J Insect Conserv
DOI 10.1007/s10841-016-9858-x
ORIGINAL PAPER
Adult population ecology and egg laying strategy in the ‘cruciata’
ecotype of the endangered butterfly Maculinea alcon
(Lepidoptera: Lycaenidae)
Márta Osváth-Ferencz1 • Zsolt Czekes1 • Gyöngyvér Molnár1 • Bálint Markó1,2
Tibor-Csaba Vizauer3 • László Rákosy4 • Piotr Nowicki5
•
Received: 4 November 2015 / Accepted: 7 March 2016
Ó Springer International Publishing Switzerland 2016
Abstract Population dynamics studies in insects mostly
focus on a specific life stage of a species and seldom
consider different stages. Here, we studied the population
demography of a protected Maculinea alcon ‘cruciata’
population and the factors that could influence the distribution of eggs. The results of the mark-recapture survey
showed a relatively short flight period between mid-June
and mid-July with a clearly marked early peak period.
Unlike in many other butterflies, protandry was not strong.
The total population of M. alcon ‘cruciata’ was estimated
at 699 individuals. The survival rate, and consequently the
average life span, was relatively low. Eggs showed a highly
aggregated pattern, and egg numbers were positively
related to general shoot size, while the number of flower
buds and the features of the surrounding vegetation did not
display any effect on egg laying. Based on our findings, the
studied population appears viable, but specific management
& Márta Osváth-Ferencz
ferenczke@hotmail.com
& Zsolt Czekes
czekes@gmail.com
1
Hungarian Department of Biology and Ecology, BabeşBolyai University, Clinicilor Str. 5-7, 400006 Cluj-Napoca,
Romania
2
Department of Ecology, University of Szeged, Közép fasor
52, Szeged 6726, Hungary
3
Romanian Lepideptorological Society, Clinicilor Str. 5-7,
400006 Cluj-Napoca, Romania
4
Department of Taxonomy and Ecology, Babeş-Bolyai
University, Clinicilor Str. 5-7, 400006 Cluj-Napoca, Romania
5
Institute of Environmental Sciences, Jagiellonian University,
Gronostajowa 7, 30-387 Kraków, Poland
techniques could ensure optimal conditions for egg laying
in this protected butterfly.
Keywords Host plant Mark-recapture Sex ratio
Species conservation Survival Vegetation characteristics
Introduction
Dynamics of insect populations, mostly in the case of pests,
and more recently also in protected species, has been the
subject of wide range of studies (Way and Heong 1994;
Hunter 2001; Yamamura et al. 2006; Thomas et al. 2009).
Most of these concentrate on a single life stage of an insect
(e.g., adults, larvae), while usually neglecting parallel
investigations into other developmental stages, or the
connection between them (Elkinton and Liebhold 1990;
Yamamura et al. 2006; Ordano et al. 2015). Admittedly, it
is much easier, and therefore much more practical, to
determine the viability of any population based solely on
the abundance of adults, consequently many pest control
and species conservation actions primarily rely on such
information (Steytler and Samways 1995; Sunderland and
Samu 2000; Thomas et al. 2009). In highly mobile insects,
such as butterflies, the information on the existence of eggs
in a given area connected to the presence of adults is of
major relevance. Therefore, linking the dynamics of adults
with, e.g., egg laying patterns can offer a more precise
picture of the sustainability of populations in a given area,
since the viability of a population is primarily determined
by the number of offspring produced in the study area, i.e.,
in the case of insects by the number of eggs and/or larvae
(Begon et al. 1996).
The population dynamics of adult butterflies is frequently
connected to weather conditions and environmental
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J Insect Conserv
stochasticity (Melbourne and Hastings 2008; Nowicki et al.
2009; Cormont et al. 2013), while adult egg laying decisions,
and thus the fate of their offspring, primarily relies on the
condition of host plants, the strength of intraspecific competition, predatory pressure or other habitat parameters
(Stamp 1980 for a review, Bergman 2001; Czekes et al. 2014;
Patricelli et al. 2015). Ovipositing females have to choose the
optimal site for their offspring, as well as the best available
host plant within the site. Additionally, the survival of the
offspring can also be affected by the host plants’ direct or
indirect responses to the presence of eggs and/or larvae as
well (see Hilker and Fatouros 2015 for a review).
Large Blue butterflies of the genus Maculinea Van
Eecke, 1915 (synonymised lately with Phengaris Doherty,
1891) are one of the most intensively studied butterfly
groups in Europe, being considered flagship and umbrella
species in nature conservation. They are highly sensitive to
habitat changes, and the conservation of their habitats is
beneficial to many other threatened species (Thomas and
Settele 2004; Settele et al. 2005). In the past decades severe
declines were recorded in most of their Western European
populations due to habitat fragmentation and intensification
of agriculture (Van Swaay and Warren 1999; Van Swaay
et al. 2010). They also raise specific scientific interest due
to the intriguing obligate myrmecophylic lifestyle of their
larvae (see Witek et al. 2014). Most Maculinea populations
are small and isolated (Thomas et al. 1998), characterized
by density dependent regulation due to intra-specific
competition between larvae on host plants and/or in host
ant colonies (Hochberg et al. 1992; Nowicki et al. 2009).
Long-term surveys have already shown the importance of
weather patterns (Roy et al. 2001; Cormont et al. 2013), but
Maculinea populations are also affected by general habitat
characteristics (Nowicki et al. 2007), and human activities
(e.g., changes in agricultural practices) (Schmitt and
Rákosy 2007).
In the case of Maculinea alcon there are two major
ecotypes differentiated based on their host plants: the
hygrophilous form feeding on Gentiana pneumonanthe
(previously treated as M. alcon), and the xerophilous form
feeding on G. cruciata (previously treated as M. rebeli,
hereafter referred to as M. alcon ‘cruciata’). Recent
molecular studies showed that the two forms cannot be
regarded as different species (Bereczki et al. 2005; Steiner
et al. 2006; Pecsenye et al. 2007). Nevertheless, in addition
to habitat and host plant segregation, they typically use
different host ant species, and they also have different
flight periods (Bálint 1994; Sielezniew et al. 2012), therefore they ought to be treated as separate Evolutionary
Significant Units worthy of specific conservation status
(Independent Conservation Units) (see Casacci et al. 2014
for a review). Moreover, the North-East European populations of the ‘cruciata’ ecotype are endangered (see
123
Casacci et al. 2014), therefore comprehensive data is of
major relevance for conservation management plans. The
Romanian populations are outstanding in addition, since it
is here that the two ecotypes co-occur syntopically (see
Czekes et al. 2014).
Although there are a relatively large number of both
field and modelling studies on the ecology of M. alcon
‘cruciata’ (e.g., Hochberg et al. 1992; Czekes et al. 2014)
in which data concerning population parameters and data
concerning egg laying patterns were combined (see MeyerHozak 2000; K}orösi et al. 2008), there are no studies
available investigating adult population size and egg laying
patterns the data for which originate in the same time
period. In addition, there is a need for complex information
on populations of protected butterflies, but such studies are
generally rare in the case of other butterfly species as well
(see Bergman 2001). Consequently, the aims of our
research were to (a) study the within-season dynamics of
an adult M. alcon ‘cruciata’ population, while also (b) examining the temporal changes in the deposition of eggs,
and (c) identifying the factors influencing the distribution
of eggs.
Materials and methods
Study species and site
Maculinea alcon ‘cruciata’ prefers semi-natural calcareous
grasslands (Rákosy and Vodă 2008), and it uses quite a
wide range of host ant species from the genus Myrmica
Latreille, 1804, which adopt them due to their efficient
chemical and acoustical mimicry (see Fiedler 2006 and
Witek et al. 2014 for a review). Their development continues inside the ant nest, where they are fed by the ant
workers (Elmes et al. 1991). The flight period of adult
butterflies is from mid-June to mid-July (K}orösi et al.
2008). The conservation status of M. alcon is Least Concern according to the IUCN Red List in Europe and Near
Threatened in the European Union (Van Swaay et al.
2010).
The field study was performed on a 9,252 m2 seminatural calcareous dry grassland of southeastern exposure
in the surroundings of Rimetea village (N46°270 51.4500 ,
E23°330 46.2600 , ca. 620 m a.s.l., Romania). The grassland
is a plant species-rich meadow dominated by Brachypodium pinnatum, Carex humilis and Festuca rupicola
with other characteristic species including Dorycnium
pentaphyllum, Cytisus albus, Hieracium bauhinii, Teucrium montanum and Thymus serpyllum, and it is intensively grazed by goats and sheep. The meadow is partially
surrounded by a mixed forest and shrubs of Crataegus
monogyna, Prunus spinosa, Pyrus pyraster and Rosa
J Insect Conserv
canina. The site is part of the ROSCI0253 ‘Trascău’ Natura
2000 protected site.
Data collection
Population dynamics survey
A mark-recapture study of adult M. alcon ‘cruciata’ butterflies was conducted between 15 June and 16 July 2012
covering the entire flight period. The survey plan followed
the requirements of the Pollock’s Robust Design approach
(Pollock 1982; Pollock et al. 1990), i.e. relatively infrequent but highly intensive capture days were established,
which constituted primary sampling periods. The sampling
took place on every fourth day, with a single exceptional
case in which the interval between consecutive capture
days was reduced to 3 days due to the forecast of unfavourable weather conditions on the following days. Butterflies were surveyed between 10 am and 5 pm during five
one-hour capture sessions, separated by 30 min breaks to
allow free mixing of butterflies between the sessions. These
sessions were regarded as independent capture occasions,
constituting secondary sampling periods of the Robust
Design. In other words, recaptures occurring on the same
day but within different sessions were treated as independent events and they were used for estimating the number
of butterflies present on that particular day.
Captured individuals were marked on the underside of
their hind-wing with unique identity numbers using a finetipped waterproof pen (Ó Schneider GmbH), and then
immediately released at the place of capture. For each
capture we recorded the date, the exact time and the
position of each capture (GPS coordinates), as well as the
identity number and the sex of the adult.
Distribution of butterfly eggs
Prior to the adult butterfly survey, we randomly placed out
22 sampling plots within the study site. The plots were
circles of 2 m radius, as generally applied in the case of
Maculinea species based on the average foraging radius of
the host ant Myrmica (see Elmes et al. 1998), with a focal
G. cruciata plant in the middle. Within the plots we
recorded the number of all G. cruciata host plants, and the
number of their shoots. Shoots were considered to belong
to the same plant when they were obviously connected
above the soil surface. In order to minimise disturbance, we
recorded the number of eggs on the shoots of the focal host
plant within each plot (n = 22) only at the end of each
mark-recapture sampling day. At the end of the whole
study period we counted all eggs found on all host plant
shoots within the sampling plots in addition to the characteristics of the host plants and general vegetation
features. The following parameters were recorded: (a) the
total number of butterfly eggs laid on the host plant shoots,
and separately on different verticils, (b) shoot height as the
length of the shoot (cm), (c) number of shoot leaves, and
(d) number of flowers (only flower buds with coloured
sepals were taken into account since small green flower
buds are impossible to count sometimes) on separate verticils of shoots, (e) the number of host plants in each plot,
(f) the maximum height of the surrounding vegetation
(cm), and (g) the proportion of vegetation cover visually
estimated to the nearest 5 %.
Data analysis
Mark-recapture data was analysed with the use of Mark 7.0
program (White and Burnham 1999) applying the Robust
Design (RD) model (Pollock 1982; Kendall et al. 1995).
The RD model allows relatively high precision of population estimates, and it has proved its applicability in butterfly population studies (Nowicki et al. 2008). The
analyses were conducted separately for males and females,
because sex-specific population parameters were of interest
for our study. The data from capture sessions (i.e. secondary periods of the RD model) within sampling days
were used to estimate daily population sizes for these days
(Ni). In the estimation we accounted for individual
heterogeneity in capture probabilities, since its existence
was revealed by the tests for violations to the equal
catchability assumption (Otis et al. 1978; Chao 1988). In
turn, the data pooled together within capture days (i.e.
primary periods of the RD model) were used for assessing
survival rate between these days (ui). The model variant
assuming no time variation in survival rate performed the
best as indicated by its lowest value of the Akaike Information Criterion corrected for small samples (AICc; Hurvich and Tsai 1989), which implies that adult survivorship
was fairly constant throughout the flight period. Subsequently, we calculated the average adult lifespan as
e = (1 - u)-1 - 0.5 (Nowicki et al. 2005a).
Based on the estimates of daily population sizes and
survival rates, we also estimated the recruitment (Bi), i.e.
the numbers of individuals eclosing from pupae and
entering the adult population during the intervals between
consecutive capture days. As the adult life span was relatively short when compared with the length of these
intervals (di), we used the formula of Nowicki et al.
(2005a; see this reference for the rationale), which accounts
for the individuals eclosing and dying within the same
intervals: Bi0 = d 9 (Ni?1 - Niud) 9 (u - 1)/(ud - 1).
The sum of recruitment for the entire flight period makesup the seasonal population size (Ntotal). In a similar way, by
summing female recruitment prior to each capture day, we
derived the total number of females present.
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Poulin’s discrepancy index (Poulin 1993) was used to
characterize the distribution of eggs on host plant shoots.
The index is generally used to describe the tendency of a
parasite to aggregate, or overdisperse within the host
population. We applied it to characterize the distribution of
eggs among host plant shoots. Biases in the distribution of
eggs among different host plant verticils were checked
using a Generalized Linear Mixed Model approach
(GLMM, Poisson error, maximum likelihood approximation; n = 133). The number of eggs laid on different verticils of egg-bearing plant shoots was introduced as
dependent variable, and the ID of verticil as independent
factor. Sampling plot and plant IDs were introduced as
nested random factors to handle dependency of data. Only
egg data from the top four verticils were taken into account
since no eggs were recorded on lower verticils.
We tested the relationship between the estimated number
of females present before each sampling day, and the total
number of eggs laid in the same period (n = 8) in order to
reveal whether the number of eggs laid was related to the
number of female butterflies. Spearman rank correlation
analysis was applied due to the lack of normality of both
variables. In addition, the effect of the abundance of eggs
already present on oviposition was checked by testing the
relationship between the number of eggs present and the
number of newly-laid eggs in the following period for seven
consecutive periods between the eight sampling days. Again,
Spearman rank correlation analysis was applied in this case.
The effects of host plant and vegetation characteristics
on egg distribution were analyzed using GLMM (Poisson
error, maximum likelihood approximation; n = 410).
Correlation between host plant characteristics were
checked using Spearman rank correlation analysis due to
non-normality of datasets. A principal component analysis
(PCA) was applied to obtained uncorrelated derived variables for plant characteristics, and the principal components were used as independent variables in the GLMM
analysis. The number of eggs laid on each focal host plant
shoot was introduced as a dependent variable, while
independent variables were the host plant shoot morphological characteristics [PC1 (correlated shoot height and
number of leaves) and PC2 (correlated number of flower
buds)], the number of host plants in sample plots, the
maximum height of the surrounding vegetation, and vegetation cover. Sampling plot and host plant IDs were
introduced as random factors to handle dependencies.
Automated model selection procedure was carried out, and
the effects of different explanatory variables were averaged
across the supported models with delta AICc \4, i.e. those
with the AICc differing by \4 from the best model (see
Grueber et al. 2011).
All statistical analyses were carried out using the R 3.1.1
Statistical Environment (R Development Core Team 2014)
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and Quantitative Parasitology 3.0 (Rózsa et al. 2000).
Normality of datasets was regularly checked with the
Shapiro–Wilk test. The Relevel function was used in order
to carry out post hoc sequential comparisons among factor
levels when performing GLMM. GLMMs were carried out
with the use of the glmer function in the package lme4
(Bates et al. 2015), and the dredge function in the MuMIn
package (Barton 2015) was applied for automated model
selection. Table-wide Bonferroni-Holm correction was
applied in the case of sequential comparisons, such as
Spearman rank correlations and comparison of factor levels
in the GLMM analysis concerning the location of eggs on
different verticils.
Results
Demography and dynamics of adult butterflies
During the entire study we captured and marked 152
(67.5 %) males and 73 (32.5 %) females, out of which 85
males and 14 females, respectively, were recaptured at
least once. The total adult population was assessed at 699
individuals, with a relatively balanced sex ratio (55 %
males vs. 45 % females) (Table 1). The estimated survival
was fairly low, which translates to a rather short adult
lifespan of ca. 2 days with no major inter-sexual difference
(Table 1).
The butterfly had a relatively short flight period between
mid-June and mid-July, with a clearly pronounced peak
occurrence in the early part of the period (Fig. 1). More
than 50 % of individuals emerged within the first week,
and more than 80 % within the first two weeks (Fig. 1).
Besides, in comparison to many other butterfly species, we
found rather weak protandry (cf. Pfeifer et al. 2000;
Nowicki et al. 2005a): the number of females peaked only
three days after the peak of males. Most of the butterflies
clearly preferred the close proximity of shrubs (Fig. 2).
Egg laying dynamics and preferences
At the end of the study altogether 94 eggs were recorded on
a total of 410 G. cruciata shoots of 201 plants within the 22
study plots. More than 90 % of the shoots lacked eggs, and
the maximum number of eggs on a single shoot was 23.
The overall mean egg density was 0.47 eggs/plant, and 0.23
eggs/shoot (4.48 eggs/plant and 4.09 eggs/shoot for plants
with eggs); while the mean host plant density was 0.72
plants/m2 (9.13 plants/plot), and 1.48 shoots/m2 (18.6
shoots/plot). The distribution of eggs on plants showed a
highly aggregated pattern (Fig. 3) as indicated by Poulin’s
discrepancy index (D = 0.97). Eggs were laid only on the
top four verticils of the plants. Most eggs were laid on the
J Insect Conserv
Table 1 Basic parameters of the investigated Maculinea alcon ‘cruciata’ population as revealed by the MRR study (95 % confidence intervals
in brackets)
Seasonal population
Survival rate (day-1)
Adult lifespan
(days)
152
382 (305–496)
0.63 (0.57–0.69)
2.2 (1.8–2.8)
73
317 (219–480)
0.57 (0.34–0.77)
1.8 (1.0–3.8)
225
699 (565–884)
0.62 (0.56–0.68)
2.1 (1.8–2.6)
Captured
individuals
Females
All
Fig. 1 Dynamics of male and
female adult butterflies
throughout the study period
based on mark-recapture
estimates. Error bars represent
95 % confidence intervals
160
males
females
total
140
no. of individuals
Males
120
100
80
60
40
20
0
15VI
19VI
22VI
26VI
30VI
4VII
8VII
12VII
16VII
390
385
10
5
0
frequency of host plant shoots
395
sampling days
0
5
10
15
20
25
no. of eggs
Fig. 3 The frequency distribution of eggs on host plant shoots
Fig. 2 The distribution of male (black) and female (white) butterfly
captures (recaptures included)
2nd verticil (33.93 % of total), but no significant differences were revealed between the number of eggs on the
different verticils (GLMM, z B 1.487, p = NS, n = 133).
Eggs were recorded even during the first part of the
study period on the focal host plants of the sampling plots
(n = 22), even if less \10 % of the focal plants bore eggs
on the 2nd sampling day (22.06). By the 6th sampling day
(08.07) 63 % of the plants had eggs, after this the percentage of egg bearing plants decreased (Fig. 4). The
number of eggs laid before each capture period did not
correlate with the number of females recruited in the same
period (Spearman r = 0.53, p = 0.13, n = 8). In turn, the
number of newly-laid eggs correlated negatively with the
number of eggs already present on host plants, the negative
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J Insect Conserv
80
70
total number of eggs
0.7
plants with eggs
eggs
0.6
60
0.5
50
0.4
40
0.3
30
0.2
20
0.1
10
0
proportion of plants with eggs
Fig. 4 Temporal dynamics of
eggs laid on the host plants
during the flight period. Error
bars represent standard
deviations
0
19VI
22VI
26VI
30VI
4VII
8VII
12VII
16VII
sampling days
correlations between the two variables reached statistical
significance during all but two sampling periods (Table 2).
Host plant morphological characteristics were mostly
correlated according to the results of the Spearman rankcorrelation analysis (n = 410): shoot height versus number
of leaves r = 0.5, p \ 0.001; number of leaves versus
number of flower buds r = 0.25, p \ 0.001; shoot height
versus number of flower buds r = 0.10, p \ 0.05. The PCA
yielded 1st (PC1) and 2nd (PC2) principal components that
explained 52 and 31 % of the variance, respectively. PC1
represented shoot height and number of leaves with loadings of 0.66 and 0.68, respectively, as a measure of general
shoot size, while PC2 reflected the number of flower buds
with a loading of 0.94. All input variables were retained in
the best average GLMM model for egg laying preferences
(see Tables 3, 4 for details on the best average model), but
only the general shoot size (PC1) had a significant positive
effect on the number of eggs laid (Table 4). Thus, there
were more eggs on taller shoots with more leaves (Fig. 5).
None of the other input variables displayed any significant
effects (Table 4).
Table 2 Spearman rank correlations (n = 22 in all cases) between
the number of eggs present and the number of newly-laid eggs on host
plants on different capture dates
Capture date
Spearman r
19.06
-0.73
0.001
22.06
-0.21
0.731
26.06
-0.51
0.006
30.06
-0.89
<0.001
04.07
0.04
0.861
08.07
-0.74
<0.001
12.07
-0.91
<0.001
Statistically significant values are bolded
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p
Discussion
The results of the present study show that the butterfly
population studied appears fairly viable based on the
comparison with other studies concerning the size of M.
alcon ‘cruciata’ populations. During a 3 year long MRR
study Árnyas et al. (2005) found that on a 0.75 ha site the
studied M. alcon ‘cruciata’ population was stable with
nearly 1,000 individuals, while Timuş et al. (2013) estimated the size of another population in Romania to 1,073
individuals for a 40 ha site. In comparison, the size of our
studied population (699 individuals on *1 ha) suggests
that the population is relatively big. Generally, Maculinea
alcon populations show very small fluctuations (Hochberg
et al. 1994; Elmes et al. 1996), thus there is a considerable
chance that our studied population is stable as well.
Similarly to other European populations (Meyer-Hozak
2000; Árnyas et al. 2005), we found that the butterflies fly
from mid-June to mid-July. In some cases the flight period
takes \1 month (Timuş et al. 2013), which can reflect
differences in habitat or/and meteorological conditions of
different populations. Although we found a relatively weak
indication of protandry, the peak emergence of males still
preceded that of females. This phenomenon is in fact
common for all Maculinea species and for butterflies in
general. According to Elmes and Thomas (1987) the males
pupate a few days before females, and thus during the
initial part of the flight period the population is dominated
by males. During the entire study we caught roughly twice
as many male individuals as female, but the estimated sex
ratio was relatively balanced, which corresponds with
results of other studies (Árnyas et al. 2005; Timuş et al.
2013). Considerably higher capture and recapture rates of
males may be attributed also to the fact that they fly more
often and higher searching for the less mobile females. The
latter tend to fly lower because they are searching for food
plants in the undergrowth (Árnyas et al. 2005).
J Insect Conserv
Table 4 The best average
GLMM model explaining the
effect of host plant and
vegetation characteristics on
Maculinea egg distribution
Fig. 5 The relationship
between shoot height and
number of leaves featuring the
quantity of Maculinea eggs laid
on specific shoots. The area of
each circle is proportional to the
number of eggs laid
Model structure (input variables)
logLik
df
DAICc
AICc
Weight
PC1 ? PC2
5
-119.61
249.37
0.00
0.25
PC1 ? PC2 ? Height
6
-119.30
250.80
1.43
0.12
PC1
4
-121.47
251.03
1.66
0.11
Cover ? PC1 ? PC2
6
-119.51
251.23
1.87
0.10
Density ? PC1 ? PC2
6
-119.56
251.33
1.96
0.10
Density ? PC1
5
-121.14
252.43
3.06
0.06
Cover ? PC1 ? PC2 ? Height
7
-119.16
252.61
3.27
0.05
PC1 ? Height
5
-121.28
252.72
3.35
0.05
Density ? PC1 ? PC2 ? Height
7
-119.26
252.79
3.43
0.05
Cover ? PC1
5
-121.37
252.89
3.52
0.05
Cover ? Density ? PC1 ? PC2
7
-119.46
253.20
3.84
0.04
Variable
Estimate
PC1
PC2
Height
SE
Adjusted SE
z
p
Relative
importance
2.299
0.499
0.500
4.594
\0.0001
1.00
-0.442
-0.009
0.432
0.029
0.433
0.029
1.020
0.333
0.308
0.739
0.73
0.28
Cover
-0.008
0.038
0.038
0.212
0.832
0.24
Density
-0.002
0.007
0.007
0.224
0.823
0.24
number of eggs
16
14
23
number of leaves
Table 3 The component
models (with delta AICc \4) of
the best average GLMM model
resulting from the automated
model selection procedure (see
Materials and Methods for the
explanations of the variables)
12
10
5
8
2
0
6
4
2
0
5
10
15
20
25
30
shoot height (cm)
Phytophagous butterfly species mostly lay their eggs
separately one by one or in clusters (Thompson and Pellmyr 1991). Both strategies can positively influence the
survival of eggs and larvae. Females can lower the chances
of predation and competition for their offspring by
depositing their eggs individually. In these cases eggs are
usually cryptic (light yellow or green) and are laid on
protected parts of the host plants (see Stamp 1980). Laying
eggs in clusters can be advantageous when other factors
can affect negatively the reproduction, like the patchy
distribution of host plants, the scarcity of resources for
larvae and adults, low population density or unfavorable
weather conditions (Stamp 1980; Karlsson and Johansson
2008). Besides, as clusters of eggs and larvae are more
protected from desiccation when clumped together, clusters
can ensure higher survivability through lower sensitivity to
ambient conditions (Stamp 1980; Clark and Faeth 1998).
During our study we found a low mean egg density per host
plant (0.47 eggs/plant) compared to that recorded by
Czekes et al. (2014) in another population (8.89 eggs/plant). In addition, the distribution of eggs among host
plants showed a clearly aggregated pattern, thus most of
the eggs were concentrated only on a few host plants. This
could suggest the patchy distribution of host ant colonies,
since some studies indicate that ovipositing females in
some Maculinea species could detect the presence of host
123
J Insect Conserv
ants indirectly (Van Dyck et al. 2000; Patricelli et al. 2015;
Wynhoff et al. 2015), although there is no evidence that
this holds true for all Maculinea (Thomas and Elmes 2001;
Nowicki et al. 2005b; Fürst and Nash 2010). The recent
comprehensive study of Patricelli et al. (2015) showed that
egg laying M. arion butterflies may detect the host ant
colonies by sensing the defensive volatile compounds
released by those host plants which have host ant colonies
residing in their roots. A similar mechanism might help M.
a. ‘cruciata’ to detect its host ants, but further inquiries
would be required to confirm it.
The number of females did not explain the number of
newly-laid eggs, which can also be attributed to the emigration of females. During the study we observed a few
females flying out of the study site. It is possible that some
of these females also laid their eggs in the surrounding land
fragments, as we noticed eggs laid outside the investigated
area. Another cause of this result could be the loss of a
large number of eggs during the egg laying season due to
predation (Bergman 2001), but also to meteorological
factors and the grazing of host plants (authors’ unpubl.
data; M. Dolek pers. comm.). There was a negative relationship between the number of eggs already present on the
plants and the quantity of newly-laid eggs. This result
could indicate that females would prefer ovipositing on
empty plants or at least with a small number of eggs present only. However, this evidence is very circumstantial
and would require a specifically-designed study for confirmation (see e.g. K}
orösi et al. 2008).
Earlier studies about egg laying preferences showed that
the most important factors influencing oviposition are the
morphological characteristics of host plants, such as the
height of the plant, the number, the size and the phenology of
buds, and the number of leaves (e.g. Czekes et al. 2014;
Wynhoff et al. 2015). In concordance with the aforementioned studies, our research suggests that females preferred
the taller shoots with many leaves for oviposition. A visually
conspicuous host plant (i.e. tall ones with many leaves) may
be more attractive or more perceptible for females than
smaller ones (Czekes et al. 2014; Wynhoff et al. 2015). The
large number of eggs on tall plants with a large number of
leaves can be beneficial for the butterflies due to an increased
egg laying surface, decreased larval competition, or even
better climatic conditions. Wynhoff et al. (2015) suggested
that larger host plants might provide high quantities of food
for the caterpillars as they would subsequently develop more
fully-developed flower buds than smaller plants. Maculinea
alcon ‘cruciata’ females laid their eggs exclusively on the
four top verticils of their host plants, which could be
attractive sites for oviposition presumably also because of
the lower predation risk for adult females (Van Dyck and
Regniers 2010) and the better microclimate for larval
development (Alonso 2003). In addition, ovipositing mostly
123
on the 2nd verticil from the top, as suggested by our data,
could ensure better climatic conditions to eggs through
reduced exposure to sun and wind.
Our findings also highlight the vulnerability of the
studied M. alcon ‘cruciata’ population. The discrepancy
between the number of females and the number of eggs,
and the reduced lifespan of adults compared to other
European populations suggests that the long-term stability
of our population might be threatened. Linking population
demography data to oviposition preferences could help the
protection of the focal butterfly species not only by offering
data to nature conservationists, but also by revealing that
specific management techniques could ensure better conditions for egg laying. Specifically, sustaining a low grazing pressure could have a positive effect on the butterfly
population (WallisDeVries and Raemakers 2001), and it
would also keep shrubs from invading the grassland.
Unfortunately, the solely species-based approach of current
European legislation (see Casacci et al. 2014 for discussion
therein) hinders the elaboration and application of specific
management plans for particular ecotypes as e.g. M. alcon
‘cruciata’. However, the survival of traditional land use
strategies in the study region, and more widely in Transylvania, Romania, may offer a good chance for the survival of this very specific ecotype of Maculinea alcon.
Acknowledgments We thank Annamária Fenesi and Krisztina
Havadt}
oi for the characterization of the study area’s vegetation,
Ádám K}
orösi for his helpful comments on the manuscript, and Paul
Kirkland for linguistic corrections which contributed to the
improvement of the manuscript considerably. M.O.-F.’s work was
supported by the Sectoral Operational Programme for Human
Resources Development 2007–2013, co-financed by the European
Social Fund, under the Project POSDRU/159/1.5/S/133391: ‘‘Doctoral and postdoctoral excellence programs for training highly qualified human resources for research in the fields of Life Sciences,
Environment and Earth’’. Furthermore the study was funded by the
Polish National Science Centre Grant DEC-2013/11/B/NZ8/00912.
During preparation of the manuscript Zs.C.’s work was supported by
a Grant of the Ministry of National Education (Romania), CNCSUEFISCDI, Project No. PN-II-ID-PCE-2012-4-0595, while B.M.’s
work by the Bolyai János Scholarship of the Hungarian Academy of
Sciences.
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