Genetic variation and inference of

demographic histories in

non-model species

Jean-Luc Tison

Department of Molecular Biosciences,

The Wenner-Gren Institute

Stockholm University

2014

ii

Genetic variation and inference of demographic histories in non-model species

Doctoral Dissertation 2014

Jean-Luc Tison

Department of Molecular Biosciences, The Wenner-Gren Institute

Stockholm University

S-10691

Stockholm, Sweden

©Jean-Luc Tison, Stockholm, Sweden, 2014

ISBN 978-91-7649-056-3

Cover by Jean-Luc Tison

Printed in Sweden by US-AB, Stockholm, 2014

Distributor: Department of Molecular Biosciences, The Wenner-Gren Institute,

Stockholm University

iii

Abstract

Both long-term environmental changes such as those driven by the glacial cycles

and more recent anthropogenic impacts have had major effects on the past demogra-

phy in wild organisms. Within species, these changes are reflected in the amount and

distribution of neutral genetic variation. In this thesis, mitochondrial and microsatel-

lite DNA was analysed to investigate how environmental and anthropogenic factors

at different spatial and temporal scales have affected genetic diversity and structure

in four ecologically different animal species.

The glacial cycles are considered to have played an important role in the history

and distribution of species. Paper I describes the post-glacial recolonisation history

of the speckled-wood butterfly (Pararge aegeria) in Northern Europe. A decrease in

genetic diversity with latitude and a marked population structure were uncovered,

consistent with a hypothesis of repeated founder events during the postglacial recol-

onisation. Moreover, Approximate Bayesian Computation analyses indicate that the

univoltine populations in Scandinavia and Finland originate from recolonisations

along two routes, one on each side of the Baltic.

Paper II aimed to investigate how past sea-level rises affected the population

history of the convict surgeonfish (Acanthurus triostegus) in the Indo-Pacific. As-

sessment of the species’ demographic history suggested a population expansion that

occurred approximately at the end of the last glaciation. Moreover, the results

demonstrated an overall lack of phylogeographic structure, probably due to the high

dispersal rates associated with the species’ pelagic larval stage. Populations at the

species’ eastern range margin were significantly differentiated from other popula-

tions, which likely is a consequence of their geographic isolation.

In Paper III, we assessed the effect of human impact on the genetic variation of

European moose (Alces alces) in Sweden. Genetic analyses revealed a spatial struc-

ture with two genetic clusters, one in northern and one in southern Sweden, which

were separated by a narrow transition zone. Moreover, demographic inference sug-

gested a recent population bottleneck. The inferred timing of this bottleneck coin-

cided with a known reduction in population size in the 19th

and early 20th

century

due to high hunting pressure.

In Paper IV, we examined the effect of an indirect but well-described human

impact, via environmental toxic chemicals (PCBs), on the genetic variation of Eura-

sian otters (Lutra lutra) in Sweden. Genetic clustering assignment revealed differen-

tiation between otters in northern and southern Sweden, but also in the Stockholm

region. ABC analyses indicated a decrease in effective population size in both north-

ern and southern Sweden. Moreover, comparative analyses of historical and con-

temporary samples demonstrated a more severe decline in genetic diversity in south-

ern Sweden compared to northern Sweden, in agreement with the levels of PCBs

found in the respective areas.

iv

v

List of papers

This thesis is based on the following papers, which are referred to in the text by their

roman numerals:

I. Tison JL, Nyström Edmark V, Sandoval-Castellanos E, Van Dyck H,

Tammaru T, Välimäki P, Dalén L, Gotthard K. (2014) Signature of post-

glacial expansion and genetic structure at the northern range limit of the

speckled wood butterfly. Biological Journal of the Linnean Socie-

ty.113:136-148.

II. Tison JL, Chan Y, Dalén L, Planes S. Indo-Pacific population structure and

demographic history of a highly abundant and widespread coral reef fish,

Acanthurus triostegus. Manuscript.

III. Wennerström L, Hasslow A, Tison JL, Dalén L, Laikre L†, Ryman N

†.

Genetic landscape with sharp allele frequency shifts in Swedish moose (Al-

ces alces) revealed by individually based. Manuscript.

IV. Tison JL*, Blennow V*, Palkopoulou E, Gustafsson P, Roos A, Dalén L.

Population structure and recent temporal changes in genetic variation in

Eurasian otters from Sweden. Conservation genetics, in press.

* These authors contributed equally to the study.

† These authors contributed equally to the senior position.

Copyright: Paper I: The Linnean Society of London © 2014

Copyright: Paper IV: Springer Science + Business Media Dordrecht © 2014

vi

Acknowledgments

First, I would like to express my warmest thanks to my supervisor Love Dalén for

giving me the chance to join his research group, and allowing me a new departure in

my PhD studies. More than being a supervisor, you have been an essential support, a

true mentor, always full of encouragement and constantly in a good mood. I am

grateful to Martine Bérubé and Per Paslbøll for giving the opportunity to start a PhD

in Stockholm and for the work together. Your scientific expertise, rigor, objectivity

and sense of quality are remarkable. I also want to thank Karin Noren, my co-

supervisor for the support. For their advices, guidance and practical help, I am grate-

ful to Ann-Beth Jonsson, Dag Jenssen, Elisabeth Håggard and Eva Petterson.

Many thanks, to everybody at the Department of Genetics, Microbiology and

Toxicology (now MBW) and to everybody at my host department Bioinformatics

and Genetics at the Swedish Natural History Museum for the stimulating research

environment. Particularly, I would like to thank the former and current members of

the ancient DNA group at NRM: Elle, Vendela, Patricia, Erik, Yvonne, Edson, the

frequent visitor-PhD student Matti Heino and the former master students George

Xenikoudakis and Victor Blennow, for the nice discussions, help, social hangouts

and fun together. I am truly grateful to Martin, Bodil, Veronica, Rodrigo, Keyvan,

Pia, Jane and Fredrick for their help, practical and technical assistance in addition to

the pleasant company at NRM.

I also want to thank Vicky and the former colleagues from the Evolutionary Genet-

ics Group at GMT: Morten Tange Olsen, Laetitia Wilkins, Mimmi Lidh, Pauline

Gauffier and Conor Ryan. A particular thanks to my roommate at GMT and friend

Morten for all the fun during these years, in the good times as well as in the less

good ones. I remember sharing a class as assistant with the best teacher ever,

kayaking in Central Sweden, the memorable moments in Québec and Boston with

you. Thank you for your permanent support and to remind me than pursuing my

dreams is the best thing to do in life. I am longing to go whale-watching with you at

some point or paddle (va’a) in the Tuamotu. Also, thanks to my former corridor

mates Bo, Hanna, Cissi, Petra, Dominik, Anne and Ivo, Miriam, Lisa, Katarina,

Nele, Sara, Jens, Niklas, Alice, Karl, Elina, Ramesh and Andrzey for the company

and nice social events throughout the years. Thanks also to Zoology department for

inviting me to Bloodbath throughout the years and to the peoples at Zoology for

including me in many other social occasions.

Many thanks, to all the co-authors for your help and support with the papers includ-

ed in this thesis. I am particularly grateful to Veronica Nyström Edmark, Kalle

Gotthard, Edson Sandoval-Castellanos, Yvonne Chan, Serge Planes, Lovisa

Wennerström, Linda Laikre, Nils Ryman and of course Love Dalén. Thank you,

vii

Love for having explained me how to use (or not use) a semi-colon and helping me

so much with improving my English writing. Again, thank you Love, Elle and Anna

for reading and commenting on the thesis.

I am also grateful to all the collaborators and peoples involved in the interesting and

fun projects, which were not included in this thesis and the ones involved in field-

work and other experience. Particularly I want to thank (i) Richard Sears and Chris-

tian Ramp at Mingan Island Cetacean Study, (ii) Olivier Van Canneyt, Ghislain

Doremus and Sophie Laran at Centre de Recherche sur les Mammifères Marins –

Université La Rochelle for the REMMOA project, (iii) Brian Bowen, Rob Toonen

and the ToBo lab at the Hawaii Institute of Marine Biology, and (iv) Love, Sverker,

Patricia and Erik for the fun “bear safari”.

I am thankful to the Knut and Alice Wallenberg foundation and C.F. Liljevach foun-

dation for providing the financial support to present my work at conferences.

Also, my warmest thanks to my former colleagues at Lycée Français Saint Louis and

friends here in Stockholm than kept asking me “When will you be done with your

PhD?” So, Marcel, Ludo, Séverine, Arnaud, Samir, Florent, Carole, Mina, Grégory,

très bientôt, ce sera le cas. Merci d’avoir été là toutes ces années.

Merci aussi aux amis d’enfance, de Paris ou Montpellier, Antoine, Mica, Hadley,

Mag, Pauline, Manue, Florent, Romain ainsi qu’à Kelly, Sam, Frank, Bella de votre

soutien et de venir me rendre visite de temps en temps. Cela me touche énormément.

Vous êtes toujours les bienvenus. Un jour, certains d’entre vous finiront peut être par

emménager ici.

Egalement, un immense merci à Alexandre et Isolde, Mélanie, Marie-Françoise et

Jean-Noël de m’avoir toujours soutenu malgré les distances et les difficultés. Papa,

Maman, vous n’avez de cesse de croire en nous et de parcourir le monde pour nous,

merci donc. Cette thèse, c’est aussi et avant tout grâce à vous. Du fond du cœur, je

vous en remercie. Enfin, Anna merci de ton amour, de me soutenir, d’être toujours là

pour moi, et d’avoir rendu cela possible. Tu es un vrai trésor dans ma vie.

“Wonder is the beginning of wisdom”

Socrates 470 BC – 399 BC

viii

ix

Contents

Abstract ..................................................................................................................... iii

List of papers .............................................................................................................. v

Acknowledgments ..................................................................................................... vi

Contents ..................................................................................................................... ix

Introduction ................................................................................................................. 1 Genetic diversity and population genetics: the basis to infer population histories ................................ 1 Reconstructing past demography ......................................................................................................... 2

The coalescent theory .................................................................................................................... 2 Identification of population expansions and bottlenecks ................................................................ 2 Inferring more complex demographies: new tools, new possibilities ............................................. 3

Consequences of historical changes in the environment....................................................................... 4 Glacial-cycles - speckled wood butterfly ....................................................................................... 4 Sea-level fluctuations - convict surgeonfish................................................................................... 4

Recent anthropogenic impacts.............................................................................................................. 5 Harvesting pressure – moose in Sweden ........................................................................................ 5 Environmental toxins – Eurasian otters in Sweden ........................................................................ 6

Objectives ................................................................................................................... 7

Materials and methods ................................................................................................ 8 Laboratory methods ............................................................................................................................. 8

Samples ......................................................................................................................................... 8 Molecular ecology markers ............................................................................................................ 8

Analytical methods ............................................................................................................................ 10 Genetic diversity .......................................................................................................................... 10 Comparisons of populations and estimates of genetic structure ................................................... 10 Neutrality tests and population history inference ......................................................................... 10

Summary of papers ................................................................................................... 11 Paper I ................................................................................................................................................ 11 Paper II .............................................................................................................................................. 12 Paper III ............................................................................................................................................. 14 Paper IV ............................................................................................................................................. 15

Future directions ....................................................................................................... 17

Contributions ............................................................................................................ 20

References ................................................................................................................. 21

Sammanfattning på svenska ...................................................................................... 31

Résumé en français ................................................................................................... 32

x

1

Introduction

“Nothing in biology makes sense except in the light of evolution."

Theodosius Grygorovych Dobzhansky - 1973

The amount and distribution of neutral genetic variation in extant organisms is a

consequence of their history. At a large time scale, historical climate-driven effects

such as glacial cycles (Paper I) and sea-level changes (Paper II) have played a major

role in influencing genetic diversity. At shorter time scales, human activities such as

overexploitation of resources (Paper III), pollution (Paper IV), habitat destruction

and introduction of exotic species have had major impacts on biodiversity. The in-

fluence of these processes on the history of populations and their genetic diversity

can be assessed using genetic tools.

Genetic diversity and population genetics: the basis to infer

population histories

The inference of demographic parameters from genetic data is based on the fact that

evolutionary forces change the frequency of alleles in a population through time.

The process of mutation creates new alleles and increases genetic variation. Muta-

tions can be neutral, or have positive as well as negative effects on the fitness of an

individual. The frequency of an allele in a population can thus increase or decrease

under the effect of natural selection (Darwin 1859; Fisher 1930), depending on

whether its beneficial or deleterious to reproductive success. The frequency of an

allele may also change due to random sampling of alleles from one generation to the

next, called genetic drift. The rate of genetic drift in a population is directly depend-

ent on the effective population size (Wright 1931). In a population with small effec-

tive population size, genetic drift is more pronounced and can lead to the fixation or

loss of alleles. However, in a large enough population without migration or selection

the effect of genetic drift can be negligible. In such situations, mutation-drift equilib-

rium can be maintained, where the loss of diversity through genetic drift is compen-

sated by the introduction of diversity through mutation. In addition, migration, or in

evolutionary terms, the movement of alleles between populations (gene-flow) will

tend to homogenize allele frequencies between populations, in absence of selection.

Gene flow among populations can take place via the dispersal of animal organisms,

planktonic larvae, seeds or even gametes.

However, in natural situations, individuals within a species rarely breed random-

ly (under panmixia). This non random-mating can be due to species-specific life-

history traits such as philopatry, ecological factors such as habitat preferences, or

environmental barriers such as mountains or rivers. As a consequence, within a

geographic range, individuals are typically more closely related to each other com-

2

pared to individuals from different geographic regions, creating genetic differentia-

tion among groups of individuals. This type of genetic structure within species leads

to the formation of genetically distinct populations.

Knowledge on how these forces drive changes in the frequency of alleles, and

depending on the spatial and temporal scale of interest, different patterns of genetic

differentiation and population history can be identified. For example, population

genetic models can be used to reconstruct the demographic history of a population in

terms of expansions and reductions in effective population size as well as population

divergence. Since also the timing of such events can be estimated, it is also possible

to explore the interaction between past changes in demography and historical geo-

logical or climatic conditions.

Reconstructing past demography

Since the advent of DNA sequencing in the early 1990s and the development of the

fields of human evolution, phylogeography and conservation biology, the interest of

estimating demographic parameters and reconstructing the past demography of pop-

ulations increased (Avise 2000; Beaumont 2004; Emerson et al. 2001). This investi-

gation was facilitated by the development and application of the coalescence theory

(Hudson 1991; Kingman 1982a; Kingman 1982b).

The coalescent theory

The coalescent theory is a population model looking back in time to interpret genetic

data. Thus, the coalescent describes the genealogical history of a sample of individ-

uals from a population back until their Most Recent Common Ancestor (MRCA).

Using the coalescent theory, it is possible to estimate population parameters, such as

effective population size, and to investigate possible population size changes. Popu-

lation size changes can be reflected in the shape of the genealogy of the coalescent.

For example, a population under expansion produces long external branches in the

genealogy, resulting in an excess of singletons. A class of statistical tests (such as

Tajima’s D test), using the frequency of segregating sites, has been developed and

measure whether there is an excess or a deficiency of rare mutations in the observed

dataset compared to expectation under the Wright-Fisher model (Fu & Li 1993;

Tajima 1989a, b). The results are often interpreted in terms of population size

changes.

Identification of population expansions and bottlenecks

Historically, to detect population expansion, analysis of the distribution of pairwise

differences among DNA sequences, also called mismatch distributions, has been

used (Excoffier & Schneider 1999; Harpending 1994; Rogers & Harpending 1992;

Sherry et al. 1994; Slatkin & Hudson 1991). Following a sudden population size

expansion, a population displays a unimodal distribution of pairwise differences.

The timing of the start of population growth can then be estimated by the position of

the peak in the distribution (Rogers & Harpending 1992). Other statistical tests, such

as Fu’s Fs, based on haplotype distributions have also been developed (Fu 1997).

3

In conservation biology, detecting population bottlenecks is essential since de-

clines in genetic diversity of a population may have a negative effect on its ability to

survive. Population bottlenecks can leave distinctive signatures in expected hetero-

zygosities and in the distributions of allele sizes. Genetic bottleneck tests typically

make use of these properties to determine if a population has gone through a demo-

graphic decline. The earliest population bottleneck tests aimed at detecting depar-

tures from expectations under mutation-drift equilibrium. For example, tests such as

“heterozygosity-excess” (Cornuet & Luikart 1996; Piry et al. 1999) and the M-ratio

test (Garza & Williamson 2001) have been extensively used (Peery et al. 2012).

Nonetheless, the statistical power to detect genetic bottlenecks using these ap-

proaches appears to be limited, especially if the bottleneck occurred only a few gen-

erations before sampling (Aguilar et al. 2008; Girod et al. 2011; Hoffman et al.

2011; Peery et al. 2012). However, more advanced methods to estimate demograph-

ic parameters and characterize demographic histories are rapidly being developed

(Beaumont 2004, 2010).

Inferring more complex demographies: new tools, new possibilities

Recently, more powerful approaches based on maximum likelihood, Bayesian and

Approximate Bayesian Computations (ABC) have been developed (Bertorelle et al.

2010; Kuhner 2009). For example, Bayesian skyline plots can provide estimates of

changes in effective population size through time (Drummond & Rambaut 2007;

Drummond et al. 2005; Ho & Shapiro 2011; Pybus et al. 2000). Bayesian methods

implemented in MSvar show a higher probability of detecting population bottle-

necks compared to more traditional heterozygosity-excess and M-ratio tests (Girod

et al. 2011; Storz & Beaumont 2002). In addition, packages such as BEAST

(Drummond & Rambaut 2007), LAMARC (Beerli & Felsenstein 2001; Kuhner et

al. 1998) and SPLATCHE2 (Ray et al. 2010) also allow estimation of effective

population sizes under different population histories.

The ABC-framework allows comparison of different scenarios of evolution, in

order to select the best scenario and to estimate posterior distributions of model

parameters. In brief, prior distributions of parameters describing various aspects of

the scenarios are given by the user. Following this, a high number of simulations

with parameter values drawn from the prior distributions are performed. Summary

statistics are then computed for the observed dataset, as well as for each simulated

dataset. The simulations with summary statistics that are most similar to those of the

observed data are kept. This allows for model selection to be implemented, as well

as recovery of posterior distributions of parameters from the selected model. Model

checking and cross validation can also be performed using pseudo-observed datasets

(Bertorelle et al. 2010; Csillery et al. 2010).

4

Consequences of historical changes in the environment

Describing the history of populations and the past variation in population size is

essential to understand the impact of past climate changes on the current distribution

of species, but also for the conservation of endangered species.

Glacial-cycles - speckled wood butterfly

During the Quaternary (2.6 Myr ago to today), fluctuations in the Earth’s climate

have led to several glacial episodes, and these have played an important role in the

abundance and distributions of species. For instance, during the Last Glacial Maxi-

mum (LGM, around 23,000-18,000 years ago), many temperate species in the north-

ern hemisphere were confined to southern refugia (Hewitt 2000; Hewitt 1999;

Taberlet et al. 1998) while, in contrast, arctic species had a much larger distribution

than they do today (Stewart et al. 2010). After the LGM, during the Pleistocene-

Holocene transition, the ice-sheets covering much of northern Europe and North

America melted. Accordingly, some species adapted to cold conditions became

constrained to smaller geographical areas, and depending on their adaptations and

environmental tolerance, decreased in population size and genetic diversity (Campos

et al. 2010) or even went extinct (Stuart & Lister 2011). In contrast to cold-adapted

species, temperate species were able to recolonise high-latitude regions and conse-

quently expanded in population size. Such postglacial recolonisation processes left

genetic footprints both in terms of genetic diversity (Lessa et al. 2003) and genetic

relatedness among populations (Hewitt 1999).

Insects and particularly butterflies are good models to study evolutionary process-

es and climate-driven range shifts (Hill et al. 2011; Hill et al. 1999; Parmesan et al.

1999). The speckled wood butterfly, Pararge aegeria, was likely confined to south-

ern refugia during the LGM and subsequently expanded northwards. Today the

species is found in Scandinavia and Finland, which constitute its northern range

margin. However, little is known about the recolonisation history of the species, nor

its genetic diversity and structure in Northern Europe.

Sea-level fluctuations - convict surgeonfish

The Indian and Pacific oceans contain the highest concentration of tropical marine

biodiversity (Ekman 1953) and are divided into several biogeographical provinces

(Briggs & Bowen 2012; Cowman & Bellwood 2013; Kulbicki et al. 2013). During

the LGM, the sea-level was about 120 meters lower than it is at present-day, which

led to a considerable reduction in connectivity between the Indian and Pacific

oceans (Sathiamurthy & Voris 2006; Voris 2000). In addition, the distribution and

abundance of coral reefs were much lower than those of today (Kleypas 1997; Ludt

& Rocha 2014). By inferring past events in coral reef taxa, one could expect to find

patterns of ancient vicariance during the last ice age, demographic expansion at the

end of this period, and Holocene high levels of gene flow.

One of the most abundant and widespread coral reef fish in the Indian and Pacific

oceans is the convict surgeonfish, Acanthurus triostegus. Its range spans several

biogeographic regions, from East Africa through the Indo-Pacific to the eastern

5

Pacific. Compared to other widespread fish, in which little genetic structure has been

found based on mitochondrial DNA (Horne et al. 2008; Klanten et al. 2007), high

levels of differentiation have been described in Acanthurus triostegus using al-

lozymes (Planes & Fauvelot 2002). Therefore, we were interested in studying the

population structure using mitochondrial DNA, and infer the demographic history of

the convict surgeonfish.

Recent anthropogenic impacts

From hunter-gatherer societies, through farming and pastoralist societies, to modern-

day societies, humans have exploited and modified their environment to meet their

needs. However, with the progress of technology, especially following the industrial

revolution, pollution as well as overexploitation of natural resources (through fish-

ing, hunting, agriculture, animal farming and forestry) have become more intense

and today constitute major threats to biodiversity.

Harvesting pressure – moose in Sweden

Many species have become extinct due to human overharvesting, both in the terres-

trial and marine environments, such as the dodo, the Tasmanian tiger, the great auk

and Steller’s sea cow. Others species, such as most whales and many shark species

have decreased dramatically in population size (Baum et al. 2003; Diamond 1989;

Jackson et al. 2001; Roberts & Solow 2003). Harvesting can reduce the effective

population size down to critical levels where genetic drift and inbreeding can be-

come a threat to the survival of the population. The genetic diversity of a population

and its spatial structure can also be modified due to intensive harvesting. Moreover,

selective harvest can change the genetic composition of a population (Allendorf et

al. 2008).

In order to determine which populations to manage and protect, it is important to

define conservation and management units. Thus, concepts such as “Evolutionary

Significant Units” and “Management Units” have been discussed and are based

mainly on genetic parameters (Crandall et al. 2000; Moritz 1994; Palsboll et al.

2007; Waples & Gaggiotti 2006). These aspects have been well studied in many

taxa, but several studies have also underlined the need to estimate and delineate

population genetic structure and to take into consideration the demographic history

of the population (Manel et al. 2004; Taberlet et al. 1995; Tallmon et al. 2004;

Waits et al. 2000). Thus, population genetic data can provide valuable information

to monitor populations and species for management and conservation (Schwartz et

al. 2007).

The largest game animal in Sweden is the moose, Alces alces. Approximately

one third (c. 100,000 animals) of the population is currently harvested annually.

However, in the beginning of the 19th

century a strong decline in population size

occurred. It is believed that this decline culminated with only a few hundred to a few

thousand animals remaining in the central part of Sweden. The population size has

subsequently increased rapidly since the 1960s (Lavsund et al. 2003). Although the

6

current demography of the population is well studied, little is known about its popu-

lation structure and past demographic history, despite the importance of these pa-

rameters for the management of the Swedish moose.

Environmental toxins – Eurasian otters in Sweden

Some of the most common toxins found in the environment are polychlorinated

biphenyls (PCBs), pesticides, phthalates and heavy metals. Depending on their con-

centration in organisms, these compounds can be highly toxic and have tremendous

effects on a wide range of organisms. They can lead to increased mortality, reduced

fertility and/or reduced reproductive rates. Thus, these toxins can result in major

decreases in population size, and can reduce the genetic diversity of populations. For

example, DDT, an organochlorine used as insecticide in the 1940s and banned in

most countries since the 1970s, poisoned the wildlife for decades due to its hydro-

phobic and lipophilic properties and its high bioaccumulation potential. According

to a well-described mechanism, a metabolite of DDT, called DDE, caused eggshell

thinning that led to egg breakage and death of embryos. This resulted in severe pop-

ulation declines in bird species in both North America and Europe (Bignert et al.

1995; Bowerman et al. 1995; Green 1998).

Another class of contaminants with high impact on biodiversity is PCBs. In the

Baltic ecosystem and in Sweden, both PCBs and DTT have impacted the environ-

ment and the fauna (Olsson & Reutergårdh 1986). For example, studies have shown

a negative impact on the Baltic guillemot (Bignert et al. 1995; Jorundsdottir et al.

2006), the white-tailed sea eagle (Hailer et al. 2006; Helander et al. 2002), seals

(Bredhult et al. 2008; Nyman et al. 2003) and Eurasian otters (Olsson & Sandegren

1991; Roos et al. 2001). The latter species, Lutra lutra, was common in Sweden

before the 1950s but went through a drastic bottleneck between the 1950s and

1980s. After the bans of DDT and PCBs in the 1970s, the population began to re-

cover. However, the genetic consequences of this demographic bottleneck have

remained unknown, both in terms of how much genetic variation was lost and

whether the bottleneck had an effect on present-day population structure.

7

Objectives

The aim of this thesis was to reconstruct past demography and assess population

structure by estimating genetic variation in four wild animal species living in differ-

ent environments.

More specifically, the objectives were to:

Assess species demographic histories using inferences based on deviations

from mutation-drift equilibrium as well as coalescent-based approximate

Bayesian computation (Papers I – IV).

Evaluate the relationship between inferred demographic changes and past

climatic (Papers I & II) as well as anthropogenic (Papers III & IV) changes.

Examine to what extent genetic structure among contemporary populations

have been affected by past changes in climate (Papers I, II & III) and hu-

man-mediated bottlenecks (Papers III & IV).

Investigate the relative amount of genetic diversity and population differenti-

ation at species range margins (Papers I & II).

8

Materials and methods

Several species that inhabit widely different environments were used in this re-

search, and a range of analyses using genetic information were conducted to learn

both about the population history of each species and understand the factors influ-

encing its distribution. The taxonomic as well as environmental diversity in these

studies comprised terrestrial invertebrates and mammals (Papers I and III), a semi-

aquatic mammal (Paper IV) and a marine fish (Paper II). Both recently collected

samples (Papers I – IV) and historical museum samples (Paper IV) were analysed to

examine the population structure and demographic history and each respective spe-

cies.

Laboratory methods

Samples

In Paper I, speckled wood butterflies (n=209) were collected between 1984 and

2011 from locations in northern Europe, but with particular emphasis on Sweden. In

Paper II, convict surgeonfishes (n=179) were collected between 1994 and 2008 from

reef slopes or lagoons at several sites across the Indo-Pacific. In Paper III, a very

large number of fresh tissue samples (n=20,358) were obtained from moose killed

throughout Sweden during one single hunting season in 1980. A smaller number of

these moose samples were genotyped for microsatellite and mitochondrial DNA

variation (n=1207 and n=48, respectively). In Paper IV, European otters (n=139)

were sampled at three time points, before 1950 (n=17), between 1950 and 1979

(n=31), and after 2000 (n=91).

In the four studies, whole genomic DNA was extracted for further analysis of

population genetic variability, differentiation and demographic history assessment.

In Paper I, DNA was extracted using the Molestrips DNA tissue kit. In Paper III,

DNA was extracted using salt extraction method modified from Aljnabi and Mar-

tinez (1997) or the QIAGEN DNeasy Blood and Tissue Kit. The latter kit was also

used for the DNA extraction of the muscles samples in Papers II and IV. For the

museum European otter bone samples, in Paper IV, after being drilled into fine

bones powder, DNA was extracted using a modified version of protocol C in Yang

et al. (1998).

Molecular ecology markers

A broad scope of molecular markers have been developed and used for population

analyses, including allozymes, RFLPs, AFLPs, microsatellites, SNPs as well as

mitochondrial and nuclear DNA sequences. In the papers included in this PhD the-

sis, three types of markers were used for different applications and are described

thereafter.

Allozymes

In Paper II, three allozyme loci (Pmi, Mdh-2, and Pgi-1) were used to detect molec-

ular heterogeneity in the full moose sample (n=20,358). Allozymes are allelic vari-

9

ants of enzymes and were historically the first molecular markers broadly used to

investigate diversity patterns within and among populations. The different alleles

can be differentiated according to size and charge through gel electrophoresis (Sick

1961).

Mitochondrial DNA sequences

Regions of the mitochondrial DNA were amplified and sequenced in Papers II and

III. In both these papers, a part of the control region of the mitochondrial DNA was

sequenced. The control region contains hypervariable parts, which are often used to

describe population genetic variability. In addition, in Paper II, a 365 bp fragment of

the cytochrome oxidase I gene was sequenced. More details about the amplification,

the purification of the PCR products can be found in the respective papers. The

laboratory work for the mitochondrial DNA for Paper III was conducted at the De-

partment of Bioinformatics and Genetics, Swedish Museum of Natural History. The

laboratory work for Paper II was conducted at URS 3278, Perpignan, France. The

sequences were edited and assembled using BioEdit (Paper II) and Geneious (Papers

II, III).

Microsatellites

Microsatellite loci consist of short tandem repeats (1-6 bp long) that are found

throughout the genome. Due to single-strand slippage during in vivo DNA replica-

tion, repeats can be added or lost. This slippage can occur at comparatively high

rates leading to mutation rates ranging between 10-3

-10-5

mutations/locus/generation

(Ellegren 2004). Thus, high levels of polymorphism can be found within species and

microsatellites are thus particularly useful to describe population variability (Selkoe

& Toonen 2006). Microsatellites were employed in Papers I, III and IV. In Paper I,

nine microsatellites previously characterized for Pararge aegeria were used. In

Paper III, twelve microsatellites were genotyped for Alces alces and in Paper IV, we

genotyped twelve loci in the Lutra lutra samples. In the three papers, the amplifica-

tions were performed in multiplex PCR reactions using the QIAGEN multiplex PCR

master mix. The grouping of the loci in the multiplex PCRs, the details of the fluo-

rescence labeled primers and the reaction settings can be found in the respective

papers. Capillary electrophoresis was conducted on an ABI 3130xl. The sizes of the

fragments were determined using the GeneScanTM

500 LIZTM

(Papers I and IV) or

the GeneScanTM

600 LIZTM

size markers (Paper III). For Paper I and Paper IV, the

laboratory work and genotyping were performed at the Department of Bioinformat-

ics and Genetics, Swedish Museum of Natural History. For Paper III, the laboratory

work and the genotyping were performed at the Center of Evolutionary Application,

University of Turku, Finland. In all three papers, genotypes were scored using

GENEMAPPER v4.0 (Applied Biosystems).

10

Analytical methods

Genetic diversity

Levels of genetic diversity were investigating in all four papers. For the microsatel-

lite datasets (Papers I, III and IV) and the allozyme dataset (Paper III), several

statistics, such as the mean number of alleles, observed and expected heterozygosi-

ties, and allelic richness were used to describe variation within and among different

sampling locations. Moreover, in Paper IV genetic diversities were also compared

across different points in time. Genetic variation was also estimated for the mito-

chondrial DNA sequences (Papers II, III) by evaluating, for example, the number of

haplotypes, haplotype diversity, as well as nucleotide diversity and the number of

segregating sites among sequences.

Comparisons of populations and estimates of genetic structure

We investigated if and how the samples were genetically structured in space and in

time. For several sampled areas, we assessed connectivity in terms of gene flow

between sampling locations. For each marker, we were interested in examining

differences in allele and haplotype frequencies and how these were distributed in

space. The phylogenetic relationships between samples and geographic locations

were inferred using tree-based methods. The relationships among mitochondrial

DNA haplotypes were also estimated using minimum spanning or median-joining

networks (Papers II and III). From the spatial distribution of alleles and haplotypes,

we assessed the genetic divergence between populations using for example FST or

ΦST statistics (Wright 1951). Genetic and geographical distances were also com-

pared using Mantel tests and tested for isolation by distance (Paper II). Population

clustering was conducted using Analysis of Molecular Variance (AMOVA) or using

individual-based approaches (i.e., spatial autocorrelograms, STRUCTURE, TESS).

Neutrality tests and population history inference

Fossil remains or museum collections are valuable in population genetics since they

allow for direct estimates of changes in genetic diversity. However, when only con-

temporary samples are available, the assessment of past changes in population size is

more challenging. Several statistical tests have been developed for DNA sequences

and for multilocus microsatellite genotypes to detect departure from mutation-drift

equilibrium, which can be used to infer demographic histories. For DNA sequences,

Tajima’s D, Fu’s FS were computed and the results were interpreted in terms of past

changes in effective population size. For microsatellites, heterozygosity-excess tests

were performed to detect earlier population bottlenecks (Papers III, IV). Further-

more, coalescent-based simulations coupled with Approximate Bayesian Computa-

tion (ABC) were employed to infer the history of populations. The ABC-framework

allows to assess more complex scenarios of evolution, selects the best scenario and

estimates posterior distributions of model parameters by comparing summary statis-

tics between observed and simulated datasets (Bertorelle et al. 2010; Csillery et al.

2010).

11

Summary of papers

Paper I

Postglacial recolonisation in the speckled wood butterfly

One of the most prominent features of the last ice age was the last glacial maximum

period around 20,000 years ago. At that time, most of Britain and Northern Europe

as far south as Germany and Poland were covered by the Scandinavian Ice Sheet.

The ice started melting around 17,000 years ago allowing temperate plants and ani-

mals, which had been restricted to refugia, to recolonise the previously glaciated

areas (Mangerud et al. 2011; Svendsen et al. 2004). In this study, we investigated

the post-glacial recolonisation of the speckled wood butterfly, Pararge aegeria, in

northern Europe using microsatellite genetic markers. We found an overall pattern

of latitudinal decrease in allelic richness, which is consistent with the hypothesis that

range expansions lead to successive losses in genetic variation due to repeated

founder events (Hewitt 2004). Furthermore, using a Bayesian model-based cluster-

ing method, a marked population structure was detected. In the dataset, six genetic

clusters were identified, corresponding to six geographically separate populations:

[1] Central Scandinavia, [2] Gotland, [3] Öland, [4] South Scandinavia, [5] Benelux

and [6] Eastern Baltic. Interestingly, previous studies have found very low genetic

differentiation further south in Europe and in North Africa (Habel et al. 2013;

Vandewoestijne & Van Dyck 2010). We hypothesized that the population structure

observed in our study is a consequence of repeated founder effects during the post-

glacial range expansion, since this type of process can lead to increased population

divergence (Klopfstein et al. 2006; Ray & Excoffier 2009).

To further examine the recolonisation of northern Europe, we compared different

postglacial range expansion models using an ABC approach, with emphasis on dif-

ferent scenarios for the origin of the population in Central Scandinavia (Fig. 1). We

tested three plausible scenarios where Central Scandinavia was recolonised either

from the south (South Scandinavia) or the East (Eastern Baltic). Among the three

scenarios tested, we could reject the recolonisation of Central Scandinavia from the

East. This means that the post-glacial recolonisation of northernmost Europe (Cen-

tral Scandinavia and Eastern Baltic) took place along two routes, with one route on

each side of the Baltic. This is interesting because Pararge aegeria displays differ-

ent local adaptations in different parts of northern Europe, where populations in both

Central Scandinavia and Eastern Baltic are univoltine (i.e. have one generation per

year), while populations further south are multivoltine. Thus, under the assumption

that the source populations in the south were multivoltine, as they are today, and that

no gene flow has occurred between Central Scandinavia and Eastern Baltic, the

ABC results suggested that univoltinism evolved independently on both side of the

Baltic Sea.

12

Fig. 1

Schematic representations of three recolonisation scenarios (A-F) tested using the

ABC approach.

Paper II

Indo-Pacific genetic structure and variation in the convict surgeon fish

The oceans cover approximately 70% of the earth’s surface, and have few obvious

geographic barriers to dispersal. This, coupled with the pelagic larval stage dis-

played by many coral reef species implies that one might expect high levels genetic

variation and little genetic differentiation among regions. On the other hand, de-

clines in global sea levels during the last glaciation likely had a major effect on coral

reef species, both because their distributions were more restricted and because the

formation of land bridges may have reduced connectivity among populations. To

investigate the demographic history and genetic structure in a widespread coral reef

fish, we analysed genetic variation in the convict surgeonfish (Acanthurus trioste-

gus) sampled across the Indo-Pacific. We recovered sequences from two mitochon-

drial DNA (mtDNA) markers, the left hypervariable domain of the control region

and the cytochrome oxidase I gene.

High levels of haplotype and nucleotide diversities (h > 99 and π = 8.9%) were

found. Moreover, a lack of phylogeographic structure across the species range was

revealed in the haplotype networks (Fig. 2). These results are consistent with a large

long-term effective population size in Acanthurus triostegus, and likely also reflect

the species’ capacity for long distance dispersal during its pelagic larval stage. Simi-

13

lar results have been observed for species with comparable wide geographic ranges

(Gaither et al. 2010; Horne & van Herwerden 2013; Klanten et al. 2007).

In addition, it should be noted that significant genetic differentiation was ob-

served for populations at the species range margin (e.g. Clipperton and the Marque-

sas). A high degree of differentiation has been commonly reported in these isolated

regions, where the presence of cryptic species is known. This is also in accordance

with the fact that the species richness is lower than in the west-Pacific and that a

high degree of endemism have been reported for Marquesas (Lessios & Robertson

2006; Szabo et al. 2014; Williams et al. 2013)

To further explore the demographic history in Acanthurus triostegus, we used an

ABC approach. The results from these analyses indicated that a ten-fold expansion

in population size took place, roughly at the end of the last glaciation. This result is

consistent with a hypothesis that climate-driven rises in sea levels at the end of the

last glaciation may have led to re-arrangements in coral reef distributions. This may

have had cascading effects on many fish species that rely on them. Interestingly, we

also observed signatures of a more ancient, probably Middle Pleistocene, demo-

graphic expansion in the distribution of pairwise differences among the mitochon-

drial DNA sequences. Thus, our results revealed a complex demographic history that

may be attributed to the sea-level fluctuations. Still, these findings also indicated the

need of large sampling efforts combined with a multi-locus analysis to better address

this complex demographic history. Moreover, to better understand the coral reef

history of the Indo-Pacific, there is a need to perform comparative multi-species

studies, based on different life-history traits.

Fig.2

Minimum spanning networks for Acanthurus triostegus sampled across the Indo-

Pacific, based on 365 bp of mitochondrial CR sequences (n= 161: A) and based on

449 bp of mitochondrial COI sequences (n=179: B). Each circle represents a single

haplotype and the circle size is proportional to the frequency of the haplotype. Each

hatch-mark represents a nucleotide change. Colours indicate haplotype location.

A B

14

Paper III

Autosomal and mitochondrial genetic variation in the Swedish moose

In Paper III, we investigated the demographic history and genetic structure in Euro-

pean moose (Alces alces) in Sweden. The European moose likely survived the Pleis-

tocene glaciations in multiple refugia south or southeast of the Scandinavian ice

sheet and recolonised Fennoscandia around 8000-9000 years ago (Haanes et al.

2011; Kangas et al. 2013; Niedziałkowska et al. 2014). These historical events have

probably influenced the present genetic structure and diversity in Sweden. However,

the moose in Scandinavia have also been strongly affected by more recent anthropo-

genic factors such as hunting and changes in landscape use. In particular, the Swe-

dish moose population was severely reduced in the 19th

and early 20th

Centuries due

to excessive hunting. Although the population has recovered, approximately one

third (c. 100,000 animals) of the population is currently killed annually.

To assess to what extent present-day genetic patterns have been influenced by

glacial dynamics as well as more recent human hunting, including the historical

bottleneck, we examined genetic variation using allozymes and microsatellite mark-

ers in 20,000 and 1200 moose samples, respectively. To further examine genetic

patterns potentially caused by the postglacial recolonisation of Scandinavia, we also

sequenced the mitochondrial DNA control region in 48 moose samples. The auto-

somal markers demonstrated the existence of two major genetic groups, one in

northern and one in southern Scandinavia, which were separated by a narrow transi-

tion zone (Fig. 3). Similar divisions into northern and southern groups have previ-

ously been observed in Finnish and Norwegian moose (Haanes et al. 2011; Kangas

et al. 2013). Genetic divergence estimates in both autosomal and mitochondrial

markers were comparatively limited among the two populations, suggesting that the

populations diverged during the Holocene and consequently are unlikely to be the

result of postglacial recolonisation from two separate glacial refugia. The ABC

analyses indicated that both the northern and southern populations went through a

bottleneck. The inferred timing of this bottleneck was consistent with the known

bottleneck that took place from the 18th

to the 20th

Century.

At a finer geographic scale, we also found some evidence of additional substruc-

ture within the southern subpopulation. Moreover, spatial autocorrelation analyses

suggested comparatively small “genetic patch sizes”. Thus, it appears that limited

dispersal distances, estimated as only a few kilometers in our study, have led to a

pattern of isolation by distance within the subpopulations.

From a management perspective, the two genetically distinct subpopulations

identified in this study, need to be taken into account in order to ensure preservation

of potentially unique genetic variation in the respective subpopulations. However,

the estimated “genetic patch size” generally exceeds the size of current management

areas, indicating that overharvesting in separate management areas would be unlike-

ly to have any major genetic effects on the overall Swedish moose population.

15

Fig. 3

Color coded 3D surface plot of assignment probabilities to the northern (red) of the

two major clusters identified by the software STRUCTURE, using the 1207 moose

data set and 15 loci (12 microsatellites and 3 allozymes). The two major clusters and

the transition zone previously identified in Norway are shown in three shades of

grey (Haanes et al. 2011).

Paper IV

Recent demographic bottleneck in Eurasian otter from Sweden

Although European otters (Lutra lutra) used to be abundant across large parts of the

Palaearctic, their population sizes started to decrease severely in the 1950s’ through-

out most parts of Europe (Mason & Macdonald 1986). Polychlorinated biphenyls

(PCBs) have been identified as one of the major drivers for the population decline

(Mason 1993; Olsson & Sandegren 1991). However, even though several studies

have examined the present-day genetic variation in otters (Hobbs et al. 2011; Mucci

et al. 2010; Randi et al. 2003; Stanton et al. 2014), little is known about the genetic

consequences of the bottleneck that took place in the 1950’s. In our study, using

microsatellite data from historical as well as modern samples, we were able to test

whether this bottleneck led to any loss in genetic diversity and/or changes in genetic

structure. Comparisons of allelic richness at different points in time demonstrated a

significant loss in diversity in southern Sweden (Fig. 4). In contrast, we found no

evidence of declines in genetic diversity in northern Sweden.

Bayesian assignment of individual genotypes into genetic clusters indicated a

pronounced genetic structure in both the modern and pre-bottleneck samples. Inter-

estingly, historical and modern samples from northern Sweden were assigned to the

same clusters, indicating that allele frequencies have remained stable through the

last 60 years. However, historical and modern samples from southern Sweden were

16

assigned to different clusters, suggesting a marked change in allelic composition

likely due to genetic drift. These results suggested that the bottleneck was more

severe in southern compared to northern Sweden.

The results from ABC analyses further supported this pattern. A bottleneck sce-

nario was supported for both northern and southern Sweden, and the inferred effec-

tive population sizes (Ne) during the height of the bottleneck were similar (~100).

However, the posteriors for the post-bottleneck effective population sizes were high-

ly different, where otters in northern Sweden appear to have recovered more (56%

of the pre-bottleneck Ne) compared to in southern Sweden (17% of the pre-

bottleneck Ne).

Overall, the genetic results fit well with a previous study on environmental toxin

loads in otters, which demonstrated a higher concentration of PCBs in otters from

southern Sweden compared to northern Sweden (Roos et al. 2001). Conservation

efforts should take into account the observed pattern of genetic structure and careful

consideration is required for the southern population, which may be particularly

vulnerable.

Fig. 4

Rarefaction curves of allelic richness. (A) Estimates of allelic richness for subpopu-

lations in northern Sweden. (B) Estimates of allelic richness for subpopulations in

southern Sweden.

A B

17

Future directions

This thesis illustrates how genetic tools can be used to reconstruct demographic

histories. The studies encompassed a broad taxonomic diversity as well as a range of

different environments, and made use of several different genetic markers. Past

demographic changes were inferred both at long time scales to assess the conse-

quences of climate change at the end of the last ice age (Papers I & II), as well as

short time scales to examine the consequences of recent anthropogenic impacts

(Papers III & IV). However, it should be noted that the accuracy in the inferences

made in these studies sometimes are imprecise due to large confidence intervals in

the estimated parameters. Moreover, the use of a limited number of loci can lead to

incorrect inferences because gene trees do not always capture the true relationships

among populations. Thus, to reiterate a declaration that likely has been around since

the start of scientific time, more data is needed! Fortunately, recent technological

advances now make this possible, moving the challenge to the analysis of the data.

Recent developments in sequencing and computational technologies

Today, with the emergence of next-generation sequencing (NGS) technologies,

large-scale datasets and complete genomes have become more easily available. This

is revolutionizing the fields of molecular ecology, conservation biology and popula-

tion genetics (Ellegren 2014; Luikart et al. 2003). Thus, the field of population ge-

netics is moving towards population genomics (Andrews & Luikart 2014) and more

and more scientists talk about conservation genomics (Narum et al. 2013). Large

SNP datasets can, for example, be obtained using restriction site-associated DNA

sequencing (RAD-seq), and these may permit more complex demographic history to

be revealed (Emerson et al. 2010; Lemmon & Lemmon 2013; Puritz et al. 2014;

Reitzel et al. 2013).

However, to estimate complex demographic and historical effects on genetic var-

iation (e.g. effective population size, gene flow, divergence), computer simulations

are needed and these have started to play an increasingly important role (Hoban

2014; Hoban et al. 2011). Thus, genomics is to some extent dependent of develop-

ments in the bioinformatics field, where new simulators and programs with more

sophisticated features emerge rapidly (Yuan et al. 2012). For example, the ABC

framework, which is both powerful and flexible, has become especially popular to

estimate demographic histories and other types of population genetic inference

(Beaumont 2010; Beaumont et al. 2002; Bertorelle et al. 2010; Cornuet et al. 2014;

Csillery et al. 2010; Wegmann et al. 2010). Additional recent developments for

inference-based computational methods also include the simultaneous use of genetic

data from several taxa to understand the interplay between, for example, geography,

climate fluctuations and demographic change (Hickerson et al. 2007). These meth-

ods use a coalescent-based hierarchical ABC (hABC) framework. For example,

MTML-msBayes allow testing of simultaneous divergence and migration across

multiple co-distributed taxon-pairs (Huang et al. 2011). Another statistical develop-

18

ment based on hABC explores the demographic history of multiple taxa to detect

concerted demographic expansions at the community-level (Chan et al. 2014).

Moreover, new methods continue to be developed to infer historical changes in

effective population size. A recent major development uses the pairwise sequentially

Markovian coalescent model (PSMC), which is based on the assumption that local

densities of heterozygotes allow inference of the local time to the most recent com-

mon ancestor (Li et al. 2008; MacLeod et al. 2013). This method has the advantage

that it enables inference of species’ population size histories based on single diploid

genomes. This has for example been used to reconstruct the demographic history in

several marine mammal species (Moura et al. 2014; Yim et al. 2014; Zhou et al.

2013), and with the aid of ABCs analyses can also help to identity ancient admixture

(Miller et al. 2012) or to reconstruct divergence history (Nadachowska-Brzyska et

al. 2013).

NGS and adaptive genetic variation

In addition to enabling more accurate inference population histories, large-scale

genomic data can also be used to detect regions of the genome under natural selec-

tion, which in turn can be used to identify locally adapted traits among populations

(Nielsen et al. 2005). For example, selective sweep mapping can be performed to

detect purifying selection (Boitard et al. 2012; Foll & Gaggiotti 2008; Kim &

Stephan 2002; Messer & Petrov 2013). Most of these tests are based on the genetic

hitchhiking concept, where genome scans are employed to identify regions with

local reduction in genetic diversity where purifying selection has acted. Moreover by

integrating genomic and environmental datasets, potential ecological and environ-

mental drivers of selection can be revealed (Jones et al. 2013; Joost et al. 2007;

Schoville et al. 2012; Stapley et al. 2010).

Ancient DNA and museum collections

The recent development of the ancient DNA field can also provide new insights to

understand how the past has affected the present. For example, the use of serially

sampled ancient DNA data (Hadly et al. 2004) now permits demographic histories to

be investigated in real-time as changes occurred, thus facilitating interpretations of

the interaction between genetic and climatic changes (de Bruyn et al. 2011; Shapiro

et al. 2004). The development of ancient DNA tools also highlights the utility of

museum collections in genetic research. By allowing the comparison of historical

and present-day genetic diversities, museum collections provide the opportunity to

better understand the impacts of recent environmental change and human activities

(Bi et al. 2013; Moritz et al. 2008; Nachman 2013; Ramakrishnan et al. 2005;

Thomas et al. 1990; Wandeler et al. 2007). In Paper IV, we made use of this ap-

proach through sampling of both contemporary samples and museum specimens

from Eurasian otters in Sweden. This allowed us to compare levels of genetic diver-

sity and differentiation before, during and after a well-documented bottleneck.

19

Palaeogenomics

Coupled with the development of more advanced extraction and next-generation

sequencing methods, the ancient DNA field has now entered the age of the palaeo-

genomics, pushing the limits of the DNA recovery (Millar & Lambert 2013;

Orlando et al. 2013) and enabling new ways to calibrate molecular clocks as well as

examining selection (Campbell et al. 2010; Fu et al. 2014; Shapiro & Hofreiter

2014). Another method that has recently been developed takes advantage of tem-

poral sampling to investigate the footprint of genomic differentiation among samples

to provide information about the populations’ histories. Thus, genetic differentiation

between temporally spaced samples now make it possible to distinguish between (i)

constant population size evolution, (ii) bottleneck models and (iii) replacement mod-

els, something which was not possible without taking into account the temporal

sampling (Skoglund et al. 2014).

A new genetic era

To conclude, the fields of molecular ecology, population genetics and conservation

genetics are being revolutionized by the fact that next-generation sequencing is

resulting in a rapidly growing amount of data becoming available. More than ever,

evolutionary biology is becoming a multidisciplinary field where archeologists,

ecologists, geneticists, statisticians, and informaticians are collaborating. As a result,

we can continue to satisfy our curiosity to understand the environmental, ecological

and evolutionary processes that shape the genetic variation and biodiversity at dif-

ferent temporal and spatial scales.

20

Contributions

Paper I

VN performed the DNA extractions. VN and JLT conducted PCRs and genotyping.

JLT conducted all the data-analysis with input from ES on the ABCs analysis. LD,

KG and JLT wrote the manuscript.

Paper II

JLT performed all the laboratory work and analysed the data, with input from LD

and SP. JLT wrote the manuscript with input from all coauthors.

Paper III

JLT performed the laboratory as well as computational analyses on the mitochon-

drial DNA. LW analyzed the allozyme and microsatellite data, except for the coales-

cent-based ABC analyses that were done by JLT. LW wrote the paper, with input

from JLT and the other coauthors.

Paper IV

JLT collected and did the laboratory work on the museum otter samples. VB and

PG performed laboratory analyses on the modern samples, under the supervision of

JLT and EP. VB and JLT performed the computational analyses. VB wrote the

paper together with JLT and LD.

21

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31

Sammanfattning på svenska

Såväl långsiktiga miljöförändringar, till exempel de som drivs av istidscykler, som

mer nutida antropogent drivna förändringar har haft stor effekt på demografin hos

vilda organismer. Inom en art speglas dessa förändringar genom mängden och den

geografiska utbredningen av genetisk variation. I denna avhandling analyserades

mitokondriellt- och mikrosatellit-DNA för att undersöka hur miljöförändringar i

olika rums- och tidsskalor har påverkat genetisk variation och struktur hos fyra eko-

logiskt skilda djurarter.

Istidscyklerna anses ha spelat en stor roll i utvecklingen och fördelningen av ar-

ter. Artikel I undersöker den postglaciala rekoloniseringen av Kvickgräsfjärilen

(Pararge aegeria) i norra Europa. En minskning av genetisk diversitet i förhållande

till latitud och en tydlig populationsstruktur upptäcktes, vilket överensstämmer med

en hypotes om att den postglaciala koloniseringsprocessen innebar ett flertal lokala

flaskhalser (s.k. ”founder events”). Bayesianska beräkningsanalyser genom ”Ap-

proximate Bayesian Computation” (ABC) indikerade att de univoltina populationer-

na i Skandinavien och Finland härstammar från rekoloniseringar längs två vägar, en

på var sida om Östersjön.

Artikel II syftade till att undersöka hur tidigare höjning av havsnivån påverkat

populationen av Sebrastrimmig kirurgfisk (Acanthurus triostegus) i Indiska Oceanen

och Stilla Havet. Inferens av artens demografiska historia indikerade en populations-

expansion ungefär vid tiden för slutet på den senaste istiden. Därtill visade resultaten

en övergripande brist på fylogeografisk struktur, sannolikt på grund av den höga

spridnigsförmågan som artens pelagiska larvstadie innebär. Populationer i den

Sebrastrimmig kirurgfiskens östligaste utbredningsområde var signifikant differenti-

erade från andra populationer vilket sannolikt är en konsekvens av deras geografiska

isolering.

I Artikel III analyserades människans effekt på den genetiska variationen hos

den svenska älgstammen (Alces alces). Genetiska analyser påvisade en tydlig spatial

struktur med två genetiska kluster, en i norra och en i södra Sverige, som var åt-

skilda med en transitionszon. Därtill indikerade demografisk inferens med hjälp av

ABC-analys en recent flaskhals i populationsstorlek. Den uppskattade tidpunkten för

denna flaskhals stämde väl överens med en känd minskning i älgstammen som

skedde under 1800- och 1900-talen på grund av högt jakttryck.

I Artikel IV undersöktes effekten av en indirekt men välbeskriven mänsklig på-

verkan, den genom miljötoxiska kemikalier (PCB), på den genetiska variationen hos

eurasisk utter (Lutra lutra) i Sverige. Genetiska klusteranalyser påvisade en differen-

tiering mellan uttrar från olika delar av Sverige. ABC-analyser indikerade att en

minskning i populationsstorlek skett i både norra och södra Sverige. Jämförande

analyser av historiska och nutida prov påvisade en kraftigare minskning av genetisk

variation i södra jämfört med norra Sverige, vilket överensstämmer med de tidigare

nivåer av PCB som uppmätts i respektive område.

32

Résumé en français

Les changements environnementaux à long terme, tels que ceux induits par les

cycles glaciaires, et les impacts anthropiques plus récents ont eu des effets majeurs

sur la démographie passée des organismes sauvages. Au sein des espèces, ces chan-

gements se reflètent dans la quantité et la distribution de la variation génétique

neutre.

Dans cette thèse, l’ADN mitochondrial et des microsatellites ont été analysés

pour quatre espèces animales écologiquement différentes, afin de déterminer com-

ment des facteurs environnementaux et anthropiques ont affecté la diversité géné-

tique et la structure des populations, à différentes échelles spatiales et temporelles.

Les cycles glaciaires sont considérés comme ayant joué un rôle important dans

l'histoire et la distribution des espèces. L’article I décrit l'histoire de la recolonisa-

tion postglaciaire du papillon tircis (Pararge aegeria) en Europe du Nord. Une di-

minution de la diversité génétique corrélée avec la latitude ainsi qu’une forte structu-

ration des populations ont été révélées. Ceci est compatible avec une hypothèse

d'effets fondateurs répétés durant la recolonisation postglaciaire. En outre, les ana-

lyses d’inférences bayésiennes approximatives semblent indiquer que les popula-

tions univoltines (produisant une seule génération par an) en Scandinavie et en Fin-

lande proviennent de recolonisations le long de deux routes distinctes, une route de

chaque côté de la Baltique.

L’article II vise à étudier comment les variations du niveau des océans ont affec-

té l'histoire des populations du poisson chirurgien bagnard (Acanthurus triostegus)

dans l'Indo-Pacifique. L’évaluation de l'histoire démographique de l'espèce a suggé-

ré une expansion de la population qui a eu lieu autour de la fin de la dernière glacia-

tion. De plus, les résultats ont démontré un manque global de structure phylogéogra-

phique, probablement en raison de taux élevés de dispersion pélagique au stade

larvaire de l'espèce. Cependant, les populations à l’extrémité orientale de la zone de

distribution de l'espèce sont significativement génétiquement différenciées des

autres populations. Ceci est vraisemblablement une conséquence de leur isolement

géographique.

Dans l’article III, nous avons évalué l'effet de l'impact humain sur la variation

génétique des élans européen (Alces alces) en Suède. Les analyses génétiques ont

révélé une structure spatiale avec deux groupes génétiques: un dans le nord et un au

sud de la Suède, séparés par une étroite zone de transition. Par ailleurs, l'inférence

démographique suggère un goulot d'étranglement de population récent, coïncidant

avec une réduction de taille de la population connue au 19ème

siècle et au début du

20ème

siècle en raison d’une pression de chasse élevée.

Dans l’article IV, nous avons examiné l'effet d'un impact humain indirect mais

bien décrit, celui des produits chimiques toxiques environnementaux (PCBs), sur la

variation génétique des loutres eurasiennes (Lutra lutra) en Suède. Les analyses

d’affectation individuelle en groupement génétique ont révélé des populations dis-

tinctes de loutres dans le nord et le sud de la Suède, mais aussi dans la région de

33

Stockholm. Les analyses d’inférence bayésienne approximative ont indiqué une

diminution de la taille effective des populations à la fois dans le nord et le sud de la

Suède. De plus, des analyses comparatives d’échantillons historiques et contempo-

rains ont démontré une baisse plus sévère de la diversité génétique dans le sud de la

Suède par rapport au nord de la Suède, en accord avec les différents niveaux de

PCBs trouvés dans ces régions.