Genetic variability and differentiation in roe deer (Capreolus capreolus L) of Central Europe

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Genetic variability and differentiation in roe deer

(Capreolus capreolus L) of Central Europe

Gb Hartl, F Reimoser, R Willing, J Köller

To cite this version:

Original

article

Genetic

_variability

and

differentiation

in

roe

deer

(Capreolus

capreolus

L)

of

Central

_Europe

GB

Hartl

F

Reimoser

1

R

_Willing

₁

J Köller

1

Veterinärmedizinische Universität

_{Wien, Forschungsinstitut für}

Wildtierkunde

und

_Ökologie,

_{Savoyenstrasse}

_1, A-1160

Vienna, Austria;

2

University of Agricultural Seiences,

Institute

_{of Zoology}

and Game

Biology,

Pater

Karoly

u _1, H-2103

Gödöllö, Hungary

(Received

21

_September

_1990;

_accepted

3 June

₁₉₉₁₎

Summary - Two hundred and

_thirty-nine

roe deer from 13 provenances in

_Hungary,

Austria and Switzerland were examined for

_{genetic variability}

and differentiation at

40

_{presumptive isoenzyme}

loci

_by

means of horizontal starch

_{gel electrophoresis.}

For

completion, previously published

data from 160 roe deer from _{7 provenances in} Austria were also included in the present

analysis.

With a total P

_(proportion

of

_polymorphic

loci)

of

_30%,

a mean

P

of 15.8%

(SD 2%)

and a

mean H

(expected

_average

_{heterozygosity}

of 4.9%

(SD 1.2%)

Capreolus capreolus

is one of the

_genetically

most variable deer

species

yet studied. Relative

_genetic

differentiation among

populations

was examined.

About 10% of the total

_{genetic diversity}

is due to

_{genetic diversity}

between demes. Absolute

_genetic

distances are

_typical

for local

_{populations throughout}

the area _except in

Hungary,

where the D-values with all other provenances suggest an

_{emerging subspecies.}

This differentiation may have been caused

by

the

_completely

fenced borders between Austria and its

_neighbouring

countries to the east.

Except

in

_Hungary,

the pattern of

allele

_frequencies

reflects the

_patchy

distribution of roe deer

populations

and

_periodical

bottlenecking

caused

_by

the

_breeding

behaviour

_and/or

_overhunting

and

recolonization,

rather than a

_large

scale

_geographic

diversification. The various _aspects of

_genetic

variability

and differentiation in roe deer are discussed in

_comparison

to a related

_species

with a rather different _strategy of

_adaptation,

the red deer.

roe

_deer

_{/ electrophoresis}

_{/ isoenzymes /}

_{genetic variability}

_/

_genetic distance

Résumé - Variabilité et différenciation génétiques chez le chevreuil

_(Capreolus

capreo-lus L)

d’Europe centrale. La variabilité et les

_{différences génétiques}

à

_,¢0

locus

isoenzyma-tiques

ont été étudiés sur 239

chevreuils,

en _provenance de 13

_régions

_{di"!"érentes}

couvrant

la

_Hongrie,

l’Autriche et la

Suisse, par électrophorèse

horizontale sur

_gel

d’amidon. Cette

étude

englobe

aussi des données

_{précédemment publiées}

sur 160 chevreuils en _provenance

*

Correspondence

and

_{reprints : Forschungsinstitut}

fiir Wildtierkunde der

de 7

régions

d’Autriche. Avec une

_proportion

de locus

polymorphes

de 30%

globalement

et

de _15,8 ± 2% en _{moyenne par}

_origine,

et un _pourcentage attendu moyen

d’hétérozygotie

de 4,9

f

1,2%, Capreolus capreolus

est une des

_espèces

les

plus

variables

_parmi

les

_espèces

de

cervidés étudiées

_{jusqu’à présent.}

Environ 10% de la diversité totale est due à la diversité

génétique

entre dèmes. Les distances

_génétiques

absolues

_(D)

sont

_typiques

de

_populations

locales sur l’ensemble de la zone,

sauf

en

_Hongrie,

où les valeurs de D _{par rapport} aux

autres provenances

suggèrent l’émergence

d’une

sous-espèce.

Cette

différenciation

peut avoir été

_provoquée

_par les

_frontières

totalement

_grillagées

entre l’Autriche et les pays

qui

l’avoisinent à l’est.

_Sauf

en

_Hongrie,

les

_différences

de

fréquences géniques reflètent

une distribution en

plaques irrégulières

des

populations

de chevreuil et des

phénomènes

périodiques

de

goulet d’étranglement

dûs au _comportement

_{reproductif et/ou}

à des chasses

excessives suivies de

_{recolonisation, plutôt qu’à}

une

_{diversification géographique}

à

_grande

échelle. Les

_différents

_aspects de variabilité et de diversité

_génétiques

chez le chevreuil sont

discutés, en _comparaison avec le

cerf,

qui est une _espèce

apparentée

_ayant une

stratégie

d’adaptation différente.

chevreuil

/ électrophorèse /

isoenzymes

/

variabilité _génétique

_/

distance génétique

INTRODUCTION

Deer are _{among the few groups of}

_large

mammals which have been

_extensively

studied

_{by electrophoretic}

multilocus

_{investigations}

to evaluate

_genetic

_diversity

within and between

_populations

and

_species

_(see

Hartl and

Reimoser, 1988;

Hartl

et

al,

1990a for

_reviews).

However,

in contrast to the red deer

_(Bergmann,

1976;

Kleymann,

1976a,

b);

Bergmann

and

_{Moser, 1985;}

Pemberton et

_{al, 1988;}

Hartl

et

al, 1990a,

1991),

the fallow deer

_(Pemberton

and

Smith, 1985;

Hartl et

al, 1986;

Randi and

_Apollonio,

_1988;

_Herzog,

_1989),

the moose

_(Ryman

et

_al,

_1977,

_1980,

1981; Reuterwall,

1980),

the reindeer

_(R

₀

_ed

et

_al,

_{1985; Røed, 1985a, b, 1986,}

₁₉₈₇₎

and the white-tailed deer

_(Manlove

et

_{al, 1975, 1976;}

Baccus et

_{al, 1977;}

Johns et

al, 1977; Ramsey

et

_{al, 1979;}

Chesser et

_{al, 1982;}

Smith et

_{al, 1983;}

Sheffield et

_al,

1985;

Breshears et

_al,

₁₉₈₈₎

the factors

_influencing

the amount and distribution of biochemical

_genetic

variation in one of the most abundant

European

deer

_species,

the roe deer

_{(Capreolus capreolus),}

are

_{only poorly}

understood.

The first multilocus

_{investigations}

to estimate the amount of

_{genetic variability}

present in roe deer

compared

with other deer were made

by

Baccus et al

₍₁₉₈₃₎

and,

using

a more

_{representative}

_sample

of

_{individuals, populations}

and

loci,

_by

Hartl and Reimoser

_(1988).

The latter authors detected a

_{comparatively high}

level of

_polymorphism

and

_{heterozygosity}

_(mean

P

=

17.6%,

SD =

2%;

mean

expected

H

=

5.4%,

SD =

1.6%)

and also a

_{comparatively high}

amount of relative

(G

ST

=

8.5%)

and absolute

(mean

Nei’s 1972 D =

_{0.006 9,}

SD =

0.004 9)

_genetic

differentiation between demes. This result was

_thought

to be due to the

_ecological

strategy

of roe deer

_(within

the r - If continuum the roe is considered to be an

r-strategist :

Harrington,

1985;

Gossow and

Fischer,

1986)

and to

_immigration

into the

_{Alpine region}

from different

_refugial

areas after the last

_glaciation.

With

respect

to subdivision of the _genus

_Capreolus

the existence of several

_subspecies

in the

_European

roe deer as well as the taxonomic status of the Siberian roe deer are under discussion

_(see

Bubenik,

1984;

Neuhaus and

Schaich, 1985;

Groves and

Grubb,

1987).

On the basis of

_{electrophoretic investigations}

and other

_evidence,

The aim of the

_present

_study

was to

_analyse

the amount and distribution of biochemical

_genetic

variation within and _among roe deer

_populations

in more

_detail,

and to

_interpret

the results

_considering

the

_{sociobiological}

and

_ecological

attributes of the roe

_(an

_{opportunistic species}

with

_{high ecological plasticity}

and

_colonizing

ability,

but with low

_{migration distances,}

scattered distribution and

_population

subdivision into local

_tribes)

as described in the literature

_(Bramley,

_1970;

Stubbe and

_Passarge,

_{1979; Reimoser, 1986; Kurt,}

_1991).

The results were

compared

to the situation in the red

deer,

a

_species

of an

_ecologically

and

_{behaviourally}

opposite

type

(K-strategist,

large

and more

homogeneous

populations, potentially

high

migration

distances :

_Bubenik,

_1984;

_Harrington,

_1985),

for which

_directly

comparable

electrophoretic

data are available

_(Hartl

et

_al,

_1990a).

_Furthermore,

the

_possible

occurrence of different &dquo;local races&dquo;

(Reimoser, 1986)

or

subspecies

of roe deer in the

_Alpine

_region

_(at

least north of the main

_crest)

was examined.

MATERIALS AND METHODS

Tissue

_samples

_{(liver, kidney)}

of 239 roe deer from 13 provenances

(Fig 1)

were collected

_by

local hunters

_during

the

_hunting

seasons of 1988-1989 and 1989-1990 and stored at -20°C.

_Preparation

of tissue

_extracts,

_{electrophoretic}

and

staining procedures

and the

_{genetic interpretation}

of

_{band-patterns}

followed routine

methods

_(Hartl

and

_H6ger,

_1986;

Hartl and

_Reimoser,

_1988).

The 27 _enzyme

_systems

_screened,

the

_presumptive

loci and alleles detected and the tissues used are listed in table I.

For

_completion,

data from

previously

studied roe deer

₍₁₆₀

individuals from 7

_{populations :}

see Hartl and

Reimoser,

1988;

and

fig

1)

are included in this

paper. Since the same _enzyme

_systems

were

screened,

the same number of loci was

_detected,

and the various iso- and

_allozymes

were

_compared

for identical

electrophoretic mobility using

reference

_samples

from the

_previous

_study,

those data are

_fully

_compatible

with the results of the

_present

_{investigation.}

At each

_polymorphic

locus the most common allele was

designated

&dquo;100&dquo; and

variant alleles were

_{assigned according}

to their relative

_mobility.

The nomenclature

is consistent with that

_already

defined

_by

Hartl and Reimoser

_(1988).

Statistical

_analysis

Genetic variation within

populations

was estimated as the

proportion

of

polymor-phic

loci

_(P),

here defined

by

the

99% criterion,

expected

average

heterozygosity

(H,

calculated from allele

_frequencies)

and observed average

heterozygosity

(H

o

,

calculated from

_genotypes)

_according

to

_Ayala

_(1982).

Relative

_genetic

differentiation _among

_populations

_(F

_ST

in a broader sense :

see Slatkin and

_Barton,

1989)

was estimated

_using

Nei’s

(1977)

_{F-statistics,}

Nei’s

(1975)

G-statistics and the method of Weir and Cockerham

_(1984).

_Average

levels of gene flow among various

arrangements

of demes were estimated

_using

the

relationship

between

_F

_ST

and Nm

_(the

number of

_migrants)

described

_by

Slatkin and Barton

_(1989).

We also used Slatkin’s

₍₁₉₈₅₎

concept of

&dquo;private alleles&dquo;,

p(1),

for

_estimating

Nm from the

formula

_{In (p(l))}

=

a ln(Nm)

₊

_b,

where values of _a

per deme of 25. In

samples deviating

considerably

from this

_size,

the correction

(1981)

concept

of the &dquo;conditional average

frequency&dquo;

of an allele

(p(i)),

which is defined to be its _average

_frequency

over those

_samples

in which it is

present

(Barton

and

Slatkin,

1986).

Absolute

_{genetic divergence}

between

_populations

was calculated

_using

several

genetic

distance measures as

_{compiled by}

_Rogers

(1986).

To examine biochemical

genetic

relationships

among the roe deer

samples studied,

dendrograms

were con-structed

_by

various methods

_(rooted

and unrooted

_{Fitch-Margoliash}

tree,

Cavalli-Sforza-Edwards

_tree,

_Wagner

network, UPGMA,

maximum

_{parsimony method;}

see Hartl et

_al,

_1990b)

_using

the

_{PHYLIP-programme package}

of Felsenstein

_(see

Felsenstein,

1985).

To check the influence of

_sample

size and the

_composition

of

genetic

loci

chosen,

the statistical methods of

bootstrap

and

_jacknife

were

applied

(see

Hartl et

_al,

_1990a).

RESULTS

Screening

of 27 _enzyme

_systems

_representing

a total of 41

_putative

structural loci revealed

_polymorphism

in the

_following

12

_{isoenzymes : LDH-2, MDH-2,}

_IDH-2,

PGD, DIA-2,

AK-1, PGM-1,

PGM-2,

ACP-1,

PEP-2, MPI,

and GPI-1. In some cases

(LDH-2,

_DIA-2,

AK-1, PGM-1, PGM-2, ACP-1,

PEP-2,

MPI)

polymorphism

was

_previously

described

by

Hartl and Reimoser

(1988).

Also ME-2 was

_slightly

from calculations of

_{genetic variability}

and

_{differentiation, reducing}

the total set of loci considered to 40. In all cases

_heterozygote

_{band-patterns}

were consistent with the known

_quaternary

structure of the _enzymes concerned

_(Darnall

and

_Klotz,

1975;

Harris and

_Hopkinson,

197G; Harris,

1980).

The

monomorphic

loci can be

seen in table I.

_{Unfortunately, linkage analyses}

of _enzyme loci are not available in roe deer. The most

_closely

related

_species

studied in this

_respect

is the

_sheep

_(Ovis

ammon),

where,

as far as

they

were

examined,

the loci

polymorphic

in the roe deer

are situated on different chromosomes

(O’Brien, 1987).

For the

_polymorphic

loci

found,

allele

frequencies

detected in each roe deer pop-ulation are listed in table II.

_Single

locus

_{heterozygosities,}

average

heterozygosities

and the

_proportions

of loci

_polymorphic

are listed in table III. With the

_exception

of Ak-1 and

Pep-2

in

_SOL,

and

Pgm-2

and

Mpi

in GWA the

_genotypes

in none of the

samples

deviated

_{significantly}

from the

_{Hardy-Weinberg}

_equilibrium.

The _average

_frequency

of

_private

alleles

_(p(1))

in all

_populations

was

_0.099,

and the number of

_migrating

individuals per

generation

(Nm),

corrected for an _average

sample

size of 20 was 1

_(0.971).

Since the overall number of

_private

alleles is

small,

Nm was recalculated for 3

subsamples

of

populations.

In the &dquo;western

group&dquo;

(SOL,

SGA, PRA, MON, BWA, GWA,

NIAL) p(1)

was 7.75 and Nm

_(for

n =

22.7)

was

8.52,

in the &dquo;central

group&dquo;

(AUB,

BMI,

TRA, SAN, MEL,

PYH)

no

_private

alleles

occurred,

and in the &dquo;eastern

_group&dquo;

_(WEI,

_{STA, SOB, LAS, BAB, OEC,}

_PIT)

p( 1 )

was 0.141 and Nm

(for

n =

16.1)

_was 0.60.

Since in

_large

mammals the numbers of

_private

alleles seem to be

_generally

rather

small,

which reduces the

reliability

of the

method,

the conditional average

frequency

(p(i))

for all alleles was

plotted against

i/d,

where i is the number of

samples containing

a

_particular

allele and d is the total number of

samples

studied

(Slatkin, 1981).

This method does not

_permit

a calculation of

_Nm,

but it

_gives

an

overall

picture

of the distribution of alleles among

populations

in relation to their

frequencies.

As shown in

_figure

_2,

the number of

populations

in which an allele is

present

(&dquo;occupancy

number&dquo; ;

Slatkin,

1981)

increases more

constantly

with an

increasing

average

frequency

of the

respective

allele in the red deer than in the roe. Nei’s

₍₁₉₇₅₎

G

ST

among all

populations

studied was 0.126

(Hs

=

_0.049,

H

T

=

0.056,

D

ST

=

0.007),

Nei’s

(1977)

F

ST

was 0.110

(0.083

when corrected

for

_{sample sizes; Nei,}

_1987),

and Weir and Cockerham’s

₍₁₉₈₄₎

_F

_ST

was 0.099. Our data show that the various estimators for relative gene

diversity

between

populations yield

results of the same order of

_magnitude,

which is to be

expected

due to the same

_underlying

model. In order to test which of the 3

_assemblages

of roe deer _provenances

_(as

defined

_above)

shows the

_highest

amount of gene

diversity

between

populations, G

ST

was recalculated for each of them. Nei’s

G

ST

between

populations

of the &dquo;western

_group&dquo;

was

_0.086,

the &dquo;central

_group&dquo;

_0.060,

and the &dquo;eastern

_group&dquo;

0.130.

From those

_G

_ST

_{-values Nm,}

estimated

_{using Wright’s}

formula for the infinite island model

_(Slatkin

and

_Barton,

_1989),

was 1.73

(all populations),

2.66,

3.92 and

1.67,

respectively.

Pairwise absolute

_genetic

_distances,

corrected for small

_sample

sizes

_{(Nei, 1978),}

showed a mean value of D = 0.006

4 (SD 0.004 7)

and _a

Genetic

_{relationships}

_among the roe deer

populations

studied are shown in a rooted

_{(fig 3)}

and an unrooted

_{(fig 4) dendogram.}

The

_stability

of clusters with respect to the influences of

_sample

sizes and the

_composition

of

_genetic

loci is demonstrated in a

_bootstrap

_{(fig 5)}

and a

_jackknife

_{(fig 6)}

consensus tree.

DISCUSSION

Gene

_diversity

l71ithin

_populations

With a

Pt

(total

_proportion

of

_polymorphic

loci for the

_species)

of

30%,

amean

P

of

15.8%

_{(SD 2%)}

and a mean

_expected

H

of

4.9%

_{(SD 1.2%)}

the amount of

_genetic

variation in roe deer detected in the _present

_study

is somewhat lower than that

described in the white-tailed deer

_(Pt

=

31.6%,

P

=

16.1%, H

=

6.2%;

ShefHeld _et

al,

1985),

similar to that in the reindeer

_(Pt

=

25.7%,

P

=

16.0%,

H

=

4.9%; Røed,

1986),

but

_higher

than that in the red deer

_(Pt

=

20.6%,

P

=

11.5%,

H

=

3.5%;

Hartl et

_al,

_1990a),

the fallow deer

_(Pt

=

2.0%,

P

=

2.0%,

H

=

0.6%;

Randi and

Apollonio,

(1988)

and the moose

(Pt

=

21.7%,

P =

9.4%,

H

=

2.0%; Ryman

_et

_al,

explain

differences in

_{biochemical-genetic}

variation _among

_populations,

_species

or

higher

taxa are weakened or corroborated

_by

our data :

- In contrast to the

predictions

of the &dquo;environmental

_grain&dquo;

hypothesis

(Selander

and

_Kaufman,

_1973;

Cameron and

Vyse,

1978),

large

mammals are not

_generally

genetically

less variable than small mammals

_(Baccus

et al

₍₁₉₈₃₎

_give

a mean

P

of

12%

and a mean

H

of

3.3%

for 25

_{species of}

small non fossorial mammals. Nevo

et al

₍₁₉₈₄₎

_give

a mean

P

of

19.1%

and H

of

4.1%

for 184

_species

of

_mammals,

most of them

_being

rodents and

_{insectivores).}

- In contrast to the

predictions

of the

_{&dquo;pleistocene}

_{glaciation&dquo;}

_{hypothesis proposed}

by Sage

and Wolff

_(1986),

mammals

_inhabiting

the northern

_hemisphere

are not

generally genetically

less variable

_(because

of fluctuations in

_population

sizes in the

areas affected

_by

glaciation)

than those

_occurring

in more southern

_regions.

From their data

_cited,

a

mean H

of

1.4%

_(SD

1.8%)

can be calculated for 16 &dquo;northern

&dquo;,

and a mean

H

of !

9%

in 32 &dquo;southern&dquo;

species

(in

the

latter,

not all

H

values are

given separately

for each

_{species, preventing}

an exact calculation of mean

H).

At

species,

which are, in most cases,

completely

outdated

_(see

Hartl et

_{al, 1988, 1990a;}

Hartl,

1990a,

for

_reviews).

- Results of Nevo

(1983, 1988)

and Nevo et al

₍₁₉₈₄₎

are

supported, according

to which

primitive

and

_generalist

species

and those with broader

_geographic,

climatic and habitat

_spectra

harbor more

_genetic

variation than their

_opposite

_counterparts

(in

mammals :

mean H

_{(specialists)}

=

3.2%

(SD

2.4%,

71

species),

mean H

(generalists)

=

5.4%

(SD

4.6%,

51

species)).

One of the most

_important

_problems

in the

_comparison

of

_{biochemical-genetic}

variation between different studies is the very

unequal

evolutionary

rate _among

proteins

(see

eg

Nei, 1987; Hartl, 1990b,

Hartl et

al,

1990b).

Therefore,

unless

much the same set of _enzymes is examined in all taxa

_{concerned, genetic diversity}

may be

seriously

under- or overestimated.

In this

_respect

our data on roe deer are

directly

comparable

to those on red

deer obtained

_by

Hartl et al

_(1990a).

The numbers of

_populations

and individuals

investigated

are similar. Half of the

_isoenzyme

loci

_polymorphic

in roe deer showed allelic variation also in red

_deer,

_Ac

_P

_-1

and Ldh-2 to a

similar, Idh-2, Pgm-2, Mpi,

and

_Gpi-1

to a _very different extent. The ratio between

_ubiquitous

and scattered

polymorphisms

is the same

_{(! 50:50)}

in both

_species.

_Pt,

P

and

_H,

_however,

Gene

diversity

among

populations

Using

the

_private

allele method of Slatkin

_(1985),

no marked differences in

_Nm,

the number of

migrants

per

generation,

could be detected between the roe deer

(Nm = 1)

and the red deer

_(Nm

=

1.28),

which is

_probably

due to the very

low number of

_private

alleles

_occurring

in both

_species.

The

_plot

of

_p(i)

_against

i/d (fig

2),

however,

suggests

a little more

_population

subdivision in the former than in the latter

_species.

This difference becomes more

prominent

when Nei’s

(1975)

G

ST

of 12.6% in the roe deer versus

7.9%

among

free-ranging

red deer

pop-ulations

_(Hartl

et

_al,

_1990a)

is considered. Here the

_comparison

of the estimated number of

_migrating

individuals

_(1.7

vs

_2.9)

reflects more

_clearly

the

_greater

mi-gration potential

of the red deer.

_Regarding

the estimation of Nm from

_F

_ST

it must be stated that a

_stepping

stone model of

_population

structure,

taking

into account the

_hypothesis

that gene flow is more

likely

_among

_neighbouring

demes,

would reflect the situation in deer more

_accurately

than the island

_model,

accord-ing

to which gene flow can occur with

_{equal probability}

_among all

populations

However, intraspecific

differences in

_G

_ST

between

_subsamples

of

_populations

are more

_prominent

in the roe deer

(&dquo;western

group&dquo;

=

8.6%;

&dquo;central

group&dquo; =

6%;

(eastern group)

=

13%)

than in the red

(5.4%

among

Hungarian

and

5.6%

among western Austrian and French

populations, respectively;

calculated from

Hartl et

al,

1990a).

Interspecific

differences _{in gene}

_diversity

between

_populations

are less

apparent

when Nei’s

₍₁₎

or Weir and Cockerham’s

₍₂₎

F-statistics are used

(1

= 0.110,

1 corr =

_0.083,

2 = 0.099 in the roe

deer;

1 =

_0.098,

1 _corr =

_0.075,

2 = 0.011 in the red

_deer).

_Altogether,

these results

_suggest

that relative differen-tiation among

populations

is rather similar in both

species

and

G

ST

may

give

an

overestimation,

because it does not contain a correction for

sample

sizes of popu-lations or individuals

_(Slatkin

and

Barton,

1989).

It

_must,

_however,

be considered that the red deer

_{populations sampled}

cover a

_{larger geographic}

_{range than those} of the roe deer and therefore a

_comparison

of

p(1),

G

ST

;

or

F

ST

-values

_may be biased towards an overestimation of relative differentiation in this

species

(Hartl

et

al,

1990a).

Genetic distances and

_geographical

distribution

If,

as

_pointed

out

_by

Slatkin

_(1987),

Nm is >

1,

gene flow will

prevent

a substantial

the roe deer

_populations

studied _range from 0-0.022 6. The latter value is of a

magnitude separating subspecies

of red deer

_(Dratch

and

_Gyllensten,

_1985).

If an uncorrected D

_{(Nei, 1972)}

were used

_(as

Dratch and

_Gyllensten

did),

the maximum

genetic

distance between roe deer

populations

would be even

_larger

(D

=

0.025 6).

Overall,

the distances between the

_Hungarian

and all other roe deer

populations

(mean

D =

_0.0112,

SD

0.0041)

are much

higher

than those _among

_populations

without the

_{Hungarian samples}

_(mean

D = 0.004 7 SD

0.003 4).

This result

_suggests

that a

separate

subspecies

of

_Capreolus

capreolus

is

_developing

in

_Hungary.

Also when relative

_genetic

differentiation is

_considered,

_apart

from the Soboth

population,

the

_Hungarian

provenances contribute most to the

_high

G

ST

-value

(13%)

found in the &dquo;eastern cluster&dquo;.

_They

are also far

_apart

from the other

populations

in the rooted

_{(fig 3)}

and unrooted

_{(fig 4)}

_dendrograms

and the stable

position

of their cluster is confirmed

_by

the

_bootstrap

_{(fig 5)}

and the

_jackknife

(fig

6)

consensus trees. Because of the

_completely

fenced border between Austria and its

_neighbouring

countries to the East

_{(Hungary, Czechoslovakia)}

human influence _may be

_responsible

for the

_{high genetic}

distance between the

_Hungarian

and all other

populations

studied. Other more

separated

populations

are

_Soboth,

Prattigau

and Maria

_Alm,

_showing

even a

larger

_average distance to all other

demes than those from

_Hungary

when distance

_algorithms

other than Nei’s are

used. With

_respect

to

_{neighbouring populations}

in the

south-SOB,

the southeast-PRA

_(separated

from

_BWA,

GWA and MON

_by

_mountains),

or the north-MAL

(separated

from BMI

_by

_mountains),

_they

are situated in

_marginal

_positions

of the

study

area.

_Therefore,

it cannot be determined whether their

_large

_genetic

distances

-

due,

for

_example,

to the

_{high frequency}

of a rare allele at the

_Pg7n-!

and the

Pe!-!

locus - are caused

by

an

_{introgression}

from areas not included in the

_present

study

or

by

a loss of these

alleles,

which were

formerly

_present

in all roe deer

populations

studied. The

_genetic

distances among the

remaining

roe deer demes are

_typical

for local

populations.

Their

positions

in the

_dendrograms

fit

_quite

well to their

_geographic

distribution in several cases

(minor

deviations _may be due to

_partially

_very similar

_genetic

_distances),

but look

quite unexpected

in others

(eg

St

_Gallen).

When the distribution of the main

_{polymorphisms}

is

_examined,

those in

_{AK-1, ACP-1,}

PEP-2

₍₂

main

_allozymes)

and MPI

_(except

for

_Hungary)

are

_quite

_homogeneous,

whereas those in

_{DIA-2, PGM-1,}

and PGM-2 are scattered. From a

methodological

_point

of view it could be

argued

that the ratio between

the number of allelic markers and the

populations

studied is too low to

produce

reliable

_dendrograms.

We therefore

_pooled

the 20

_samples

in various combinations

according

to

_geographical

_criteria,

to construct

_{dendrograms using}

smaller numbers of

_{populations. However,}

in neither case was the

topology

of the

dendrograms

fully

consistent with the

_geographical

distribution of the

_sampling

_sites,

and there seemed to be more information lost than benefit

_gained

from this method. In

spite

of

_{comparatively}

few

_polymorphic

markers in relation to the number of

provenances and the rather small

sample

sizes of individuals in relation to _very small

_genetic

_distances,

in the red deer the

_pattern

of

_genetic

differentiation _among

free-ranging populations

agrees better with their

geographic

positions

(Hartl

et

al,

1990a).

Therefore,

other than

_{methodological}

factors may be

responsible

for the

partial

disagreement

between

_genetic

and

_geographic

distances. We

_put

forward the

of roe deer

_populations

(Bramley,

_{1970; Reimoser, 1986; Kurt,}

₁₉₉₁₎

led towards an increased

_genetic

differentiation _among them

_by

the differential loss of one or

the other rare allele at _enzyme loci

_polymorphic

in all roe deer at the time of the re-invasion of the

_Alpine

_region

after the last

_glaciation

_and/or

after bottlenecks caused

_by

_{overhunting during}

the last 3

centuries,

especially

in Switzerland

_(see

Kurt,

1977).

On the other

_hand,

it should be noted that the occurrence and distribution of some rare alleles at less

polymorphic

loci

_(eg

_Pg

_d

_7’

in

_Prattigau

and

_Montafon,

_Gpi-l

_5oo

in

_Auberg

and

_Traun,

_{Gpi- 1}

₃₀₀

in Weiz and

_Stainz)

is in accordance with the

_{geographic neighbourhood}

of the

_respective

_populations,

contrasting

with the

_large

allele

_frequency

differences at other loci

_{(table II),}

which

are

responsible

for their

_{unexpected positions}

in the

_dendrograms.

This could be

explained by

the

_assumption

that those _very rare alleles arose rather

_recently

_by

mutation,

when the

_geographic

distribution of the

_populations

was

already

_very similar to the _pattern observed

today.

A similar case, in which the distribution of _very rare alleles

_displayed

the

_present

_degree

of isolation between demes much better than overall gene

diversity,

was detected in the red deer

_by

Hartl et al

_(1991).

Besides

_past

_{genetic bottlenecks,}

_{temporal changes}

in the

_composition

of roe deer gene

pools

due to alterations in the social structure of tribes

_{(Kurt, 1991)}

may

also be

_responsible

for an

_unexpected

_pattern

of

_{genetic similarity}

_among roe deer demes and

_long-term

studies are

under-way

to

_investigate

such

_possible

short-term

changes

in allele

_frequencies

in more detail.

In contrast to the results of Beninde

_(1937),

who found the east-west distribution most

_important

to

_explain

differences in

_{morphological}

characters of the red

_deer,

(apart

from the situation in

_Hungary)

the east-west distribution of roe deer demes is not reflected

_by

_any cline in allele

_frequencies

or

_by

considerable

_genetic

diversification. The

_question

of a

_possible

north-south differentiation cannot be treated on the basis of the data

available,

but the Danube and also the

_Alps

seem

to be less

_important

for

_genetic

diversification between _provenances than

_previously

assumed

_(see

Hartl and

_Reimoser,

_1988).

ACKNOWLEDGMENTS

The authors are indebted to HG

_Blankenhorn,

C

_R5hle,

A

_Budde,

P

_{Ratti, M}

Giacometti from

_Switzerland,

R

Scherrer,

H

_St6ckl,

G

_Kamsker,

F

_Meran,

F

_Mitter,

A

_H

₆

_fler,

G

_Zettel,

J

Zandl,

J

_Spachinger,

A

_Precht,

F

_V61k,

WG Menke from Austria and the local hunters in

_Hungary

for the

_gift

of material and

_help

in the collection of

_samples.

The excellent technical assistance of A Haiden and the

_graphic

work of A K6rber are

gratefully acknowledged.

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