Faculty of Sciences
Department of Biology
Research group Terrestrial Ecology
Academic year 2013-2014
Climate change and intraspecific
phenological mismatches as a consequence
of asynchronic development.
Margaux Boeraeve
Promotor: Prof. Dr. Dries Bonte
Tutor: Drs. Katrien Van Petegem
Thesis submitted to obtain the degree of Master in Biology
©December 2013 Faculty of Sciences – Terrestrial Ecology
© All rights reserved. This thesis contains confidential information and confidential research results
that are property to the UGent. The contents of this master thesis may under no circumstances be
made public, nor complete or partial, without the explicit and preceding permission of the UGent
representative, i.e. the supervisor. The thesis may under no circumstances be copied or duplicated in
any form, unless permission granted in written form. Any violation of the confidential nature of this
thesis may impose irreparable damage to the UGent. In case of a dispute that may arise within the
context of this declaration, the Judicial Court of Gent only is competent to be notified.
2
Inhoudsopgave
Introduction......................................................................................................................................... 4
Objective ............................................................................................................................................. 7
Materials and Methods ....................................................................................................................... 7
Results ................................................................................................................................................. 9
Experiment 1 ................................................................................................................................... 9
Experiment 2 ................................................................................................................................. 11
Discussion .......................................................................................................................................... 14
Conclusion ......................................................................................................................................... 16
Samenvatting..................................................................................................................................... 17
Acknowledgements ........................................................................................................................... 19
References ......................................................................................................................................... 19
3
Introduction
The timing of life cycle events of organisms, also known as their phenology, strongly depends on
environmental factors like temperature (Kelly et al. 2008), moisture availability (Kimball et al. 2010)
and photoperiod (Vitasse & Basler 2013). Over the past decades some of these environmental factors
have been changing due to climate change. Surface temperatures for example have increased by
about 0.74 °C (as a global average) between 1906 and 2005 and eleven of the twelve warmest years
on record have occurred in the past twelve years (Solomon et al. 2007). Global warming causes
regional changes in the length of the growing seasons and seasonal temperatures. In Germany for
example Menzel et al. (2008) found that four deciduous tree species unfolded their leaves on
average 0.36 days earlier per year since 1951. Such changes in the phenology of species are called
phenological shifts (Clausen et al. 2013).
When the phenology of interacting species shifts differently, negatively affecting the fitness of (one
of) these species, we can expect a phenological mismatch to arise between those species. An
example of this can be found in Great tits (Parus major) (Visser et al. 2006) (Fig. 1). These
insectivorous birds rely on the presence of caterpillars on oak to feed their offspring. The caterpillars
appear after bud burst and disappear when they are fully
grown and ready to pupate in the soil. The reproductive
output of Great tits is maximal when the peak in caterpillar
biomass coincides with the nestlings being eleven to twelve
days old. The recent increase in global temperatures has
shifted the peak in caterpillar biomass to an earlier time in
the year and has compelled Great tits to follow. The peak in
caterpillar biomass, however, has advanced more in time
than the egg-laying schedule of Great tits, resulting in a
decreased fitness of late breeders, whose chicks miss the
short food peak. Other examples of phenological
mismatches can be found between plants and their
Fig. 1 Phenological mismatch between the
pollinators (Kudo et al. 2013), between species of different
Great tit and the food source for its nestlings.
In a normal situation will the caterpillar
trophic levels (Edwards et al. 2004) and between other
biomass peak around the time when the
interacting ecological groups. This makes phenological
nestlings are eleven to twelve days old.
Climate change has caused a shift in time of
mismatches between (groups of) species a well-studied
the caterpillar biomass, decreasing the fitness
subject.
of late-breeding Great tits (from Durant et al.
2007).
In theory, however, mismatches should also be possible
within a single species. Populations can become reproductively isolated because of differences in
phenology (Heard et al. 2012), as illustrated by Petrova et al. (2013) in Pinus sylvestris L., or
previously isolated populations can become reunited, which could result in outbreeding. Moreover,
phenological mismatches are also possible within a single population; for example between the sexes
of a species. Differences between sexes can be found in many taxa for morphological (Stillwell &
Davidowitz 2010), ecological (Houston & Shine 1993) and life history traits (Wiklund et al. 2003).
These differences between sexes might result in male and female phenology to react differently to
changes in environmental factors.
One way in which differently changing phenologies of sexes could result in a phenological mismatch,
is by impeding protandry. Protandry occurs when males arrive or emerge earlier at sites of
4
reproduction than females. This phenomenon is very common in arthropods. Protandry allows males
to maximize their mating opportunities with females, and allows females to minimize their risk of
pre-reproductive death (Morbey 2013). The fitness of a male individual not only depends on the
timing of his emergence relative to the emergence of females, but also on the timing of his
emergence relative to the timing of emergence of other males in the population (Holzapfel &
Bradshaw 2002). A slightly shorter developmental time relative to other males in the population will
result in more mating opportunities. But a shorter development also implies a greater risk of precopulatory death and greater costs as a result of the need for an increased growth rate. While a short
developmental time is advantageous for males, it is not necessarily advantageous for females. In
females, a longer development allows a larger adult body size, which leads to a higher fecundity.
Male development knows fewer constraints than female development. It is therefore possible that
an environmental factor decreases female development more than male development, resulting in a
disruption of protandry. Such a disruption could result in a decreased individual fitness of females
because of a higher risk of pre-reproductive mortality.
A decrease in fitness on the individual level, however, does not necessarily imply a decrease in fitness
on the population level. In the earlier example of the Great tits, Reed et al. (2012) did not find an
effect of the phenological mismatch on demography, despite the strong effect on the individual level.
There are several possible explanations. Firstly, decreases in the reproductive output of late breeders
could be compensated for by increases in the reproductive output of early breeders. This is because
the nestlings of the latter develop with fewer at the same time during a peak period in caterpillar
biomass, resulting in a lowered competition for food. Secondly, if climate change increases survival
outside the breeding season, this could counteract negative fitness effects during the breeding
season. And thirdly, high environmental stochasticity in demographic rates makes it difficult to
detect the signals of a potential mismatch.
This thesis will focus on a possible phenological mismatch between
the sexes of the two-spotted spider mite, Tetranychus urticae Koch
(Acari, Tetranychidae) and its potential consequences for fitness at
the level of the individual and the population.
Tetranychidae, the family of the spider mites, have a worldwide
distribution. They comprise over 70 genera with about 1200 species
(Zhang 2003), including some of the most important pest species in
the world, like T. urticae. They are all soft-bodied mites with a size of
approximately 400µm (oral-aboral axis) for an adult female and
190µm for an adult male (Sato et al. 2013).
T. urticae is a herbivorous mite species with a cosmopolitan
distribution. It has a rather short life cycle, comprising five stages:
Fig. 2 Adult female Tetranychus
egg, larva, protonymph, deutonymph and adult. The development
urticae (From Zhang 2003)
time of T. urticae decreases with temperature. For female mites (Fig.
2), it takes about 15 days to develop from egg to adult at 20°C. Males, however develop a little faster
than females. After reaching adulthood a male searches for a female teleiochrysalis (the resting stage
between the deutonymph stage and adulthood) and guards her until she emerges, allowing him to
fertilize her immediately. This mate-guarding behaviour invokes strong male-to-male mate
5
competition: males guarding a female are often challenged to a fight by other males (Sato et al.
2013).
T. urticae has an arrhenotokous haplodiploid genetic structure; unfertilized eggs become males and
fertilized eggs become females. This genetic structure has several consequences. Firstly, haplodiploid
species suffer less from inbreeding than diploid species (Henter 2003) because males are haploid and
will thus express deleterious recessive alleles, which can then be purged, reducing genetic load. This
is an advantage as inbreeding is quite common (colonies are mostly founded by a single mated
female). Secondly, the primary sex ratio can vary greatly. Female mites are supposed to have some
control over the fertilization of their eggs and thus over the sex of their offspring. According to
Hamilton’s local mate competition model, females will bias their progeny’s sex ratio towards a more
female-biased sex ratio in order to reduce the male-to-male mate competition and according to
Roeder et al. (1996) this is indeed the case for the two-spotted spider mite. This female-biased sexratio, together with the rapid development and high fecundity, results in a very fast population
growth.
As the species has a very broad host range (more than 1000 plant species (Migeon et al. 2006-2013))
and the highest incidence of pesticide resistance in arthropods (currently for at least 92 active
ingredients (Van Leeuwen et al. 2010)), it is considered a major pest for both field crops and
greenhouse production around the world.
These same characteristics that make this species a pest also make it a useful organism for
experiments: it can easily be grown in the lab in large numbers and it has a short development time
allowing it to evolve very fast and to be highly adaptive.
In previous experiments we tested several populations (from different latitudinal gradients) for the
influence of temperature on development time and fecundity (Volckaert 2012). We found that
temperature did not influence male and female development in the same way (Fig. 3). Furthermore,
we found the difference in development time between females and males to decrease with
increasing latitude. This suggests that females that are locally adapted to lower temperatures (as is
expected to be the case with females from northern latitudes) will have a development time that is
as short as or even shorter than that of local males when temperatures increase.
22.2
16
development time (days)
development time (days)
Development time at 17°C
21.7
21.2
20.7
Male
20.2
50
Female
Development time at 21°C
15.5
15
14.5
14
Male
13.5
55
latitude
50
Female
55
latitude
Fig. 43 In populations from higher latitudes (adapted to colder temperatures) the difference in development time between
females and males decreases with increasing temperature. In populations from lower latitudes (adapted to higher
temperatures) it is the other way around.
6
Since males might need their shorter development time to find a female soon enough to fertilize her,
a decrease in female development time might results in a phenological mismatch between the two
sexes. The purpose of my thesis therefore is to examine the potential influences of such a
phenological mismatch on the population.
Objective
The main objective of my thesis is to know whether temperature causes a phenological mismatch
between the sexes of T. urticae and whether this could have an influence on the population growth
and sex ratio in such way that it outbalances positive effects of temperature. My hypothesis is that a
higher temperature will have a long-term negative influence on population growth, especially in
northern populations. I also expect that the longer it takes for a female to get fertilized (= the smaller
the difference between male and female development), the slower the population will grow and the
higher the sex ratio (number of males to total number of adults) will be. This is because a nonfertilized female will only produce sons. Only after being fertilized, she will be able to produce female
offspring. I therefore expect the number of male offspring to initially be higher and the number of
female offspring to initially be lower (Fig. 4). Population growth will thus be slower as it will take
longer before a second generation of females is able to reproduce.
Normal first generation: adult
females and males
5
10
15
20
Time since founding female is adult (in days)
Female
Male
Expected first generation: adult
females and males
5
10
15
20
Time since founding female is adult (in days)
Female
Male
Fig. 5 On the left: how we expect the numbers of adult males and females in the first generation to be distributed
in time. On the right: distribution of numbers of females and males in time when the founding mother is fertilized
later than in the normal situation. We expect to see a higher peak in male offspring and a shift in increase of
female offspring to later in time.
Materials and Methods
Spider mites were collected in August 2012 at three different sites along a latitudinal gradient: in
55.74° north latitude (Lonne hede, Denmark -hereafter referred to as BLA), in 53.85° north latitude
(Arensch, Germany -hereafter referred to as ARE) and in 51.68° north latitude (Burgh-Haamstede,
The Netherlands -hereafter referred to as KVS). At the first two sites, mites were harvested from
leaves of European honeysuckle (Lonicera periclymenum), at the last site, mites were harvested from
European elder (Sambucus nigra). Once in the lab (of the Terrestrial Ecology Unit, University of
Ghent), the mites were grown on bean plants (Phaseolus vulgaris, variety ‘Prélude’) at room
temperature with a fixed light regime (16 hours light – 8 hours dark) until the beginning of the
experiments.
Two experiments were performed. In a first experiment, spider mites from the three different
latitudes were reared at three different temperatures (17° C, 19° C and 21° C) to see whether coldadapted female mites performed worse at higher temperatures (effect op temperature at
7
population-level). In a second experiment, freshly emerged males from KVS were placed together
with KVS females from one out of five different age-classes (deutonymph, teleiochrysalis and one,
two or three day old adults) at three different sex ratios (1 male : 3 females, 1 male : 2 females, 1
male : 1 female) to see whether a shift in male development relative to female development results
in a fitness effect at the individual level.
In each experiment, ten replicates of each treatment were monitored for at least two generations.
The numbers of all developmental stages (from egg to adult) were recorded every other day. The
second experiment was performed for five replicates at a time (because of practical reasons), in two
series.
Before starting these experiments, a pool of same-aged adult female mites was produced each time
by putting 30 mated females on a bean leaf (in a petri dish, on wet cotton) and allowing them to lay
eggs for 24 hours. For the first experiment, the offspring of these 30 females was used. For the
second experiment, however, this procedure was repeated several times in order to produce a large
enough pool of female mites from the five different age-classes. To produce the pool of freshly
moulted male mites, needed for the second experiment, 30 non-fertilized females were put on a
bean leaf and allowed to lay eggs for 24 hours. (As T. urticae is an arrhenotokous haplodiploid mite
species, all non-fertilized eggs develop into male individuals.)
The gathered data were analysed in SAS 9.4, with the GLIMMIX procedure. For the first experiment a
generalized linear mixed model was used with population size, temperature and time as fixed factors
and source population (ARE/BLA/KVS) as random factor. A poisson distribution and a log link function
was specified. The LSmeans of population sizes were determined at day 21-23 (moment at which one
of the replicates started to decrease in population size). A Tukey-Kramer test was applied to
determine the differences between LSmeans of the populations from different latitudes. Microsoft
Excel was used to plot the model and simulate population growth of the different populations in
time.
For the second experiment a generalized linear mixed model was used to determine whether
treatment and initial sex ratio had a significant influence on the population growth and the
secondary sex ratio (number of adult males/total number of adults).Fixed factors in the model were
population size, secondary sex ratio (number of males/total number of adults) and time. Treatment
(moment at which the male is put with the female), initial sex ratio and replicate were put in the
model as random factors. For analysing population growth a poisson distribution and a log link
function was specified, for analysing the secondary sex ratio a binomial distribution and logit link
function was specified. In order to correct for overdispersion a residual random component was
added. In order to simulate population growth in time, the model was plotted in Microsoft Excel.
LSmeans of secondary sex ratio at three moments in time (9-11 days, 14-16 days and 19-21 days
after the founding female(s) reached adulthood) were calculated.
8
Results
Experiment 1
A significant influence of temperature, time, source population and interaction between time and
temperature was detected (Table 1). There was no significant interaction effect between population
and time and between population and temperature.
Type III Tests of Fixed Effects
DFnum
DFden
2
944
1
944
2
27
2
944
4
940
2
938
Factor
Temperature
Time
Source population
Time*Temperature
Population*Temperature
Population*time
F Value
72.97
1277.51
5.44
26.61
1.76
0.00
p value
< 0.0001
< 0.0001
0.0103
< 0.0001
0.1340
0.9972
Table 1 Degrees of freedom, F and p values for the factors included in the generalized linear mixed model used to
analyse
size. size at day 21-23 show that populations perform best at 21°C (Fig. 5). At 21°C
LSmeanspopulation
of population
there’s a clear difference between KVS, the most southern population and ARE and BLA, the more
northern populations. AT 17°C and 19°C this difference is absent.
90
LSmeans of population size
80
population size
70
KVS
60
BLA
ARE
50
40
30
Fig. 6 LSmeans of population size at day 2123 (moment at which one of the replicates
started to decrease in population size). Red
indicates LSmeans of populations reared at
21°C, yellow at 19°C and blue at 17°C.
Population size is for every population
largest at 21°C. There is no significant
difference in population size at 17°C and
19°C
20
10
51
52
53
Latitude 54
55
56
This is on the short term (within one generation), to observe effects on the long term, the model was
plotted in Microsoft Excel. In the resulting graphs, we see a clear difference between short term
(before day 30) and long term (after day 30) (Fig. 7). The form of the curve also differs between the
three temperatures; the incline is much steeper at 17°C than at the other two temperatures (Fig. 6).
Because of this, the population size on day 50 is much larger in populations reared at 17°C than at
19°C and 21°C. KVS clearly performs better at any temperature, but the difference is smaller at lower
temperatures (Fig. 6).
9
7000
3000
Population growth at 17°C
Population growth at 19°C
6000
ARE
BLA
2500
KVS
ARE
Population size
Population size
5000
4000
3000
2000
2000
1500
1000
0
0
10
800
20
30
Time (in days)
40
0
50
0
Population growth at 21°C
700
Population size
KVS
500
1000
ARE
600
BLA
BLA
10
20
30
40
Time (in days)
50
60
Fig. 6 Population growth curves of the three population
at three different temperatures. There is a clear
difference in form of the curves between the three
temperatures: at 17°C the curves have a much steeper
incline than at the other temperatures.
KVS
500
400
300
200
100
0
0
10
20
30
40
Time (in days)
50
60
7000
140
Population growth of KVS
Population growth of KVS
6000
120
19
17
21
80
60
21
4000
3000
40
2000
20
1000
0
0
5
10
15
20
Time (in days)
10
19
5000
100
Population size
Population size
17
25
30
0
20
25
30
35
Time (in days)
40
45
50
120
7000
Population growth of ARE
19
21
17
5000
80
Population size
Population size
17
Population growth of ARE
6000
100
60
19
21
4000
3000
40
2000
20
1000
0
0
20
0
10
Time (in days)
20
30
30
50
6000
100
Population growth of BLA
17
19
Population growth of BLA
5000
21
Population size
80
Population size
40
Time (in days)
60
40
17
19
21
4000
3000
2000
20
1000
0
0
5
10
15
20
Time (in days)
25
30
0
20
25
30
35
40
Time (in days)
45
50
Fig. 7 Population growth of the three populations at the three different temperatures. At the left, the first thirty days, at the
right population growth projected further in time. Populations always perform best at 21°C at first but worst later on. Around
day 25-30 population growth at 21°C is taken over by population growth at 17°C. In the populations coming from higher
latitudes, this happens sooner than in the populations from the lowest latitudes.
Experiment 2
Population growth
Treatment alone (the time interval between the moment a female reaches adulthood and the
moment a male is put with her) appeared to have no significant effect on population size. In
interaction with time and in interaction with initial sex ratio however, treatment did significantly
influence population size (Table 2). The initial sex ratio (1male:1female, 1male:2females,
1male:3females) did have a significant effect, also in interaction with time.
When population size was analysed separately for every initial sex ratio, treatment alone never had a
significant influence (Table 3). Time alone had every time a significant influence and in interaction
with treatment it had a significant influence for initial sex ratios 1m:2f and 1m:3f.
11
Type III Tests of Fixed Effects
DFnum
DFden
4
60
2
60
1
1533
4
1533
8
60
2
1533
Factor
Treatment
Initial Sex Ratio
Time
Time*Treatment
Treatment*Initial Sex Ratio
Time*Initial Sex Ratio
F Value
1.99
15.89
1346.87
8.52
3.57
16.19
p value
0.1079
< 0.0001
< 0.0001
< 0.0001
0.0019
< 0.0001
Table 2 Degrees of freedom, F and p values for the factors included in the generalized linear mixed model used to
analyse population size
Type III Tests of Fixed Effects
DFnum
DFden
Initial Sex Ratio: 1 male : 1 female
4
20
1
427
4
427
Initial Sex Ratio: 1 male : 2 female
4
20
1
484
4
484
Initial Sex Ratio: 1 male : 3 female
4
20
1
614
4
614
Factor
Treatment
Time
Time*Treatment
Treatment
Time
Time*Treatment
Treatment
Time
Time*Treatment
F Value
p value
1.74
478.49
1.95
0.1807
< 0.0001
0.1019
1.17
400.12
5.04
0.3534
< 0.0001
0.0005
1.63
383.16
4.13
0.2046
< 0.0001
0.0026
Table 3 Degrees of freedom, F and p values for the factors in the generalized linear mixed model when population size
was analysed separately for every initial sex ratio.
8000
14000
Population growth
initial sex ratio 1m3f
12000
initial sex ratio 1m2f
6000
10000
Population size
Population size
7000
Population Growth
5000
4000
3000
2000
1000
8000
6000
4000
2000
0
0
T
20
D
80000
2dA
3dA
Population growth
70000
Population size
1dA
40
Time (in days)
initial sex ratio 1m1f
60000
50000
40000
30000
20000
10000
0
0
T
12
D
20
1dA
2dA
3dA
40
Time (in days)
0
T
0
D
1dA
2dA
20
3dA
40
Time (in days)
Fig. 8 Population size (total number of juvenile and adult
individuals) in function of time (days since founding
female(s) reached adulthood), for the five different
treatments and the three different initial sex ratios. 3dA
(male is put with female that is three days adult) performs
systematically better than average. 1dA (male is put with
female that is one day adult) performs systematically
worse than average.
Secondary Sex Ratio
Statistical analysis of the secondary sex ratio (number of adult males/total number of adults)
revealed that the initial sex ratio had no effect on the secondary sex ratio (Table 4). This variable was
thus excluded from any further analysis. Treatment, time and the interaction between those two
were all significant.
Factor
Treatment
Initial Sex Ratio
Time
Time*Treatment
Type III Tests of Fixed Effects
DFden
F Value
65
26.24
65
0.23
1071
358.12
1071
56.30
DFnum
4
2
1
4
p value
< 0.0001
0.7979
< 0.0001
< 0.0001
Table 4 Degrees of freedom, F and p values for the factors included in the generalized linear mixed model analyzing the
200
200
First generation: adults
Treatment: 3dA
150
100
50
50
0
0
200
10
15
Male
Female 20
25
5
200
First generation: adults
Treatment: 1dA
150
Treatment: 2dA
150
100
5
First generation: adults
10
100
50
50
0
20
Female
25
First generation: adults
Treatment: T
150
100
15
Male
0
5
200
10
15
20
Male
Female
25
Treatment: D
100
50
0
5
10
15
Male
20
10
Male
15
Female
20
25
Fig. 9 Number of adult individuals of the first
generation: males versus females. It is clear that
depending on when a female gets fertilized the
distribution of male and female offspring in time
differs. When a female gets fertilized three days after
she reaches adulthood, there is first a peak in male
offspring which is taken over by female offspring
after a few days. When the female is fertilized the
moment she reaches adulthood, the peak in male
and female offspring fall at the same time.
First generation: adults
150
5
25
Female
Secondary sex ratio.
When the numbers of males and females are plotted in time (Fig. 9), there’s a clear difference
between the treatments. In 3dA (female is three-days-old when the male is put with her) there is first
a peak of male individuals that is then taken over by a strong increase in females. In 2dA (female is
13
LSmeans of Secondary Sex Ratio
1
Secondary sex ratio (# males/# adults)
two-days-old when the male is put with her)
there is more overlap between the peak in
males and the peak in females. In the other
treatments, there’s complete overlap of the
peak in females and in males.
0.9
0.8
0.7
0.6
This can also be seen in the LSmeans of the
secondary sex ratio (number of adult
0.5
males/total number of adults) at three
0.4
moments in time (day 9-11, day 14-16 and day
0.3
19-21) (Fig. 10). 3dA has at moment one the
0.2
highest (most male-biased) sex ratio (0.939 ±
0.1
0.02109, significantly different from 1dA, T and
0
D (p<0.0001), not significantly different from
0
1
2
3
2dA (p=0.0955)), while at moment two and
moments in time
1dA 2dA 3dA D T
three its sex ratio does not significantly differ
Fig.
10
LSmeans
of
Secondary
Sex Ratio at three moments in
from the other treatments. At moment one,
time (moment 1: day 9-11, moment 2: day 14-16 and moment 3:
1dA has the lowest value (0.4657 ± 0.0745) but day 19-21). 3dA and 2dA are at moment 1 clearly more malebiased than the other treatments, while at moment two and
is only significantly different from 3dA
three there's no clear difference in secondary sex ratio between
(p<0.0001). 1dA, T and D all differ significantly
the five treatments.
from 3dA but not from each other. At moment
two and three none of the treatments significantly differs from each other.
Discussion
At first (in the first 30 days after founding the colony), there’s no indication of a population-level
effect of the shift in male development compared to female development: populations perform
better at higher temperatures. Temperature-effects on population growth overrule any possible
result of its uneven effect on female and male development. But after about one generation there is
a clear shift; populations reared at 17°C start to grow faster and overrule populations reared at
higher temperatures. This is possibly the result of a phenological mismatch. There is also some
indication of local adaptation; in populations coming from higher latitudes, the moment when
populations reared at 17°C catch up with populations reared at 21°C, happens sooner than in
populations coming from the lowest latitude. The population coming from the most southern
latitude always performs better, but the difference is smaller at lower temperatures.
At the individual level, when effects of the shift in development is separated from other effects of
temperature (in the second experiment), both population growth and sex ratio are affected. Most
striking is how the population growth in populations founded by a female fertilized a day too late is
much lower than in the populations founded by a female that was fertilized two or three days too
late or a female that was fertilized on time. Populations founded by a female fertilized two or three
days too late grow even faster than the control populations. This suggests some kind of
compensation mechanism that is only active when the timing of male development compared to
female development is really bad and not when it only deviates a bit from the normal situation.
The sex ratio in populations founded by females fertilized three days too late is strongly male-biased
at first but becomes soon female-biased, indicating a sudden increase in female offspring. Although
14
less distinct this pattern is also visible in populations founded by females that were fertilized two
days after reaching adulthood. This can also be seen in the absolute numbers of males and females;
first there is a clear peak in males (founding female is not fertilized yet and thus can only produce
males) followed by a strong increase in females, while numbers of males are in decline (founding
female is fertilized and will produce mostly females). In control populations the increase in males and
females happens almost at the same time, with males reaching adulthood only slightly before
females. This indicates that females that are fertilized two or three days after reaching adulthood will
adjust their primary sex ratio to compensate for the days they were unable to produce female
offspring. This is most probably the compensation mechanism causing the faster population growth
in populations founded by females fertilized two or three days after reaching adulthood.
Tetranychus urticae Koch is known to adjust its sex ratio in response to the environment (Young et al.
1986) or to its relatedness to other individuals in the population (Roeder et al. 1996). This is in
accordance with the sex allocation theory (West 2009), which states that mothers should change the
allocation of resources towards sons versus daughters as the fitness returns of producing sons versus
daughters changes. The sex-ratio adjustment is achieved through alteration of egg size (Macke et al.
2012): larger eggs have a higher chance of getting fertilized (Macke et al. 2011). Here we find an
adjusted sex ratio in response to delayed mating. Our findings are also in accordance with the sex
allocation theory. As founding females that are fertilized too late, have already produced some male
offspring by the time they get fertilized (and are able to determine the sex of their offspring), the
fitness returns of male offspring are then much lower than normal and the sex ratio of their offspring
will be more female-biased than normal. Note that the secondary sex ratio does not differ between
the treatments from about day fifteen. It is thus only the primary sex ratio (at the individual level)
that is adjusted and not the secondary sex ratio (at the population level). A female will thus allocate
her resources more towards female offspring until a normal, female-biased secondary sex ratio is
reached.
In some species the reproduction is negatively affected by delayed mating. This is especially wellstudied in crop-damaging Lepidoptera, which can be controlled by using sex-pheromones to interfere
with the timing of mating. Delayed mating causes in for example the autumn gum moth
(Mnesampela privata) a decreased likelihood of mating and a decreased likelihood that mating
results in fertile eggs (Walker & Allen 2011). In the haplodiploid, parasitoid wasp Diaeretiella rapae
McIntosh (Hymenoptera: Aphidiidae) delayed mating has an influence on the sex ratio of the
offspring; the percentage of females produced decreases with increasing mating delay. Like T.
urticae, most parasitoid wasp species typically have a female-biased sex ratio to minimize local mate
competition. Hence, if the sex ratio of the progeny is female-biased a mother increases the number
of mates for her sons and thus decreases the competition among her sons (Reece et al. 2004). But
unlike T. urticae these parasitoids are unable of adjusting the sex ratio of their offspring when
delayed mating decreases the percentage of female offspring. This adjustment of sex ratio to more
female-biased in reaction to delayed mating can also be found in another parasitic wasp species,
Aphelinus asychis Walker (Hymenoptera: Aphelinidae) (Fauvergue et al. 1998). Our findings show a
high plasticity of primary sex ratio in the spider mite; within one generation a highly male-biased sexratio can be converted to female-biased. This high plasticity also contributes to the high adaptation
potential of T. urticae.
15
The adjustment of sex ratio could also have an influence on dispersal and the founding of new
colonies. In T.urticae only adult, fertilized females will disperse. If more female offspring is produced
to compensate for the male offspring produced during the pre-mating period, also more dispersing
individuals are produced. Thus colonies, in which such compensation mechanism is active, will grow
faster and will sooner send out dispersing individuals, founding new colonies. Roy et al. (2003) found
a more female-biased sex ratio when temperatures were more extreme. One possible explanation
for this pattern is the higher dispersal capacity (which is advantageous in extreme, unreliable
circumstances) caused by this increase in females.
That females which are fertilized a day too late perform the worst indicates that disruption of
protandry can negatively affect individual fitness. This is probably why populations reared at 21°C
perform worse at the long term than population reared at 17°C. In the first generation, higher
temperature fastens development and thus population growth, but the disruption of protandry soon
slows down population growth at higher temperatures. Thus climate change can cause a
phenological mismatch by differentially influencing male and female development. In a highly
adaptive species like T.urticae this fitness effect is limited, but in other species this fitness effect
could have more far-reaching consequences. In Scaphoideus titanus (Hemiptera: Cicadellidae) for
example increasing temperatures during egg stage alter hatching patterns of females but not of
males (Chuche & Thiery 2012). As a result the degree of protandry decreased at higher temperatures.
Phenotypic plasticity has proven to be very important in adaptation to changing environments
(Hoffmann & Sgro 2011); it allows individuals to endure a certain change in the environment and
gives them time to adapt. These experiments show how a plastic response can easily undo the
negative fitness effects of increased temperature on a very short time-scale. As this plastic response
happens within a single individual and thus can easily be undone, we can expect this species not only
to be able to adapt to steadily increasing temperatures, but also to increasing variability in
temperature (which is also predicted in climate change models). The high adaptive potential of
Tetranychus urticae Koch make it unlikely that this species will suffer much under climate change.
Conclusion
It is clear that increasing temperature can differentially influence the sexes of a species and by doing
so can cause a phenological mismatch. In Tetranychus urticae Koch, the fitness effect is restricted;
only a small shift in male development compared to female development will result in a decreased
fitness (a slower population growth). When the shift in development delays mating by at least two
days, the female will compensate for the time she was only able to produce male offspring. As sex
allocation is highly plastic in this species, it is able to shift its sex ratio from highly male-biased to
female-biased very fast. This high plasticity in sex allocation contributes to the very high adaptive
potential of this species. Despite the possibility of climate change to have negative fitness effects on
this species, it is unlikely that its populations will decline under increasing temperatures.
16
Samenvatting
Het is algemeen bekend dat klimaatverandering de fitness van soorten kan beïnvloeden door
verschuivingen te veroorzaken in de levenscycli. Het timen van de levenscycli, ook wel de fenologie
genoemd, gebeurd op basis van bepaalde omgevingsfactoren zoals temperatuur, vochtigheid en
licht. Als klimaatverandering een effect heeft op één van deze factoren dan kan ook de fenologie van
soorten beïnvloed worden. Aangezien de fenologie niet alleen gestuurd wordt door de omgeving,
maar ook door de genetische achtergrond van een soort, reageren soorten vaak niet gelijk op een
bepaalde verandering in omgevingsfactoren. Wanneer interagerende soorten verschillend reageren
op omgevingsveranderingen kan dit de fitness van die soorten beïnvloeden. Zulke verschuivingen in
fenologie die een daling van de fitness veroorzaken, worden ook wel fenologische mismatches
genoemd. Ondertussen zijn al talloze voorbeelden van fenologische mismatches bekend; tussen
planten en hun bestuivers, tussen soorten van verschillende trofische niveaus en tussen andere
ecologische groepen. Maar ook binnen een soort is theoretisch gezien een mismatch mogelijk.
(Meta)populaties kunnen reproductief gescheiden worden als hun fenologie ongelijkmatig beïnvloed
wordt door een omgevingsfactor. Of voormalig geïsoleerde populaties kunnen opnieuw reproductief
verbonden worden en daardoor leiden onder outbreeding. Maar ook binnen eenzelfde populatie is
het mogelijk dat er een verschuiving van fenologiëen optreedt, bijvoorbeeld tussen de geslachten. In
veel soorten verschillen mannelijke en vrouwelijke individuen op vlak van bijvoorbeeld gedrag,
morfologie, ecologie of andere levensgeschiedeniskenmerken. Deze verschillen kunnen ervoor
zorgen dat de fenologie van mannetjes en vrouwtjes niet op dezelfde manier zal reageren op
bepaalde veranderingen in de omgeving. Als die ongelijke verandering in fenologie een effect heeft
op de fitness kunnen we spreken van een fenologische mismatch tussen de geslachten. Eén manier
waarop een fitness effect zou kunnen veroorzaakt worden is door aantasting van protandry.
Protandry is het eerder verschijnen of aankomen van mannetjes op de plaats van reproductie dan
vrouwtjes, iets wat veel voorkomt binnen de arthropoden. Verschillende verklaringen worden
gegeven voor dit fenomeen; mannetjes zouden zo hun paringskansen vergroten en vrouwtjes zouden
zo de kans om te sterven voor reproductie verkleinen. Het succes van een mannetje hangt dan niet
alleen af van hoe snel hij is ten opzicht van vrouwtjes maar ook hoe snel hij is ten opzichte van
andere mannetjes. Een korte ontwikkelingstijd is dus voordelig bij mannetjes. Bij vrouwtjes is dit niet
het geval aangezien er een trade-off bestaat tussen lichaamsgrootte en ontwikkelingstijd. We kunnen
dus verwachten dat een mannetje beperkter is in het aanpassen van zijn ontwikkelingstijd dan
vrouwtjes en dat omgeving dus een groter effect kan hebben bij vrouwtjes. Nu is het niet
noodzakelijk zo dat een fitness effect op individueel niveau ook betekent dat de populatie op zijn
geheel achteruit zal gaan. Een daling in reproductie bijvoorbeeld kan gecompenseerd worden door
een hogere overlevingskans als gevolg van verlaagde competitiedruk. In mijn thesis onderzoek ik of
een toename in temperatuur een fenologische mismatch tussen de geslachten van de
Bonenspintmijt (Tetranychus urticae Koch, Acari: Tetranychidae) kan veroorzaken. Deze soort is een
herbivore mijt die over de hele wereld voorkomt en bekend staat als een pestsoort voor land- en
tuinbouw. De ontwikkeling bestaat uit vijf stadia en is vrij kort. Mannetjes ontwikkelen iets sneller
dan vrouwtjes en zullen van zodra ze volwassen zijn op zoek gaan naar vrouwtjes die in hun laatste
ruststadium (dit is de laatste vervelling vooraleer ze volwassen zijn) zijn. Daar houden ze de wacht
om het vrouwtje direct te kunnen bevruchten wanneer ze te voorschijn komt uit haar vervelling. De
Bonenspintmijt heeft een arrhenotoke, haplodiploïde genetische structuur. Dit wil zeggen dat
onbevruchte eitjes ontwikkelen tot mannetjes en bevruchte eitjes tot vrouwtjes. Dit zorgt ervoor dat
vrouwtjes het geslacht van hun nakomelingen zelf kunnen bepalen.
17
In voorgaande experimenten onderzochten we de invloed van temperatuur op ontwikkelingstijd en
fecunditeit in populaties afkomstig van verschillende breedtegraden. We vonden dat temperatuur
een ongelijk effect had op de ontwikkeling van mannetjes en vrouwtjes en dat het verschil in
ontwikkelingstijd afnam met toenemende breedtegraad. Aangezien mannetjes afhankelijk zijn van
dat verschil in ontwikkelingstijd om vrouwtjes op tijd te kunnen bevruchten, onderzoek ik in deze
thesis of het te laat bevruchten van vrouwtjes een invloed heeft op de individuele fitness en op de
populatiegroei en secundaire sex ratio. Dit gebeurde in twee experimenten. In een eerste werden
volwassen, bevruchte vrouwtjes afkomstig van drie verschillende breedtegraden opgekweekt bij drie
verschillende temperaturen (17°C, 19°C en 21°C). In een tweede experiment werden mannetjes bij
onbevruchte vrouwtjes van vijf verschillende leeftijden gezet (laatste juveniel stadium (D), laatste
vervelling (T), één dag oud (1dA), twee dagen oud (2dA) en drie dagen oud (3dA). Dit gebeurde bij
drie verschillende sex ratio’s (1 mannetje:3 vrouwtjes, 1 mannetje: 2 vrouwtjes, 1 mannetje: 1
vrouwtje), aangezien we ook verwachtten dat de sex ratio van de nakomelingen beïnvloed zou
worden. Van zodra een vrouwtje volwassen wordt, begint ze eitjes te leggen, als ze op dat moment
nog niet bevrucht is, ontwikkelen die eitjes allemaal tot mannetjes. De nakomelingen werden om de
dag geteld (per stadium) voor twee generaties. Uit het eerste experiment bleek dat de rechtstreekse
invloed van temperatuur op populatiegroei (door het verkorten van de ontwikkelingstijd) op korte
termijn (eerste generatie) een groter effect had dan de onrechtstreekse invloed via de mogelijke
fenologische mismatch. Maar vanaf ongeveer dag 25-30 oversteeg de populatiegrootte bij 17°C die
bij 21°C. Dus hogere temperatuur bleek nadelig te zijn op langere termijn. Dit was het geval bij alle
populaties. Ook bleek de meest zuidelijke populatie bij alle temperaturen het snelst te groeien. Maar
het verschil tussen de drie populaties nam af met dalende temperatuur. Vermoedelijk zijn de
populaties aangepast aan lokale temperaturen, waardoor de populatiegroei van noordelijke
populaties sterker afneemt met toenemende temperatuur. Uit het tweede experiment bleek het
fitness effect af te hangen van het tijdsinterval tussen het volwassen worden van het vrouwtje en het
aankomen van het mannetje. Wanneer dit tijdsinterval vrij groot was (twee of drie dagen) bleken
vrouwtjes hun primaire sex ratio zodanig aan te passen dat ze vanaf het moment van bevruchting
bijna uitsluitend vrouwtjes produceerden. Op die manier werd een hoge sex ratio (groot aandeel
mannetjes) op korte tijd omgezet naar een vrij lage sex ratio (meer vrouwtjes dan mannetjes), die
normaal is bij T.urticae. Dit compenseerde zodanig dat de populatiegroei bij die behandelingen de
populatiegroei bij alle andere behandelingen oversteeg. Dit compensatiegedrag past binnen de sex
allocatie theorie, die voorspelt dat vrouwtjes hun energie zo zullen verdelen over hun nakomelingen
dat het geslacht dat de grootste opbrengst in fitness oplevert, bevoordeeld zal worden. Wanneer het
tijdsinterval echter minder groot was (één dag) bleek de populatiegroei het laagst van al. Dit is
waarschijnlijk het gevolg van een verstoorde protandry; mannetjes komen net iets te laat bij
vrouwtjes, maar niet zodanig veel te laat dat vrouwtjes gaan compenseren. Daaruit kunnen we dus
besluiten dat temperatuur een fenologische mismatch tussen de geslachten van T. urticae kan
veroorzaken en dat deze zelfs op populatieniveau van belang kan zijn. Maar de hoge mate van
plasticiteit in de primaire sex ratio zorgt ervoor dat bij een vrij groot tijdsinterval tussen het
volwassen worden en de bevruchting, er compensatie optreedt voor de periode waarin uitsluitend
mannetjes konden worden geproduceerd. Die plasticiteit is één van de kenmerken die bijdraagt tot
het grote aanpassingsvermogen van de Bonenspintmijt. Maar er zijn nog soorten waarbij
temperatuur een ongelijk effect heeft op de geslachten, bijvoorbeeld Scaphoideus titanus
(Hemiptera: Cicadellidae). Bij deze cicade zorgt een normale, lage temperatuur tijdens het ei-stadium
ervoor dat vrouwtjes gemiddeld later ontluiken dan mannetjes, terwijl bij een hogere temperatuur
18
vrouwtjes over een langere periode zullen ontluiken, die meer samenvalt met het ontluiken van de
mannetjes. Mannetjes vertonen hier geen verschillende reactie op temperatuur. Algemeen kan
besloten worden dat fenologische mismatches tussen geslachten mogelijk zijn en dat fenotypische
plasticiteit belangrijk kan zijn in een veranderende omgeving.
Acknowledgements
First of all, I want to thank my promotor Prof. Dr. Dries Bonte and my tutor Drs. Katrien Van
Petegem. I also want to thank my fellow thesis students at the Terec Emily Veltjen, Charlotte
Vanmoorleghem, Katrien De Wolf, Rieneke Vanhulle, Hannah Volckaert, Harti Ningsih, Jelle Van den
Bergh, Karen Bisschop and Willem Proesmans for the company and the nice working environment.
Also my parents, Mieke Harinck and Luc Boeraeve and my friends Marilyn De Graeve, Daan
Dekeukeleire, Dieter Slos, Els Timmerman, Anya Vanraemdonck and Hanne Hendrickx have been very
supportive. And last but not least I want to thank Ward Tamsyn for being there during hard times and
long days in the lab.
References













19
Chuche J., Thiéry D. (2012) Egg incubation temperature differently affects female and male
hatching dynamics and larval fitness in a leafhopper. Ecology and Evolution 2: 732 – 739.
Clausen K.K., Clausen C. (2013) Earlier Arctic springs cause phenological mismatch in longdistance migrants. Oecologia 173: 1101 – 1112.
Durant J.M., Hjermann D.Ø., Ottersen G., Stenseth N.C. (2007) Climate and the match or
mismatch between predator requirements and resource availability. Climate Research 33:
271-283.
Edwards M., Richardson A.J. (2004) Impact of climate change on marine pelagic phenology
and trophic mismatch. Nature 430: 881 – 884.
Fauvergue X., Hopper K.R., Antolin M.F., Kazmer D.J. (1998) Does time until mating affect
progeny sex ratio? A manipulative experiment with the parasitoid wasp Aphelinus asychis.
Journal of Evolutionary Biology 11: 611-622.
Halzapfel C.M., Bradshaw W.E. (2002) Protandry: the relationship between Emergence time
and Male Fitness in the Pitcher-Plant Mosquito. Ecology 83: 607 – 611.
Heard M.J., Riskin S.H., Flight P.A. (2012) Identifying potential evolutionary consequences of
climate-driven phenological shifts. Evolutionary Evology 26: 465 – 473.
Henter H.J. (2003) Inbreeding depression and haplodiploidy: experimental measures in a
parasitoid and comparisons across diploid and haplodiploid insect taxa. Evolution 57: 1793 –
1803.
Hoffmann A.A., Sgro C.M. (2011) Climate change and evolutionary adaptation. Nature 470:
479-485.
Houston D., Shine R. (1993) Sexual Dimorphism and Niche Divergence: Feeding Habits of the
Arafura Filesnake. Journal of Animal Ecology 62: 737 – 748.
Kelly D., Turnbull M.H., Pharis R.P., Sarfati M.S. (2008) Mast seeding, predator satiation, and
temperature cues in Chionochloa (Poaceae). Population Ecology 50: 343 – 355.
Kimball S., Angert A.L., Huxman T.E., Venable D.L. (2010) Contemporary Climate change in
the Sonoran Desert favors cold-adapted species. Global Change Biology 16: 1555-1565.
Kudo G., Ida T. Y. (2013) Early onset of spring increases the phenological mismatch between
plants and pollinators. Ecology 94: 2311 – 2320.


















20
Macke E., Magelhães S., Bach F., Olivieri I. (2012) Sex-ratio adjustment in response to local
mate competition is achieved throughan alteration of egg size in a haplodiploid spider mite.
Proceedings of the Royal Society B 279: 4634-4642.
Macke E., Magelhães S., Khan H. D., Luciano A., Frantz A., Facon B., Olivieri I. (2011) Sex
allocation is mediated by egg size: evidence in the spider mite Tetranychus urticae Koch.
Proceedings of the Royal Society B 278: 1054-1063.
Menzel, A., Estrella N., Heitland W., Susnik A., Schleip C., Dose V. (2008) Bayesian analysis of
the species-specific lengthening of the growing season in two European countries and the
influence of an insect pest. International Journal of Biometeorology 52: 209 – 218.
Migeon A., Dorkeld F. (2006-2013) Spider Mites Web: a comprehensive database for the
Tetranychidae. http://www.montpellier.inra.fr/CBGP/spmweb (consulted on 30/11/2013).
Morbey Y.E. (2013) Protandry, sexual size dimorphism and adaptive growth. Journal of
Theoretical Biology 339: 93 – 99.
Petrova I.V., Sannikov S.N., Cherepanova O.E., Sannikova N.S. (2013) Reproductive isolation
and disruptive selection as factors of genetic divergence between Pinus sylvestris L.
populations. Russian Journal of Ecology 44: 296 – 302.
Reece S.E., Shuker D.M., Pen I., Duncan A.B., Choudhary A., Batchelor C.M. (2004) Kin
discrimination and sex ratios in a parasitoid wasp. Journal of Evolutionary Biology 17: 208216.
Roeder C., Harmsen R., Mouldey S. (1996) The effects of relatedness on progeny sex ratio in
spider mites. Journal of Evolutionary Biology 9: 143-151.
Roy M., Brodeur J., Cloutier C. (2003) Temperature and sex allocation in a spider mite.
Oecologia 135: 322 – 326.
Sato Y., Sabelis M.W., Egas M., Faraji F. (2013) Alternative phenotypes of male mating
behaviour in the two-spotted spider mite. Experimental Applied Acarology 61: 31-41.
Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller
(2007) Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change. Cambridge University Press. 996 p.
Stillwell R.C., Davidowitz G. (2010) Sex differences in phenotypic plasticity of a mechanism
that controls body size: implications for sexual size dimorphism. Proceedings of the Royal
Society B 277: 3819 – 3826.
Van Leeuwen T., Vontas J., Tsagkarakou A., Dermauw W., Tirry L. (2010) Acaricide resistance
mechanisms in the two-spotted spider mite Tetranychus urticae and other important Acari: A
review. Insect Biochemistry and Molecular Biology 40: 563 – 572.
Visser M.E., Holleman L.J.M., Gienapp P. (2006) Shifts in caterpillar biomass phenology due to
climate change and its impact on the breeding biology of an insectivorous bird. Oecologia
147: 164 – 172.
Vitasse Y., Basler D. (2013) What role for photoperiod in the bud burst phenology of
European beech. European journal of Forest Research 132: 1-8.
Volckaert H. Klimaatverandering en locale adaptatie in een herbivoor.2012
Walker P.W., Allen G.R. (2011) Delayed mating and reproduction in the autumn gum moth
Mnesampela privata. Agricultural and Forest Entomology 13: 341-347.
West S.A. (2009) Sex Allocation. Princeton University Press.



21
Wiklund C., Gotthard K., Nylin S. (2003) Mating system and the evolution of sex-specific
mortality rates in two nymphalid butterflies. Proceedings of the Royal Society B 270: 1823 –
1828.
Young S.S.Y., Wrensch D.L., Kongchuensin M. (1986) Control of Sex Ratio By Female Spider
Mites. Entomologia Experimentalis et Applicata 40: 53-60.
Zhang Z. (2003) Mites of Greenhouses. Identification, Biology and Control. CABI Publishing.
256p.