population dynamics of the periwinkle littorina littorea (linnaeus, 1758) in the east frisian wadden...

IntroductionObjectives

MethodsResults

Conclusions

Population dynamics of the periwinkle Littorinalittorea (Linnaeus, 1758) in the East Frisian

Wadden SeaDiplomarbeit

Alexander Jüterbock

Animal Biodiversity and Evolutionary BiologyCarl von Ossietzky University Oldenburg

Supervisors: Prof. Dr. Gabriele Gerlach, Dr. Thomas Friedl

April 13, 2010

Alexander Jüterbock Population dynamics of the periwinkle


MethodsResults

Conclusions

Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions



MethodsResults

Conclusions

Populations get Connected by Dispersing LarvaeB

EN

THO

SP

LAN

KTO

N

Population 1 Population 3Population 2

adults adults adults



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae

Reef fish

Photo: Randall, J.E.Study: Gerlach et al., 2007



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae

Corals

Photo: Ronald L. ShimekStudy: Whitaker, 2004



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae

Gastropods

Photo: Keith HiscockStudy: Dupont et al., 2007



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae

Divergent selection



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae larvae larvae

Divergent selection



MethodsResults

Conclusions


EN

THO

SP

LAN

KTO

N



larvae larvae larvae

Divergent selection

Larval recruitment



MethodsResults

Conclusions

Hydrodynamics of the East Frisian Wadden Sea

a

15

10

5

0

km

0 5 10 15 20 25 30 35 40 45 50 55 60km

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 45 50 55 60

(cm/s)

b

15

10

5

0

km

0 5 10 15 20 25 30 35 40 45 50 55 60km

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 45 50 55 60

(cm/s)

Norderney Langeoog Spiekeroog

(Staneva et al., 2009)



MethodsResults

Conclusions

The Periwinkle’s Life Cycle Includes a PlanktotrophicLarva

(Fretter and Graham, 1962)

(Reid, 1996)

4–7 weeks



MethodsResults

Conclusions

Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions



MethodsResults

Conclusions

Main Objectives of the Study

ObjectivesLarval recruitment?Population preference?Morphological differentiation?Genetic differentiation?



MethodsResults

Conclusions

Larval RecruitmentPopulation PreferenceShell MorphologyPopulation Genetics

Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions



MethodsResults

Conclusions


Outline

3 MethodsLarval RecruitmentPopulation PreferenceShell MorphologyPopulation Genetics



MethodsResults

Conclusions


Larval Dispersal in the Wadden Sea was Simulated

2000

1500

1000

500

0

600

500

400

300

200

100

0

a

b

L1

W2

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge

Programmed by: Gräwe, U.



MethodsResults

Conclusions


Sampling Sites

0 500 1000kilometersN

EFWS



MethodsResults

Conclusions


Sampling Sites

0 50 100kilometers N

Borkum

NorderneyLangeoog

Wangerooge

B2

B2.2B1

N3N2 N1

L1 W1

W2



MethodsResults

Conclusions


Sampling Sites

0 1000 2000kilometers N

Woods HoleNew York

USA

CANADA



MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Conspecifics Aggregate on Hard Bottom Substrate

(Geller–Grimm, 2000)



MethodsResults

Conclusions


Snails of 2 Populations Aggregated in Basins

10 cm

60 cm60 cm

Population 1 Population 2



MethodsResults

Conclusions


Snails of 2 Populations Aggregated in Basins

10 cm

60 cm60 cm

60 cm

60cm Individual from population 1

Individual from population 2

1



MethodsResults

Conclusions


Analysis of Aggregation Experiments

. . . one hour later

10 cm

60 cm60 cm

1

23

4

5



- Population Preference Index PPI -



MethodsResults

Conclusions


Testing Snails in Olfactory Choice Flumes

22 cm

5 cm

Snail at startpositionStimulus waterfrom population 1

Stimulus waterfrom population 2

1



MethodsResults

Conclusions



22 cm

5 cm



1

. . . %

. . . %



MethodsResults

Conclusions



22 cm

5 cm



1

. . . %

. . . %

Wilcoxon signed-rank test



MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Measurements of the Shell

CL

SP

SW

LA

Linear discriminant analysis



MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Genetic Differentiation at Microsatellite Markers

48–55 individuals/population5 microsatellite lociDifferentiation index Dest,R package DEMEtics (Jüterbock et al., 2010)



MethodsResults

Conclusions


Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions



MethodsResults

Conclusions


Outline

4 ResultsLarval RecruitmentPopulation PreferenceShell MorphologyPopulation Genetics



MethodsResults

Conclusions


No Local Recruitment by Passive Drift in the EFWS

2000

1500

1000

500

0

600

500

400

300

200

100

0

a

b

L1

W2

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge




MethodsResults

Conclusions


No Local Recruitment by Passive Drift in the EFWS

. . . one week later

300

250

200

150

100

50

0

10

8

6

4

2

0

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge

a

b




MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Snails Prefer Conspecifics of the Own Population

Population-wise aggregation

PPI significant (p ≤ 0.1) in 6 of 17 tests

Attraction to volatile chemicalsNo significant preference in any of 18 tests



MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Populations Differ Morphologically

Shell morphology differsbetween . . .

Woods Hole – EFWSNorth coasts – SouthcoastsNorth coastsSouth coasts

Woods Hole

EFWS

Wilks’ Lambda = 0.867, p < 0.001 ***



MethodsResults

Conclusions





Borkum

NorderneyLangeoog

Wangerooge

Wilks’ Lambda = 0.802, p < 0.001 ***



MethodsResults

Conclusions





Borkum

NorderneyLangeoog

Wangerooge

Wilks’ Lambda = 0.135, p < 0.001 ***



MethodsResults

Conclusions





Borkum

NorderneyLangeoog

Wangerooge

Wilks’ Lambda = 0.731, p < 0.001 ***



MethodsResults

Conclusions


Outline




MethodsResults

Conclusions


Genetic Distance . . .

. . . between Woods Hole and East Frisian populations

Dest = 0.033–0.057 ***p ≤ 0.05

Woods Hole

EFWS



MethodsResults

Conclusions


Genetic Distance . . .

. . . between islands

Dest = -0.007–0.001p > 0.05 Borkum

NorderneyLangeoog

Wangerooge



MethodsResults

Conclusions

Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions



MethodsResults

Conclusions

Do the Results Indicate Reproductive Isolation?

ObjectivesLarval recruitment?Population preference?Morphologicaldifferentiation?Genetic differentiation?

Unanswered questionsLarval behavior?Intrinsic differencesRecognition cues?Assortative mating?Expressed loci?Phenotypic plasticity?



MethodsResults

Conclusions

Do the Results Indicate Reproductive Isolation?

Overall conclusion



MethodsResults

Conclusions

Acknowledgements

Gabriele Gerlach

Thomas Glatzel

Thomas Friedl

Ulf Gräwe

Peter Harmand

Achim Wehrmann

Anke Müller

Andreas Sommer

Philipp Krämer

Jana Deppermann

Cornelia Hinz

Jelle Atema

René Spierling

Elke Frahmann

Marén BökampFunded by the

NiedersächsischeWattenmeerstiftung


Appendix

Further ReadingIntroductionMethodsResults

For Further Reading I

Reid, D.G. (1996)Systematics and Evolution of Littorina.The Ray Society, London.

Cowen, R.K. & Sponaugle, S. (2009)Larval dispersal and marine population connectivityAnnual Review of Marine Science 1:443–466.


Appendix


For Further Reading II

Staneva, J.; Stanev, E.V.; Wolff, J.-O.; Badewien, T.H.;Reuter, R.; Flemming, B.; Bartholomä, A. & Bolding, K.(2009)Hydrodynamics and sediment dynamics in the GermanBight. A focus on observations and numerical modelling inthe East Frisian Wadden Sea.Continental Shelf Research 29(1):302–319.

Jost, L. (2008)Gst and its relatives do not measure differentiation.Molecular Ecology 17(18):4015–4026.


Appendix


Residual Current in the German Bight

55.4N

55.2N

55.0N

54.8N

54.6N

54.4N

54.2N

54.0N

53.8N

53.6N

53.4N

6.3E

6.6E

6.9E

7.2E

7.5E

7.8E

8.1E

8.4E

8.7E

9.0E

(m/s)

0.160.140.120.100.080.060.040.02

0.25

(Staneva et al., 2009)


Appendix


L. littorea Occurs on Both Sides of the Atlantic

(Reid, 1996)


Appendix


The Periwinkle’s Life Cycle Includes a PlanktotrophicLarva

a b| ~



(Reid, 1996)

5–6 days

4–7 weeks

12–18 months

1–12 hoursafter fertilization


Appendix


Sampled Snails Were Kept in Aquaria


Appendix


Snails Were Individually Characterized

CL

Shell height Barnacle fouling Sex


Appendix


Snails Were Individually Characterized

Shell height Barnacle fouling Sex


Appendix


Aggregation Experiments Were Performed in SpecialBasins

10 cm

60 cm60 cm

60 cm

60cm Individual from population 1


1


Appendix


Detailed Analysis of Aggregation experiments

. . . one hour later

10 cm

60 cm60 cm

. . . 15 tests at least


Appendix



10 cm

60 cm60 cm

1

23

4

5

Are certain types ofconspecifics preferred?

Snails of the samepopulationSnails of the same sexSnails of the same size


Appendix



10 cm

60 cm60 cm

1

23

4

5



- PPI -




Appendix



10 cm

60 cm60 cm

|||||

1

|||2

|

|3

~~~ 4

~~~~5

~

~

- Sex-PI -




Appendix



10 cm

60 cm60 cm

1

23

4

5

- Size-PI -




Appendix



10 cm

60 cm60 cm

1

23

4

5

PPI and Size-PI, both high




Appendix


Defining the Population Preference Index

Population mixture

p = var =

Real population preference

p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p =1.0 var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p =1.0 var =0.000


Appendix



Population mixture

p =0.5 PPI =0.000


p =0.5 PPI =0.263

Ambiguous

p =1.0 PPI =0.000


Appendix


Defining the Population Preference Index in Detail

Population mixture

p = var =


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =5

10 ∗10+ 510 ∗10

20var =


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =( 5

10−0.5)2∗10+( 510−0.5)2∗10

19


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p = var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =1010 ∗10+ 0

10 ∗1020

var =

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =( 10

10−0.5)2∗10+( 010−0.5)2∗10

19

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p = var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p =1010 ∗10

10var =


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p =1.0 var =( 10

10−1)2∗109


Appendix



Population mixture

p =0.5 var =0.000


p =0.5 var =0.263

Ambiguous

p =1.0 var =0.000


Appendix



Population mixture

p =0.5 PPI =0.000


p =0.5 PPI =0.263

Ambiguous

p =1.0 PPI =0.000


Appendix


Snails Aggregate Assortatively

Borkum

NorderneyLangeoog

Wangerooge

B1 B2 N3 N1 N2 L1 W1 W2 WH

B1

B2

N3

N1

N2

L1

W1

W2

****

·**

··

· **

Population preference

significanceSize preference

significance

· p≤0.10,* p≤0.05, ** p≤0.01,*** p≤0.001


Appendix


Simplified Monte Carlo Simulation

10 cm

60 cm60 cm

1

23

4

5



Appendix



10 cm

60 cm60 cm

1

23

4

5


Random allocationRandom allocation


Appendix



10 cm

60 cm60 cm

1

23

4

5


Appendix



10 cm

60 cm60 cm

1

23

4

5

Calculation of PPI


Appendix



10 cm

60 cm60 cm

1

23

4

5

A histogram of PPI values

Mean PPI

Fre

quen

cy

0.00 0.02 0.04 0.06 0.08 0.10

0

20

40

60

80

100100

80

60

40

20

0

Freq

uenc

y

0.00 0.02 0.04 0.06 0.08 0.10

Mean PPI

Critical value

90% < 0.068

significantnot significant


Appendix


Detailed Monte Carlo Simulation

10 cm

60 cm60 cm

1

23

4

5

~~|~|||~~| ~|~|~||~|~


Appendix



10 cm

60 cm60 cm

1

23

4

5

~~|~|||~~| ~|~|~||~|~



Appendix



10 cm

60 cm60 cm

~||~| 1

||~ 2

|

| 3

~|~4

~~|~5

~|

~


Appendix



10 cm

60 cm60 cm

~||~| 1

||~ 2

|

| 3

~|~4

~~|~5

~|

~

Calculation of PPI, Sex-PI and Size-PI


Appendix



10 cm

60 cm60 cm

1

23

4

5

~~|~|||~~| ~|~|~||~|~

1000-fold repetition


Appendix



10 cm

60 cm60 cm

1

23

4

5

~~|~|||~~| ~|~|~||~|~



Appendix



10 cm

60 cm60 cm

|~|~~ 1

|~|2

|

| 3

~|~4

~~|~5

|~

|

1000-fold calculation of PPI, Sex-PI and Size-PI


Appendix



10 cm

60 cm60 cm

|~|~~ 1

|~|2

|

| 3

~|~4

~~|~5

|~

|

A histogram of PPI values

Mean PPI

Fre

quen

cy

0.00 0.02 0.04 0.06 0.08 0.10

0

20

40

60

80

100100

80

60

40

20

0

Freq

uenc

y

0.00 0.02 0.04 0.06 0.08 0.10

Mean PPI

Critical value

90% < 0.068

significantnot significant


Appendix


Testing Snails in Olfactory Flumes

22 cm

5 cm



1


Appendix


Testing Snails in Olfactory Flumes in Detail

22 cm

5 cm

Stimulus water B

Stimulus water A

1


Appendix



22 cm

5 cm

Stimulus water A

Stimulus water B

1

1


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

1


Appendix



22 cm

5 cm

Stimulus water A

Stimulus water B

1

1

1


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

1

1


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

1

2


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

1

3


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

75%

25%


Appendix



22 cm

5 cm

Stimulus water B

Stimulus water A

1

Difference75%−25% = 50%


Appendix



15 Differences50%25%...0%

Wilcoxon signed-ranktest


Appendix


Allometric correction

Arithmetic plot

0 2 4 6 8 10 12 140

2

4

6

8

10

12

14

x = shell length (cm)

y=

shel

lw

idth

(cm

)y = 0.13 ∗ x1.32


Appendix



Logarithmic plot

−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3

log10(x) = log10(shell length (cm))

log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

log10(y) = log10(0.13) + 1.32 ∗ log10(x)


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

log10(y) = log10(0.13)+1.32∗log10(x)

1

1.32 1.321 = 1.32

b: slope = allometric coefficient


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

log10(y) = log10(0.13)+1.32∗log10(x)

1

1.32 1.321 = 1.32


a: intersection of y-axis when x = 0


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

log10(y) = log10(0.13)+1.32∗log10(x)

1

1.32 1.321 = 1.32



log(y) = log(a)+b∗log(x)


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

log10(y) = log10(0.13)+1.32∗log10(x)

1

1.32 1.321 = 1.32



log(y) = log(a)+b∗log(x)

log(a) = log(y)−b∗log(x)


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

)) log(a) = log(y)−b∗log(x)


Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of x



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of xlog(x)



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of xlog(x)

Correctionlog(a) = log(y)−b∗(log(x)−log(x))



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of xlog(x)

Correctionlog(a) = log(y)−b∗(log(x)−log(x))log(a) = log(y)−b∗(log(x)−log(x))



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of xlog(x)


log(a) = log(y)−b∗(log(x)−log(x))



Appendix



−3 −2 −1 0 1 2 3

−3

−2

−1

0

1

2

3


log 1

0(y)

=lo

g 10(

shel

lw

idth

(cm

))

spread of x

x mean of xlog(x)






Appendix


Genetic Differentiation at Microsatellite Markers 1

Pop1 Pop2


Appendix



Pop1 Pop2

DNA extraction


Appendix



Pop1 Pop2

DNA extractionPCR


Appendix



Pop1 Pop2

-

+

DNA extractionPCR

gel electrophoresis


Appendix



Pop1 Pop2

-

+

DNA extractionPCR

gel electrophoresis

178

212

162


Appendix



Pop1 Pop2

-

+

DNA extractionPCR

gel electrophoresis

178

212

162

Pop1 Pop2allele1 allele2 allele1 allele2

178 178 212 162


Appendix



Pop1 Pop2

-

+

DNA extractionPCR

gel electrophoresis

178

212

162


178 178178 234234 234234 178... ...... ...... ...

212 162162 162212 212212 162... ...... ...... ...


Appendix



Pop1 Pop2

-

+

DNA extractionPCR

gel electrophoresis

178

212

162


178 178178 234234 234234 178... ...... ...... ...

212 162162 162212 212212 162... ...... ...... ...

Differentiation index Dest


Appendix



CATGTA


Appendix



CATCATCATCATCATCATGTAGTAGTAGTAGTAGTA


Appendix



GTCTCAGC CATCATCATCATCATCATACATCGACCAGAGTCG GTAGTAGTAGTAGTAGTATGTAGCTG


Appendix




Repeat no.

12


Appendix




Repeat no.

12

9


Appendix




Repeat no.

12

9

15

15


Appendix




Repeat no.

12

9

15

15

amplification byPCR


Appendix




Repeat no.

12

9

15

15

15

12

9

gelelectrophoresis


Appendix




Repeat no.

12

9

15

15

15

12

9


Appendix




Repeat no.

12

9

15

15

15

12

9

15

9 12


Appendix




Repeat no.

12

9

15

15

15

12

9

15

9 12

Pop1165 165230 165230 230165 230230 230165 165165 165230 165

Pop2170 170198 170198 198170 198198 198170 170170 170198 170


Appendix




Repeat no.

12

9

15

15

15

12

9

15

9 12

Pop1165 165230 165230 230165 230230 230165 165165 165230 165

Pop2170 170198 170198 198170 198198 198170 170170 170198 170

Difference Dest


Appendix


Snails Prefer Conspecifics of the own Population

Population-wise aggregation

PPI significant (p ≤ 0.1) in 6 of 17 tests

Sex-bias aggregation

~~~~~~~~~~ |||||||||| Sex-PI significant (p ≤ 0.1) in 0 of 17 tests

Size-wise aggregation

Size-PI significant (p ≤ 0.1) in 2 of 17 tests


Appendix



Populationsdiffer

intrinsically


Appendix



. . . aggregation frequencyincreasesduring the

mating season


Appendix


Snails do not Prefer any Volatile ChemicalsP

refe

renc

e (%

)

−0.6

−0.4

−0.2

0.0

0.2

0.4

0.6

B2 −

L1

L1 −

B2

B2 −

N1

N1 −

B2

N1 −

L1

L1 −

N1

N2 −

N3

N3 −

N2

W1

− B2

B2 −

W1

W1

− L1

L1 −

W1

W1

− N1

N1 −

W1

W2

− N2

N2 −

W2

WH −

B2.

2

B2.2

− W

H

N1ma

− N1f

e

N1fe

− N1m

a

B1u −

B1m

B1m −

B1u

N1 −

Sw

0.93 0.32 0.54 0.47 0.59 0.62 1 0.22 0.12 0.19 0.81 0.58 0.91 1 0.99 0.22 1 0.43 0.19 0.76 0.52 0.1 0.59

own

other

.0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Pre

fere

nce

(%) ow

not

her

B2–L1

L1–B

2

B2–N1

N1–B2

N1–L1

L1–N

1

N2–N3

N3–N2

W1–

B2

B2–W

1

W1–

L1

L1–W

1

W1–

N1

N1-W

1

W2–

N2

N2–W

2

WH–B

2.2

B2.2–W

H

N1ma–

N1fe

N1fe–N

1ma

B1u–B

1t

B1t–B1u

N1–Sw


Appendix



refe

renc

e (%

)

−0.6

−0.4

−0.2

0.0

0.2

0.4

0.6

B2 −

L1

L1 −

B2

B2 −

N1

N1 −

B2

N1 −

L1

L1 −

N1

N2 −

N3

N3 −

N2

W1

− B2

B2 −

W1

W1

− L1

L1 −

W1

W1

− N1

N1 −

W1

W2

− N2

N2 −

W2

WH −

B2.

2

B2.2

− W

H

N1ma

− N1f

e

N1fe

− N1m

a

B1u −

B1m

B1m −

B1u

N1 −

Sw

0.93 0.32 0.54 0.47 0.59 0.62 1 0.22 0.12 0.19 0.81 0.58 0.91 1 0.99 0.22 1 0.43 0.19 0.76 0.52 0.1 0.59

own

other

.0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Pre

fere

nce

(%) ow

not

her

B2–L1

L1–B

2

B2–N1

N1–B2

N1–L1

L1–N

1

N2–N3

N3–N2

W1–

B2

B2–W

1

W1–

L1

L1–W

1

W1–

N1

N1-W

1

W2–

N2

N2–W

2

WH–B

2.2

B2.2–W

H

N1ma–

N1fe

N1fe–N

1ma

B1u–B

1t

B1t–B1u

N1–Sw

Population preference


Appendix



refe

renc

e (%

)

−0.6

−0.4

−0.2

0.0

0.2

0.4

0.6

B2 −

L1

L1 −

B2

B2 −

N1

N1 −

B2

N1 −

L1

L1 −

N1

N2 −

N3

N3 −

N2

W1

− B2

B2 −

W1

W1

− L1

L1 −

W1

W1

− N1

N1 −

W1

W2

− N2

N2 −

W2

WH −

B2.

2

B2.2

− W

H

N1ma

− N1f

e

N1fe

− N1m

a

B1u −

B1m

B1m −

B1u

N1 −

Sw

0.93 0.32 0.54 0.47 0.59 0.62 1 0.22 0.12 0.19 0.81 0.58 0.91 1 0.99 0.22 1 0.43 0.19 0.76 0.52 0.1 0.59

own

other

.0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Pre

fere

nce

(%) ow

not

her

B2–L1

L1–B

2

B2–N1

N1–B2

N1–L1

L1–N

1

N2–N3

N3–N2

W1–

B2

B2–W

1

W1–

L1

L1–W

1

W1–

N1

N1-W

1

W2–

N2

N2–W

2

WH–B

2.2

B2.2–W

H

N1ma–

N1fe

N1fe–N

1ma

B1u–B

1t

B1t–B1u

N1–Sw

Sex preference


Appendix



refe

renc

e (%

)

−0.6

−0.4

−0.2

0.0

0.2

0.4

0.6

B2 −

L1

L1 −

B2

B2 −

N1

N1 −

B2

N1 −

L1

L1 −

N1

N2 −

N3

N3 −

N2

W1

− B2

B2 −

W1

W1

− L1

L1 −

W1

W1

− N1

N1 −

W1

W2

− N2

N2 −

W2

WH −

B2.

2

B2.2

− W

H

N1ma

− N1f

e

N1fe

− N1m

a

B1u −

B1m

B1m −

B1u

N1 −

Sw

0.93 0.32 0.54 0.47 0.59 0.62 1 0.22 0.12 0.19 0.81 0.58 0.91 1 0.99 0.22 1 0.43 0.19 0.76 0.52 0.1 0.59

own

other

.0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Pre

fere

nce

(%) ow

not

her

B2–L1

L1–B

2

B2–N1

N1–B2

N1–L1

L1–N

1

N2–N3

N3–N2

W1–

B2

B2–W

1

W1–

L1

L1–W

1

W1–

N1

N1-W

1

W2–

N2

N2–W

2

WH–B

2.2

B2.2–W

H

N1ma–

N1fe

N1fe–N

1ma

B1u–B

1t

B1t–B1u

N1–Sw

Control for effect oflabel color


Appendix



refe

renc

e (%

)

−0.6

−0.4

−0.2

0.0

0.2

0.4

0.6

B2 −

L1

L1 −

B2

B2 −

N1

N1 −

B2

N1 −

L1

L1 −

N1

N2 −

N3

N3 −

N2

W1

− B2

B2 −

W1

W1

− L1

L1 −

W1

W1

− N1

N1 −

W1

W2

− N2

N2 −

W2

WH −

B2.

2

B2.2

− W

H

N1ma

− N1f

e

N1fe

− N1m

a

B1u −

B1m

B1m −

B1u

N1 −

Sw

0.93 0.32 0.54 0.47 0.59 0.62 1 0.22 0.12 0.19 0.81 0.58 0.91 1 0.99 0.22 1 0.43 0.19 0.76 0.52 0.1 0.59

own

other

.0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Pre

fere

nce

(%) ow

not

her

B2–L1

L1–B

2

B2–N1

N1–B2

N1–L1

L1–N

1

N2–N3

N3–N2

W1–

B2

B2–W

1

W1–

L1

L1–W

1

W1–

N1

N1-W

1

W2–

N2

N2–W

2

WH–B

2.2

B2.2–W

H

N1ma–

N1fe

N1fe–N

1ma

B1u–B

1t

B1t–B1u

N1–Sw

Own population –seawater


Appendix


Snails do not Prefer any Volatile Chemicals

Populationsare

not discriminatedby

volatile chemicals


Appendix


Results of Discriminant analyzes

EFWS – Woods Hole

9

8

7

6

5

4

3

2

-2 -1 0 1 2 3 4 5 6 7

Can

onic

al2

Canonical 1

-SP (Spire height)

Nor

thA

mer

ica

Eur

ope

Continent

North AmericaEurope

Wilks’ Lambda: 0.867p < 0.001 ***significant influence: SP


Appendix



North coasts – South coasts

10

9

8

7

6

5

4

3

2

Can

onic

al2

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5Canonical 1

+CL (Columellar length)-LA (Length of aperture

sout

h

nort

h

Sidenorthsouth

Wilks’ Lambda: 0.802

p < 0.001 ***

significant influence: CL > LA


Appendix



Within north coasts

12

11

10

9

8

7

6

5

4

3

Can

onic

al2

-SP

(Spi

rehe

ight

)-C

L(C

olum

ella

rlen

gth)

-7 -6 -5 -4 -3 -2 -1 0Canonical 1

+SP (Spire height)-CL (Columellar length)

Wan

gero

oge

Bor

kum

Nor

dern

ey

PlaceBorkum

Wangerooge

Wilks’ Lambda: 0.135

p < 0.001 ***

significant influence: SP > CL

Norderney


Appendix



Within south coasts

6

5

4

3

2

1

0

-1

-2

Can

onic

al2

-CL

(Col

umel

larl

engt

h)+S

W(S

hell

wid

th)

-LA

(Len

gth

ofap

ertu

re)

-SP

(Spi

rehe

ight

)

7 8 9 10 11 12 13 14 15 16 17 18 19Canonical 1

+CL (Spire height)-SW (Shell width)+LA (Length of aperture)+SP (Spire height)

Nor

dern

ey

Lang

eoog

Wan

gero

oge

Bor

kum

PlaceBorkumLangeoogNorderneyWangerooge

Wilks’ Lambda: 0.731p < 0.001 ***significant influence: CL > SW > LA > SP


Appendix



Sexes

4

3

2

1

0

-1

-2

-3

-4

-5

Can

onic

al2

3 4 5 6 7 8 9 10 11 12Canonical 1

mal

efe

mal

e

Sex

malefemale

Wilks’ Lambda: 0.985p < 0.277


Appendix


Genetic (Dest) and Geographic (km) Distance

B2 W1 N2 WHB2 . . . 0.011 -0.007 0.033 *W1 82.5 . . . 0.006 0.056 **N2 38.0 39.9 . . . 0.057 *

WH 5662.8 5730.7 5692.3 . . .


Appendix



B2 W1 N2 WHB2 . . . 0.011 -0.007 0.033 *W1 82.5 . . . 0.006 0.056 **N2 38.0 39.9 . . . 0.057 *

WH 5662.8 5730.7 5692.3 . . .

Borkum

NorderneyLangeoog

Wangerooge

Within the EFWS


Appendix



B2 W1 N2 WHB2 . . . 0.011 -0.007 0.033 *W1 82.5 . . . 0.006 0.056 **N2 38.0 39.9 . . . 0.057 *

WH 5662.8 5730.7 5692.3 . . . Woods Hole

EFWS

Between the EFWS and Woods Hole


Appendix



Wadden SeaPopulations

arenot differentiated

atneutral loci
