in unburnt soil) there was no

difference in displacement in September or October. For canola in unburnt soil, the highest

mean displacement was the October release (low rainfall, but moist soils, mild minimum

soil temperature (approx 9"C)); with the September release giving the lowest mean

displacement. During the September release there was heavy rainfall and cold minimum

temperature (2'C).For the medic treatment, there was no difference in displacement

between the July and October; however, the September release gave the lowest mean

displacement. Minimum temperatures may be important for snail movement because snails

are mostly nocturnal, and thus are active when minimum temperatures are experienced.

When all the data were pooled together, the mean displacement after two days for C. acuta

and, C. virgata over all treatments and releases were 29.3 cm and 44.3 cm respectively' The

displacement of C. acuta was highest in July for all treatments except those released in

canola seeded on unburnt soil and in medic (Figure 5.5a and b). C virgata and C' acuta

released in September tended to move lesser distances than those released in July and

October. This could be related to heavy rainfall and cold minimum temperatures

(Appendix 4).

125

E.!)100c980tsoË60CL

€40c820=

b.

;70ts

-9 oo

bsotr

þ¿oåeo'Ê zo

F10o

=O


L,

120 In burnt soil In unburnt soil

Barley Canola BarleY Canola Medic

In burnt soil In unburnt soil

Barley Canola Barley

Treatment

Canola Medic


day two after release in each of the five treatments for July r; September r and October ¡.

0

t26


5.3.3 Individual mark-release-recapture

The work presented in this section is for the dispersal of individual adult and juvenile C.

virgata and C. acuta from the 2002 field season. Descriptive statistics for adult and

juvenile C. virgata and. C. acuta data arc presented separately according to the month in

which they were released (Appendix 6). Fisher's omnibus tests for bias in directional

headings and turning angles are presented. Outputs from the mixed models are presented at

the beginning of each section ascertaining the effect of crop tlpe on dispersal' At the end

of both the adult snail and juvenile snail sections, output from mixed models to determine

the effect of crop type and the month in which C. virgata and C. acuta were released are

given. More detailed analysis of the factors that influence the dispersal of individual adult

and juvenile C. virgata and C. acuta are presented in Chapter 6'

5.3.3.1 Adult snøils

Within each release period, irrespective of snail species, snails in both medic and barley

treatments moved in a biased direction. However, snails did not move in a biased direction

on each day (Table 5.I4). Headings and turning angles were determined from IMRR

releases in 2002.Individual snail paths within each treatment differed (e.g. Figure 5.6),

even when there was biased movement for the snail species in a treatment.

t27

CIIAPTER5: DISPERSAL

20.0

-90.0 -40.0 10.0

-20.0

-60.0

-80.0

5.0

-120.0 -60.0 0 60.0

-5.0

-10.0

-15.0

-25.0

Figure 5.6. Movement paths over five days of two individual adult C. virgata, released in

barley in July 2002. Distances measured in cm.

t28


In June, C. virgata showed no heading bias until day 3 in medic, and day 5 in Barley'

(Table 5.14). These biases were associated with precipitation (Chapter 6). For all but day

four in medic, C. acuta showed significant bias in direction (Table 5.14). Thus different

factors may be driving biased movement for C. virgata and C. acuta. Additionally, C.

acuta may be more sensitive to certain stimuli than are C. virgata, and therefore, behave

differently.


medic over five days for C. virgata and C. acuta in June. n: 3/treatment.

C. virgata C. acuta

DayBarley Medic Barley Medic

NS P < 0.001 P < 0.05

NS P < 0.001 P < 0.001

P < 0.001 P < 0.001 P < 0.001

P < 0.001 NS

P < 0.001 P < 0.001 P < 0.001 P < 0.001

NS not significant

There was a bias in turning angles for C. virgato at days four and frve in both barley and

medic in June (Table 5.15). A bias was also seen in C. acula for barley and medic over

each day, with the exception of the barley treatment aT day two. This is a similar pattern to

that seen for headings, and therefore, similar factors are probably driving the turning

angles as with the headings.

1

2

J

4

5

NS

NS

NS

NS

NS

r29



over five days for C. virgata and C. acuta in June. n: 3/treatment'

DayC. virgata

Barley Medic

C. acuta

Barley Medic

2

J

4

5

P < 0.001 P < 0.001

P < 0.001 P < 0.005

P < 0.005 P < 0.001 P < 0.001 P < 0.005

P < 0.001 P < 0.001 P < 0.001 P < 0.001

NS not significant

There ,ù/as no effect of crop type on dispersal of C. virgata in June (P : 0.8337) (Table

5.16). At this release, the barley and medic plants were approximately the same size (ca. 3-

4 cm). Given that the humidity and temperature in both habitats would not have varied

greatly, it would be expected that movement of C. virgata would not vary between plant

tlpes unless they had a preference to feed or rest on one ofthe crops over the other'

NSNS

NSNS

130


Table 5.16. Solution for fixed effects from mixed model analysis to investigate the effect

of crop type on the daily dispersal of adult C. virgata in June 2002.

Crop Estimate Standard Error DF t value P>ltl

Intercept 16.83 2.08 J 8.09 0.0039

Barley -0.42 2.00 7t5 -0.21 0.8337

Medic 0

The movement of C. acuta in June was affected by the crop t1,pe in which the snails were

released (P : 0.0092). C. acuta released in medic moved further each day than those

released in barley (Table 5.17). This may be attributed to the differences in density and

structure of the plant types. C. acuta behave differently than C. virgata in barley and medic

habitats. C. acuta bury into soil, and may have done this to avoid predation in the medic, a

relatively open habitat.


of crop type on the daily dispersal of adult C' acuta in June 2002'

Crop Estimate Standard Error DF t value

Intercept t8.72 1.60 3 lt.72

Barley -4.99 l.9l 673 -2.6r

Medic 0

P>ltl

0.0013

0.0092

131


Data for the July release were analysed for C. virgata. Fisher's omnibus test showed that

for each day and for both barley and medic treatments, there was biased heading direction

(p < 0.001) and turning angle (P < 0.001). Data were not analysed for C. acuta at this

release, as there was an unusually high mortality rate (82%) at this time' The reason for

this high mortality among C. acuta was unknown.

The crop into which C. virgata was released in July 2002 affected the distance moved by

individual adult snails (P < 0.0001). C. virgala released into medic moved further than

those released into barley (Table 5.18). At this time the barley was still less dense but was

higher than the medic.


of crop tlpe on the daily dispersal of adult C. virgata in July 2002'

Crop

Intercept

Barley

Medic

Estimate Standard Error

66.09 14.97

-34.31 4.0s

DF tvalue P>ltl

-') 4.42

683 -8.48

0.0216

<0.0001

0

Fisher's omnibus test showed that there were biased directional headings at days three

through hve for C. virgata released in barley in September 2002. C. virgata released in

medic showed biased dispersal on days four and five, and random movement on days one

through three (Table 5.19). C. acttta released in barley showed biased movement on days

r32


two, four and five. However, C. acuta released into medic in September showed no biased

movement (Table 5.19).


medic over five days for C. virgata and C. acuta in September. n: 3/treatment'

Day

P < 0.05

P < 0.05 NS

P < 0.001 P < 0.001 P < 0.05

P < 0.001 P < 0.001 P < 0.001

NS not si

Fisher's omnibus test showed that there were biases in the turning angles fot C. virgata and

C. acuta in September (Table 5.20). C. virgata released into barley showed biased turning

angles on day three, four and five. In addition, C. virgata released into medic in September

showed biased turning angles on day five. C. acuta released into barley showed biased

turning angles on days three and f,rve. As seen in C. virgata, C. acuta released into medic

showed biased turning angles on day five only.

C. vìrgata

Barley Medic

C. acuta

Barley Medic

2

aJ

4

5

NS

NS

NS

NS

NS

NSNS

NS

NS

NS

NS

.-'i

133



over five days for C. virgata and C. acuta in September. n : 3/treatment.

DayC. virgata

Medic

C. acuta

Barley Medic

2

J

4

5

Barley

NS

P < 0.005 P < 0.005

P < 0.005

P < 0.001 P < 0.001 P < 0.001 P < 0.01

NS not significant

The crop type into which C. virgata were released in September affected the distance

moved by the snails on a given day. C. virgata released into medic moved further than

those snails released into barley (Table 5.21).

Table 5.21. Effect of crop tlpe on the dispersal of adult C. virgaÍa in Septembet 2002

Crop Estimate Standard Error DF t value P>ltl

NS

NS

NS

NS

NS NS

NS

NS

Intercept

Barley

Medic

52.67 16.8s

- 10.36 4.t2

aJ 3.13

562 -2.51

0.0522

0.0122

0

134


Movement of C. acuta was influenced by the crop type in which they were released (P <

0.0001). C. acuta released in medic moved greater distances than those released in barley

on any given day (Table 5.22).

Table 5.22. Solution for fixed effects from the mixed models investigating the effect of

crop tlpe on the daily dispersal of adult C. acuta in Septembet 2002.

Crop Estimate Standard Error DF t value P>ItI

Intercept 58.64 7.27 J 8.07 0.0040

Barley -36.45 4.48 329 -8.14 <0.0001

Medic 0

In addition, the month in which C. virgata (P < 0.0001) and C. acuta (P < 0'0001) were

released, regardless of crop t1pe, affected movement. C. virgata moved the least distance

in June (Figure 5.7). During the June experiment, there was rainfall on three of the five

days, two of which were light or moderate, and on the other heavy day rain fell. Minimum

air and soil temperatures were low (down to 3"C). As there was no data for C. acuta in

July, no comparison can be made between C. virgata and C. acuta for this month.

However, in September, C. virgata dispersed greater distances thanC. acuta overthe f,tve

days. Over the period of this release, there was a heavy rainfall on day one, however, light

rainfall continued for days two through five. Additionally soil and air temperature were

mild (lowest 8"C). Again the interaction between moisture and minimum temperature is

the most likely the factors influencing movement of C. virgata and C' acuta.

135


The net displacement from the origin of adult C. virgata in barley was lowest in June, then

increased in July, and again in September (Figure 5.7). This displacement from the origin

shows that C. virgata in barley dispersed further from the origin as the barley plants

increased in height and in foliage density. For those C. virgata released in medic, the

lowest displacement was in June, however, the greatest displacement from the origin was

in July. This may be due to the interaction between moisture and minimum temperature

resulting in greater dispersal.

C. acuta released in barley in September dispersed further from the origin than those

released in June (Figure 5.7). This is likely to be related to the barley crop increasing in

height and density, and thus the soil has a greater chance of retaining higher humidity and

moisture. This change in microhabitat would be more suitable for C. acuta dispersal' C.

acuta released in medic showed no difference in distance moved over five days between

June and October. This may suggest that C. acuta are responding to the climatic variables

there differently than are C. virgata.

136

L.


180

160

140

120

100

80

60

40

20

0

Barley Medic

Grop type

Barley Medic

Grop type


day five after release in barley and medic habitats in June r; July r and October r. NB.

No data available for C. acuta inluly 2002

E(,

ÊoEoofltCL

.2IttrGo

=

b

^60E9sotr940ÈoË30CL

.2 20ttF10o

=o

t37


Whilst there were biases in direction of heading and in turning angles for C. virgata and C.

acuta over consecutive days, the direction of heading and turning angles varied from day

to day. As there were two snail species, three releases and three replicates over two

treatments, there are 180 graphs that could be shown for turning angles, anda fui'ther 180

graphs for heading angles. Therefore, only example graphs for C. virgata in July (Figure

5.8) are shown here to illustrate the frequency of heading directions, and the mean

direction heading. The frequency of distances moved each day is shown for C. virgata in

barley in July (Figure 5.9). Snails moved a greater distance on day one than on day two. At

days three, four and five, the distribution of distance moved each day is larger than on day

two

138


4.. 900

z=8.94,P<0.001

Mean angle: 650

,t

t,

t,

1

,,

N1b.

z=4.09,P<0.001

Mean angle: 93o

00

2700

Figure 5.8. Frequency of the distribution of the directional headings of adult C. virgata

released in barley, in July 2002 - at a. Day 4 and b. Day 5' Mean angle of directional

heading ---. Rayleigh's test of bias (z) shows significant bias in directional heading.

Headings are grouped in 30o categories. n:40'

t

I

I

III

180 o

139


I1

1

I1

I6

42

0

I6

4

2

0

oÊo5ETolr

0>10 11>20 21>50 51>75 76>100 101>150

Distance moved (cm)

Figure 5.9. Frequency of distances moved by adult C. virgata in barley in July 2002 fot

day 1 r, day2 t, day 3 r daY 4 and daY 5 r.

140


The observed mean squared displacement (MSD) 'ù/as generally lower than the expected

for C. virgata released in barley in June (Figure 5.10a) and for C. acuta released in barley

(Figure 5.10c) and in medic (5.10d) in June. The predicted MSD closely f,rt the observed

MSD for adult C. virgata released in medic in June (Figure 5.10b). Until day five, the

predicted MSD was greater than the observed MSD for C. virgata released in barley in

September (Figure 5.10e) and C. acuta released in barley in September (Figure 5.10i). The

predicted mean square displacement was initially greater than observed for adult C. virgata

in medic (Figure 5.10Ð in July and for C. virgata in barley in September (Figure 5.109).

Predicted MSD was greater than observed MSD over the five days for C. virgata released

into medic in June (Figure 5.10h). The MSD for C. acuta in medic in September (Figure

5.10j) indicates that these snails moved back and forth relative to the release point.

For all C. virgata and C. acuta across all treatments, and releases, with the exception of C.

virgatareleased in medic in June, the mean squared displacement did not fit the correlated

random walk (Figure 5.10a through j). These data were then further analysed using a

spatial model presented in Chapter 6.

r4t

^,


t¡

0

b.

d

ÞI

€)

é)Icll

Êaa)

€c)L6l

vt)

clo)

tstà

6000

5000

4000

3000

2000

1 000

0

4000

3000

2000

1000

0

1 2 3

23Number of days

4

4

5

5

¡t

0 I


of the number of days following release for C. virgata in a. barley b. medic; C. acuta in c.

barley, d. medic in June. For C. virgata in e. barley and f. medic in July; and C. virgata in

g. barley, h. medic, and C. acuta in i. barley and j. medic in September. n : 120'

t42

c.

3000

2000

1 000

0

5000

4000

3000

2000

1000

¡


0

1

2

2

3

3

4

4

5

5

t

0

0

d.

êl

q)

É€)

é)cJcË

Êatt

rt€c)Lcll

gurt

cËq)

=À

e.

14000

12000

10000

8000

6000

4000

2000

0

0 23Number of days

I

4 5

Figure 5.L0. Continued.

t43

f.40000

30000

20000

10000

0

0

g.

20000

15000

10000

5000

0

40000

30000

20000

1 0000

0

0 I 23Number of days

CT{APTER 5: DISPERSAL

3 4

¡

5

¡

¡¡

2

3

t¡0

d

E9

Éq)

HÐq)6lÊaÀ

€Ëo¡Lcl

gaÀ

cË€)t=À

2 4 5

h.

Figure 5.10. Continued.

4 5

t44

I

4

I

3 4

CTIAPTER 5: DISPERSAL

0

0

d

FI

É€¡

E(¡)I6lÈ.a)

€€€)LcË

uÀ

6lq)

FTÀ

3000

2000

1000

J.14000

12000

10000

8000

6000

4000

2000

0

T

I 32 5

0 1 2

Number of days

5

Figure 5.10. Continued.

t45


5.3.3.2 Juvenile snails

The work presented in this section is for the dispersal of individual juvenile C. virgata and

C. acuta from September 2002. Dispersal data shown in this section are for individual

snails on each given day. More detailed analysis on dispersal data for individual juvenile

C. virgata and C. acuta are presented in Chapter 6.

The dispersal of C. virgata and C. acuta jreniles in barley and medic were measured in

September 2002. The directional heading for C. virgata and C. acuta juvenile snails in

medic was biased on days one through five (Table 5.23). C. virgata and C. acutajuveniles

released in barley moved in random directions on days two and three, however, their

direction of heading was non-random on days one, four and five.


medic over five days in September 2002 for juvenile C. virgata and C. acuta. n :

3/treatment.

C. virgata

Medic

P < 0.001

P < 0.01

P < 0.01

P < 0.05

C. qcuta

Day

1

2

aJ

4

5

Barley

P < 0.001

NS

NS

P < 0.001

Barley

P < 0.005

NS

NS

P < 0.001

Medic

P < 0.001

P < 0.05

P < 0.001

P < 0.001

P < 0.001 P < 0.005 P < 0.001 P < 0.005

146


Turning angles for C. virgata and C. acuta in September were also biased (Table 5.24).

The turning angles for C. virgata released in barley were random on day four, but were

non-random on days two, three and five. C. virgata released in medic showed random

turning angles on days three and four, and non-random turning angles on days two and

five. Turning angles for C. acuta released in both barley and the medic were non-random

on days two through five. The results suggest that different factors may be affecting the

movement of C. virgata and C. acuta, or that C. acuta is more sensitive to certain stimuli

than C. virgata are. Between crop treatments, direction of heading and turning angles were

biased on the same days, however, they were not following the same pattern between

species.


over five days in September 2002, for juvenile C. virgata and C. acuta. n: 3/treatment.

C. virgata C. acuta

Barley Medic Barley Medic

P < 0.005 P < 0.005 P < 0.005 P < 0.005

P < 0.05 NS P < 0.001 P < 0.005

P < 0.001 P < 0.05

P < 0.001 P < 0.01 P < 0.001 P < 0.001

NS not significant

Day

2

aJ

4

5

NSNS

147


The crop type into which C. virgata was released in September 2002 affected dispersal (P

: 0.0004). C. virgata released into barley did not disperse as far as those released into

medic on a given day (Table 5.25).

Table 5.25. Solution for fixed effect from mixed model analysis investigating the effect of

crop type on the daily dispersal ofjuvenrle C. virgala in September 2002.

Crop Estimate Standard Error DF tvalue P>ltl

Intercept 47.80 9.97 J 4.79 0.0173

Barley -t2.94 3.60 253 -3.59 0.0004

Medic 0

The crop type into which C. acuta was released also affected dispersal in September 2002

(P < 0.0001). C. acuta released into barley did not disperse as far as those snails released

into medic (Table 5.26).


of crop tyrpe on the daily dispersal ofjuvenile C. acuta in September 2002.

Estimate Standard Error DF t value P>lrl

6.83

Crop

Intercept

Barley

Medic

41.01 6.01

-25.20

3 0.0064

0

5.19 307 -4.85 <0.0001

148


The displacement of juvenile C. virgata released in September in barley and medic was

greater than for C. acuta (Figure 5. 1 1). Whilst movement was greater in medic for both C.

virgata and C. acuta, it can be seen that the net displacement from the release point for C.

virgata was greater in medic than barley, but C. acuta, were displaced further from the

release point in the barley than in the medic. This indicates that while C. acuta moved

larger distances in the medic, they moved around their release point, and thus daily

movement excluding reference to turning angles, are inadequate to explain snail population

movement

By way of example, the frequency of distances moved by juvenile C. virgata in medic

show that on day one, most snails moved between 100 cm and 150 cm (Figure 5.12). On

day two, the majority of the snails moved less than 50 cm. On day three, snails moved

between 100 cm and250 cm. On days four and five, the snails moved between l1 cm and

300 cm. A large number of snails moved between 250 cm and 300 cm.

r49


Barley Medic

Grop type

Figure 5.11. Mean displacement +l- standard error ofjuvenile C. virgata r and C. acuta t

at day five after release in barley and medic, September 2002.

100

Êe0.!¿ Bo

ã70560Ë50*40õ30F206)

=100

150


15

12

otroctoII

I

b

3

0

0>10 11>20 21>50 51>75 76>100 101>150 151>200 20'.1>250 251>300

Distance (cm)

Figure 5.12. Frequency of distances moved by juvenile C. virgata in medic in September

2002for day 1 r, day2r,day3 tday4 andday 5 I'n:40.

151


For all juvenile snails, the observed mean squared displacement was generally lower than

the predicted displacement (Figure 5.13a-e). This suggests that the juvenile C. virgata and

C. acuta dispersed around the release point, and did not disperse in a linear malìner.

Therefore, simple diffusion cannot explain the displacement for juvenile C. virgata or C.

acuta in any treatment, and therefore the CRW cannot be used'

152


^.

9000

6000

3000

3

t

2

0

b

d

I

{)É€)()6lÈU'

ËË0)¡r(Ë

+çt)

6lé)tiÀ

0 I 4 5

20000

1 5000

1 0000

5000

0

2 3 4 5

Number of days

Figure 5.1.3. Observed mean squared displacement r and expected MSD - as a function

of the number of days following release for juvenile C. virgata in a. barley b. medic; and

juvenile C. acuta in c. barley, d. medic in September 2000. t=120.

I

0

153

c.

23Number of days


¡

420

0

d

CJ

É€)

É€)I6lÈ.tË€€)Lcl

daÀ

.Ë6)lra

2000

1000

d.

25000

20000

1 s000

10000

5000

0

3 5

¡

5410

T

Figure 5.13. Continued

ts4


5.4 DISCUSSION

5.4.1 Density release

Marked C. virgata adults were large and easy to detect, and it's recapture rates after two

days were high, betwe en 92o/o and 97o/o, and similar to recapture rates (87'/o and 9I%) by

Baker (1988a, b, d). For C. acuta the recapture rates were betweenSlo/o and97o/o over all

treatments. While the recapture rate for C. acuta was reasonably high, there was more

variation in recapture rate. C. acuta were smaller and thus, were harder to detect.

Furthermore, C. acuta tend to burrow into the soil, making detection harder. Despite this,

recapture rates for other invertebrates are routinely much lower than those obtained here.

For example, recapture rates of 3olo for Bactrocera tryoni (Carne, unpublished), and 0.03yo,

southern pine beetle (Turchin and Thoeny,7993) have been observed. This suggests that C.

virgata and C. ctcutq are not as dispersive and are easier to find than many other

invertebrates. As snails do not fly, they are therefore easier to relocate than flying

invertebrates. Snails are easy to mark, making them good subjects for studying individual

movement

The effect of density on dispersal varies. Baur and Baur (1988) found that snail density did

not affect dispersal in the minute land snail Punctum pygmaeum. However, density

dependent dispersal been shown in other species such as Cepaea nemoralis (Greenwood,

1974, Oosterhoff, 1977) and Chondrina clienta (Baur, 1992). Therefore the effect of

density varies with species, and may only become apparent at certain densities.

155


5.4.2 Mass-mark-release-recapture dispersal

The present MMRR experiment generated large volumes of complex data, however, taken

together a number of patterns emerged that are discussed below. Biased movement was

noticed in both C. virgata and C. acuta throughout the 2001 field season. While non-

random headings were seen across the season and across different treatments, non-random

movement was not always seen across replicates. Directed movement has been reported for

several other molluscs (Edelstam and Palmer, 1950; Wolda, 1963; Pollard, 1975; Peake,

1978; Johnson, 1981; Livshits, 1985; Baur and Gosteli, 1986, Baker, 1988b; Baker and

Yogelzang, 1988).

The direction in which snails moved was inconsistent, varying with snail species, days

after release, and between treatments. Therefore, it appears that the non-random movement

was not due to cues based on topography or the position of a landmark. However, it is not

possible to eliminate movement to a landmark, particularly as the snail's heading may vary

depending on when they move, which may also be correlated with temperature, rainfall or

time of day. That is, the snails may be moving towards the moon, for example, but the

relative position of the moon will change. Biased direction was noted in medic, barley and

canola seeded in unburnt soil, and in barley seeded in burnt soil. This biased direction was

unlikely to be the result of long-range cues. Snails in the barley and canola treatments were

too small and would be unlikely to detect cues such as a landmark in these microhabitats'

However, the medic remained relatively low throughout the season due to gtazing.

The non-random movement observed for C. virgata and C. acuta across treatments can

most likely be explained by the environmental structure. This may include the alignment of

156


crops, with nutrients and crop management practices being concentrated in these rows.

Furthermore, tyre compaction from machinery would occur when the soil was being

prepared for seeding, then again at seeding, and each time any chemicals were added by

vehicles. As these crops were sown in rows, there were corridors where compaction would

be concentrated in order to minimise damage to the crops. The rows between crops and the

compacted rows would have concentrated moisture from precipitation runoff. Additionally,

the rows in which crops were planted would have increased nutrients and organic matter in

the soil, which these snails feed upon (Pomeroy, 1966, 1967, 1969). While it is unknown

which of these factors were driving biased movement in C. virgata and C' acula, iI is

probable that these factors interacted with climatic variables such as rainfall, wind and

temperature, to have a large influence on snail movement and orientation. The vegetation

structure within different crops and pastures plays an important role in snail movement,

and these factors need to be investigated further. Furthermore, if snail movement is

correlated with the weather, then their direction of heading will change in response to

certain cues. Pomeroy ( 1 969) demonstrated that C. virgata is essentially nocturnal and its

activity is closely (positiveþ associated with moisture. This has been shown to also be the

case for the slug Arion ater (Lewts,1969b).

Crop type had an effect on the displacement of both C. virgata and C. acuta within the

season. Each of the crops was planted at the same spacing, however, once the crops grew,

they shaded the soil to different levels, providing different microclimates to the snails

(Geiger, 1965). Activity in land snails is known to be related to not only seasonal variation

but also to short term variation in weather conditions, snails being least active when

humidity is low (Cameron and Williamson, 1977). Additionally, slug and snail activity is

closely related to the daily variations of environmental factors, since locomotory activity

t57


usually takes place during the night when temperatures decrease and relative humidity

increases (Biannic et al, 7995). Decreasing temperatures have been shown to initiate

activity in the slug Arion ater (Dainton,l954a; Dainton and Write, 1985), however in the

snail Helix aspersa humidity was considered to be the main environmental factor

controlling activity (Biannic et al, 1995).

C. virgata and C. acuta showed different behavioural responses in different crop types'

However, in July, when the crops were smaller, both species moved further in crops that

were sown in burnt soil. This may be due to less ground cover, and therefore the snails

may have needed to travel further in order to find food and resting places. Individual

organisms interact in various ways and compete for food or space through direct

behavioural interactions (Kawata, 1993). When the crops were taller in September, C'

virgata dispersed a greater distance in barley grown on unburnt soil, compared with C.

acuta, which was dispersing greater distances in crops grown in burnt soil. In October,

both C. virgata and C. acuta were dispersing greater distances in crops grown in unburnt

soil, and the least distance in crops grown on burnt soil. By this time, the effect of the

stubble left on the unburnt soil may have been negligible as other plant material including

weeds and parts of the crop may have provided more food and sheltering resources. This

suggests that there is an interaction between the time of year and crop type in which the

snails were released. This interaction was shown in the mixed model analysis, and further

highlighted in the analyses of the individual snail releases in Chapter 6.

Directional movement of C. virgata and C. acuta may be influenced by crop type, crop

damage, food source, temperature and wind direction. However, Baker (1988c) found no

close association between movement of C. virgata and wind direction. Welby Q96a)

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showed that temperature was a controlling influence upon slug activity, but found little

relationship between slug activity and relative humidity. This is unusual in that the body

water lost in the production of mucus and by evaporation through the permeable

integument may limit slug movement. White (1959) observed that the activity of slugs

decreased when the temperature fell below 4.4oC. Barnes and Weil (1944; 1945) showed

that slug activity was not controlled by a single factor, but was a function of the changing

combination of factors. They concluded that activity was in part influenced by temperature

and that slug activity ultimately depended upon the presence of a film of moisture covering

the surfaces over which the slugs moved.

Visual cues are important in directing snail movements (Baker, 1988b). Peake (1978)

argued that snails move towards shapes silhouetted against the sky at night, such as trees

and shrubs that they use as resting places. Zanforlin (1976) showed lhat T. pisana were

skotatic (moving towards dark objects against a light background) preferring the largest

objects when given a choice in lab arenas. However, this would suggest that the snails

were moving with directional persistence, and therefore we would expect that headings

would be consistent for each step.

The movement of C. virgata and C. acuta were biased, however, the direction of biased

movement changed daily indicating that movement was not towards a specif,rc landmark.

The primary sense used by land snails for detection and location of objects is olfaction

(Voss, 2000). Anemotaxis (moving upwind in the presence of an odour cue) is one means

by which snails orientate by olfaction (Stanley et al, 1976; Farkas and Shorey, 1976;

Goodfriend, 1983; Baur and Gosteli, 1986). Positive anemotaxis in response to odours of

food or resting sites was proposed as the cause of an observed pattern of directional

159


migration in the land snail Cepaea nemoralis (Goodfriend, 1983) and Deroceras

reticulatum (Howling, 1991). It has been shown that Limax slugs using olfactory cues

move predominantly upwind to their diurnal resting sites (Cook, 1980). Cain (1977), Cain

and Cowie (1978), and Cameron (1978 and 1981) argued that sites of snail activity are

related to shell shape, tall snails preferring vertical surfaces, flat snails preferring

horizontal surfaces and globular snails showing little speciflrcity (Cameron, 1978).

The extent and direction of movement varied seasonally and between habitats, as was

observed by Baker (19S8b; 1992; 1998). Snails have been reported to move more in

autumn / winter than in spring, especially in crops (Baker, 1988b; 1989;1992; Baker and

Yogelzang, 1938). C. virgata and C. acuta moved further in autumn and spring than in

winter during the 2001 field season. Reasons for this conflict are most likely attributed to

climatic differences for seasons between years and the interaction among climatic

variables. Rainfall and temperature do not always conform to the calendar season' and

therefore, differences between years would be expected. Snails near the edges of crops

move towards adjacent pastures in autumn and winter (Baker, 1988b; 1989; 1992; Baker

and Vogelzang, 1988). Reasons for these biases are unknown. It has been suggested that

visual and olfactory cues could direct movements of snails (Peake, 1978; Chase and Croll,

1981). C. virgata has been shown to behave differently depending on the habitat into

which they were released (Cowie, 1980a). Reduction in the height of vegetation in pastures

in spring, seasonal grazing resulting in soil disturbance, plant damage and an increase in

animal dung may increase the invasion of snails into adjacent crops (Baker, 1992).

Goodhart (1962), found that the distribution of local populations of C. nemoral¡s shifted

gradually over time. Cameron and V/illiamson (1977) found that dispersal rates for Cepaea

160


nemoralis in the United Kingdom were highest in spring and early summer, when mating

activity (Cain and Currey, 1968; Wolda and Kreulen, 1973) and feeding were at a

maximum (Williamson, 1976). C. virgata move between adjacent fields of pasture and

crop in autumn, winter and spring (Baker, 1988b, c). The net displacement by C. virgata in

the present studywas nearlytwice that of C. acuta throughout the releases. This could be

attributed to the smaller foot size of C. acuta compared to C. virgata. Fot both species,

snails released in October moved half as far as those released in June. Both migration and

dispersal may lead to emigration of a pest fiom one crop and its eventual immigration into

another (Byrne et aL,2002). Slug activity was found to be pronounced on favourable nights

(Barnes and Weil, 1944; 1945) with slug activity greatest on warm nights when the soil

surface was moist (Barnes and Weil, 1945). This present study further highlights the

complex interactions that drive movement as described by Barnes and Weil, (1944;1945)'

The mean displacement for C. virgata and C. acuta followed a similar pattern between

treatments. The mean displacement in September was lower than in June, July, and

October. Reasons for this may be that in June the density and height of vegetation was

lower, which increased the response for snails to move and locate resources. By

September, the crops were high and the foliage dense, and therefore the snails did not need

to disperse as far to find food and shelter. The reduced movement in September was likely

to have been driven by the interaction between moisture and temperature. Heavy rainfall

was recorded in September, and the minimum temperature \Mas very low. Temperatures in

September were cooler than those in June, July or October, and therefore may have

inhibited movement by C. virgata and C. acuta. There was no difference in displacement

of snails in medic between June and October, as would be expected, as this treatment was

grazed, and therefore the height and density of this crop remained relatively stable. The

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greatest movement in canola, seeded in burnt soil, was October. The reasons for this are

unknown, as the crop was the same height as the canola in the unburnt soil at each time'

Therefore we can deduce that movement of C. virgala and C. acuta was determined by a

range of factors, including the climate (temperature and rainfall) and microhabitat into

which the snails were released. The factors that influence movement are further examined

in chapter 6.

Disturbance by marking animals can be a problem associated with MRR. For the dispersal

trials discussed in this chapter, snails \ryere removed from their microhabitat, marked, and

kept in plastic containers for 3-4 hours. This could influence the snail's subsequent

behaviour (Oggier et al, 1998). Cameron and Williamson (1977) demonstrated that MRR

caused disturbance, however in their study the snails were brought back to the lab and kept

for marking for two-four days. In contrast, in all experimental work presented in this

chapter, snails were collected, marked and released within eight hours, and had minimal

transport time (see also the analysis presented in chapter 6).

5.4.3 Individu al-mark-release-recapture dispersal

It was deduced that a greater understanding of snail movement, and the factors that drive

movement could be gained using IMRR. IMRR is a very practical and potentially powerful

approach to study movement of organisms (Turchin, 1998). It yields a more detailed

understanding of movement and the factors affecting it, than MMRR as it takes into

account individual movement rather than population movement as a whole. It is not known

whether animals that appear to be moving randomly are in fact moving randomly, each

individual could be the perfect automaton, rigidly reacting to environmental cues and its

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internal states in accordance with some set of behavioural rules (Turchin, 1997), thus

movement is directionally biased (tendency of individuals to move in a non-random

direction). Differences in local food availability, exposure to directional cues for

movement, suitability of microclimate or structural complexity of the vegetation in each

habitat type might explain these movements (Baker, 1988b).

An important point to keep in mind with IMRR studies is that typically only the start and

end points of each move are recorded (Turchin, 1997). Even if one 'biological' move

combines together several consecutive automation, the path that the snail took between

fixes is still unknown (Turchin, 1997 1998). The effects of fine-scale spatial variation in

movement cannot be analysed.

Directional bias and a bias in turning angle were seen in all treatments and across both

snail species. However, the direction in which snails headed and turned varied between

days, species and treatments. Therefore, given the non-random turning angle and direction

of heading for C. virgata and C. acuÍa, their dispersal is driven by one or more external

factors (Barnes and Weil, 1944). Between treatments, direction of heading and turning

angles are biased on the same days, however, the directions of bias differed between

species. Non-random heading and turning angles for each crop tlpe for both C. virgata and

C. acuta was not necessarily consistent across replicates. Turning angles and heading

direction were not biased until days four and five for C. virgata in June, coinciding with

rainfall events, similarto that seen in September. However, for C. acula, there was biased

heading and turning angles for June and July, and in September on days four and five.

Furthermore, in medic in September, there was no bias in turning angle or heading

direction. Separate factors or different thresholds may be driving the movement of C'

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virgata and, C. acuta. These factors could be climatic, particularly temperature (White,

1959; Welby, 1964) and moisture (Barnes and Weil, 1944; Rollo , 1991; Murphy, 2002)' lf

the factors driving movement were landscape features, then directional persistence would

be expected rather than directional bias. Juvenile C. virgata and C. acuta showed biased

heading and turning angles for each day across treatments'

Crop type, the month in which adult and juvenile C. virgata and C. acuta wete released,

and the interaction between release month and crop type affected snail movement. The

crop type into which adult C. virgata were released in June did not affect movement on a

given day, however, adult C. acuta released into medic moved further than those released

into barley. The crop type into which adult C. virgata were released in July, and adult and

juveniles were released in September, affected snail dispersal. Similarly the dispersal of

adult and juvenile C. acuta was affected by crop type in September. Over the season, both

adult and juvenile C. virgata and C. acuta dispersed further in the medic than those

released into barley regardless of the month in which the snails were released. In addition,

C. virgata and C. acuta adtlts moved the least distance in June. C. virgata dispersed the

greatest distance in July, and C. acuta adults in September, however, there was no data for

C. acuta dispersal in July, and therefore, it is unknown as to whether or not C. acuta would

have similarly dispersed a greater distance in July. This pattern of C. virgata moving

further in medic than barley \Mas seen across the field season, and may be due to a visual or

olfactory stimulus detected by snails. This stimulus may not be detectable to those snails in

the barley crop where the vegetation height and density would inhibit perceptions of more

distant cues. Crop type could affect snail movement as the food sources and resting

resources would vary. The foliage of the barley crop was denser and grew taller than the

medic, which was grazed and therefore kept relatively short. Additionally, snails released

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in the barley may have a less humid microhabitat due to the boundary layer at the soil

surface, than those released in medic, particularly in July and September, and would

therefore be expected to disperse lesser distances than those released in medic. The month

in which the snails were released is impoftant because it is correlated with rainfall and

temperature and are the focus of Chapter 6.

To determine the factors that are influencing population displacement, the factors that

affect individual movement should be assessed. However, a farmer or agronomist is

interested in what is happenin g aT a population level, and not an individual level.

Additionally, the total distance moved by individual snails is not always an accurate

indicator of the displacement of the population. This is highlighted in the juvenile C. acuta,

where analysis showed that juvenile C. acuta moved further in total distance moved over

the five days in medic than in barley, however, when looking at net displacement from the

release, juvenile C. acuta were further displaced from the release point in the barley than in

the medic. Measuring total movement on daily basis without including turning angles will

give rise to inaccurate predictions about population spread.

Distances moved by snails may be influenced by micro-climatic and substrate factors

(Baur and Baur, 1988). Mass mark recapture results show that C. virgata moved up to 200

cm within 24 hours, but with IMRR studies, C. virgata moved up to 150 cm in a given day.

C. virgata has been shown to move up to 300 cm in 24 hours (Cowie, 1980a). However, in

another study, C. virgata were found to move between l0 cm and 40 cm per day (Baker, .

1988e). C. virgata showed different behaviour depending onthe microhabitat in which it

was released. Distances moved by the snails followed similar trends through time. In the

present study, individual movement on day one tended to be greater than that seen on later

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days. Day one dispersal data could include behavioural afiefacts as marking of the snails

can interfere with movement. The process of handling and marking snails was found to

inhibit movement in Cepea nemoralis (Cameron and Carter, 1979), Helix aspersa (Dan

and Bailey, 1982) and Arianta arbustorum (Baur, 1992). Contrary to this however, Baker

(1988b) found that marking C. virgata had no effect on movement. In addition, crowding

was found to increase the dispersal rate of Cepea nemoralis (Cain and Currey, 1968,

Ooosterhoff, 1,977), decrease it in Helix aspersq (Greenwood,7974; Cameron and Carter,

1979;Dan and Bailey, 1982) and in A. arbustorum (Baur,1988b), and have no effect on

dispersal of Cepea nemoralis (Cameron and V/illiamson, 1977), C. virgata (Baker, 1988b)

andA. arbustorum (Baur and Baur, 1993). While snails moved the greatest distance on day

one in the present study, this may be a result of snails being marked, moved and disturbed.

This may be less of a problem by day two, when the snails are not affected and are moving

more naturally. However, by days three, four and five, which coincided with rainfall events

at each release time, movement for individual adult snails increased up to 150 cm per day.

The snails may also have been stimulated into moving through barometric change, and

therefore moving the day before a rainfall event occurred as was recorded for T. pisana by

Heller (1981).

It was important to determine not only the factors that drive movement of adult snails, but

also to investigate the factors that influence movement of juvenile snails. Juvenile snails

pose a greater threat at harvest time, as they are harder to detect and separate (or clean)

from grains. A similar biased pattern of dispersal was seen in juvenile snails to that seen in

the adult snails. However, juvenile snails moved twice as far as adult snails on each day;

this may be an adaptive means of emigration from their place of origin. They may also be

more susceptible to handling, and their movement may be a result of disturbance.

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However, if this were the case, then it would be expected that the juvenile snails would not

have consistent biased heading and turning angles. Baur and Baur (1988) found that the

mean displacement of the minute land snail Punctum pygmaeum was signiflrcantly

influenced (positively) by snail size. This has been noted in many other species including

Helminthoglypta arrosa, Arion ater (See Baur and B. Baur, 1988) and Monadenia

hillebrandi mariposa (Szlavecz,l986). Conversely, Pomeroy (1969) found that juvenile C.

virgala were more active and moved further than adults. However, there was no difference

noted in distances covered between adults and halÊgrown juveniles in several other snail

species (Hamilton and Wellington, 1981). Greater activity by juvenile snails than adult

snails does not seem to be a regular behaviour of terrestrial gastropods. No differences

were seen between adult and juvenile snails in Cerion bendalli (Woodruff and Gould,

1980), andArianta arbustorum (Baur and Baur, 1988)'

Distances moved by juvenile C. virgata and C. acuta may be influenced by finding

appropriate food resources. Abd El-Hamid (1996) found a variation between the different

ages of snails in locating different attractants or food sources, and that adults were more

efficient than juveniles at locating these resources. Similarly, Madsen (1992) found that

small Helisoma duryi and, Brtlinus truncatus appeared to be less efficient at locating food

than their larger conspecifics. This was attributed to a lower velocity of smaller snails'

Kpikpi and Thomas (1992) found that juvenile Biomphalaria glabrala snails were attracted

to sugars more than the adult stage and suggested this behavioural response \¡/as because

the sugars would be likely to be more important as a food source to the juveniles as their

mouths may not be adequately developed for ingesting solid food. In addition, the

chemoreceptor niche of older snails might be reduced because they may become more

discriminating in their response to chemical factors as a result of learning processes

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(Kpikpi and Thomas,1992). These differences might be attributed to the differences in the

nature of feeding behaviour as well as in the metabolism in these different snail species

(Abd El-Hamid, 1996). The differences in food preference between adult and juvenile in

many species of molluscs may explain the difference in dispersal behaviour of adult and

juvenile C. virgata and C. acuta in this present study.

There are a number of ways to describe the dispersal patterns of snails. Bias movement can

be determined from Rayleigh's z test, and the degree of angular variation and circular

deviation can be used to determine the spread of the snails. In addition, dispersal can be

described as a correlated random walk dependent on three parameters: number of steps,

step size, and distribution of random turning angles. Kareiva and Shigesada (1983) used

these parameters to predict the mean squared displacement distance (MSDD), (Byers,

2001). Simple diffusion, which predicts that the mean squared displacement (MSD)

increases linearly with time, is a good test to determine applicability of a correlated

random walk (Rudd and McEvoy, 1996; Turchin, 1998). The movement of individuals

over the five days in the present study did not conform to MSD. Rather, observed

movement rates varied over time, and the relationship between MSD and time varied with

snail age and treatment. Therefore, the CRW could not be used to describe the dispersal of

adult or juvenile C. virgala and C. acuta.

Dispersal rates depend on many factors, for example, species-specifrc characters such as

the mode of dispersal, mobility of individuals, and the ability and propensity to disperse

(Akçakaya and Baur, 1996). These factors determine the speed and ease with which

individuals search for and colonise empty patches. The results from this present study

showed that the dispersal behaviour of snails varied according to snail species and age

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class, and according to the time of year and the plant type in which the snails were

released. From this it would be expected that the degree of snail control would also vary

with these factors, and other factors that may be driving snail dispersal that were not

investigated. It has been shown that the success of control measures (including chemical

and cultural) against snails varies with soil type, vegetation, and prevailing wind conditions

such as temperature and humidity, soil moisture content and solar radiation (Akçakaya and

Baurr,7996). It varies daily with seasonal behaviour of the snails concerned, that is, where

and when they are active and feed, and how far they travel (Baker, 1986).

IMRR of adult and juvenile snails provided an insight into the factors that drive individual

snail movement. It is apparent that while biased movement was seen across adult and

juvenile C. virgala and C. acuta, in barley and medic treatments, that movement is

determined by climatic factors, particularly temperature and moisture. These factors are

dependent not only on the time of year in which the snails were released, but also as to

which crop the snails are moving in. It is also clear that adult and juvenile snails behave

differently, as do C. virgata and C. acuta to different stimuli. These factors are explored in

more depth in Chapter 6, however, it is clear that control measures against these snails

must be targeted more directly to the problem. That is, a farmer cannot expect to apply a

particular level of snail control, and manage different age classes and species of snails to

the same degree. He / she must take into account climatic conditions, and the dispersal

behaviour of particular snail populations in order to successfully manage his / her snail

problem

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Conclusion

Information on the movement of snails is critical to understanding the spatial spread,

dynamics, and genetic structure of their populations, as well as their interactions with other

species (Cronin et al, 2001). An understanding of dispersal can aid in the forecasting of

pest outbreaks (Loxdale et al. 1993). This is especially true if we need to predict these

occurrences or design management programs. Pest management decisions should take into

consideration quantitative information on dispersal of insect pests, but such information is

often lacking (Turchin and Thoeny, 1993). It is well understood that migration by pest

invertebrates is a phenomenon that impacts crop production.

While density did not have an effect on net displacement of snails after two days, it is

likely that handling and disturbing the snails did. Therefore, results obtained for day one in

all experiments needs to be treated with this in mind. The population dispersal data

(MMRR) provided important information on snail movement in different crop types and

treatments over the season, showing a bias in heading direction, however, this could not

provide detailed information into the factors that drive individual movement. Therefore,

IMRR was used which allowed for information on the effect of crop type and time of year,

as well as information on turning angles, distance moved and heading direction to be

obtained.

Understanding the factors that influence movement of individual snails, along with the

properties of chemical baits could lead to better control. For example, higher temperatures

may enhance the toxicity (Cragg and Vincen|, 1952) and attractiveness to the baits

(Crawford-Sidebothom, I970). Furthermore, from the field trials conducted in this study, it

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is known that C. virgata aîd C. acuta move further when the minimum temperatures are

mild, but movement is inhibited when too warrn or too cold. If snails were more active

when the baits are more effective (i.e. Metaldehyde is more effective when applied in dry

conditions, than under moist conditions, whereas methiocarb is more effective under moist

conditions than under drier conditions) and have enhanced toxicity, then control of snails

would be greater.

Calculating MSD provided an insight into how the snails are behaving with regard to

movement, that is, whether or not snail movement could be explained by simple diffusion

and thus a CRW. Therefore, a more complex simulation model was required; the IMRR

data are analysed with climatic data using mixed models. Factors that were important were

then used to build a model to simulate snail movement in the following chapter.

17I

Ecology of Mediterranean snails in Southern Australian ......1.4 UNDERSTANDING THE BIOLOGY AND...

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