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Ecology Evolutionary Centre Uppsala University

The of in life history traits

Josefine Stångberg

Introductory Research Essay No. 108 ISSN 1404 – 4919 Uppsala 2017

Introductory Research Essay No. 108 Postgraduate studies in Biology with specialization in Animal Ecology

The evolution of sexual dimorphism in life history traits

Josefine Stångberg Department of Ecology and Genetics / Animal Ecology Evolutionary Biology Centre Uppsala University Norbyvägen 18D SE-752 36 Uppsala Sweden

1 ISSN 1404-4919

1. Abstract ...... 3

2. Introduction to and sexual dimorphism ...... 4 2.1. Intra- and interlocus sexual conflict ...... 5 2.2. -specific expression ...... 8

3. Sexual conflict and rapid evolution ...... 10

4. Life History Theory framework ...... 11 4.1. Quantitative genetics ...... 11 4.2. G and B matrices...... 14

5. A model system for the study of sexual dimorphism in life history syndromes: C. remanei ...... 17 5.1. Experimental approach ...... 19 5.2. Acknowledgement ...... 20

References ...... 20

2 1. Abstract

Many dioecious organisms exhibit some level of sexual dimorphism; the can differ in , and can have different optima for certain traits and have different reproductive strategies. Sex-specific selection, thus, can be highly diverging in both magnitude and direction. When selection for a trait differs in direction we have antagonistic selection; often leads to sexual conflicts since the two sexes share most of their genetic architecture. Sexual dimorphism is often seen as a resolution to sexual conflict, a way to decouple the genetic basis of traits under conflict and allow sex-specific expression. One way to better understand the evolution of sexual dimorphism is using a life history theory framework; where traits linked to growth, reproduction and survival are studied and quantified. These quantitative traits, their genetic architecture and how they covary within and between the two sexes, can be further studied using a quantitative genetics approach – G and B matrices. These are essentially genetic variance-covariance matrices of all traits measured, pairwise comparisons that give a picture of how these traits coevolve within an individual (G), but also how different traits covary between the sexes (B). These tools allow us to understand the underlying genetic architecture of life history traits, and also how these traits change under different and sex-specific selection pressures. This, in turn, will aid our understanding of how sexual dimorphism evolves. I end this review by focusing on a particular model for studying these questions; the nematode

Caenorhabditis remanei.

3 2. Introduction to sexual conflict and sexual dimorphism

Difference between the sexes has been an area of interest for a long time and Darwin presumably mentioned it first in relation to in his unpublished work from 1858 where he discusses the idea that can work by the “struggles of males and ”(Darwin & Wallace, 1858). In his famous publication, The Descent of , and Selection in Relation to Sex

(Darwin, 1871), he discusses sexual selection in great length, although mostly in relation to evolution. He uses the following definition of sexual selection:

“[…] that kind of selection, which I have called sexual selection.

This depends on the advantage which certain individuals have over

other individuals of the same sex and species, in exclusive relation to

reproduction.”

Most early studies, including Darwin’s observations, aimed at understanding and explaining sexual ornaments, such as a peacock’s . These large extraordinary characters seemed maladaptive, going “against” natural selection, since often they make the individual more conspicuous and less able to escape predators. Darwin also asked himself why males often are the more “elaborate” sex (Darwin, 1871). Another long-standing question is the presence of sexual dimorphism itself. How come two individuals of the same species, sharing most of their genetic architecture, can exhibit such large phenotypic differences? In order to approach this question, we have to understand the underlying cause of

4 sexual dimorphism, that is sexual conflict. The field of sexual conflict was shaped by two landmark publications; first Trivers, in 1972, identified the connection between , adult and sexual selection (Trivers, 1972), second Parker, in 1979, coined the theory of sexually antagonistic coevolution

(Parker, 1979). Since these two publications new insights have, however, been achieved and sexual conflict took a place in the mainstream research world in the

1990s (Lande, 1980; Arnqvist & Rowe, 2005; Bonduriansky & Chenoweth,

2009).

2.1. Intra- and interlocus sexual conflict Genomes contain an enormous number of loci, many with several .

Even closely related individuals have different alleles at many of these loci, which is to say that all (non-clonal) individuals are unique in this aspect. With different alleles comes competition between them, and potentially also different evolutionary interests, which can result in a conflict. Intuitively, this conflict will be stronger between less related individuals as they will be more dissimilar

(Hamilton, 1964). This is usually the situation for two individuals with each other, they are not only outbreeding but also belong to different sexes that often possess different mating strategies, increasing the potential for conflict, in this case often referred to as sexual conflict (Arnqvist & Rowe, 2005). To optimise fitness of traits important for such segregated reproductive strategies, the sexes experience different selective pressures often differing both in magnitude and direction. Selection favouring sex-specific optima is called sexually antagonistic

5 selection (Parker, 1979; Rice, 1984; Clutton-Brock, 1991). Sexually antagonistic selection will be more or less present in all sexually reproducing taxa (Trivers,

1972; Parker, 1979).

There are two main types of sexual conflict characterised by the genetic basis of the conflict; either a trait with a common genetic basis in the two sexes have sex-specific optima, or two sex-specific traits with different genetic basis are a source of sexual conflict (Rice, 1984; Gibson et al., 2002; Arnqvist & Rowe,

2005; Bonduriansky et al., 2005). A trait that has sex-specific fitness optima, but an underlying genetic correlation between the sexes due to a shared genetic basis, which prevents them from reaching their optima independently is said to be under intralocus sexual conflict, described in figure 1 (Lynch & Walsh, 1998; Rice &

Chippindale, 2001; Arnqvist & Rowe, 2005). This can result in three situations; i) an unresolved conflict, the mean trait value being somewhere intermediate of the two optima (B), ii) a partially resolved conflict where the sexes have diverged but not fully reached their individual optima or mean trait values that are skewed towards one sex-specific optima with the other sex suffering fitness costs (C), or iii) a sexual dimorphism where the genetic basis of the trait has been decoupled allowing for sex-specific expression (D). Intralocus sexual conflict is present in all those cases where the direction of selection on a given depends on which sex it exists in, i.e., whenever there is a sex * genotype interaction.

6

Figure 1. Intralocus sexual conflict. Grey area symbolises the trait distribution of a population, and the dotted line represents the trait optimal value (or fitness surface) Cox & Calsbeek 2008. Interlocus sexual conflict happens via the interaction between two traits of different genetic basis, that exist in either a male or a . In these cases, a trait often increases fitness for one sex, but results in lower fitness in the other sex. In these cases, it is common for the other sex to evolve a “counter adaptation”, and this leads to an evolutionary arms race or coevolution with a of counter- adaptations (Rice & Holland, 1997). One example of this is genital morphology, where one sex (1) evolves a genital trait to manipulate the investment of the other sex (2) into the offspring from their mating, increasing the of (1). This trait can reduce the fitness of (2) and/or make it less able to invest in subsequent reproductive events. This will result in strong selection in favour of any occurring in (2) that contribute to a counter adaptation that limit the effects of the manipulations from (1). This, in turn, will increase the selective

7 pressure on (1) to further evolve this genital trait to better manipulate (2) and overcome its evolved counter adaptation, and so on. There is often no clear resolution to these kinds of conflicts (Parker, 1979). However, they can contribute to rapid evolution such as divergence between lineages and (section 3).

2.2. Sex-specific expression In general, the sexes share a large majority of their genomes, and in organisms with chromosomal sex determination there are a small number of genes, on parts of the sex , that are not shared between the sexes.

Their traits are, thus, usually strongly genetically correlated. Moreover, many cases of sexual dimorphism are the results of changes in genes on the , and since these genes occur in both sexes this can cause a constraint for sexual dimorphism to evolve (Lande, 1980; Lande & Arnold, 1983).

In theory, if the genetic correlation between the sexes equals 1 (i.e. no independent genetic variance for the trait in either of the sexes), the presence of sexually antagonistic selection will result in an intermediate mean trait value (Figure 1.

B)(Lande, 1980, 1987; Reeve & Fairbairn, 2001). It is, however, believed that the majority of shared traits harbour at least some sexually independent genetic variation.

One obvious solution to intralocus sexual conflict is the decoupling of the genetic basis, resulting in the sexes expressing the trait independently – sex- specific expression. Additionally, a change in gene function is much rarer than a

8 change in gene expression in these cases, this is likely due to the additional steps involved in changing gene function; gene expression can in theory be altered with a single mutation in the DNA coding for one regulatory element, while change in gene function often take several following each other in a specific order. Moreover, theory predicts that sex-specific selection can favour the invasion of antagonistic mutations, but only when its benefits in one sex outweighs the cost to the other sex (Rice, 1984).

Reaching sex-specific gene expression is not easy or fast. First, a novel mutation has to appear. This type of trait, a quantitative trait, often involve a large number of loci and the appearance of this trait can be a long-term process, unless a mutation appears in a regulatory element which, as mentioned above, may cause larger scale changes in gene expression. The resulting trait will have to have sex- specific effects such as one sex experiencing higher fitness, but the other sex may suffer a fitness cost. If this mutation is going to spread in the population, however, it needs to avoid the negative effects of being expressed in sex where it causes a fitness cost, and this can only happen by a new mutation occurring that affects gene regulation in such a way that the gene is silenced in that sex. This kind of mutation would be hugely beneficial but may take time to occur by chance (Rhen,

2000).

9 3. Sexual conflict and rapid evolution

Another interesting aspect of on-going intralocus sexual conflict is what happens before a sex-specific expression is reached, when a trait has sex-specific fitness effects but is still expressed in both females and males. Such sexually antagonistic genes are thought to be an important source of genetic variation for a population (Foerster et al., 2007). Such traits are not removed by natural selection as fast as a trait that has negative effects in both sexes, because on average effect of the trait’s expression on the population will be neutral. Many traits that are being studied are in this stage of conflict, and it is these traits that can actually tell us something about the evolution of sexual dimorphism (Hesketh et al., 2013). It has been found that the resolution of intralocus sexual conflict by sex-specific expression may be constrained by the pleiotropic (multiple effects from a single gene) of many loci. In fact, one study found that loci exhibiting sex-biased expression are less pleiotropic than genes that are not under sex-specific expression (Mank et al., 2008), which suggests that there are evolutionary constraints acting on these antagonistic loci, potentially impacting the determination of the resolution of the intralocus sexual conflict.

In the case of an interlocus sexual conflict, as mentioned previously, the antagonistic selection can lead to a co-evolutionary arms race between males and females, and there is no obvious solution. The selection pressure to evolve a

“counter adaptation” against a progressively harmful adaptation in the other sex

10 is very strong, which may lead to fast changes on an evolutionary timescale. This is one kind of process by which of the same species can come to diverge and form new species, perhaps even when existing in the same environment, due to differences between populations becoming reproductive barriers (Parker & Partridge, 1998).

4. Life History Theory framework

Life history traits are phenotypic traits that are directly linked to growth, reproduction and survival. These traits are often strongly linked to each other and selection on one trait is often seen as a response in other traits, resulting in a life history syndrome of functionally integrated traits (Promislow & Harvey, 1990).

Trade-offs between the traits are common, this is when a beneficial change (with regard to fitness) in one trait leads to a detrimental change in another trait (Gadgil

& Bossert, 1970). The aim of life history theory is to understand variation in life history strategies, the relative investment into each life history trait and potential trade-offs (Stearns, 1989). This framework can also help us to answer questions about the evolution of sexual dimorphism; what do the sex-specific life history syndromes look like, how do they interact with each other, and what happens under ongoing sexual conflict?

4.1. Quantitative genetics In order to study the patterns of life history evolution, and to understand genetic variation, mathematical analysis is essential (Cole, 1954; Provine, 1971;

11 Roff, 2001) and has been an integrated part of life history theory since the late

1950s. Applied life history studies are, thus, often accompanied by the use of the quantitative genetics theory framework; this is the theory of inheritance of quantitative (or continuous) traits (Stearns, 1989). This theory uses a toolkit which is derived from the univariate Breeder’s equation;

R=h2S.

Where R is response to selection, h2 is heritability and S is the selection differential. Heritability is the proportion of the phenotypic variance in a population that is due to variance in additive genetic factors, essentially, it is the quantitative genetic parameter that tells us to which degree selection can produce a response in the next generation. The selection differential is the difference in mean between the selected and unselected individuals. By conducting certain so called breeding designs in an experiment, the genetic component can be estimated and correlated for multiple traits, giving an idea of how traits will respond to given selection pressures and in relation to each other (Falconer & Mackay, 1996). We can estimate the genetic component by looking at Parent-Offspring regression

(Figure 2.), where the offspring value is plotted against mid-parent value and the slope is the broad sense heritability (h2). The parent-offspring regression will, however, give a simplified view of the genetic variance, because in addition to the additive genetic variance it will also include other sources of genetic variance, such as dominance, epistasis and linkage (hence the term broad sense heritability,

12 as compared to the narrow sense heritability, which refers to the ratio between the additive genetic variance and the phenotypic variance). This adds to the complexity to the study of evolutionary response to selection. By looking at specific sets of relatives that share different types of genetic variance (in various so called breeding designs), it is possible to achieve estimates that come closer to capturing only the additive genetic variance component.

Figure 2. An example of a parent-offspring regression. The slope represents h2 (heritability) of the trait measured. Figure from (Brommer et al., 2005).

In order to get a realistic estimate of how life history traits interact, and get a better indication of the true life history syndromes, we would have to look at a suite of traits with a multivariate approach. For this, the multivariate Breeder’s equation is used;

R=Gβ

Here, G is the genetic variance-covariance matrix and β is the vector of directional selection gradients (Lande & Arnold, 1983).

13 4.2. G and B matrices G matrices are often used to investigate life history syndromes; they summarize the inheritance and genetic covariance of multiple life history traits

(Lande, 1979). Life history traits may also have sex-specific optima, and as a result life history syndromes can differ between the sexes. When investigating sex-specific life history syndromes it can be helpful to think of the sexes as separate populations and estimate a separate G matrix for each sex (GF and GM), which allows us to also compare traits between the sexes using the between-sex between-trait matrix (B).

Figure 3. A simple G matrix of two traits (1 & 2).

Figure 3 shows a simple additive genetic variance-covariance (G) matrix of

2 2 two traits; σ 11 is the additive genetic variance of trait 1 within the population, σ 22

2 is the variance of trait 2 within the population, and σ 12 is the covariance between the two traits within the population.

14

Figure 4. Multivariate matrix, where Gm is the full male G matrix, Gf is the full female G matrix, and B is the covariance of the traits between males and females.

In Figure 4, instead of two traits, we compare one trait in both sexes

(here treated as two populations); Gm is the variance of the traits in males, Gf is the variance of the traits in females, and B is the covariance matrix of the traits in males and females with its transpose BT. This is analogous to the G matrix, but extends it by looking at between-trait, between-sex covariances, treating the two sexes as two populations (Lande, 1980).

Figure 5. Examples of covariance plots for traits. A circular shape indicates no covariance between the traits, whereas an elongated shape shows a covariance. Figure from Arnold et al. 2008.

When measuring covariance, we can use standardised phenotypic values to estimate covariances on the phenotypic level, or genetic values to estimate genetic

15 covariances (see section 4.1.). The relationship between the values tells us something about how they interact; in Figure 5, we see a simplified example of two cases, the first case shows no covariance between the traits, while the second case shows a strong positive covariance. Covariance can be of different strengths and directions, which is of great importance when attempting to understand the interaction between traits and, thus, how they behave in the adaptive landscape

(Lande, 1979; Arnold et al., 2001). The adaptive landscape is simply a visualisation of the relationship between one or more genotypes and reproductive fitness. If a trait has a negative covariance between the sexes, this means that there is antagonistic selection for that trait; an on-going intralocus sexual conflict.

As mentioned above, a response to selection depends on the underlying genetics of the trait involved. Traits can constrain or facilitate each other’s response to selection via genetic covariances between them, and this is captured by the G matrix. In addition, different traits in the two sexes can similarly constrain or facilitate each other’s responses via the B matrix. One way to investigate the potential for sexual dimorphism to evolve, is to compare the relative stability of the B to the G matrix. Theory predicts that the G matrix is more stable than the B matrix, since B is less subject to multivariate stabilising selection within an individual and is mostly a subject to indirect selection because it is not expressed within, but rather between, individuals (Barker et al., 2010).

Additionally, a population with existing sexual dimorphism is assumed to already

16 have an asymmetric B matrix, since some traits have evolved sex-specific expression. This could mean that an already asymmetric matrix would be easier to shift even further with increased directional selection on one sex, but could also help stabilise it under some circumstances (Lande, 1980).

Investigating several key life history traits and creating their underlying G and B matrices allows us to understand what might happen to the shared genetic architecture in a population in response to sex-specific selection, and under on-going sexual conflict. It will also give us a better understanding for how, and how rapidly, genetic decoupling of a trait between the sexes could take place when the trait is under strong sex-specific selection. These are two interesting processes underlying the evolution of sexual dimorphism.

5. A model system for the study of sexual dimorphism in life

history syndromes: C. remanei

The nematode Caenorhabditis remanei (Figure 6) is a close relative of the commonly used model species C. elegans. However, C. remanei has two separate sexes – males and females, whereas C. elegans are and males, as is the case for C. elegans. In nature, C. remanei can be found in compost, decomposing vegetation and soil where they live of bacteria (Sudhaus, 1974). C. remanei have a short generation time, approximately 3-4 days, with individuals reaching after 48hr, and a lifespan of 10-16 days. They are easy to keep and cultivate in the laboratory, and like many other nematodes, they can

17 be stored long-term in -80°C freezers (Sulston & Hodgkin, 1988). They naturally occur at large population sizes, and show large amount of genetic diversity (Cutter et al., 2006), which is beneficial for keeping genetically healthy populations in the lab, and the genetic diversity is crucial for selection experiments. The natural sex ratio for this species is 50:50 and both sexes mate with multiple partners throughout their lifetime.

C. remanei exhibits sexual dimorphism in important life history traits, such as timing of reproduction and body size. Hence, there is some level of sex- specific selection in this species that has resulted in sex-specific expression.

There is strong inter- and intralocus sexual conflict in C. remanei (Palopoli et al.,

2015), which is to be expected since the two sexes have different reproductive strategies, and theory predicts that the majority of the sexual conflicts are on- going rather than resolved (Rice, 1984).

Figure 6. C. remanei male on the left, female on the right. (Picture by Kristin Sikkink)

18 5.1. Experimental approach In order to investigate how life history traits differ between the sexes of a species, and how these differences have evolved, one can empirically investigate how the underlying genetic architecture of important life history traits are affected by on-going sexual conflict. This will help us better understand the processes taking place during evolution of sexual dimorphism.

In an attempt to do this, I am using an experimental evolution approach with artificial manipulation of the sex ratio so that it is strongly biased, which should increase the opportunity for sexual conflict. This is done for both sexes to create two treatments; male- (10:1) and female-biased (1:10). Populations will be allowed to reproduce under these conditions for 30 generations, and populations are also cryopreserved (frozen) worms from 15, 20 and 30 generations. I expect that selecting more strongly on one sex will cause the other sex to initially be

“dragged” towards the life history trait optima of the other sex. Over time, however, strong sex-specific selection should break down the genetic covariances between traits and allow for sex-specific expression, and sexual dimorphism, to evolve.

Using a quantitative genetic breeding design, I can quantify the changes in phenotype occurring due to the experimental evolution, and use the fact that relatives share parts of their genomes to estimate quantitative genetics parameters of the traits. I will assay the worms from the breeding designs to estimate the

19 genetic variances and covariances both within and between the sexes (Gf, Gm, B,

BT, see Figure 4.); a midparent-midoffspring regression for G, mother-daughter and father-son regression for Gf and Gm, and mother-son and father-daughter regressions for B. From this data, I can construct full G and B matrices. Thus, this experimental evolution, and the subsequent quantitative genetics approach, will allow me to study how the B matrix acts as a constraint for sex-specific expression, both in the short- and long term.

I aim to utilise the promise of experimental evolution and the tools of the

G and B-matrices to in detail further our understanding of the evolution of sexual dimorphisms and sex-specific expression in any trait, and life history traits in particular.

5.2. Acknowledgement

I would like to thank my supervisor Elisabeth Bolund, and Ingrid Ahnesjö for helpful feedback and suggestions. I also want to thank the nematode lab

(Martin Lind and Alexei Maklakov groups) for useful discussions.

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23 ESSAYS IN THE SERIES ISSN 1404-4919

1. Reproductive patterns in marine on shallow bottoms. - Anne-Marie Edlund. 1979 2. Production in estuaries and saltmarshes. - Staffan Thorman. 1979 3. The evolution of life history traits. - Anders Berglund. 1979 4. in marine littoral communities. - Carin Magnhagen. 1979 5. Insular biogeographic theory, developments in the past decade. - Stefan Ås. 1979 6. Theories and tests of optimal diets. - Juan Moreno. 1979 7. Ecological characters in insular communities. - Mats Malmquist. 1980 8. / relationships: a synopsis. - Ola Jennersten. 1980 9. Sexual size dimorphism in of prey. - Per Widén. 1980 10. The evolution of avian mating systems. - Per Angelstam. 1980 11. Dispersal, dispersion and distribution in small populations. - Fredric Karlsson. 1980 12. Age-related differences of competence in birds. - Karin Ståhlbrandt. 1980 13. Respiration measurements as a tool in ecology. - Bengt Fladvad. 1981 14. Intraspecific variation; its adaptive value and consequences. - Lars Gustafsson. 1981 15. Cooperative breeding in birds: theories and facts. - Mats Björklund. 1982 16. Some aspects of . - Göran Sundmark. 1982 17. Evolution and ecology of migration and dispersal. - Jan Bengtsson. 1982 18. Are animals lazy? - Time budgets in ecology. - Bodil Enoksson. 1983 19. Ecology of island colonization. - Torbjörn Ebenhard. 1983 20. Reproductive habits and parental care in some lacustrine African (Pisces) with special reference to Lake Malawi species. - Ulrich Jessen. 1983 21. or ? - Mating systems in birds. - Björn Westman. 1983 22. Distributional patterns in and . - Per Sjögren. 1983 23. Some theoretical considerations of dispersal. - Gunnar Nilsson. 1983 24. Interactions between animals and . - Urban Wästljung. 1984 25. Reproductive modes and parental care in . - Ingrid Svensson. 1984 26. Reproductive strategies in fishes. - Peter Karås. 1984 27. Sexual selection and female choice based on male genetic qualities. - Jacob Höglund. 1984 28. The timing of breeding in birds with special reference to the proximate control. - Mats Lindén. 1985 29. Philopatry and inbreeding versus dispersal and outbreeding. - Tomas Pärt. 1985 30. Evolution of sociality in Hymenoptera. - Folke Larsson. 1985

24 31. song and sexual selection. - Dag Eriksson. 1986 32. The energetics of avian breeding. - Lars Hillström. 1986 33. Sex role reversal in animals. - Gunilla Rosenqvist. 1986 34. Factors affecting post-fledging survival in birds. - Kjell Larsson. 1986 35. Quantitative genetics in evolutionary ecology: methods and applications. - Pär Forslund. 1986 36. Body size variations in small mammals. - Anders Forsman. 1986 37. Habitat heterogeneity and landscape fragmentation - consequences for the dynamics of populations. - Henrik Andrén. 1986 38. The evolution of predispersal predation systems in insects. - Mats W. Pettersson. 1987 39. Animal aggregations. - Anette Baur. 1988 40. Operational and other sex ratios: consequences for reproductive behaviour, mating systems and sexual selection in birds. - Jan Sundberg. 1988 41. Genetic variation in natural populations. - Annika Robertson. 1989 42. Adaptations for a parasitic way of life. - Reija Dufva. 1989 43. Predator-prey coevolution. - Lars Erik Lindell. 1990 44. Parasite impact on host biology. - Klas Allander. 1990 45. Ecological factors determining the geographical distribution of animal populations. - Berit Martinsson. 1990 46. - mechanisms and decision rules. - Elisabet Forsgren. 1990 47. Sexual selection and mate choice with reference to lekking behaviour. - Fredrik Widemo. 1991 48. Nest predation and nest type in passerine birds. Karin Olsson. 1991 49. Sexual selection, costs of reproduction and operational sex ratio. - Charlotta Kvarnemo. 1991 50. Evolutionary constraints. - Juha Merilä. 1991 51. Variability in the mating systems of parasitic birds. Phoebe Barnard. 1993. ISRN UU-ZEK-IRE--51—SE 52. Foraging theory: static and dynamic optimization. Mats Eriksson. 1993. ISRN UU-ZEK-IRE--52—SE 53. Moult patterns in passerine bird species. Christer Larsson. 1993. ISRN UU-ZEK-IRE--53--SE 54. Intraspecific variation in mammalian mating systems. Cheryl Jones. 1993. ISRN UU-ZEK-IRE--54--SE 55. The Evolution of Colour Patterns in Birds. Anna Qvarnström. 1993. ISRN UU-ZEK-IRE--55--SE 56. Habitat fragmentation and connectivity. Torbjörn Nilsson. 1993. ISRN UU-ZEK-IRE--56—SE 57. Sexual Selection. Models, Constraints and Measures. David Stenström. 1994. ISRN UU-ZEK-IRE--57—SE

25 58. Cultural Transmission and the Formation of Traditions in Animals. Henk van der Jeugd. 1995. ISRN UU-ZEK-IRE--58—SE 59. Ecological Factors Affecting the Maintenance of Colour Polymorphism. Sami Merilaita. 1995. ISRN UU-ZEK-IRE--59—SE 60. The Evolution and Maintenance of Hermaphroditism in Animals. Anna Karlsson. 1996. ISRN UU-ZEK-IRE--60—SE 61. Costs and Benefits of Coloniality in Birds. Tomas Johansson. 1996. ISRN UU-ZEK-IRE--61—SE 62. Nutrient reserve dynamics in birds. Måns S. Andersson. 1996. ISRN UU-ZEK-IRE--62—SE 63. Nest-building for parental care, mate choice and protection in fishes. Sara Östlund. 1996. ISRN UU-ZEK-IRE--63—SE 64. Immunological ecology. Dag Nordling. 1996. ISRN UU-ZEK-IRE--64—SE 65. Hybrid zones and speciation by reinforcement. Anders Ödeen. 1996. ISRN UU-ZEK-IRE--65—SE 66. The timing of breeding onset in temperate zone birds. Robert Przybylo. 1996. ISRN UU-ZEK-IRE--66—SE 67. Founder speciation - a reasonable scenario or a highly unlikely event? Ann-Britt Florin. 1997. ISRN UU-ZEK-IRE--67—SE 68. Effects of the Social System on Genetic Structure in Populations. Göran Spong. 1997. ISRN UU-ZEK-IRE--68—SE 69. Male Emancipation and Mating Systems in Birds. Lisa Shorey. 1998. ISRN UU-ZEK-IRE--69—SE 70. Social behaviours as constraints in mate choice. Maria Sandvik. 1998. ISRN UU-ZEK-IRE--70—SE 71. Social monogamy in birds. Kalev Rattiste. 1999. ISRN UU-ZEK-IRE--71--SE 72. Ecological determinants of effective population size. Eevi Karvonen. 2000. ISRN UU-ZEK-IRE--72—SE 73. Ecology of animals in ephemeral habitats. Jonas Victorsson. 2001. ISRN UU-ZEK-IRE--73--SE 74. Extra-pair paternity in monogamous birds. Katherine Thuman. 2001. ISRN UU-ZEK-IRE--74-SE 75. Intersexual communication in fish. Niclas Kolm. 2001. ISRN UU-ZEK-IRE--75—SE 76. The role of postmating prezygotic reproductive isolation in speciation. Claudia Fricke. 2002. ISRN UU-ZEK-IRE--76—SE 77. Host parasite interactions: Local adaptation of parasites and changes in host behaviour. - Lena Sivars. 2002. ISRN UU-ZEK-IRE--77—SE 78. The molecular clock hypothesis. Reliable story or fairy tale? Marta Vila-Taboada. 2002. ISRN UU-ZEK-IRE--78—SE 79. Chemical cues in mate choice. Björn Johansson. 2002. ISRN UU-ZEK-IRE--79—SE

26 80. Does sexual selection promote speciation? A comparative analysis of the Family Labridae (). - Sarah Robinson. 2002. ISRN UU-ZEK-IRE--80—SE 81. Population bottlenecks and their effects on genetic diversity: introducing some recent methods for detection. Marnie H Demandt. 2003. ISRN UU-ZEK-IRE--81—SE 82. Immune response and its correlations to other traits in poultry. Joanna Sendecka. 2003. ISRN UU-ZEK-IRE--82--SE 83. Resistance of Hybrids to Parasites. Chris Wiley. 2003. ISRN UU-ZEK-IRE--83—SE 84. The Role of Genetics in Population Viability Analysis. Johanna Arrendal. 2003. ISRN UU-ZEK-IRE--84—SE 85. Sexual Selection and Speciation – The Scent of Compatibility. Nina Svedin. 2003. ISRN UU-ZEK-IRE--85—SE 86. Male-female coevolution: patterns and process. Johanna Rönn. 2004. ISRN UU-ZEK-IRE--86—SE 87. Inbreeding in wild populations and environmental interactions. Mårten Hjernquist. 2004. ISRN UU-ZEK-IRE--87—SE 88. Sympatric speciation – A topic of no consensus. Emma Rova. 2005. ISRN UU-ZEK-IRE--88—SE 89. Man-made offshore installations: Are marine colonisers a problem or an advantage? Olivia Langhamer. 2005. ISRN UU-ZEK-IRE--89—SE 90. “Isolation by distance”: – A biological fact or just a theoretical model? Sara Bergek. 2006. ISRN UU-ZEK-IRE--90—SE 91. Signal evolution via sexual selection – with special reference to Sabethine mosquitoes. - Sandra South. 2007. ISRN UU-ZEK-IRE--91—SE 92. Aposematic Colouration and Speciation – An Anuran Perspective. Andreas Rudh. 2008. ISRN UU-ZEK-IRE--92—SE 93. Models of evolutionary change. Lára R. Hallson. 2008. ISRN UU-ZEK-IRE--93—SE 94. Ecological and evolutionary implications of hybridization. Niclas Vallin. 2009. ISRN UU-ZEK-IRE--94—SE 95. Intralocus sexual conflict for beginners. Paolo Innocenti. 2009. ISRN UU-ZEK-IRE—95—SE 96. The evolution of animal mating systems. Josefin Sundin. 2009. ISRN UU-ZEK-IRE—96—SE 97. The evolutionary ecology of host-parasite interactions. Katarzyna Kulma. 2011. ISRN UU-ZEK-IRE—97—SE 98. Sensory exploitation – trends, mechanisms and implications. Mirjam Amcoff. 2011. ISRN UU-ZEK-IRE—98—SE 99. Evolutionary biology of aging. Hwei-yen Chen 2012. ISRN UU-ZEK-IRE—99—SE 100. and Speciation: from prezygotic to postzygotic isolation Murielle Ålund 2012. ISRN UU-ZEK-IRE—100—SE

27 101. Resting metabolic rate and speciation. Eryn McFarlane 2014. ISRN UU-ZEK-IRE—101—SE 102. Vertebrate Brain Evolution: Insights from comparative studies Masahito Tsuboi 2014. ISRN UU-ZEK-IRE—102—SE 103. Dispersal and hybrid zone dynamics. Jakub Rybinski 2015. ISRN UU-ZEK-IRE—103—SE 104. Parasitism and speciation in a changing world. William Jones 2017 105. An evolutionary perspective on sex in animals. Ivain Martinossi-Allibert 2017. 106. Relating life history and physiology. Kevin Fletcher 2017. 107. Multidimensional adaptive dynamics and evolutionary diversification. Paula Vasconcelos 2017. 108. The evolution of sexual dimorphism in life history traits. Josefine Stångberg 2017.

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