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

Outline

1 Introduction

2 Objectives

3 Methods

4 Results

5 Conclusions

MethodsResults

Conclusions

Populations get Connected by Dispersing LarvaeB

Population 1 Population 3Population 2

adults adults adults

MethodsResults

Conclusions

larvae

MethodsResults

Conclusions

larvae

Reef fish

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

MethodsResults

Conclusions

larvae

Corals

Photo: Ronald L. ShimekStudy: Whitaker, 2004

MethodsResults

Conclusions

larvae

Gastropods

Photo: Keith HiscockStudy: Dupont et al., 2007

MethodsResults

Conclusions

larvae

Divergent selection

MethodsResults

Conclusions

larvae larvae larvae

Divergent selection

MethodsResults

Conclusions

larvae larvae larvae

Divergent selection

Larval recruitment

MethodsResults

Conclusions

Hydrodynamics of the East Frisian Wadden Sea

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)

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

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)

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)

MethodsResults

Conclusions

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)

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)

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

MethodsResults

Conclusions

MethodsResults

Conclusions

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

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge

Programmed by: Gräwe, U.

MethodsResults

Conclusions

Sampling Sites

0 500 1000kilometersN

MethodsResults

Conclusions

Sampling Sites

0 50 100kilometers N

Borkum

NorderneyLangeoog

Wangerooge

B2.2B1

N3N2 N1

MethodsResults

Conclusions

Sampling Sites

0 1000 2000kilometers N

Woods HoleNew York

CANADA

MethodsResults

Conclusions

Outline

MethodsResults

Conclusions

Conspecifics Aggregate on Hard Bottom Substrate

(Geller–Grimm, 2000)

MethodsResults

Conclusions

Snails of 2 Populations Aggregated in Basins

60 cm60 cm

Population 1 Population 2

MethodsResults

Conclusions

60 cm60 cm

60cm Individual from population 1

Individual from population 2

MethodsResults

Conclusions

60 cm60 cm

MethodsResults

Conclusions

60 cm60 cm

MethodsResults

Conclusions

Analysis of Aggregation Experiments

. . . one hour later

60 cm60 cm

- Population Preference Index PPI -

MethodsResults

Conclusions

Testing Snails in Olfactory Choice Flumes

Snail at startpositionStimulus waterfrom population 1

Stimulus waterfrom population 2

MethodsResults

Conclusions

. . . %

MethodsResults

Conclusions

. . . %

Wilcoxon signed-rank test

MethodsResults

Conclusions

Outline

MethodsResults

Conclusions

Measurements of the Shell

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

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge

MethodsResults

Conclusions

No Local Recruitment by Passive Drift in the EFWS

. . . one week later

Baltrum

LangeoogSpiekeroog

Wangerooge

Baltrum

LangeoogSpiekeroog

Wangerooge

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

Snails Prefer Conspecifics of the Own Population

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

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

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

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

MethodsResults

Conclusions

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

0.160.140.120.100.080.060.040.02

Appendix

L. littorea Occurs on Both Sides of the Atlantic

(Reid, 1996)

Appendix

a b| ~

(Reid, 1996)

5–6 days

4–7 weeks

12–18 months

1–12 hoursafter fertilization

Appendix

a b| ~

(Reid, 1996)

5–6 days

4–7 weeks

12–18 months

Appendix

a b| ~

(Reid, 1996)

5–6 days

4–7 weeks

12–18 months

Appendix

Sampled Snails Were Kept in Aquaria

Appendix

Snails Were Individually Characterized

Shell height Barnacle fouling Sex

Appendix

Aggregation Experiments Were Performed in SpecialBasins

60 cm60 cm

Appendix

60 cm60 cm

Appendix

60 cm60 cm

Appendix

Detailed Analysis of Aggregation experiments

. . . one hour later

60 cm60 cm

. . . 15 tests at least

Appendix

60 cm60 cm

Are certain types ofconspecifics preferred?

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

Appendix

60 cm60 cm

- PPI -

Appendix

60 cm60 cm

- Sex-PI -

Appendix

60 cm60 cm

- Size-PI -

Appendix

60 cm60 cm

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 = 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 = 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 = 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 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 =

Ambiguous

p = var =

Appendix

Population mixture

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

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

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

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 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

Population preference

significanceSize preference

significance

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

Appendix

Simplified Monte Carlo Simulation

60 cm60 cm

Appendix

60 cm60 cm

Random allocationRandom allocation

Appendix

60 cm60 cm

Appendix

60 cm60 cm

Appendix

60 cm60 cm

Calculation of PPI

Appendix

60 cm60 cm

A histogram of PPI values

Mean PPI

0.00 0.02 0.04 0.06 0.08 0.10

100100

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

60 cm60 cm

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

Appendix

60 cm60 cm

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

Appendix

60 cm60 cm

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

Appendix

60 cm60 cm

~||~| 1

Appendix

60 cm60 cm

~||~| 1

Calculation of PPI, Sex-PI and Size-PI

Appendix

60 cm60 cm

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

1000-fold repetition

Appendix

60 cm60 cm

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

Appendix

60 cm60 cm

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

Appendix

60 cm60 cm

|~|~~ 1

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

Appendix

60 cm60 cm

|~|~~ 1

A histogram of PPI values

Mean PPI

0.00 0.02 0.04 0.06 0.08 0.10

100100

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

Appendix

Testing Snails in Olfactory Flumes in Detail

Stimulus water B

Stimulus water A

Appendix

Stimulus water A

Stimulus water B

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water A

Stimulus water B

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water B

Stimulus water A

Appendix

Stimulus water B

Stimulus water A

Difference75%−25% = 50%

Appendix

15 Differences50%25%...0%

Wilcoxon signed-ranktest

Appendix

Allometric correction

Arithmetic plot

0 2 4 6 8 10 12 140

x = shell length (cm)

)y = 0.13 ∗ x1.32

Appendix

Logarithmic plot

−3 −2 −1 0 1 2 3

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

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

Appendix

−3 −2 −1 0 1 2 3

log10(y) = log10(0.13)+1.32∗log10(x)

1.32 1.321 = 1.32

b: slope = allometric coefficient

Appendix

−3 −2 −1 0 1 2 3

log10(y) = log10(0.13)+1.32∗log10(x)

1.32 1.321 = 1.32

a: intersection of y-axis when x = 0

Appendix

−3 −2 −1 0 1 2 3

log10(y) = log10(0.13)+1.32∗log10(x)

1.32 1.321 = 1.32

log(y) = log(a)+b∗log(x)

Appendix

−3 −2 −1 0 1 2 3

log10(y) = log10(0.13)+1.32∗log10(x)

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

)) log(a) = log(y)−b∗log(x)

Appendix

−3 −2 −1 0 1 2 3

Appendix

−3 −2 −1 0 1 2 3

Appendix

−3 −2 −1 0 1 2 3

spread of x

Appendix

−3 −2 −1 0 1 2 3

spread of x

x mean of x

Appendix

−3 −2 −1 0 1 2 3

spread of x

x mean of xlog(x)

Appendix

−3 −2 −1 0 1 2 3

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

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

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

spread of x

x mean of xlog(x)

Appendix

−3 −2 −1 0 1 2 3

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

Appendix

Pop1 Pop2

DNA extractionPCR

gel electrophoresis

Appendix

Pop1 Pop2

DNA extractionPCR

gel electrophoresis

Pop1 Pop2allele1 allele2 allele1 allele2

178 178 212 162

Appendix

Pop1 Pop2

DNA extractionPCR

gel electrophoresis

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

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

Appendix

Pop1 Pop2

DNA extractionPCR

gel electrophoresis

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

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

Differentiation index Dest

Appendix

CATGTA

Appendix

CATCATCATCATCATCATGTAGTAGTAGTAGTAGTA

Appendix

CATCATCATCATCATCATGTAGTAGTAGTAGTAGTA

Appendix

GTCTCAGC CATCATCATCATCATCATACATCGACCAGAGTCG GTAGTAGTAGTAGTAGTATGTAGCTG

Appendix

Repeat no.

Appendix

Repeat no.

Appendix

Repeat no.

Appendix

Repeat no.

amplification byPCR

Appendix

Repeat no.

gelelectrophoresis

Appendix

Repeat no.

Appendix

Repeat no.

Appendix

Repeat no.

Appendix

Repeat no.

Pop1165 165230 165230 230165 230230 230165 165165 165230 165

Pop2170 170198 170198 198170 198198 198170 170170 170198 170

Appendix

Repeat no.

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

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

−0.6

−0.4

−0.2

B2 −

L1 −

B2 −

N1 −

L1 −

N2 −

N3 −

− B2

B2 −

− L1

L1 −

− N1

N1 −

− N2

N2 −

WH −

− N1f

− N1m

B1u −

B1m −

N1 −

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

(%) ow

B2–L1

L1–B

B2–N1

N1–B2

N1–L1

L1–N

N2–N3

N3–N2

B2–W

L1–W

N2–W

WH–B

B2.2–W

N1ma–

N1fe–N

B1u–B

B1t–B1u

N1–Sw

Appendix

−0.6

−0.4

−0.2

B2 −

L1 −

B2 −

N1 −

L1 −

N2 −

N3 −

− B2

B2 −

− L1

L1 −

− N1

N1 −

− N2

N2 −

WH −

− N1f

− N1m

B1u −

B1m −

N1 −

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

(%) ow

B2–L1

L1–B

B2–N1

N1–B2

N1–L1

L1–N

N2–N3

N3–N2

B2–W

L1–W

N2–W

WH–B

B2.2–W

N1ma–

N1fe–N

B1u–B

B1t–B1u

N1–Sw

Population preference

Appendix

−0.6

−0.4

−0.2

B2 −

L1 −

B2 −

N1 −

L1 −

N2 −

N3 −

− B2

B2 −

− L1

L1 −

− N1

N1 −

− N2

N2 −

WH −

− N1f

− N1m

B1u −

B1m −

N1 −

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

(%) ow

B2–L1

L1–B

B2–N1

N1–B2

N1–L1

L1–N

N2–N3

N3–N2

B2–W

L1–W

N2–W

WH–B

B2.2–W

N1ma–

N1fe–N

B1u–B

B1t–B1u

N1–Sw

Sex preference

Appendix

−0.6

−0.4

−0.2

B2 −

L1 −

B2 −

N1 −

L1 −

N2 −

N3 −

− B2

B2 −

− L1

L1 −

− N1

N1 −

− N2

N2 −

WH −

− N1f

− N1m

B1u −

B1m −

N1 −

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

(%) ow

B2–L1

L1–B

B2–N1

N1–B2

N1–L1

L1–N

N2–N3

N3–N2

B2–W

L1–W

N2–W

WH–B

B2.2–W

N1ma–

N1fe–N

B1u–B

B1t–B1u

N1–Sw

Control for effect oflabel color

Appendix

−0.6

−0.4

−0.2

B2 −

L1 −

B2 −

N1 −

L1 −

N2 −

N3 −

− B2

B2 −

− L1

L1 −

− N1

N1 −

− N2

N2 −

WH −

− N1f

− N1m

B1u −

B1m −

N1 −

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

(%) ow

B2–L1

L1–B

B2–N1

N1–B2

N1–L1

L1–N

N2–N3

N3–N2

B2–W

L1–W

N2–W

WH–B

B2.2–W

N1ma–

N1fe–N

B1u–B

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

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

Canonical 1

-SP (Spire height)

Continent

North AmericaEurope

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

Appendix

North coasts – South coasts

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

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

Sidenorthsouth

Wilks’ Lambda: 0.802

p < 0.001 ***

significant influence: CL > LA

Appendix

Within north coasts

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

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

PlaceBorkum

Wangerooge

Wilks’ Lambda: 0.135

p < 0.001 ***

significant influence: SP > CL

Norderney

Appendix

Within south coasts

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)

PlaceBorkumLangeoogNorderneyWangerooge

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

Appendix

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

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

Between the EFWS and Woods Hole

Appendix

Wadden SeaPopulations

arenot differentiated

atneutral loci

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

Science

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