<oological Journal of the Linnean Soczety (1991), 101: 1 4 9 . With 10 figures
A multivariate approach to the determination
of faunal structures among European butterfly
species (Lepidoptera: Rhopalocera)
R. L. H. DENNIS
The Manchester Grammar School, Manchester M13 O X 7
W. R. WILLIAMS
Computer Centre, Science Laboratories, South Road, Durham DHI 3LE
AND
T. G. SHREEVE
School of Biological and Molecular Sciences, Oxford Polytechnic, Oxford O X 3 OBP
Receiued July 1989, accepled for publication March 1990
Multivariate analyses of 393 butterfly species over 85 geographical areas (R- and Q-data matrices)
in Europe and North Africa have produced a consistent pattern of faunal structures (units and
regions). Prominent features to emerge are the latitudinal zonation of geographical units and the
division of the Mediterranean into western and eastern components; southwards in Europe,
endemicity increases whereas faunal structures decrease in spatial dimensions. Central
Europe-from the Urals to the British Isles-forms a single large faunal structure (extent unit and
region). A model has been constructed to account for Pleistocene evolutionary changes and
endemism in European butterflies and for the east-west taxonomic divisions in the extent faunal
structure which dominates central Europe. Periodic Pleistocene climatic changes have resulted in
cycles of population extinction, isolation, evolution and migration, but the nature and timing of
events has depended on the environmental tolerances of species belonging to different faunal units.
During Pleistocene glaciations, southern species have been relatively static and more isolated and
have evolved independently. By comparison, northern species have been more mobile and have
migrated over large distances. Contact and hybrid zones among cosmopolitan species in northern
Europe are probably of some antiquity. They result from persistent survival and isolation of refuge
populations in the west and east Mediterranean during glacial phases; dispersal from these refuges
leads to their regeneration during each interglacial.
KEY WORDS-lihopalocera
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Europe
~
biogeography
-
evolution
~
Pleistocenc
CONTENTS
Introduction
Methods.
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Results
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Between-sub- region association matrix . . . . . . . . . . . . .
Between-species association matrix
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R. L. H. DENNIS E T AL.
Discussion
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28
Faunal structures among European butterflies . . . . . . . . . . . 28
Butterfly faunal structures: biogeographical inferences . . . . . . . . . 29
Acknowledgements
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References
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38
Appendices . . . . . . . . . . . . . . . . . . . .
40
INTRODUCTION
Base maps of organisms are fundamental to biogeographical research; those of
subsets of the European butterfly fauna, particularly in Britain, have led to
significant ecological findings. Biological Records Centre data (Heath, Pollard &
Thomas, 1984) have allowed the determination of the principal environmental
influences on butterfly distributions in Britain (Dennis, 1985; Dennis &
Williams, 1986; Turner, 1986; Turner, Gatehouse & Corey, 1987; Barbour,
1986), their evolutionary history (Dennis, 1977, 1985 and in press) and their
ecological constraints and conservation status (Pollard, 1979; Heath et al., 1984;
Thomas, 1983a, b; Thomas et al., 1986; Warren, 1984; 1987a-c).
In Europe mapping at similar high resolution ( < 10 km2 units) has now been
undertaken in several countries (e.g. Luxemburg: Meyer & Pelles, 1981;
Holland: Geraedis, 1986; Switzerland: Gonseth, 1987; Yugoslavia: Jaksic, 1988)
and there are a number of regional texts which include distribution maps (e.g.
Saarland: Schmidt-Koehl, 1971; Scandinavia: Henriksen & Kreutzer, 1982;
Iberia: Bustillo & Rubio, 1974). Much of the west Palaearctic still remains
under-surveyed and no complete biogeographical analysis has been undertaken
on the butterfly fauna (Larsen, 1986). The only European work that includes
base maps for each species is that of Higgins & Riley (1983) and Higgins &
Hargreaves (1983). These illustrate outlines of the distributions but are imprecise
and inaccurate. Nevertheless, with the text, they describe the basic features of
European butterfly distributions.
The European butterfly species are worthy of biogeographical analysis
because they do not present a single geographically homogenous unit. The
present paper applies multivariate analytical techniques cautiously to the
generalized base maps of Higgins & Riley ( 1983). Previous biogeographical
analysis of European butterflies have been made without the benefit of even this
research tool (Pagenstecher, 1909; de Lattin, 1967; Varga, 1977). The
recognition of several faunal units prompts a number of questions regarding their
evolution and history. It is only possible to explore a few of these questions: in
particular the status and significance of the faunal units recognized. These
observations may open the way to a more detailed historical treatment of the
group. In conjunction with ecological knowledge of the species this may further
their own conservation as well as that of other groups of invertebrates, for which
they allegedly serve as an indicator taxon (Kudrna, 1986).
METHODS
The region studied corresponds to the limits of the base maps of Higgins &
Riley (1983) (see Fig. 1, Appendix), although three additional zones have been
included from a further publication by Higgins (Higgins & Hargreaves, 1983).
The entire region extends from northern Scandinavia to north Africa and from
EUROPEAN BUTTERFLIES
3
Britain and Portugal to the Urals and the Caspian Sea. It contains more than
393 species (Higgins, 1975), but the number increases as new species are
described (Kudrna, 1986). The nomenclature corresponds with that of Higgins
(1975). The data comprise dichotomous scores (0, absence; 1 presence) on
species for 85 natural regions (subsequently termed sub-regions to avoid
confusion with faunal regions) extracted using a transparent overlay (Fig. 1).
Infra-species data (subspecies, races) have not been used in the current analysis.
Natural regions based on relief have been selected for two main reasons. As the
geographical data are relatively crude, appropriate Cartesian units at a scale of
100 km squares (UTM grid) would overlap distinctive natural units (see
Dutreix, 1988). A finer resolution would give a wholly spurious impression of
accuracy. Text details on distributions also refer to natural regions (i.e.
mountain and hill areas) usually without specifying localities, facilitating
mapping to these regions. One disadvantage of natural units is that areas are
unequal in size. Regional centroids have been applied to compare species
richness statistics and for plotting faunal units, but it has been regarded as more
important to have a complete enumeration of species for faunal regionalization
than strictly identical sampling intensity, which in any case would assume survey
equivalence for different points on the European map.
For analysis, the sub-region (85) X species (393) matrix has been used directly
(TWINSPAN) and converted into square matrices defining associations between
sub-regions and between species. For the square sub-region matrix, association
measures used are the PHI coefficient which is the binary form of the zero order
correlation coefficient, and the Jaccard similarity coefficient SJ (Siegel, 1956;
Sneath & Sokal, 1973). As these two coefficients give monotonic results in the
placement of sub-regions, only results for PHI are reported here, which can be
interpreted as correlation coefficients in ordination analyses. For the betweenspecies matrix, the Jaccard coefficient was applied; PHI was found to give
aberrant (very low) values for species sharing distributions over wide regions but
lacking joint absences from spatial units in the contingency tables. The two
coefficients are formally described in Table 1. Similarity coefficients have their
disadvantages and probability indices are argued to be more appropriate, but
these require complete knowledge of the species pool and the computations were
estimated to be too expensive for such a large file (McCoy & Heck, 1987).
Jaccard’s coefficient proves to be among the more stable similarity measures
tested (Raup & Crick, 1979).
TABLE
1. Format for the Jaccard similarity coefficient S, and the Kendall
PHI coefficient. PHI is the binary form of the Pearson product-moment
correlation coefficient
OTU,
l
0
b
1
a
a+b
OTU,
0
d l c+d
b+d N = a+b+c+d
1 c
a+c
Taccard S. = a / a + b + c
kendal Ph I,,, = ad - bc/J( (a b) (a c) ( b + d ) (c + d ) )
= Jx2/N
+
+
4
R. L. H. DENNIS E T AL.
EUROPEAN BUTTERFLIES
5
The two square matrices have been used to identify different levels of spatial
structure. Links between sub-regions (Q mode analysis---Johnston, 1980)
involve cosmopolitan species as well as localized species, but are dominated by
the former which are more abundant. More generalized structures emanating
from a Q-mode analysis are here termed faunal regions. Analysis of the larger
between-species matrix (R-mode; Johnston, 1980) draws out smaller units
defined by more localized species, unaffected by cosmopolitan fauna. This
involves a two-stage process, first of identifying species which share similar
distributions (here termed faunal groups, then of determining the spatial units
defined by them on their conjoint occurrence (termed faunal units).
Multivariate techniques used included (i) non-hierarchical ordination by
principal component analysis, factor analysis (VARIMAX, orthogonal
rotation), principal co-ordinate analysis and non-metric multidimensional
scaling (ALSCAL), (ii) hierarchical (SAHN) cluster analysis by complete
linkage and single linkage (see Sneath & Sokal, 1973) and (iii) clustering by a
polythetic divisive algorithm (TWINSPAN; Hill, 1979). TWINSPAN is derived
from indicator species analysis (Hill, Bunce & Shaw, 1975); it is based on the
ordination method of reciprocal averaging and makes dichotomies by dividing
ordinations in half-thus “dichotomized ordination analysis”. For experimental
purposes the axes in principal coordinates analyses were rotated to improve
resolution on the groups of species in the species matrix (Gower, 1967). The use
of a variety of techniques is important. Ordination techniques are effective in
representing distances between major clusters but are less good than SAHN
clustering in reproducing affinities between close neighbours. Also greater
confidence can be placed on results reproduced by different analytic techniques
(Sneath & Sokal, 1973). Analyses were conducted via the AMDAHL 58/60
computer at Durham University using routines in SPSS and TWINSPAN (Nie
et al., 1975; Hill., 1979). Data from 254 sites in the west Palaearctic have been
used for the comparison of faunal units on climatic parameters (Wall&, 1970).
A number of species are endemic to the natural units identified at the outset of
the analysis. However, for the purposes of later discussion, endemic species are
defined as those whose distributions are restricted to the area mapped in Fig. 1.
RESULTS
Between-sub-region association matrix
Non-metric multidimensional scaling
Much of the variation between sub-regions can be adequately depicted in two
dimensions. A non-metric two-dimensional scaling plot has low stress (Kruskal
stress, 13%) and the proportion of variance of the scaled data (disparities) in the
partition which is accounted for by their corresponding distances is very high
(2= 0.939). Young’s S-stress is not significantly improved ( 1.1”/) by increasing
the number of dimensions. T h e placement of sub-regions on horizontal vector 1
(Fig. 2) suggests a continuum rather than discrete faunal regions and
Figure 1 . The survey region of Europe and north Africa mapped by Higgins & Riley (1983) and
Higgins & Hargreaves (1983) illustrating the 85 sub-regions used in the present analysis (named in
Appendix 1 ) .
6
R. L. H. DENNIS E T AL.
Figure 2. A non-metric two-dimensional scaling plot of 85 European and north African regions on
their affinity for 393 butterfly species (PHI coefficients). Horizontal vector 1, vertical vector 2.
(Kruskal’sstress 0.13). Lines represent edges of the minimal spanning tree from single linkage cluster
analysis. Connections between developing clusters are between members (sub-regions) which have
maximum values for PHI and not nearest neighbours in the non-metric scaling plot.
corresponds largely with geographical order, extending from the Arctic and
northern Europe on the right, to southern Europe and north Africa on the left of
the plot. Some disjunction occurs between groups on vector 2. The central Alps
(37) occupy a position midway on vector 1 but apart from the main body of
regions in central Europe on vector 2. Arctic units (1, 5, 1l ) , the British Isles (14,
15, 16, 17), north Africa (72, 73, 74, 75), southern Iberia (31, 32) and the
Mediterranean islands except Sicily are largely spatially discrete. Geographical
units in the west Mediterranean (27, 33-36) are separated from those in the east
Mediterranean (56, 57, 5-3,
76). Italian units (35, 41, 42) are placed closer to
Iberia than Balkan units.
Princ$al component analysis
Eigenvalues for principal components attribute to each of nine or ten
components as much variance as an original variable. However, 48% of the
variance is accounted by the first component and only three components
determine 5% or more of the total variance (Table 2). Metric ordination of units
in the first two principal components produces an arcuate-shaped plot (Fig. 3)
similar to the non-metric scaling solution in two dimensions. The main difference
is that the latitudinal gradient is described by vector 2. Vector 1 separates north
Africa from Mediterranean Europe and the Mediterranean islands, the British
Isles from the European mainland, and the Arctic from the remainder of
EUROPEAN BUTTERFLIES
7
TABLE
2. Eigenvalues, percentage variances and cumulative
variances for the first 12 components for European regions
based on 393 butterfly species
Factor
I
I2
:3
4
!i
6
'7
8
9
10
11
1 !?
Eigenvalue
40.91
8.59
5.71
3.27
2.71
1.94
1.59
1.37
1.26
0.92
0.85
0.82
Percentage
variance
Cumulative
variance
48.1
10.1
6.7
3.8
3.2
2.3
1.9
1.6
1.3
1.1
48.1
58.2
65.0
68.8
72.0
74.3
76.2
77.8
79.1
80.2
81.2
82.2
1.o
1 .o
northern Europe. Geographical order once again emerges for the west and east
Mediterranean, the Italian peninsula similarly having closest affinity with
Iberia. The main distinction from the non-metric scaling plot is that the central
Alps emerge as a more distinct entity.
Factor analysis
As the number of factors (faunal regions) remains unknown, a series of factor
solutions for &12 factors has been extracted. These are similar in what they
disclose, but the 9 varimax factor solution is most appropriate from the overall
distribution of loadings (Table 3). The pattern of loadings for two levels 0.75,
0.5) have been superimposed on the plot of the first two components (Fig. 3);
factor regionalization based on the classification of sub-regions to factors on their
highest loading is illustrated in Fig. 4, together with the pattern of
communalities for regions. Polarization of loadings and the sharp transition from
high to low values indicates eight discrete factors; the ninth is less clear.
Reification points to a general size factor and clear factors for each of the Arctic,
Scandinavia, Britain, west Mediterranean, east Mediterranean, north Africa,
and Mediterranean islands. The size factor includes a large number of subregions with high loadings (loading > 0.75, N = 19; loading > 0.5, JV = 33).
As these sub-regions comprise a vast expanse of central Europe, it is more
appropriately described as an extent factor. The final factor for the south
European mountains is weak. Increasing the number of factors that are
extracted leads to a better resolution of loadings on the Alps and the
Carpathians, and draws Italy, especially unit 41, from Iberia.
Classification of sub-regions to factors on their prime loadings has produced
contiguous faunal regions without overlap or redundancy of spatial units
(Fig. 4). However, there is evidence that these faunal regions are not entirely
discrete. Not all sub-regions have high loadings ( > 0.75) on factors. Many
sub-regions attributed to factors have as little as 25% to 50% of their variance
accounted for by those factors. Also, there is clearly overlap between factors, the
amount depending on the choice of arbitrary cutoffs for loadings. For a loading
of 0.5, there is not a great deal of overlap and those that do occur (between the
8
R. L. H. DENNIS E l AL.
Figure 3. A principal component plot (first two vectors) of 85 European sub-regions based on their
affinity for 393 butterfly species (PHI coefficients). Isolines represent loadings at 0.75 (continuous
lines) and 0.5 (pecked lines) for the varimax orthogonal factor analysis (number of factors, 9).
east Mediterranean, west Mediterranean and the extent region; between
Scandinavia and the extent region) involve sub-regions that occupy intermediate
geographical positions between factor regions. Two sub-regions do fail to classify
to factors on loadings > 0.5: Sicily (with the west Mediterranean 0.44; with the
east Mediterranean 0.43) and Turkmenistan (sub-region 80), which lies outside
Europe. Isolines for communalities (Fig. 4) highlight sub-regions for which
accounted variance is low. The pattern is identical for all the 8 to 12 factor
solutions. The sub-regions involved, especially the Alps (37), Cantabrians (29),
Crete (85), Sicily (84) and the Balearic islands (81), also have lower loadings on
factors and are either mountain zones, islands or areas peripheral to Europe.
EUROPEAN BUTTERFLIES
Figure 4. Summary regionalization of the European butterfly fauna from factor analysis (Number of
factor, 9) of 85 sub-regions on 393 species. Faunal regions: I, extent factor; I1 Scandinavia and
northern Europe; 111, arctic fringe; IV; British Isles; V, western Mediterranean; VI, eastern
Mediterranean; VII , Mediterranean islands of Corsica, Sardinia and Crete; VIII, north Africa. T h e
Italian peninsula was not well defined and links up with the east Mediterranean at a marginally
lower level than with the west Mediterranean. Loadings for vector 9 were low and focused on the
Alps (sub-region 37). Crete separated from Corsica and Sardinia in analyses extracting additional
factors. Isolines illustrate communalities from the nine factor solution; areas scoring low ( < 0.7) are
stippled and high ( > 0.9) are shaded.
9
12
R. L. H. DENNIS E T AL.
These sub-regions have higher levels of unique variance, which point to the
presence of localized endemics, unusual combinations of species or faunal
elements restricted in Europe but with wider affinities outside the mapped zone
investigated.
Complete linkage cluster analysis
Complete linkage confirms both the geographical order of relationships and
the clustering of sub-regions (Fig. 5). At the same time it highlights the
hierarchical structure of associations among sub-regions. Using a cutoff of PHI
0.4, the factor regions are virtually reproduced with the single marginal
exception of Libya (75) which links up to north Africa at PHI 0.39. Homostat
production with complete linkage, compared to factor analysis, also points to the
relative independence of the Balearics (81), Crete (85) and the Italian peninsula
which includes Sicily. Some structural subdivision becomes evident in the
European extent group; in particular, the central European uplands and
mountains and the division of central Europe into east and west.
Single linkage cluster analysis
The results of single linkage cluster analysis are illustrated as a minimal
spanning tree on the non-metric scaling plot in Fig. 2. As links between
developing clusters are drawn between the most closely related sub-regions for
PHI, this technique more accurately reproduces relationships than a
dendrogram. The results are consistent with previous clustering and ordination
analyses. Sub-regions link up in sequence on the two dimensional plot and make
geographical sense. Similar clusters emerge as for complete linkage analysis
(Britain; Arctic; Scandinavia; north Africa; Mediterranean islands; west
Mediterranean; east Mediterranean), despite the fact that single linkage analysis
generally produces a ‘loose chain’ in dendrograms: Moreover, sub-regions
linking u p late in the analysis (e.g. Alps, 37; Turkmenistan, 80) are those which
are independent in previous analyses. However, not all links occur between
nearest points in the non-metric scaling plot; as connections in the single linkage
analysis often correspond with geography (e.g. sub-region 79 with 76 rather than
with 59; sub-region 14 and 15 separately with 16 rather than with each other),
there is some indication that non-metric scaling causes some distortion of fine
relationships, but this was expected from the Kruskal stress coefficient (Fig. 2).
It should also be considered that edges are drawn between nearest neighbours
and that affinity with other sub-regions may be but fractionally less. For
example, the link between sub-regions 31 and 32 is PHI = 0.798, which is
marginally less than for that between sub-regions 30 and 31 (PHI = 0.799) and
that between sub-regions 32 and 33 (PHI = 0.824).
Polythetic division ( T W I N S P A N )
The results of TWINSPAN are illustrated to three levels of division (Fig. 6).
The first division has separated northern from southern Europe. Divisions at two
subsequent levels produce eight regions which reproduce some of the features of
factor analysis and complete linkage clustering: the Arctic, northern Europe,
Britain, the extent region, north Africa and Mediterranean islands. The most
significant difference is the existence of a single Mediterranean region, but the
west and east division of this region occurs at the next step and Italy spalls away
13
R. L. H. DENNIS E l AL.
14
110
f
\
Figure 6. Primary regionalization (Q-mode) by plythetic division using TWINSPAN of 85 subregions in Europe and north Africa on dichotomousscores for 393 butterfly species. Breakdown has
been advanced to the third tier, the first dividing northern from southern and central Europe.
from Iberia in later divisions as do all Mediterranean islands, but for Sardinia
and Corsica, from each other. Minor differences occur in the classification of
sub-regions in geographically intermediate positions, for example southern Spain
and Portugal (31, 32) but their position in the ordinate plots (Fig. 2, 3) does not
make this surprising.
EUROPEAN BUTTERFLIES
15
Summary of results
Despite the development of a geographical continuum in the sub-regions on
the plots for principal component analysis and non-metric multidimensional
scaling, there is good evidence for the existence of a regional structure:
(1) agreement in the location of boundaries and in the composition of clusters
from factor analysis, complete linkage clustering and polythetic division; (2) the
polarization of loadings on factors in factor analysis and the very high loadings
( > 0.75) for sub-regions characterizing factors; (3) few discrepancies between
results of different analyses which generally influence sub-regions marginal to
factor regions. Nevertheless, faunal regions need to be interpreted cautiously.
Here, they can be shown to be characterized only by having distinctive
combinations of species. In some cases this is associated with high levels of
endemism (e.g. west and east Mediterranean); in others, it points to the
coincidence of spatial structures for species which range beyond the west
Palaearctic (e.g. extent region; arctic region). However, regions can also be
distinguished by containing unusual combinations of species. The British Isles
comprises no endemics but species which have the most extensive ranges in the
Palaearctic and which are found in almost all other regions of the mapped zone.
For islands, such combinations can be produced by the stochastics of
colonization or extinction. In the case of Britain, there are indications that
faunal impoverishment owes much to extinction subsequent to Holocene
colonization (Dennis, 1977).
Regionalization has produced other features which need to be resolved. Some
regional structures (e.g. Mediterranean islands focusing on Sardinia and
Corsica) comprise sub-regions which are not geographically contiguous (e.g.
Crete) and exclude others that are closer (e.g. Sicily). Some regions include subregions which have low loadings and communalities and which also remain
peripheral in ordination plots (e.g. central Alps, 37). The unique variance
belonging to these sub-regions conveys several implications: ( 1) localized
endemics confined to particular sub-regions (e.g. Crete), (2) allochthonous
faunal elements (e.g. Libya, 75; Turkmenistan, 80) restricted to a small part of
the mapped zone, and (iii) atypical combinations of species as for single isolated
islands which are subject to the stochastics of colonization and extinction (e.g.
Balearics). On the basis of the last alternative, the coding of species for the
separate Balearic islands would produce a distinctive Balearic region, as the
subdivision of the British Isles has for that region.
Between-species association matrix
The sheer size of the file placed limitations on analyses of the species matrix.
Thus, it has been necessary to apply principal coordinate analysis to five family
divisions (see Table 4). The file exceeded the bounds available for non-metric
scaling but not for SAHN clustering. Copies of all analyses on the betweenspecies matrix have been placed in the Royal Entomological Society library.
Cluster analysis
Both complete linkage and single linkage analysis have been carried out on the
between-species matrix; complete linkage to identify tight clusters and single
linkage to determine the effects of a chaining algorithm on the extent unit (see
16
R. L. H. DENNIS E T AL.
below). The detailed results (dendrograms; agglomeration schedules) are too
extensive to include here and because it is difficult to illustrate the results of the
single linkage clustering, these are only commented on briefly.
Complete linkage analysis discloses a large number of units among the 393
species; 23 basal stems for Jaccard’s SJ = 0, and 37 for Jaccard’s SJ = 0.1. The
distribution of 21 of the 23 basal stems in complete link clustering are displayed
in Figs 7, 8. Three species failed to classify meaningfully and Tomares nogelli
dobrogensis has a unique and localized distribution in Europe (see Appendix 2
legend). Finer subdivisions of some clusters (where Jaccard’s S
, = 0.2) are also
shown separately: for Scandinavian and arctic Europe; montane southern
Europe; west Mediterranean and east Mediterranean (see Fig. 8 and Appendix
2 legend). Important features are the subdivision of faunal regions emanating
from analyses of the between-sub-region association matrix, and the appearance
of new spatial structures for mountains and islands.
The most prominent structures to emerge are two clusters both containing
large numbers of species with wide ranges, thus termed extent clusters. As
division of an extent unit was unexpected the organization of these two clusters
has been analysed in greater detail. Extent cluster 2 contains almost twice the
number of species of extent cluster 1 (see Appendix 2). There is also a disparity
in their relative dominance for sub-regions on the European map; extent cluster
1 has proportionately more species in the north, east and central Europe,
whereas extent cluster 2 dominates in southern, western and north-west Europe
(Fig. 7A, B). Independence of the two extent clusters has developed because
pairs or groups of ‘root’ species belonging to extent cluster 1 (e.g. Nordmannia
ilicis and Coenonympha arcania) have narrower ranges in Europe than those
forming the nucleus of extent cluster 2 (e.g. Artogeia rapae; Pieris brassicae; Lycaena
phlaeas; Vanessa atalanta; Maniola jurtina; Pararge aegeria) . The latter all have
distributions which extend into Britain and by extension into other marginal
parts of Europe. This is particularly interesting as the only faunal region, from
analysis of the between-sub-region matrix, for which there is no faunal unit
counterpart, from analysis of the between-species matrix, is the British Isles.
Thus, the emergence of a second extent unit corresponds with the absence of a
unit limited to the British Isles.
These two extent clusters condense into one stepped structure in the single
linkage dendrogram. Moreover, when the species from the two complete linkage
clusters are distinguished on the single linkage dendrogram, the early steps are
dominated by wider ranging species from extent cluster 2 and the later ones have
a preponderance of species from extent cluster 1. Isolines of species richness for
complete linkage extent clusters 1 and 2 combined reveal a peninsula structure
with highest frequencies in east central Europe declining steadily to the margins
(Fig. 7C).
The Mediterranean region is structurally complex. Complete linkage analysis
determines at least four distinct structures for each of the west and east
Mediterranean regions and a further three for north Africa; this excludes
structures for the high mountain areas (Fig. 8A). When mapped at the 70%
species inclusion level, none of these covers Italy. Some of these structures are
endemic to a single regional unit, three in the Balkans alone. Italy also has a
single endemic cluster (unit 41); as would be expected so do Corsica and
Sardinia together and Crete, but not Sicily nor the Balearics. A pan-
EUROPEAN BUTTERFLIES
17
t
10/
3.007 6
70
32.
'L,
,
OO
10
I
20
30
1
I
40
50
60
Extent unit 1 (% species3
I
1
I
-L
70
80
90
100
Figure 7A. See caption on p. 19.
Mediterranean unit also occurs; at the 70% species inclusion level this mainly
defines the northern Mediterranean shore, but embraces the whole coastline at
the 50% level.
Faunal affinities in the mountain areas of southern Europe are even more
structurally complex (Fig. 8B) and the crude nature of the data cannot do them
full justice. Three single regional unit endemics are located in the Atlas
mountains, Pyrenees and Alps proper. Other structures draw various links
between faunas of the Cantabrians and Pyrenees, the Alps and foreland massifs
to the north of it, and the Alps and Appenines. Larger structural entities
comprise the mountains from north Spain, to the Carpathians and Tatras. There
is also confirmation of an 'arctic-alpine' component.
Finally, species limited to northern Europe are classified into two groups,
arctic species proper and a Scandinavian or northern European group (Fig. 8C).
The only structure not to reemerge from the species matrix is one defining the
18
R. L. H. DENNIS E T AL.
Figure 7B. See caption on p. 19.
fauna of the British Isles. No butterfly species is restricted to the British islands.
All but one butterfly, Erebia epiphron, fall into the extent units, species which
range across large parts of the palaearctic, although four northern British
butterflies, Carterocephalus palaemon, Aricia artaxerxes, Erebia aethiops and
Coenonympha tullia, belong to northern subunits in complete linkage clustering.
E. epiphron classifies to the widest of montane units in Europe (Appendix 2).
19
Figure 7. Composition of the two extent units determined from complete linkage cluster analysis of
393 European butterfly species. A, Scattergram and linear regression for the relative numbers of
species attributed to the two extent units which occur in 85 European sub-regions. Equivalence in
relative frequencies is given by the pecked line. B, Sub-regional bias for relative numbers of species
(% species) attributed to the two extent units. Excess ( + ) or deficit(-) of extent unit two over
extent unit 1. Absence of any bias (0).C , Isolines of species richness (%) for the two extent units
comprising 159 of 393 European butterfly species.
K. L. H. DENNIS E T A L .
20
I
C
&?
I
F
.
.
I
Figure 8A, C. See caption on p. 21.
Despite the feature of chaining in single linkage analysis, several of the
prominent units remain intact. Some 11 1 species of the 159 species belonging to
the complete linkage extent clusters are contiguous in a single block on the single
linkage dendrogram, and all but five species of the remainder are separated by
EUROPEAN BUTTERFLIES
B
I
I
21
I
Figure 8. Regionalization of the European butterfly fauna (R-mode analysis) based on complete
linkage analysis on Jaccard coefficients; 70y0 species inclusion levels are used to determine limits of
units. A, Faunal units in the Mediterranean region.
Pan-Mediterranean; - - west
Mediterranean;
east Mediterranean;
north Africa; . . islands and west Italy. B, Faunal
units over montane Europe. Mountain units in the Balkans illustrated in (A). - - Pan-montane;
arctic-alpine; - Alps-Appenines; - - - Alps & Bavarian Foreland; -. . - Pyrenees and
Cantabrian mountains; . . . . specific units focused on single regions. C, Faunal units in northern
Europe.
Arctic and montane Scandinavia; . . . Scandinavian and boreal. Note: arctic-alpine
placed in B.
~~
~
~
~
~~~
22
R. L. H.DENNIS E T AL.
three or fewer species. Similar blocks of species occur for the Arctic, Scandinavia,
west and east Mediterranean, the various Mediterranean islands and southern
European mountains.
Princ$al co-ordinate analysis
The principal coordinates analysis is certain to result in some differences of
classification, especially as regards individual species, if only because the file is
divided into five. Some faunal or spatial units are small as regards the number of
species represented and, when divided up in this way, there is a much lower
probability that a vector will be determined for them. In this situation, species
without a unique vector become associated with a surrogate vector and this is
usually evident from the modest nature of the loadings. As the five taxonomic
divisions contain different numbers of species, it is not surprising that a different
number of coordinate vectors are produced by the eigenvalue default cutoff of 1.
Table 4 contains eigenvalues and percentage variances for the first 20 vectors.
The average variance accounted for by the first vector is 27%, and the
cumulative variance for vectors with eigenvalues exceeding unity, 73%. The
loadings generally place species clearly into one specific vector (see Appendix 2),
although some overlap does occur (Table 5).
An extent vector dominates the analysis in each of the five family divisions
(Tables 4, 5). The lowest ‘loading’ value emerging as a cutoff for vector 1 is 0.46
for Coenonympha oedippus, but there are other species which classify to other
vectors, which load higher than this on the extent coordinate. The broad range
of ‘loadings’on the first coordinate suggests a spectrum of affinity (Fig. 9). When
species associated with the first vector from each of the five principal coordinate
analyses are distinguished on the complete linkage dendrogram, it is clear that
they cover both of the extent clusters 1 and 2 (see legend of Appendix 2). Species
from the five taxonomic divisions do not form aggregations on one or other of the
extent clusters. It is also worth noting that species occurring in the two complete
linkage extent clusters, but which do not have their highest loadings on vector 1
in the five principal coordinate analyses, nevertheless have high loadings on
vector 1.
A large number of species have 0 loading on vector 1 and have close
associations with alternative specific vectors. The faunal units identified by
complete linkage are confirmed (Table 5 and Appendix 2). No vector defines the
British Isles, but it is noteworthy that the species with highest loadings on vector
1 are found in Britain. Some faunal units are clearly associated with particular
taxonomic groups. For example, many of the montane divisions within southern
Europe are defined by the Satyrinae Erebia species and southern Greece by
Lycaenidae.
Classijication of species to faunal units
Principal coordinates analysis and complete linkage of the species matrix allow
classification of the species to faunal units, but such classifications have to be
regarded with a great deal of caution (see Appendix 2). For most species there is
a close correspondence between the classification using the two methods despite
the partition of the file for principal coordinate analysis. Fidelity of species to
faunal units facilitates estimates of endemicity. A very distinctive pattern is the
increase in endemicity within faunal units southwards (Table 6). Based on
R. L. H. DENNIS E T AL.
26
I
120
6
c
100
0
Q
In
c
c
.-
0)
c
0
In
Q)
80
4-
X
a,
Y-
O
s
2k 60
u-
c
0
3
c
-
3
Z
0
40
In
Q)
3
20
0
0
0.10
0.20
0.30
‘0.40
0.50
0.60
Factor loadings
0.70
0.80
0.90
1. 0
Figure 9. The distribution of principal coordinate ‘loadings’ for the first vector on 393 butterfly
species, based on analyses for five family divisions. R-mode on affinities for 85 regions for Jaccard
coefficients.
species classified to particular faunal units, only one species in the northern unit
is endemic to Europe, whereas over 60% are in north Africa, the west
Mediterranean and southern European mountains. The east Mediterranean has
fewer endemics but then a larger proportion of species classified to that region
are limited to the west Palaearctic. The single endemic butterfly belonging to the
northern unit is Pyrgus andromedae which has an arctic-alpine distribution. The
vast majority of species (95%) belonging to the northern faunal unit extend over
the entire Holarctic (57%) or Palaearctic (38%). Those belonging to the extent
unit(s) are more restricted in distribution; the east and west Palaearctic
components increase relatively to that of the Holarctic. Species belonging to
units in southern Europe infrequently extend beyond the west Palaearctic. Very
few species have ranges which enter the Afrotropical or Oriental realms.
Summay of results
The size of the between-species matrix places limitations on analytical
techniques used to determine patterns of faunal units. However, analysis of the
between-species matrix is essential to provide insights into the structure of faunal
regions determined from the between-sub-region matrix, especially when the
number of species greatly exceeds the number of regions. With one notable
exception, corresponding with each faunal region is one or more faunal units.
The multiplicity of faunal units for areas occupied by a single faunal region is
well-illustrated for the Mediterranean zone (Fig. 7A). A more complex example
28
R. L. H. DENNIS ET AL.
is that of the extent faunal region which requires a more detailed analysis than
can be attempted here.
Lack of correspondence between faunal regions and faunal units is also
informative. Faunal regions, for which there are no corresponding faunal units,
identify spatial structures which lack a unique (endemic) element. The British
Isles and the Balearic islands are zones deficient in species affected by the
stochastics of colonization and extinction (Dennis, 1977). Conversely, there are
many faunal units for which no clear faunal region emerged, especially the
southern European mountains. I n analyses of the between-sub-region matrix,
spatial affinities are influenced by the numerical dominance of faunal elements at
different scales. Analyses of the between-species matrix effectively ‘filters’ the
linkages a t different scales by identifying groups of species which share similar
distributions; faunal units within the various mountain systems of southern
Europe emerge from analysis of the between-species matrix because
cosmopolitan species aggregate into structures a t a wider scale. Overlap between
faunal units occurs extensively; this is to be expected as faunal units are a
product of complex historical processes (see below) triggered by glacialinterglacial cycles.
DISCUSSION
Faunal structures among European butterjies
Faunal regions, faunal units and endemism
The present study has identified faunal structuring among European and
north African butterflies. The fact that similar regions consistently emerge from
R and Q mode using different analytical techniques suggests that the structures
are biologically valid. Both faunal regions and units are primarily identified from
congruence in assemblages of species. Faunal regions and faunal units differ in a
number of respects: (1) the number of faunal units greatly exceeds that of faunal
regions, many of which are subdivisions of the faunal regions; (2) faunal units do
occur for parts of Europe (e.g. southern European mountains) not represented
adequately by faunal regions; (3) one faunal region only, the British islands, fails
to emerge as a faunal unit. The difference in the number of spatial structures
produced results primarily from the excess in numbers of species over regions,
and therefore from the additional information in the between-species matrix
compared to the between-sub-region matrix. The determination of faunal
regions from the between-sub-region matrix is also constrained by the numerical
dominance of species with wide distributions over those with distributions
restricted to smaller parts of Europe. Analysis of the between-species matrix
filters out relationships at different spatial scales. I t is suggested here that as the
prime extent unit is characterized, on principal coordinate loadings, by species
which are resident in Britain, the British faunal region is one of faunal
impoverishment. The islands lack species which collectively describe the
European extent units.
However, faunal regions and units do share similar patterns which may be
characterized as follows. (1) Both have a latitudinal zonation. Northern
structures are not restricted to the map area as the majority of their species
extend across the Palaearctic. Southern structures, including montane southern
EUROPEAN BUTTERFLIES
29
Europe, are mainly restricted to the survey area and comprise high frequencies
of endemic species, organisms confined to Europe and smaller areas within
Europe. (2) They also, significantly, divide into east-west components. The
western region is :8mallernumerically and is represented by faunal units in Iberia
and north Africa. A south centre Italian peninsula unit is numerically restricted
at the species 1evc.l. ( 3 ) Despite the abstraction of the faunal regions and units
there are few absolute physical boundaries separating them and there is a
substantial overlap between them on their included species. Some loo/, of species
belonging to the extent group occupy much of the mapped area. Thus, some
species are difficult to classify to any one group. All regions are also
characterized by some degree of internal diversity. This is perhaps most obvious
for the extent region and units, but islands such as Crete have a mix of endemics
and other species which have affinities with other parts of Europe.
Some of these features point to the faunal units as being much more than a
random collection of species and the outcome of stochastic processes; such are the
consistencies in pattern, latitudinal banding, east-west divisions in the
Mediterranean, and the steep gradient in endemic species. However, the
associated species do not represent interdependent or integrated community
structures. The faunal units comprise species often with different distributions,
hostplants, habits and life histories; environmental changes can therefore
influence species separately, as evident over smaller regions (Pollard, Hall &
Bibby, 1986; Dennis, 1977; Bink & Siepel, 1986). Integrity of faunal units is
made unlikely too by the overlap between them, the nested structure of faunal
subsets and the rriisclassification of species.
Environmental correr'ates of faunal structures
The main faunal divisions have a marked latitudinal zonation which relates to
climatic differences. T h e arctic-montane, extent and Mediterranean groups can
be largely distinguished on summer temperatures and insolation, but there is
extensive overlap between the north African, west and east Mediterranean
divisions. T h e groups cannot be separated so successfully on winter temperatures
(Fig. 10). The latitudinal zones are more clearly distinguished on combinations
of climatic attributes. Species of the extent group are characterized by biotopes
receiving modest levels of energy (temperature and insolation) and moisture; by
comparison, northern species are associated with summer low temperatures and
insolation, but adequate moisture supplies, whereas Mediterranean groups occur
in areas with summer high temperature and insolation levels but a moisture
deficit. The contrast is heightened because the high summer insolation levels
result in excessive evapotranspiration within the Mediterranean region. Despite
similar temperature and sunshine regimes, arctic and southern European
montane environments are not directly comparable, as radiation levels in the
latter regions are much higher. These climatic distinctions have an obvious
impact on the distribution of larval hostplants (Higgins & Riley, 1983; Polunin,
1969).
Butte$y faunal structures: biogeographical inferences
A large number of questions emanate from these observations but the present
discussion focuses on two main issues. ( 1 ) Clear structures have been determined
R. L. H. DENNIS E T AL.
30
..............
:
30
.:
-
NORTH
AFRICA
i
i
h
025-
0,
a
5
c
2 209)
n
-s
C
B
15-
:
=*
7
HIGH ARCTIC GROUP
10-
5-
EUROPEAN
MOUNTAINS*..,
*,
j
0-
.-#
0
-...)...
0-20
-15
-10
-5
0
5
10
l!
January mean temperatures (OC)
Figure 10. The characterization of faunal units identified from complete linkage and principal
coordinate analyses (R-mode) on July and January mean temperatures for 254 locations over
Europe and north Africa to 60" E. The lower altitude limit for the southern European montane unit
is 1500 m which is generally the lowest residence level quoted for the majority of alpine butterflies
by Higgins & Riley (1983). (Climatic data from Walltn, 1970.)
from multivariate analysis. But how stable and permanent are the faunal units or
faunal groups over time? (2) Fossil Carabidae (Coleoptera) show little or no
evolutionary transformations throughout the Upper Pleistocene but are known
to have traced climatic changes over huge distances (Coope, 1979, 1987).
However, butterflies are extremely variable organisms (Higgins & Riley, 1983;
Higgins & Hargreaves, 1983). This variation (subspecies, sibling species pairs
and boundary regions) has traditionally been explained by the influence of
glacial-interglacial cycles on distributions. Does the faunal structuring of
European butterflies and the pattern of endemicity provide insights into the
question?
Pleistocene-Holocene temQle^t
Apart from structural features of the faunal units, there is some evidence that
they could reflect particular historical processes and evolutionary events. The
shared distribution patterns among butterfly species which define the faunal
EUROPEAN BUTTERFLIES
31
structures, implicate covariation for appropriate life conditions and resources. I n
turn, they have very different climatic tolerances; there are precedents for
assuming this to have significance for the ecology of adults and early stadia
(Dennis & Williams, 1986; Turner, 1986; Turner er al., 1987; Pollard, 1979,
1988) and therefore for the spatial dynamics of the organisms. It is well known
that the biota of Europe have been exposed to periodic high amplitude
oscillations in environmental conditions associated with glacial-interglacial
cycles over the past 2 ma. I t may therefore be expected that as the species
describing the faunal units have very different requirements of environmental
conditions and resources they will behave differently in relation to
environmental changes. Moreover, as these changes have been marked, it should
be possible to predict the basic response of faunal units individually to the
glacial-interglacial cycles, despite the lack of details on hostplants for the
construction of a complete historical framework (see Dennis, 1977).
More than 17 glacial-interglacial cycles characterize the Pleistocene over the
past 2 ma. A quasi-regular periodicity has been observed in which the glacial
episodes are two to four times as long as temperate interludes. The switch from
cold to warm stages seems to have been more abrupt than the reverse (Atkinson
et al., 1987; Ruddiman & McIntyre, 1976, 1981). During glacial maxima, July
mean temperatures are known to have been 8°C cooler than today and winter
temperatures much lower (Atkinson et al., 1987). Precipitation was also lower
over much of Europe, although regional variations have yet to be determined for
all climatic attributes. The polar front is known to have been forced south off the
coast of Portugal. During glacial maxima, ice sheets extended over much of
northern Europe, Scandinavia and Britain. Large ice caps covered substantial
areas on southern European mountains from the Pyrenees to the Carpathians
and Caucasus. Apart from areas subject to positive glacio-isostacy (north
Britain), sea levels fell by some 120 m (Tooley in Huntley, 1988; Greensmith &
Tooley, 1982). Vegetation belts shifted over enormous distances. Europe north of
the alpine mountain chain was covered by tundra and polar desert; much of the
region to the south of it was dry steppe. Temperate forests were apparently
restricted to bands at mid altitudes in southern Europe, where moisture was
sufficiently high from orographic rainfall and temperatures not too extreme, and
along river valleys (Blondel, 1987). The boreal forest had retreated eastwards
into Asia, whereas the main focus for the Mediterranean sclerophyll forest seems
to have been in the south-east Mediterranean.
These shifts in vegetation geography have as much consequence for
phytophagous insects as the climatic changes. Thus, there is little reason to
doubt that the response of butterflies would have been similar to that of plants;
movements southwards, eastwards and downhill during glacial stages and
northwards and uphill during interglacial phases. These movements have
involved population extinctions, dispersal, the temporary occupation of refuges,
isolation and evolutionary changes, but the effect on the various groups must
have been very different depending on their specific adaptations, life-cycle
requirements and behaviour.
During glacial stages, widespread extinction of populations affected arctic and
alpine species in areas occupied by ice sheet and ice cap, temperate species over
the vast part of northern Europe and the Mediterranean fauna over much of the
north Mediterranean shore and over higher elevations in Iberia and the Balkans
32
R. L. H . DENNIS E T AL.
(Beug, 1975). During interglacial phases, similarly widespread extinctions
affected arctic and alpine species in mid-latitudes and low altitudes, and cool
temperate species from large parts of the Mediterranean.
Refuges differ in their location and nature enormously depending on the
fauna under consideration. Our perception is to consider them only for glacial
phases when temperate and Mediterranean flora and fauna occupied low
latitudes, but the arctic fringe and high alpine pastures are effectively refuges for
cold tolerant species in interglacials (see Huntley, 1988). Shifts in distribution
involve dispersal of fecund adult female butterflies; successful colonization
requires suitable climatic conditions, and the availability of hostplants and their
habitats. This process, and the speed and duration of effective dispersal, is
controlled by succession, much of it virtually primary succession, over northern
Europe in the early (protocratic) phase of an interglacial, but retrogressive
succession in the later (telocratic) phase (Godwin, 1975); the two may not
provide the same opportunity for any one group to successfully colonize regions
which become climatically suitable.
Integrity or instability in faunal structures? A n historical perspective
The above observations suggest that species belonging to different faunal
groups experienced very different pressures during glacial-interglacial cycles.
The latitudinal zonation of the regions and units very probably infer ancient
structures, probably pre-Pleistocene, which evolved in conjunction with other
elements of the temperate fauna and flora. But, the faunal structures can only be
regarded as stable in so far as vegetation types over Europe have been so during
the upper Pleistocene. Clear evidence now demonstrates that plants, especially
tree taxa, migrate at different rates and that vegetation composition continued
to vary throughout the Holocene (Godwin, 1975; Huntley, 1988). At times
vegetation ‘communities’ existed which have no contemporary analogues. The
faunal units comprising phytophagous insects may well have varied in much the
same manner. Certainly the fact that some faunal units are indistinct and that
others overlap, or are nested structures, is consistent with vegetation history
(Huntley, 1988). So too is the composition of species belonging to faunal units
which can have very different life-history strategies (Bink & Siepel, 1986).
Despite the latitudinal zonation of faunal structures and climatic associations,
there is evidence that they have been influenced by the stochastics of
colonization and extinction. For example, isolines of species richness describe a
typical peninsular effect for the fauna belonging to the extent units (Fig. 7C).
This suggests dominant Post Glacial inmovement from the east. However, it
could also implicate colonization from a number of refugia in the west and east
Mediterranean and subsequently selective elimination of species with the
development of climax forest in western Europe. This second, more complex,
process involves more stochastic elements than the first which infers systematic
migrations of faunal groups. Most European butterflies depend on herbaceous
plants which are curtailed under forest succession (Kudrna, 1986). The
probability with which species are eliminated by forest cover depends greatly on
their life history strategies, which are not equally vulnerable to environmental
change (Bink & Siepel, 1986) and the composition of the forests, which are
known to have differed substantially in each interglacial (Godwin, 1975). The
decline in species richness westwards indicates that the small British fauna, made
EUROPEAN BUTTERFLIES
33
up almost entirely of pan-Euroasiatic species, is restricted by more than island
biogeography issues.
Dynamism of and interrelationships between faunal units is also well
illustrated by associations between the arctic and montane groups. The patterns
associating them are not difficult to reconstruct in general terms but links
between closely related species, especially among the genus Erebia, ensure an
extremely complex history for the group. During glacial stages, there is potential
for these cold tolerant species to colonize large areas at lower latitudes and
altitudes and for taxa from different mountain regions and the Arctic to come
into contact. During interglacial phases they are once again isolated on
mountain tops and the arctic fringe (Warnecke, 1958). The various subsets for
mountain and arctic butterfly fauna indicate that each glacial-interglacial cycle
provides new opportunities for species to colonize different mountain ranges
dependent on the nature of climatic changes and the availability of corridors
suitable for movement. The cycle of processes can theoretically be extremely
complex as there is potential for isolation and adaptation on south facing
nunataks during glaciations as well as on mountain tops during interglacials
(Erhardt, 1989).
Do butterjies evolve as well
as migrate during glacial-interglacial cycles?
A traditional interpretation for much of the geographical variation is that it
has evolved during glacial-interglacial cycles (de Lattin, 1967; Varga, 1977).
This view conflicts with that of Coope (1979, 1987), based on the fossil record.
For the carnivorous Carabidae (Coleoptera) there is ample evidence for stability
in morphology, for low extinction rates and the ability of beetles to track climatic
changes over thousands of kilometres. Coope (1979, 1987) argues that only on
Atlantic islands (Canaries group; Madeira), south of the polar front, have
appropriate conditions, stable environments for small areas, existed for recent
speciation. As environmental disturbance has been severe throughout the
Mediterranean, in the alpine mountain chain and northwards during the past
500 Ka, this begs the question as to how the high frequency of butterflies
endemic to regions in southern Europe may be interpreted, especially the clusters
in the west and east Mediterranean. Are they all relicts-preor early
Pleistocene palaeoendemics? Or, has there been ongoing evolution in the Upper
Pleistocene which has resulted in speciation?
Before discussing this tissue, it is important to consider the degree of
equivalence in species definition for fossil beetles and living butterflies. Butterflies
and beetles can presumably be good biological species without showing any
consistent morphological differences that would be required to identify them in
fossils. All beetle species found as fossils are distinguished on morphological
criteria. In the main, so too are butterfly species, but occasionally these
morphological differences are not adequate (e.g. Aricia agestis and A . artaxerxes)
and other external criteria (i.e. phenology) are required (see Higgins, 1975;
Higgins & Riley, 1983). Thus, there may not be direct equivalence in the term
species for fossil Coleoptera and extant Lepidoptera. Evolutionary changes
among carnivorous beetles may be more extensive than is possible to determine
from the fossil record (see references in Erhardt, 1989); this presumably can be
tested directly using enzyme, DNA or other molecular methods.
The lack of a fossil record makes it impossible to determine the rate of
R. L. H.DENNIS E T AL.
34
morphological species production among Lepidoptera, but there are reasons for
supposing that it might be higher for temperate Lepidoptera than for the
Carabidae, and higher in southern than northern Europe. First, it is generally
accepted that allopatry provides the basis for most evolutionary change and
speciation. I n the short term, the probability for evolutionary change increases
in relation to the spatial (inversely) and temporal (directly) dimensions of the
isolate and the intensity of the selection pressures. I t is important to consider one
proviso; evolution among groups without fossils are particularly difficult to
study, because conditions that are most likely to induce changes are those that
also readily cause extinctions. There is no precedent for the argument that all
species have to adapt to environmental conditions (Turner, 1987).
Second, closely related taxa that are isolated in parts of the Mediterranean
now would, in the main, be more isolated during glacial phases (e.g. Zerynthia
polyxena and
rumina). The north Mediterranean comprises three sizeable
blocks of land, Iberia, the Italian peninsula and the Balkans, separated by a
narrow littoral. The fact that faunal groups can be demonstrated for these today
despite the wide overlap in climate points to ecological obstacles. During glacial
phases, isolation was more effective, because mountains (Pyrenees, Apennines,
Alps) and the north Mediterranean littoral presented physical and climatic as
well as ecological barriers; isolation was for longer, the distribution of species
compressed as appropriate habitats were restricted, and selection pressures
presumably increased as conditions became marginal. Even though taxonomic
subunits within mainland areas in southern Europe presumably tracked
appropriate resources and conditions, isolation and evolutionary independence
could be maintained despite any population mobility. A similar process may also
have affected montane southern Europe. Because of ecological specialism in
alpine butterflies, contact between affiliated segments of montane species may be
less than might be surmised during glacial phases. Although the most rapid
evolution would be expected to occur on isolated islands, and there is growing
evidence for, as yet, undescribed species on islands in the east Mediterranean
(Thomson, 1987; personal communication), the finite resources also makes
island populations most vulnerable to environmental changes. It is interesting
that many of the endemics on Mediterranean islands (e.g. Papilio hospiton on
Corsica and Sardinia; Kretania psylorita on Crete) have restricted habitats often at
high altitudes. It seems that on some islands (e.g. Balearics) much of the fauna
was virtually eliminated during the Devensian glaciation and that they have
been re-colonized in the Holocene.
Thirdly, the potential for evolutionary change depends greatly on powers of
dispersal. Phytophagous Lepidoptera, because of hostplant and habitat
limitations, probably evolve somewhat more readily and move somewhat less
than the Carabidae (see Kudrna, 1986). In the Mediterranean region, the
number of endemic butterfly species is less than that for nematodes and plants
(low dispersal) but vastly more than that of birds (high dispersal) (Topham &
Alphey, 1985; Blondel, 1987). Similarly, butterflies with wider dispersal powers
(e.g. Nymphalini) also have few endemics than those with ‘closed’ populations
(e.g. Lycaenidae) (see Higgins & Riley, 1983). Evolutionary rates are also
known to be fast in Lepidoptera, as much regional variation in morphology,
biochemistry, physiology and ecology, of genetic origin, has developed in areas
that can only have been colonized from a single source in the Holocene (Dennis,
1977; Thomson, 1987a; Dennis & Shreeve, 1989).
<.
EUROPEAN BUTTERFLIES
35
Collectively, the evidence suggests that the east and west Mediterranean areas
as well as the southern European mountain region have been centres (zones) of
evolutionary change in recent geological times (Late Tertiary & Quaternary.
The occurrence of sibling species and the large number of infra-specific taxa
limited to west or east Europe associated with species having pan-Mediterranean
distributions is further evidence of this (Higgins & Hargreaves, 1983). Species
occupying northern Europe also seem to be affected. Contact zones between
western and eastern components of extent unit butterflies occur (e.g. Maniola
jurtina, Thomson, 1973, 1987a; Mellicta athalia, Bourgogne, 1953; Melanargia
galathea, Higgins, 1969; Tilley, 1983, 1986; Wagener, 1984; Mazel, 1986; Pyrgus
malvae, Guillaumin, 1971). Moreover there is the possibility that an undisclosed
number of temperate butterflies belonging to the extent unit may divide up into
genetically distinct east and west groups. The migrant Pontia daplidice has now
been separated into two electrophoretically distinct taxa, in west and east
Europe ( P . daplidice and P . edusa respectively) despite the absence of any clear
physical distinctions (Geiger, Descimon & Scholl, 1988; Wagener, 1988). The
Italian Peninsula may have provided a small third region of isolation and
evolution during glacial-interglacial cycles, especially as new species have been
described for the region since 1983 (Kudrna & Leigheb, 1988).
An evolutionary model f o r European butterjies
A model can be constructed to account for higher speciation rates and higher
endemicity levels among butterflies in southern Europe, including the
Mediterranean zone and southern European mountains. To be entirely
successful, this should also accord with other biogeographical features in west
Palaearctic butterflies: ( 1 ) taxonomic boundary zones in the extent unit, many of
which occur in France (see Higgins, 1975; Higgins & Riley, 1983; vide supra); (2)
the lack of endemic species but profusion of infraspecies endemics north of the
Alps; (3) the latitudinal zonation of faunal structures among European
butterflies, and (4) the overlap of faunal units especially those in southern
European mountains and the Mediterranean. It is argued here that different
levels of endemism and possibly speciation rates between northern and southern
butterflies relates to two main features: (1) the substantial variation in
environmental tolerances between species of west Palaearctic butterflies (viz.
climate, habitats, hostplants), and more importantly (2) the very different
opportunities available for butterflies restricted to northern and southern Europe
respectively during glacial-interglacial cycles, particularly the spatial dimensions
of resources and their continuity. For butterflies of arctic and boreal
environments, resources have been more extensive and continuous than those for
butterflies of cool and warm temperate regimes (Blondel, 1987). The periods for
which distributions are reduced to a residual fraction of maximal spatial
coverage, here called core or refuge populations, also differ for the two groups.
For northern species it is the shorter interglacials; for southern species, it is the
longer glacials. Refuge zones for northern species are also impermanent
compared to those for species in southern Europe. The result is that warm and
cool temperate butterflies have experienced longer periods of isolation and
independent development than butterflies of boreal and arctic environments.
Despite the numerous cycles of extinction and migration that have influenced
temperate faunas, the core or refuge populations of many cool and warm
temperate European butterflies could have been isolated from one another for
36
R. L. H. DENNIS ET AL.
much of the Pleistocene. As discussed above, Mediterranean species (e.g.
Melanargia spp.) whose distributions do not overlap in the current interglacial
would have been more isolated during glaciations. Furthermore, the same
process would affect cool temperate species (parapatric sibling species such as
Spialia sertorius and S. orbifer and others discussed earlier) now in contact. During
each glacial stage, cool temperate butterfly species are reduced to these core
populations at Mediterranean latitudes. Then, during the early (protocratic)
phase of each interglacial, the high temperatures encourage massive populations,
dispersal of adults as their hostplants spread, panmixia between populations
from refuge areas and widespread recombination of genotypes, releasing a vast
amount of genetic variation which allows the species to exploit the changing
landscape of northern Europe. Subsequently, this also allows them to adapt
regionally and locally when forest closure occurs over northern Europe and
when climate deteriorates during the second part of the interglacial. At the
inception of the next glaciation, most of this variation in northern Europe is once
again erased. During each cycle, the core populations continue to be separated
from each other and depart genetically as the period of isolation increases and in
response to different environmental conditions. Thus, there is potential for
divergence and speciation which is tested during every interglacial phase. The
process may lead to the production of good biological species such as Pontia
daplidice and Pontia edusa which would not be noticeable from any fossil record.
This model could explain the increased endemicity of species in southern
Europe, inasmuch as it distinguishes species whose populations are mobile and in
continuous contact throughout the glacial-interglacial cycles (taxa subject to en
mane extinctions and movements having current distributions north of the Alps)
from those which are relatively static and isolated (taxa south of the Alps). A
similar process probably affects butterflies in the southern European mountains.
These are isolated on mountain peaks (subalpine and alpine zones) during
interglacials, but may, because of ecological specialization (e.g. Erebia spp.) be
equally isolated on the lower slopes and on nunataks during glaciations
(Erhardt, 1989, personal communication).
It is possible that the higher frequency of endemics among other southern
European and north African faunal units may result, in part, from a continuous
turnover of species rather than simply reflect long-term isolation throughout the
Pleistocene. Infraspecific variation in northern and southern Europe differs in
one important respect; although there is little reason to suggest that production
rates differ, there is a much greater probability (c. 1 in the case of the British
Isles) that it will be destroyed in the former region during a glacial phase.
Nevertheless, in the Mediterranean, species vary in their distributions from
cosmopolitan to extremely restricted, and they have not been static. In the case
of the localized endemics in Spain and Greece, it would be unwise to regard
them as having always had limited distributions. Coope (1979) describes the
example of the beetle Aphodius holderi which was found throughout north-west
Europe during the Devensian, but is now a localized endemic in Tibet. It is
argued here that as there is a stochastic element to the changing distributions
and because environmental conditions are never exactly repeated during glacialinterglacial cycles (Godwin, 1975), there is a random element to isolate
production. Ecological adaptations and continued isolation of such
subpopulations have potential for speciation. However, much as in the case of
EUROPEAN BUTTERFLIES
37
the equilibrium theory of island biogeography the production of new species may
well be matched by the extinction of taxa, new as well as old. Infra-species taxa
may be new species in the making at Mediterranean latitudes. Conversely,
localized endemics may represent species close to extinction. Two observations
are consistent with this reasoning: first, the relatively small size of the faunal
units (species richness) ascribed specifically to the Mediterranean regions and
the low level of faunal enrichment in the basin suggest that extinction rates at
least match speciation rates. Secondly, the disparity in distinctions
(morphological; biochemical) between pairs of related species is substantial.
Some species (e.g. Archon apollinus) have no congeneric relatives in Europe,
whereas others do (e.g. Thersamonia spp.; Melanargia spp.), including sibling
species (e.g. Pontia daplidice and P. edusa). This may suggest the existence of
seemingly ‘new’ as well as ‘old’ taxa (Higgins, 1975).
Although northern species of arctic and cold temperate environments have less
opportunity for further speciation, there are at least two scenarios, concordant
with the current model, which provide opportunities for this. First, northern
species (e.g. Pyrgus andromedae) which are able to permanently colonize habitats
on and in the vicinity of southern European mountains during the switch from
glacial to interglacial phases respectively can evolve independently of their
conspecifics elsewhere at the arctic fringe. Secondly, temporal divergence in
flight period can permanently isolate populations. Both arctic and boreal Erebia
and Oeneis species fly in alternate years as do moths of the genus Xestia (Douwes,
1980; Mikkola & Kononenko, 1989). Populations occur which consistently have
flight periods in odd or even years. The pattern of distribution in odd and even
year Xestia species, repeated in the Nearctic, is consistent with isolation in refugia
on either side of the continental ice sheets in Eurasia and North America
(Mikkola & Kononenko, 1989).
There is no reason for the model, which assumes the influence of stochastic
processes in distributional changes, to be discordant with the concept or features
of faunal structures determined from multivariate analysis. Latitudinal zonation
in European butterfly faunal structures can be maintained throughout glacialinterglacial cycles by individual species tracking resources (i.e. climate,
hostplants, habitats) over different parts of the Palaearctic. Some degree of unity
and permanence in butterfly faunal structures would be maintained because
hostplants with similar environmental tolerances will retain similar distributions
whilst tracking appropriate conditions during climatic changes. But, as plants
migrate at different rates (Huntley, 1988) and adaptations among hostplants are
not identical, this accounts for overlap between butterfly faunal structures. It
also allows for a switch in allegiance of taxa for faunal structures insofar as new
adaptations can be acquired by survival in isolated refugia under marginal
conditions. Thus, the latitudinal division and biological distinctions between
sibling species Artica artaxerxes (univoltine) and A . agestis (multivoltine) could
have evolved from isolation of ancestral populations during a recent glaciation;
for instance in isolated western (cooler, cloudier summers) and eastern (warmer,
brighter summers) parts of southern Europe during the Devensian glaciation.
Although this survey makes some progress on European butterfly
biogeography, it has been greatly handicapped by the lack of accurate
information on distributions, taxonomic distinctions and hostplants. For this
reason the findings must be regarded as preliminary and interpreted cautiously.
R. L. H. DENNIS E T AL.
38
Accurate and detailed biogeographic and taxonomic data are required not only
for evolutionary research but for conservation too; this is clear from the
extinction of populations over Europe in the post-1945 period.
ACKNOWLEDGEMENTS
We are grateful to Derek Whiteley for kindly drawing the figures, to Margaret
Dennis for her painstaking work in coding up the initial file, to two anonymous
referees, and Andreas Erhardt, Jeremy Holloway and Dick Vane-Wright for
comments which have greatly helped to improve the text.
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APPENDIX 1
European sub-regions illustrated in Fig. 1.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Norway, Lapland
Norway, mountains
Norway, Vestlandet (fjords)
Norway, south east slopes
Sweden, Lapland
Sweden, Norrland mountains
Sweden, Norrland coastal lowlands
Sweden, central lowlands
Sweden, SmHland
Sweden, Sklne
Finland, Lapland
Finland, lakes
Denmark
Ireland
Britain, Scotland
Britain, highland England and Wales
Britain, lowland
Holland
France and Belgium, Flanders
France, Armorica
France, Paris basin
France, Belgium and Luxembourg, Ardennes
France, Lorraine
France, Aquitaine
France, Central Massif
EUROPEAN BUTTERFLIES
APPENDIX
1 continued
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
France, RhBne-SaBne corridor
France, Mediterranean coast
France and Spain, Pyrenees
Spain, Cordillera Cantabrica
Spain and Portugal, north Portugal and
Galicia
Portugal, south and Algarve
Spain, Andalusia
Spain, south Meseta tableland
Spain, north Meseta
Spain, Levant
Spain, Ebro vallry
Central Europe, Alps proper
France and Switzerland, Jura and Swiss
plateau
Italy, Apennines
Italy, northern plain
Italy, Tyrrhenian coast
Italy, Adriatic coast
West Germany, north German plain
West Germany, Rhineland, Eifel,
Westenuald, Hunsruck, Taunus
West Germany, north central uplands
West Germany and France, Alsace, and
south Rhineland, Vosges and Black Forest
West Germany, south central uplands
West Germany, Bavarian foreland.
East Germany, northern plain
East Germany, Thuringian Forest to Ore
mountains (Err. Gebirge)
Poland, plain
Poland and Czechoslovakia, Sudeten mountains
Czechoslovakia, Moravian heights and
Bohemian Forest
Austria, upper and lower Austria
Central Europe, Hungarian plain
Yugoslavia, Danube plain
Yugoslavia, Albania, Dalmatian alps
Yugoslavia, coastal plain (Dalmatia)
Greece, Yugoslavia and Albania, Pindus
mountains
Greece, Albania, Ionian coast and
Peloponnisos
Greece, Aegean coast
Bulgaria, Rhodope mountains and Stara
Planina
Bulgaria, Turkey and Romania, Wallachia
and Istanbul.
East central Europe, Carpathian mountains
East central Europe, Tatra mountains
Romania, USSR, Ukraine
USSR, Byelorussia
Lithuania
Latvia
Estonia
USSR. Muscovy
Morocco, Algeria, Mediterranean coast
North Africa, Atlas mountains
Tunisia, outside Atlas
Libya
Turkey, west
41
R. L. H. DENNIS E T AL.
42
APPENDIX
1 continued
77*
78*
79*
80*
81
82
83
84
85
USSR, north of 60"N
USSR, north of Black and Caspian seas to
60"N
Caucasus and Zagros mountains
Aral sea, Ust Urt plateau and Turkmenistan
Balearic islands
Corsica
Sardinia
Sicily
Crete
*Regions illustrated in Higgins & Hargreaves (1983) but not in Higgins & Riley (1983), as far east as 60"E.
APPENDIX 2
T h e classification of European butterfly species into faunal units, identified by principal coordinates analysis and complete linkage clustering, together with a description of their ranges
No.
1
1
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
(392)
24
25
26
27
28
29
30
31
32
33
34
35
36
Species
Papilio machaon
Papilio hospiton
Papilio alexanor
Iphiclides podalirius
zetynthia polyxena
zeynthia rumina
zeynthia cerisyi
Archon apollinus
P a m s i u s apollo
Parnassius phoebus
Pamassius mnemosyne
Aporia crataegi
Pieris brassicae
Artogeia rapae
Artogeia manni
Artogeia ergane
Artogeia napi
Artogeia krueperi
Pontia daplidice
Pontia chlorodice
Pontia callidice
Euchloe ausonia
Euchloe simplonia
Euchloe insularis
Euchloe tagis
Euchloe pechi
Euchloe falloui
Euchloe belemia
Elphinstonia charlonia
Anthocharis cardamines
Anthocharis belia
Anthocharis damone
Anthocharis gruneri
Zegris euphme
Colotis evagore
Colias phicomone
Colias nates
Principal
coordinate
analysis
1
8b
3, 7
1
2
4
7
7
1
10
1
1
1
1
3
3
1
7
1
7
10
10
3
8b
4
5
5
4
5
1
4
3, 7
7
4
5
10
9
Complete
linkage
2a
8b
7a
2b
2c
4a
7b
7b
Id
1Od
Id
2a
2a
2a
2c
2c
2a
7a
2b
7b
1Od
1oc
2c
8b
4a
5b
5b
4d
5c
2a
4a
3
7a
4d
5c
1Od
9a
Range
H
E
WP
EP
WP
E
WP
WP
EP
H
EP
EP
EP
EP, (N)
WP
WP
H
WP
EP
H
H
H
H
E
E
E
E
WP
WP, A
EP
E
WP
WP
WP
WP, A
E
H
EUROPEAN BUTTERFLIES
43
APPENDIX
2 continued
No.
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
Species
Colias palaeno
Golias chrysotheme
Colias libanotico
Golias myrmidone
Colias crocea
Colias balcanica
Colias hecla
Colias hyale
Colias australis
Golias erate
Gonepteryx rhanrni
Gonepteryx cleopatra
Gonepteryx farinosa
Leptidea sinapis
Leptidea duponcheli
Leptidea morsei
Cigaritis zohra
Cigaritis siphax
Cigaritis allardi
Thecla betulae
Quercusia quercus
hesopis robori,
Nordmannia acaciae
Nordmannia ilicis
Nordmannia escrili
Strymonidia spini
Strymonidia ru-album
Strymonidia pruni
Callophrys rubi
Callophys avis
Tomares ballus
Tomares mauretanicus
Tomares n. dobrogensis
Lycaena helle
Lycaena phlaeas
Lycaena dispar
Heodes virgaureae
Heodes ottomanur
Heodes tityrus
Heodes alciphron
Thersamonta thersamon
Thersamonia phoebus
Thersamonia thetis
PalaeochTsophanus hippasthoe
Lompides boeticus
Syntarucus pirithous
Tarucus theophrastus
Tarucus rosaceus
Tarucus balkanims
Azanus jesous
zizeeria knysna
Everes argiades
Everes decoloratur
Everes alcetas
Cupido minimus
Cupido osirts
Cupido lorquinti
Cupido carswelli
Principal
coordinate
analysis
1
2
7
2
1
7
9
1
I
7
1
3
7
1
7
2
5
5
5
1
1
4
2
I
4
1
1
1
1
4
4
5
2
9, 1
1
1
1
7
1
1
2
5
7
1
2
2
5
5
7
5
4
1
7
2
1
2
4
4
Complete
linkage
le
2d
7a
2d
2b
7b
9a
Ic
2b
7b
2a
3
7a
2a
7a
2e
5a
5a
5b
le
2a
4a
2b
lc
4a
2b
lc
lc
2a
4a
4d
5b
(2f)
le
2a
lc
2a
7a
Ic
lc
2c
5b
7a
2a
3
3
5c
5c
7a
5a
4d
2b
2e
2c
2a
2c
4d
4c
Range
H
EP
WP
WP
WP
E
H
EP
WP
EP, A
EP
WP
WP
El’
WP
EP
E
E
E
EP
WP
E
WP
WP
E
WP
EP
EP
EP
E
WP
E
WP
EP
H, A
EP
EP
E
EP
WP
WP
E
WP
EP
EP, A, 0
EP, A, 0
WP, A, 0
WP
WP
WP, A, 0
WP, A, 0
EP
E
E
El’
EP
E
E
R. L. H. DENNIS E T AL.
44
APPENDIX
2 continued
No.
95
96
97
98
99
100
101
102
103
104
105
(385)
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
(386)
(387)
137
138
139
140
141
142
143
144
145
146
(388)
147
148
Species
CeImtrina argiolus
Glaucopsyche alexis
Glaucopsyche m h n o p s
Turanana panagaca
Maculinea alcon
Maculinea arion
Maculinea telejus
Maculinea nauritlrous
Iolana iolas
Pseudophilotes baton
Pseudophilotes panoptes
Pseudophilotes barbagiae
Pseudophilotes abcncmagus
Pseudophilotes bavius
Scolitantides orion
Frqynia trochylus
Plebejus vogeIii
Plebgus martini
Plebgus pylaon
Plebejus argus
Lycm'des idas
Lycacides argyrognomn
Vacciniina optilete
Kretania psylorita
Eumedonia eumcdon
Aricia agestis
Aricia artaxerxes
Aricia morronensis
Aricia anteros
Pseudaricia nicias
Albulina orbitulus
Agriades glandon
Agriades pyrenaicus
Cyaniris soniargus
Cyaniris helm
Agrodiaetus iphigmia
Agrodiaetus d a m n
Agrodiaetus d o h
Agrodiaetus ainsac
Agrodiaetus admctus
Agrodiaetw fabressei
Agrodiaetus araansnuis
Agrodiaetus ripartii
Agrodiaetw violetae
Agrodiaetus nephohiptamenos
Agrodiactus escheri
Agrodiaetus amanda
Agrodiaetus thersiks
Agrodiactus coelestinus
Plebicula dorylas
PIebicula golgas
Plebicula nivescnu
Plebicula atlantica
Meleagcria akphnis
Lysandra coridon
Lysandra phiIippi
Lysandra hispana
Lysandra albicam
Principal
coordinate
analysis
1
1
4
7
1
I
1, 2
1, 2
2
1
4
8b
4
7
1
7
5
5
7
1
1
1
I
8a
1
1
1
4
7
9
9
9
10
1
7
7
1, 2
4
10
7
4
7
4
4
7
4
I
2
7
1
4
4
5
2
1
7
4
4
Complete
linkage
2a
2a
4a
7e
IC
IC
Ib
Ib
2c
2b
4d
8b
4d
7a
Id
7a
5a
5b
7a
2a
2a
lc
le
8a
la
2b
Id
4b
7b
10b
10b
9c
-
2a
7e
7e
Ib
1Of
1oc
7a
4b
7b
4b
4d
7d
4b
Id
2b
7e
lc
4c
4b
5b
2c
lc
7d
4b
4d
Range
H
EP
E
WP
EP
EP
EP
WP
WP
WP
E
E
WP
WP
EP
WP, A, 0
E
E
WP
EP
H
WP
H
E
EP
EP
EP
E
WP
WP
EP
H
WP
EP
WP
WP
EP
E
E
E
E
E
WP
E
E
E
WP
EP
WP
WP
E
E
E
WP
WP
E
E
E
EUROPEAN BUTTERFLIES
45
APPENDIX2 continued
No.
149
I50
151
I52
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
20 1
202
203
204
205
206
Species
Lysandra bellargus
Lysandra punct@ra
Polyommatus icarus
Polyommatus eroides
Polyommatus eros
Hamearis lucina
Libythea celtis
Charaxes jasius
Apatura iris
Apatura ilia
Apatura metis
Limenitis populi
Limenitis reducla
Limenitis Camilla
Neptis sappho
Neptis rivularis
N p p h a l i s antiopa
N p p h a l i s polychloros
N p p h a l i s xanthomlas
N p p h a l i s vau-album
Inachis io
Vanessa atalanta
Cpthia cardui
Aglais urticae
Polygonia c-album
Polygonia egea
Araschnia levana
Pandoriana pundora
Argynnis paphiu
Argyronome laodice
Mesoacidalia aglaia
Fabriciana ad$@
Fabriciana niobe
Fabriciana eliso
Issoria lathonia
Brmthis hecate
Brenthis daphne
Brenthis in0
Boloria pales
Boloria napaea
Boloria aguilonaris
Boloria graeca
Proclossiana eunomia
Clossiana euphrosyne
Clossiana titania
Clossiana selene
Clossiana chariclea
Clossianafreiju
Clossiana dia
Clossiana polaris
Clossiana thore
Clossianafrigg6,
Clossiana improba
Melitaea cinxia
Melitaea arduinna
Melitaea phoebe
Melitaea aetherie
Melitaea didyma
Principal
coordinate
analysis
1
5
1
7
10
Complete
linkage
lc
5b
2a
7a
1Of
1
IC
2
3
2c
3
1
Ic
1
7
lc
7b
le
2b
lc
2d
2d
2a
2b
2d
2d
2a
2a
5c
2a
2a
7a
lc
2c
2a
la
2a
2a
2a
8b
2a
2c
2c
le
1Oa
9c
le
7c
le
2a
la
le
9a
9b
lc
9a
9c
9b
9a
2a
1
1, 2
1
2
2
1
1
2
2
I
1
5
1
1
2, 7
1
1, 2
1
2
1
1
1
8b
1
2
2
1
10
9, 10
1
7
1
1
9, 10
1
9
9
1
9
9
9
9
1
7
1
5
1
7b
2b
5c
2b
Range
WP
E
EP
EP
EP
EP
EP
WP, A
EP
EP
EP
EP
WP
EP
EP
EP
H
WP
EP
H
EP
H
H, A, 0
EP
EP
WP
EP
WP
EP
EP
EP
EP
WP
E
EP
EP
EP
EP
EP
H
EP
E
H
EP
H
H
H
H
EP
H
EP
H
H
EP
EP
EP
E
EP
R. L. H. DENNIS E'T AL.
46
APPENDIX
2 continued
No.
207
208
209
210
21 1
212
213
214
215
216
217
218
219
220
22 1
222
223
224
225
226
22 7
228
229
230
23 1
232
233
234
235
236
237
238
239
240
24 1
242
243
244
245
246
247
248
249
(389)
(390)
250
25 1
252
253
254
255
256
25 7
258
259
260
26 1
262
Species
Melitaea deserticola
Melitaea trivia
Melitaea diamina
Mellicta athalia
Mellicta deione
Mellicta uaria
Mellicta parthoides
Mellicta aurelia
Mellicta britomartis
Mellicta asteria
Hypodyas matuma
Hypodyas inlcrmedia
Hypodyas Cynthia
H y p o d y u iduna
Eurodyas aurinia
Eurodyas aurinia debilis
Eurodyas dcsfonh'nii
Melanargia galathea
Melanargia russioe
Melanargia larissa
Melanargia occitanica
Melanargia arge
Melanargia ines
Hipparchia f a g i
Hipparchia alcyone
Hipparchia syinca
Hipparchia ellena
Hipparchia neomiris
Hipparchia delattini
Hipparchia cretica
Hipparchia semele
Hipparchia aristcus
Neohipparchia statilinus
Neohipparchia fatua
Neohipparchia hansii
Neohipparchia powelli
Pseudohgumia Jidia
Chazara briseis
Chazara prieuri
Pseudochazara atlantis
Pseudochazara hippolyte
Pseudochazara amymone
Pseudochazara graeca
Pseudochazara orestes
Pseudochqara tisiphone
Pseudochazara cingouskii
Pseudochazara &lea
Pseudochazara gyeri
Oeneis noma
O m i s bore
Oeneis glacialis
Oeneisjutta
Satyrus actaea
Satyrus ferula
Minois dyas
Berberia abdelkader
Brintesia circe
Arethusana arethusa
Principal
coordinate
analysis
5
2
1
1
4
10
4
1
2
10
1
10
10
9
1
10
4
1
10, 4
7
4
6
4
1
1
7
5
8b
7
8a
1
7
1
7
5
5
4
1
4
5
4
7
7
7
7
7
7
7
9
9
10
9
4
1
1
5
1
1
Complete
linkage
5b
2c
2a
2a
4a
1Of
4a
lc
2d
1Oe
le
10e
1Od
9a
2a
1Od
4b
2b
4b
7a
4a
6
4d
2b
Ic
7b
5a
8b
7C
8a
2a
7a
2b
7a
5b
5a
4a
2b
4d
5b
4c
7c
7e
7d
7C
7C
7b
7c
9b
9a
1Od
9b
4a
2c
2b
5a
2b
2b
Range
WP
WP
EP
EP
E
E
E
EP
EP
E
EP
EP
E
EP
EP
E
E
WP
EP
WP
E
E
E
E
E
WP
E
E
E
E
WP
WP
WP
WP
E
E
E
EP
E
E
EP
E
E
E
E
E
WP
WP
EP
H
E
H
WP
EP
EP
E
EP
EP
47
EUROPEAN BUTTERFLIES
APPENDIX
2 continued
~~
No.
263
264
265
266
267
268
269
270
27 1
272
273
274
275
276
277
278
279
280
28 1
282
283
284
285
286
287
288
289
290
29 1
292
293
294
295
296
297
298
299
300
30 1
302
303
304
305
306
307
308
309
310
31 1
312
313
314
315
316
317
318
319
320
Species
Erebia ligea
Erebia e u y a k
Erebia eriphyle
Erebia manto
Erebia Claudine
Erebia Jauofasciata
Erebia epiphron
Erebia serotina
Erebia christi
Erebia pharte
Erebia melampus
Erebia sudetica
Erebia aethiopJ
Erebia triaria
Erebia embla
Erebia disa
Erebia medusa
Erebia polaris
Erebia alberganw
Erebia Pluto
Erebia gorge
Erebia aethiopella
Erebia mnestra
Erebia gorgone
Erebia epistygne
Erebia Qndarw
Erebia cassioidts
Erebia hispaniu
Erebia niualis
Erebia calcaria
Erebia ottomana
Erebia pronoe
Erebia melas
Erebia lefeburei
Erebia scipio
Erebia styria
Erebia styx
Erebia montana
Erebia zapateri
Erebia neorides
Erebia oeme
Erebia meolans
Erebia palarica
Erebia pandrose
Erebia sthennyo
Erebia phegea
Maniola jurtinu
Maniola nurag
Hyponephele maroccana
Hyponephele lycaon
Hyponephele lupina
Aphantopus hyperanthus
Pyonia tithonu
Pyronia Cecilia
Pyronia bathseb,i
Pyronia janiroides
Coenonympha tullia
Coenonympha rhodopensis
Principal
coordinate
analysis
1
10
10
10
10
10
10
10
10
10
10
10
1
10
9
9
1
9
10
10
10
10
10
10
10
10
10
10
10
10
7
10
10
10
10
10
10
10
4
10
10
10
10
9
10
2
1
8b
5
1
7, 4
1
1
4
5
5
1
7
Complete
linkage
Id
I Oa
1Od
1Oa
1Oe
1Oe
1Oa
10b
1Oe
1Od
1Od
1Oa
lc
4b
9b
9a
lc
9a
1Of
1Of
10a
7c
I Od
lob
4b
1Od
I Oa
4d
1Oe
1Oe
7c
10a
2e
I oc
I Oe
1Oe
1Od
1Of
4c
1 Of
1Oa
10a
1oc
9c
10b
__
2a
8b
5b
Ic
3
le
2b
3
4a
5a
le
7b
Range
EP
EP
E
E
E
E
E
E
E
E
E
E
E
E
EP
H
EP
EP
E
E
E
E
E
E
E
E
E
E
E
E
WP
E
E
E
E
E
E
E
E
E
E
E
E
EP
E
EP
WP
E
E
EP
EP
EP
WP
E
E
E
H
E
R. L. H. DENNIS E T AL.
48
APPENDE2 continued
~~
No.
32 1
322
323
324
325
326
327
328
329
330
331
332
(393)
333
334
335
336
337
338
339
340
34 I
342
343
344
345
346
347
348
349
350
35 1
352
353
354
355
356
357
358
359
360
36 1
362
363
364
365
366
(391)
367
368
369
370
37 1
372
373
374
375
376
~~~~~~~~
Species
Comonppha pamphilus
Comonppha corinna
Comonppha elbana
Comonppha hrus
Coenonppha austati
Comonppha u a u c k
Coenonppha arcania
Comonppha danviniana
Coenonppha gardcfta
Comonppha arcanwides
Comonppha leander
Comonppha glycerion
Comonppha iphioides
Comonppha hero
Comonppha oedippus
Pararge aegnia
Lasiommata megera
Lasiommata maera
Lasiommata peiropolihna
Lapinga achine
Kirinia roxelana
Kirinia climcne
P y g u maluae
Pygus a l u m
Pygus armoncanus
Pygus foulquim.
Pygus warrmnrris
Pygus smaidae
Pygus c. carlinac
Pygus c. cirsii
Pygus onopordi
Pygus cinarae
Pygus sidae
Pygus carihami
Pygur andromedac
Pygus cacaliac
Pygus cmhuruu
Spialia sertorius
Spialia orbifct.
Spialia phlomidis
Spialia doris
Sjvichtus tessellum
SyTichtus m'bellwn
Sjrichtus proio
S$vichtus mohammd
Syichius leuzeae
Carcharodus alcaea
Carcharodus tripolinus
Carcharodus laoatherae
Carcharodus boeticus
Carcharodusjoccifnur
Carcharodus orientalis
E r p i S tages
Erynnis marloyi
Hetcr0picru.s morphcus
Cartcrocephaluspalaemon
Carterocephalus siluicolus
Thynelicus acteon
Principal
coordinate
analysis
1
8b
6
4
5
5
1
10
LO
5
7
1
1
1
1
1
1
1
9
1
7
7
1
1
1
10
10
1
10
4
3, 4
J
7
1
9
10
9
4
7
7
5
7
2
3
5
5
1
4, 5
1
3, 4
1
7
1
7
1
1
9
1
Complete
linkage
2a
8b
6
4a
5a
5b
Ic
1Oa
1Od
5a
2e
Ic
4b
le
Ib
2a
2a
2a
9b
Ic
7a
7b
2a
2a
2b
1Of
1Oe
Ic
1Od
4a
4a
7a
7a
2b
9c
10b
9b
4a
2d
7a
5b
7a
-
3
5b
5a
2b
5c
2b
4a
2b
Ja
2a
7a
IC
le
9b
2b
Range
EP
E
E
E
E
E
WP
E
E
E
WP
EP
E
EP
EP
EP
WP
EP
EP
EP
WP
WP
EP
EP
WP
E
E
EP
E
E
E
WP
WP
EP
E
E
H
EP
EP
WP
WP, 0
EP
EP
WP
E
E
EP
E
WP
WP
E
WP
EP
WP
EP
H
EP
WP
EUROPEAN BUTTERFLIES
49
APPENDIX
2 continued
No.
377
378
379
380
38 1
382
383
384
Species
Thymelicus hamza
Thymelicus lineola
Tlymelicus Jauus
Hesperia comma
Ochlodes uenatus
Gegenes nostrodamus
Gegenes pumilio
Borbo borbonica
Principal
coordinate
analysis
5
1
1
1
1
3
3
4, 5
Complete
linkage
Range
5c
2a
2b
2a
2a
3
3
4d
E
H
WP
H
EP
WP, 0
EP, A
WP, A
Complete linkage clustering faunal unit coding: 1. European extent cluster: a, north-east and east-central
Europe; b, east and central Europe; c, pan-continental Europe exScandinavia and Britain; d, Europe apart
from the north west; e, pan-north continental Europe with Scandinavia. 2. European extent cluster: a, panEurope (cosmopolitan group); b, south central Europe; c, southern Europe; d, south-east central Europe; e,
central southern Europe (northern Balkans). 3. Mediterranean zone. 4. Western Mediterranean zone: a, south
west Europe and north Africa; b, central and northern Iberia; c, southern Iberia; d, central and southern Spain
and north Africa. 5. North Africa: a, coastal north Africa; b, Atlas mountains; c, north Africa and southern
Spain. 6. Italy peninsula and islands. 7. Eastern Mediterranean zone; a, southern Balkans and Armenia; b,
south east Europe; c, north Greece; d, eastern Greece; e, southern Greece. 8. Mediterranean islands: a, Crete;
b, Sardinia and Corsica. 9. Northern zone: a, arctic unit; b, arctic-alpine group; c, Scandinavian mountain and
arctic group. 10. European mountains: a, widespread mountain unit; b, Pyrenees; c, Cantabrians and
Pyrenees; d, Alps and adjoining uplands; e, high Alps and dinaric Alps; f, Alps and Apennines.
Principal coordinate coding: 1, European extent vector; 2, Subsidiary European extent vector describing
eastern and southern Europe in Papilionids, Pierids, Lycaenids and Nymphalids; 3-10, as for complete linkage
analysis. Joint coding indicates modest loadings on two factors. Three species linked on the complete linkage
dendrogram failed to classify meaningfully to any units, but resolved on distinct vectors in Principal
coordinates analysis: Agriades pyrmaicus; Erebia phegea and Syrichtus cribellum. Tomares nogelli dobrogmsis is only
found in Romanian Dobrogea and has a unique branch on the dendrogram.
Neither analysis determines the statistical significance of units identified. Subsets of the European extent
clusters 1 and 2 are given here only to describe the bias for the part of Europe covered by their species.
Notation for range as in Table 6.
Note added in proof
The terms ‘sub-regions’, ‘faunal units’ and ‘extent’ correspond closely with
‘primary areas’, ‘faunal elements’ and ‘widespread’ respectively in J. D.
Holloway and N. Jardine, 1968. Two approaches to zoogeography; a study
based on the distribution of butterflies, birds and bats in the Indo-Australian
area. Proceedings of the Linnean Society of London, 179: 153-188.