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Table 1 Abbreviations, geographical position, country of origin and MOTU of the 67 Radix locations sampled, number of individuals scored for COI, ITS-1 sequence variation and shell shape and whether data on the habitat structure for the site was available.

From: Comparing the efficacy of morphologic and DNA-based taxonomy in the freshwater gastropod genus Radix (Basommatophora, Pulmonata)

Abbreviation

Location

Latitude

Longitude

Country

NCOI

NITS-1

Nmorph

Habitat data

MOTU

OUM

Umea

63.845

20.259

Schweden

4

 

6

 

2

FLE

Flensburg

54.699

9.505

Germany

1

 

7

X

2

EGG

Eggebek

54.614

9.372

Germany

1

 

-

 

2

BUC

Groβ Buchwald

54.172

10.073

Germany

1

 

-

 

2

KBW

Kühlungsborn

54.149

11.725

Germany

3

 

12

X

2

RIE

Riedensee

54.149

11.689

Germany

2

 

24

X

2

BDO

Bad Doberan

54.075

11.936

Germany

2

 

32

X

2

LES

Lesno

53.945

17.718

Poland

1

 

8

X

6

MIS

Mistorf

53.884

12.175

Germany

3

 

4

X

2

TRE

Tressower See

53.851

11.323

Germany

4

 

4

X

4

KOS

Kosewo

53.834

21.382

Poland

1

 

3

X

1

DYW

Dywity

53.818

20.477

Poland

2

 

5

X

1

KLU

Klusy

53.803

22.120

Poland

2

 

7

X

1

JEG

River Jegrznia

53.730

22.706

Poland

1

 

-

 

6

RAJ

Lake Rajgrodzkie

53.730

22.619

Poland

1

 

7

X

1

ROG

Roggeliner See

53.729

10.940

Germany

3

 

5

X

2

CZA

Czarne

53.682

16.925

Poland

2

 

-

 

2

DRA

Lake Drawsko

53.567

16.22

Poland

1

 

3

X

4

CZE

Czechowizna

53.333

22.886

Poland

1

 

7

 

1

KIE

Kierzkow

52.996

14.811

Poland

1

 

-

 

4

OSN1

Osno, River Lenka

52.454

14.871

Poland

3

 

4

X

1

BIA

Bialobrzegi

51.650

20.962

Poland

2

 

3

X

6

SOM

Sömmerda

51.236

10.977

Germany

3

 

-

 

2

SUL

Sülze

51.087

11.625

Germany

3

 

49

X

2

SUC

Suchedniow

51.072

20.846

Poland

2

 

8

X

1

OUR

Oberurff

51.036

9.161

Germany

3

 

24

X

4

MMA

Maarfelder Maar

50.101

6.758

Germany

5

 

-

 

4

STR

Steinrodsee

49.992

8.6

Germany

2

 

14

X

4

GGK

Groβ Gerau

49.935

8.479

Germany

3

 

9

X

2

SMH

Stuttgart-Mühlhausen

48.838

9.229

Germany

1

 

8

X

5

GLO1

Glomel

48.225

-3.404

France

1

 

8

 

4

GLO2

Glomel

48.225

-3.404

France

3

 

14

 

2

REE

Rennes

48.106

-1.705

France

3

 

17

 

4

BOD1

Bodensee

47.709

9.051

Germany

7

 

-

 

1

BOD2

Bodensee

47.667

9.213

Germany

11

 

-

 

2

BOD3

Bodensee

47.667

9.213

Germany

4

 

-

 

4

EST

Estavayer-le-Lac

46.856

6.840

Switzerland

5

 

20

X

2

BIH

Bihar

46.747

22.210

Romania

1

 

-

 

4

ROS

Barrage des Rossens

46.720

7.109

Switzerland

6

 

24

X

2

AUG

Les Auges

46.615

7.181

Switzerland

6

6

25

X

2

GVD1

Grandvillard

46.555

7.072

Switzerland

4

1

120

X

2

GVD2

Grandvillard

46.554

7.074

Switzerland

3

2

-

 

2

LYS

Les Lys

46.502

6.989

Switzerland

3

2

13

X

5

MBV

Montbovon

46.492

7.047

Switzerland

3

 

11

X

2

MUR

Muraszemenye

46.478

16.609

Hungary

1

 

-

 

1

HON

Lac de Hongrin

46.419

7.072

Switzerland

3

3

30

X

5

VIL

Villeneuve

46.399

6.890

Switzerland

6

6

19

X

1

REN

Rennaz

46.385

6.895

Switzerland

2

2

27

X

2

ROC

Les Roches

46.364

6.938

Switzerland

2

 

24

X

2

RET

Lac de Retaud

46.363

7.194

Switzerland

5

5

42

X

5

VEG

River Vegre

46.150

-0.226

France

3

 

3

X

2

LAV

Laval

45.830

4.804

France

4

 

38

 

2

HER1

Herbasse

45.117

4.974

France

2

 

18

 

2

HER2

Herbasse

45.117

4.974

France

2

 

18

 

4

CAZ

Cazevielle

43.769

3.798

France

2

 

16

 

2

STL

St. Laurent de la Cabrierisse

43.070

2.720

France

2

 

32

X

3

ARG

Argeles sur Mer

42.564

2.902

France

3

 

2

 

3

RLL

Rwan Lxjuka à Ljuka

42.541

18.374

Croatia

3

 

55

 

5

DEL

Delvinë

39.947

20.091

Albania

1

 

3

 

4