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Abstract
The cave lion (Panthera spelaea), the grey wolf (Canis lupus) and the brown bear (Ursus arctos) all
shared an intercontinental distribution across the northern hemisphere during most of the Late
Quaternary, and experienced repeated events of climate change. The cave lion went extinct at the end
of the Pleistocene and although the wolf and the bear have survived until present day, recent human
persecution has caused demographic bottlenecks and local extinctions. In this thesis, mitochondrial
and nuclear DNA was analyzed from ancient and modern samples in order to study spatiotemporal
changes in genetic diversity in the three species. Mitochondrial sequences analyzed from 48
radiocarbon dated cave lion remains revealed two haplogroups, of which the more genetically diverse
seemingly disappeared around 41,000 years BP. Serial coalescent simulations on the data supported a
population bottleneck in Beringia between roughly 47-18,000 years BP. Its long duration prevents a
specific causal factor to be singled out, but the early onset and overlapping declines of other large
mammals in the region suggests that major environmental changes greatly impacted the fauna of
Beringia during this time. Using a similar genetic marker, a set of 126 modern wolves and two
Siberian wolf remains of Late Pleistocene age were analyzed. The sequences yielded from the latter
samples pertained to a basal haplogroup, which contained all Late Pleistocene wolves from previous
studies. As data from both modern and ancient wolves were combined, a pattern of decreasing genetic
diversity was identified around the Pleistocene-Holocene transition. This decrease was further tested
by serial coalescent simulations, which supported a bottleneck in northern North America around this
time. Further analyses were applied to one of the ancient wolf remains from Siberia, producing a draft
genome sequence and a complete mitochondrial genome. Given the radiocarbon date of the Siberian
wolf, a slower mutation rate could be inferred, which pushed back the split between the lineages
leading to modern wolves and dogs to at least 27,000 years BP. The Siberian wolf was positioned
close to the split but basal to these lineages. A global comparison with modern dogs indicated a closer
genetic affiliation between the Siberian wolf and some arctic breeds. For the brown bear,
phylogeographic changes in Europe were studied over the last 50,000 years, using radiocarbon dating
and mitochondrial sequences. When concatenated and compared with published data, the mtDNA
revealed a turnover event just before the LGM, while the dating confirmed a presence of brown bears
at relatively high latitudes during this period. Marked shifts in population size were also inferred.
Furthermore, data of stable isotope levels confirmed a dietary shift to increasing herbivory around the
LGM. Finally, a recent anthropogenic bottleneck among Scandinavian brown bears was studied.
While no change in genetic structure could be detected, mitochondrial and microsatellite markers
showed a decline in genetic diversity, especially pronounced in the southern subpopulation. ABC
simulations supported a bottleneck taking place across all of Scandinavia. Taken together, this thesis
have identified and elucidated several impacts on genetic diversity in the past populations of large
carnivores. The use of different genetic markers has enabled comparisons with published data, but also
revealed their comparatively different benefits and limitations. Overall, the presented studies compose
a synthesis of past population dynamics in large carnivores, uniquely revealed by ancient DNA.
List of Papers
I.
Ersmark E., Orlando L., Sandoval-Castellanos E., Barnes I., Barnett R., Stuart A., Lister A.,
Dalén L. (2015) Population demography and genetic diversity in the Pleistocene cave lion.
Open Quaternary, 1: 4, 1-14.
II.
Ersmark, E., Klütsch, C., Chan, Y., Dalén, L., Sinding-Larsen, M., Gilbert, T., Arvestad, L.,
Fain, S. R., Illarionova, N., Oskarsson, M., Uhlén, M., Zhang, Y.-P., Savolainen, P. From the
past to the present: Wolf phylogeography and demographic history based on the
mitochondrial control region (manuscript).
III. Skoglund, P., Ersmark, E., Palkopoulou, E., Dalén, L. (2015) Ancient wolf genome reveals
an early divergence of domestic dog ancestors and admixture into high-latitude breeds.
Current Biology, 25, 1515-1519.
IV. Ersmark, E., Baryshnikov, G., Higham, T., Döppes, D., Germonpré, M., Lidén K., Lipecki
G., Marciszak A., Pacher, M., Stewart, J., Storå, J., Valdiosera, C., Villaluenga A., Dalén, L.
Genetic revolutions and northern survival during the last glacial maximum in European
brown bears (manuscript).
V.
Xenikoudakis, G. *, Ersmark, E. *, Tison, J. L., Waits, L., Kindberg, J., Swenson, J. E.,
Dalén, L. (2015) Consequences of a demographic bottleneck on genetic structure and
variation in the Scandinavian brown bear. Molecular Ecology, 24, 3441-3454.
* Authors contributed equally to this study.
I am also co-author on the following papers, which are not included in this thesis:
Cahill, J. A., Stirling, I., Kistler, L., Salamzade, R., Ersmark, E., Fulton, T. L., Stiller, M., Green R.
E., Shapiro, B. (2015) Genomic evidence of geographically widespread effect of gene flow from polar
bears into brown bears. Molecular Ecology, 24, 1205-1217.
Palkopoulou, E., Baca, M., Abramson, N. I., Sablin, M., Socha, P., Nadachowski, A., Prost, S.,
Germonpré, M., Kosintsev, P., Smirnov, N. G., Vartanyan, S., Ponomarev, D., Nyström, J., Nikolskiy,
P., Jass, C. N., Litvinov, Y. N., Kalthoff, D. C., Grigoriev, S., Fadeeva, T., Douka, A., Higham, T.
F.G., Ersmark, E., Pitulko, V., Pavlova, E., Stewart, J. R., Węgleński, P., Stankovic, A. and Dalén, L.
(2016) Synchronous genetic turnovers across Western Eurasia in Late Pleistocene collared lemmings.
Global Change Biology, in press.
Contents
Introduction………...………………………………………………………………………..... 1
Climate and chronology...…………………...…………………………………………… 1
Expansions and extinctions….…….……………………...………………………….….... 3
Large carnivores……………………………………………………………………….….... 4
Anthropogenic impact…....…..………...…………..……………………………….….… 6
Ancient DNA………........……………………………...………………………………… 8
Stable isotope analysis……….....……………………...……………………………..… 12
Data analyses………........……………………………..…………………………..…… 13
Study species……………...……………………………………………………………….… 14
The cave lion (Panthera spelaea)………………………………………………….…… 14
The grey wolf (Canis lupus)………………….………………………………….……… 15
The brown bear (Ursus arctos)…………………………………………………….…… 17
Research objectives……..………………………..……………………….………….……… 18
Summary of papers………...………………………………………………………...……… 18
Paper I…….……………………………………………………………….…………… 18
Paper II…………………………………………………………………………….…… 20
Paper III…….……..……………………………………………………….…………… 21
Paper IV……...…………………………………………………………………….…… 23
Paper V…....………………………………………………………………….………… 24
Concluding remarks………..…….…………………………………………………..……… 26
Svensk sammanfattning………………………………………………..………….………… 29
Acknowledgements……….…………………………………………………………………..30
Contributions……...…………………………………………………………………………..31
References…...………………………………………………………………………………..32
“The long summer was over. For ages a tropical climate had prevailed over a great part of the earth,
and animals whose home is now beneath the Equator roamed over the world from the far South to the
very borders of the Arctics ... But their reign was over. A sudden intense winter, that was also to last
for ages, fell upon our globe.”
— Louis Agassiz
Geological Sketches (1866)
Introduction
Climate and chronology
Change is a basis for evolution, and one of the most basic changes affecting the biosphere is that of the
climate. Until very recently, global climate has been characterized by a long period of relatively mild
and stable conditions that has spanned more or less the last 11,500 years, the entire Holocene era.
Looking at a wider timescale, this is however something of an exception. Further back in time, the
stable conditions were preceded by considerable variation, as well as long periods of dwindling
temperatures. This pattern goes back to the start of the Pleistocene around 2.6 million years ago
(Mya), which marked the onset of a relatively colder and drier climate globally (Lowe & Walker
2014). The cold periods, often described as glacials, were dominating from this point in time and only
interrupted by shorter interludes of warmer interglacials. The climatic shifts profoundly altered
landscapes across the globe, and many geological formations of today can be traced back to these
events, which included both continent-wide glaciations and inundations.
The cyclic but irregular pattern of glacials and interglacials has been possible to trace several million
years back in time, by studying levels of stable oxygen isotopes in marine sediments and glacial ice
cores (Shackleton & Opdyke 1973; Dansgaard et al. 1993). The sequential variation of the isotope
levels has been used as a proxy for changing global temperatures and has led to a chronologic division
of Marine Isotope Stages (MIS), with odd numbers for interglacials and even numbers for glacials.
Sediments from the Atlantic have also revealed layers of coarse gravel originating from terrestrial
glaciers, which have been deposited after major discharges of ice bergs into the sea. These so called
Heinrich events appear to have been quite infrequent but are thought to have triggered short periods of
intense cooling (Heinrich 1988).
The general cooling that took place during the glacials have in many ways been associated with
glaciers and ice. Accordingly, the last two glacials (MIS2 & MIS4), together with the intervening but
generally cold MIS3, are together often referred to as the last Ice Age. The association with ice derives
from the great ice sheets that expanded across many regions during this time. In Europe, they covered
large parts of Scandinavia and the British Isles, while northern North America held two bodies of ice,
growing in parallel and merging at the continental divide (Clark & Mix 2002). Around halfway
through MIS2, 25-18,000 years ago, the ice sheets reached their maximum extent, and this period has
accordingly been termed the Last Glacial Maximum (LGM).
Widespread glaciers that have survived until the present also contain records of oxygen isotopes,
which have offered a more detailed record of past climate change (Wolff et al. 2010). Ice cores from
Greenland, containing climate records with relatively high resolution, have thus been used to identify
shorter phases of cold and warm climate (Fig. 1), which have been termed Greenland Stadials (GS)
and Interstadials (GI) (Svensson et al. 2006). A multitude of synonymous terms exist for many of
these climate periods and phases, often differing between continents and geographic regions. One
example is the last Greenland Stadial (GS1), occurring just before the start of the Holocene, which is
often referred to as the Younger Dryas (Kennett 1990). Although it had a limited duration of just over
a millennium, this cold phase brought back glacial conditions similar to those prevailing during the
LGM along with re-expanding ice sheets.
Figure 1. Chronology of the Late Quaternary with climatic periods and events over the past 60,000 years. The
curve indicates levels of oxygen isotopes recorded in the NorthGRIP ice core from Greenland. Glacial
Interstadials (GI1-17) and Heinrich events (HE1-5) are indicated. The Last Glacial Maximum (LGM) and the
Younger Dryas (YD) are highlighted in blue (modified from Svensson et al. (2006)).
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The LGM, although representing a maximum extent of ice sheets, was only the last peak in a long
series of intense glacials, and ice sheets had lingered both at high latitudes and high altitudes
throughout much of the Pleistocene (Lowe & Walker 2014). The accumulation of water into the
massive glaciers contributed to a generally cool and dry climate with much lower sea levels than
today. Over time, these conditions paved the way for expansive steppes, constituting a biome often
referred to as “steppe tundra” or “mammoth steppe” (Guthrie 2001). The steppes stretched across the
entire Eurasian continent all the way from the Iberian Peninsula in the west to Siberia in the east. Here
they continued across Beringia, a northern landmass bridging Eurasia and North America in the Late
Pleistocene.
The mammoth steppe seems to have harbored a varied vegetation with no contemporary analogs
(Anderson et al. 1994; Zazula et al. 2003; Willerslev et al. 2014). It has often been described as a
mosaic of different vegetation types, which together formed a vast interconnected ecosystem that
allowed for a wide dispersal of many species. The fossil record has indeed shown that it contained a
high degree of faunal diversity, including mammoths, horses, woolly rhinos and a multitude of other
large mammals (Kurtén 1968). Several of these large-bodied animals, often described as megafauna,
seem to have been highly adapted for this environment and played important roles in maintaining its
ecosystem (Bocherens 2003; Zimov et al. 2012). In recent years, however, it has become increasingly
apparent that the composition of the fauna was far from static, likely due to that the fluctuating climate
repeatedly altered the environment (Hofreiter et al. 2007; Cooper et al. 2015; Palkopoulou et al.
2015).
Expansions and extinctions
The natural world of today is to a great extent shaped by the climatic upheavals that took place
throughout the Pleistocene, including our own species, which emerged from Africa during this time
period (Stewart & Stringer 2012). But at the same time as climate change brought opportunities for
some, it pushed others to the brink of extinction and beyond. The outcome was mainly decided by the
speed, duration and range of the changing environments, but also by the adaptability and ecological
requirements of the different species within them (Stewart et al. 2010).
Glacials and interglacials alternatingly favored cold- and warm-adapted species, allowing them to
expand their ranges across the continents. As the conditions shifted, this brought demographic changes
in form of range contractions or expansions, bottlenecks and extinctions (Hofreiter & Stewart 2009).
Many of these population dynamics have been traced in the fossil record, and with the application of
radiocarbon dating it has been possible to obtain a more detailed chronology of these events (Stuart et
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al. 2004a; Pacher & Stuart 2009). The fossil remains have also served as evidence of the animals that
went extinct; mammoths, saber-toothed cats, woolly rhinos and Neanderthals to name a few. The final
decline of many of these species of megafauna seem to have coincided and this is most apparently
observed at the very end of the Pleistocene around 14,000 years before present (BP) (Stuart 1999). The
cause behind this seemingly synchronized event is still a matter of debate, mainly whether it was
mediated by humans, climate change or the two in combination (Koch & Barnosky 2006). Other
causal factors have also have been put to the table, including hyper-disease or an extraterrestrial
impact (MacPhee 1997; Firestone et al. 2007).
Even though the end-Pleistocene extinctions are conspicuous, not all megafauna died out
synchronously. Many species disappeared long before the end of the Pleistocene (Stiller et al. 2010),
while others survived in scattered and isolated populations into the Holocene (Vartanyan et al. 1993;
Stuart et al. 2004b). The nature of these final disappearances and their causes have been the subject of
numerous studies and there have been attempts to find common denominators behind them, often
related to climate (Cooper et al. 2015). In some cases, the final disappearance seems to have coincided
with human expansions (Martin & Steadman 1999). However, the arrival of modern humans has been
difficult to pinpoint for many regions, as well as estimating their numbers and impact on the
environment.
As many of the large mammals went extinct, this profoundly changed the ecosystems of which they
had been a part, including conditions for the species that survived (Hofreiter 2007). The survivors too
were directly affected by the climate fluctuations during the Pleistocene, and many species’ current
distribution was largely shaped by the most recent shift to warmer conditions after the last glacial.
Some of the cold-adapted species were able to track a shrinking habitat (Lagerholm et al. in prep.),
while others went locally extinct (Dalén et al. 2007; Campos et al. 2010). Although general models
have been proposed for the processes behind the distribution and diversity of modern populations
(Hewitt 1996), these have also been opposed by more complex and species-specific scenarios (Stewart
2009).
Large carnivores
Large carnivores play a key role in the ecosystems they inhabit, dictating conditions for entire
communities of other species (Flueck 2000; Ripple et al. 2014). This is primarily achieved through
predation, creating trophic cascades from the top-down within the food web (Berger et al. 2001;
Terborgh et al. 2001). More indirectly, the very presence of large carnivores can affect the behavior of
prey and smaller predators (Ripple & Beschta 2004; Prugh et al. 2009; Pasanen-Mortensen et al.
4
2013). Trophic cascades are also going the reverse way, bottom-up: As top predators these animals are
highly dependent on the availability of prey and as a consequence, they are ultimately affected by
changes at lower trophic levels or by species competing over these resources. Their large size further
implies a general requirement for both large prey and large continuous habitats (Carbone et al. 1999;
Sinclair et al. 2003). Together with low reproductive rates, this fact makes them vulnerable to the
restrictions of resources, and this is especially true for more specialized species (Rode et al. 2015).
Figure 2. Cave lions depicted in Chauvet cave, France, dated to roughly 30,000 years
ago (museum replica). By HTO [Public domain], via Wikimedia Commons.
Current distributions of large carnivores have been greatly reduced, and in terms of species, most
ecosystems today are impoverished to a large extent (Hofreiter & Barnes 2010). This is in stark
contrast to the Late Pleistocene, when many now extinct carnivores were still around. The carnivore
guilds present during this time period were not only more diverse, but also included larger and more
specialized species. One example is the sabretooth cats (Smilodon sp. & Homotherium sp.), which
seems to have been highly adapted for killing large prey (Antón 2013). Other examples include the
dire wolf (Canis dirus) and the short faced bear (Arctodus simus) of North America, both representing
the largest contemporary members of their families. The generally larger size and more robust
morphology of many Pleistocene carnivores can be seen as an adaptation for preying and scavenging
5
on megaherbivores, which were likely not exempt from predation to the extent that they are today
(Van Valkenburgh et al. 2015). The high abundance of different large carnivores also meant more
intense competition over carcasses and more thorough consumption of these, which have been implied
by a high frequency of dental fractures in carnivore remains from the Late Pleistocene (Van
Valkenburgh & Hertel 1993). Even the fossil record of extant carnivores show trends of increased
robustness going back in time from the Holocene (Leonard et al. 2007; Marciszak et al. 2015), which
might be considered as adaptations to ecological niches that no longer exist.
Anthropogenic impact
To us humans, large carnivores hold a special status, since we among them have identified both our
closest companions and most feared adversaries. Hunters have revered them, but also competed with
them for prey, and though our view of these animals has changed over time, it has rarely been one of
indifference. Cave art and anthropomorphic representations of carnivores from pre-history have
indicated their importance in early human cultures (Fig. 2) (Chauvet et al. 1996; Dalton 2003). In
many indigenous cultures, cults and rituals surrounding carnivores have prevailed, exemplified by the
different kinds of bear worship observed across the Holarctic (Hallowell 1926; Pentikäinen & Tolley
2007). However, when negative attitudes have gained influence, this has led to devastating effects:
Human encroachment and outright persecution have severely reduced the populations of large
carnivores world-wide, especially over the last centuries (Hunter 2011). Conflicts have often emerged
in regions where natural prey species have declined along with the introduction of domestic livestock
(Treves & Karanth 2003; Ray et al. 2005). This pattern goes far back in time and seems intimately
linked to the spread of agro-pastoralism and increasing human populations (Goudie 2013). In Eurasia,
this process most likely started already with the Neolithic revolution in the Holocene. As farmland
spread across the continents, large carnivores were forced to track the retreating forests and were
confined to less fertile areas with lower human densities. In time, they became intimately associated
with the wilderness and were even regarded as a threat to human society, civilization and religion
(Pentikäinen & Tolley 2007; Pastoureau & Holoch 2011). Similar associations were made in North
America by European settlers, especially farmers and livestock producers, who actively pursued large
carnivores on their lands (Kellert et al. 1996). In Sweden, the trapping of large carnivores was
encouraged already in legal texts from the Middle Ages (Jansson 1985). Later eradication campaigns
were sponsored both by states and local governments, encouraging hunters and offering bounties for
killed animals (Matthiessen 1987; Pohja-Mykrä et al. 2005). The eradication efforts in Europe
impacted all carnivore populations, with the most dramatic decreases and range contractions taking
place in the early 20th century (e.g. Fig. 3). The effects were most notable in the northern and western
parts of Europe, where wolves for instance were practically exterminated (Mech & Boitani 2010).
6
Human impact has not exclusively consisted of hunting and persecution. Events of domestication and
translocation have also affected large carnivores and their distribution. The best example being the
domestication of wolves, which has not only sparked a wide array of dog breeds, but also mediated a
spread of domestic dogs all across the globe. In a few cases, like the Australian dingo and the New
Guinea singing dog, domestication was followed by translocations and return to a feral state (Corbett
1995). Beside wolves, few carnivores have submitted to domestication. Bears have for instance never
been fully domesticated, but seem to have been occasionally tamed already in Mesolithic times (Chaix
et al. 1997). There are also early records of keeping bears in enclosures (O’Regan 2002), and they
were frequently used in Roman spectacles along with other wild animals (Kyle 2014). Translocations
for this kind of entertainment have been hypothesized as the reason why brown bear remains from
North Africa yielded a genotype that had previously only been found in Spain (Calvignac & Hughes
2008). The same purpose was probably behind a translocation of bears to Corsica in the 15th Century,
where a population survived for around 200 years (Vigne 1988). Being prized game animals, bears
have also been translocated for hunting, for instance to Bulgaria in the 1970’s and 80’s (Nowak et al.
2014).
Figure 3. Reported numbers of hunter-killed brown bears in Sweden during
the late 19th Century (Lönnberg 1929).
As game animals, large carnivores have in some instances paradoxically been saved from extinction
by hunters. One example is the legal protection of brown bears in Sweden, which was established on
the initiative from hunters in the early 20th Century (Lönnberg 1935; Swenson et al. 1995). Starting
around this time, attitudes toward wildlife in general were starting to change, inspiring efforts to
7
preserve natural environments (Ladle & Whittaker 2011). Although national parks and nature reserves
were created as a result in many countries, large carnivores were mostly exempt from protection until
the second half of the 20th Century. Reduced hunting and increasing urbanization did have positive
effects in many regions, allowing the recovery of some populations. The recovery was also promoted
by increased knowledge and appreciation of the ecological functions of large carnivores. However,
negative attitudes are still common and controversies have frequently arisen between different interest
groups regarding issues like livestock predation, hunting quotas and re-introductions (Dickman et al.
2013; Chapron et al. 2014).
Ancient DNA
The field of ancient DNA (aDNA) arose a mere three decades ago and studies were first applied to
samples of historical age (Higuchi et al. 1984; Pääbo 1985; Hänni et al. 1990). From the very start the
focus was on retrieval and comparison of short DNA sequences from the mitochondria, the energy
generating organelles within the cell. Amplification of these genetic markers was considerably
facilitated by the introduction of the Polymerase Chain Reaction (PCR) method, which together with
Sanger sequencing formed the foundation for production of aDNA data for a long time. These
techniques opened up for the analysis of even older remains, but were unfortunately also susceptible to
contamination, a fact that hampered the reliability of the results from many early studies. To counter
these effects, new and higher standards of sterility were introduced as well as more rigorous testing to
authenticate aDNA results (Cooper & Poinar 2000).
In spite of some early mistrust against aDNA, its application to genetic studies has revolutionized our
insights into the past. By retrieving and analyzing old genetic material, the past diversity within
species and populations has become increasingly better understood. While modern DNA has been
successfully used to describe current diversity and relationships between extant populations, it has
proven limited when inferring estimates of past demographic events and population histories
(Hofreiter et al. 2004; Valdiosera et al. 2008). For this purpose, the introduction of ancient DNA has
provided invaluable sources of information. Not only has it given access to genetic data from remains
of considerable antiquity, but it has also elucidated links between now living species and those long
extinct. In combination with radiocarbon dating it has enabled more detailed estimates to be made of
past population dynamics both in terms of magnitude and timing. Moreover, by connecting genetic
diversity to specific points in time, it has become possible to make more accurate estimates of
mutation rates, which has been of great importance for establishing divergence times between lineages
(Drummond et al. 2003).
8
By adding a spatial dimension to comparisons of genetic diversity, questions of phylogeography have
also been possible to address. The term was coined in the late 1980’s and signifies the geographical
distribution of genetic lineages or species (Avise et al. 1987; Avise 2000). Phylogeographic studies on
modern samples have been hugely popular and covered a wide range of organisms. But the use of
modern material has failed to describe past diversity and resolve historical processes that have led up
to current phylogeographic patterns. However, these limitations have been overcome by targeting
aDNA, which successfully has been used to track population dynamics, extinctions and recolonizations as far back as the Late Pleistocene (Leonard et al. 2000; Shapiro et al. 2004; Thalmann
et al. 2013; Horn et al. 2014). Together with data from other disciplines like archaeology,
paleoclimatology and geology, aDNA has consequently facilitated connections to be made with
possible causal factors behind past shifts in genetic diversity; anthropogenic, climate-induced or
others.
Being far more abundant and accessible from ancient remains, mitochondrial DNA (mtDNA) has been
used in a majority of past aDNA studies (Hofreiter et al. 2001b). Its relatively high mutation rate,
together with its non-recombining mode of inheritance has also made this genetic marker ideally
suited for estimating intraspecific diversity. However, the data retrieved from mitochondrial sequences
is limited by only providing the evolutionary history of a single, maternally inherited locus. Given the
uniparental inheritance, mtDNA consequently only describes female lineages, which might complicate
extrapolations to be made for entire populations (Waits et al. 2000).
Since aDNA is available only in small amounts and inherently fragmented, usually to below 100 base
pairs (bp) in length (Sawyer et al. 2012), a continuing difficulty has been to amplify longer sequences
and thereby achieve greater genetic coverage from a sample. Most often, this has been resolved by
amplifying several smaller, sometimes overlapping sequences. Although a straightforward approach, it
can imply tedious, costly and time consuming lab work, requiring several re-amplifications in order to
obtain reliable consensus sequences. Another way to achieve high genetic resolution that can facilitate
comparisons within species and populations has been to target the most variable regions of mtDNA.
One example, frequently used for studying intra-specific evolutionary relationships is the
hypervariable control region, assumed to be made up of non-coding DNA with a relatively high
mutation rate (Moritz et al. 1987). Despite these efforts, amplified sequences can provide varying
resolution, which sometimes is not high enough for unambiguous comparisons to be made. For short
sequences, the effect of identical mutations arising in different lineages, so called homoplasies, can
also cause misinterpretations of population histories. In general, increasing sequence length thus
provides better resolution and more well-supported phylogenies (Fig. 4).
9
Figure 4. The effect of sequence length on phylogenetic resolution, exemplified by medianjoining network analyses based on mtDNA from brown bears (modified from (Keis et al.
2013)).
Many of these difficulties have been overcome with the advent of so called next generation
sequencing (NGS) methods. Instead of targeting specific DNA fragments and priming sites, these
methods, which allow millions of sequences to be analyzed simultaneously, incorporate all the genetic
material from an extracted sample (Margulies et al. 2005). According to this principle, all DNA is
prepared with specific oligonucleotides, which are attached as adapters to produce sequencing libraries
(Meyer & Kircher 2010). Since especially short fragments can be sequenced with this approach, it has
proven highly suitable for aDNA. It has also made it possible to sequence the much scarcer and more
fragmented nuclear DNA from ancient remains, which has resulted in compilations not only of
complete mitochondrial but also nuclear genomes (Green et al. 2010; Miller et al. 2012a; Thalmann et
al. 2013; Palkopoulou et al. 2015).
Compared to the mitochondrial genome, data from the nuclear genome can provide significantly more
information, not only as a result of its vastly larger size. Since nuclear DNA is inherited from both
parental lineages and recombined in the offspring, a wider array of genetic analyses can be performed
on this material, also revealing more complex processes like selection and admixture. However, given
that sequences from the nuclear genome only exist in two copies per cell, establishing the correct
genotypes can be challenging and is highly dependent on the available amounts of well-preserved
endogenous DNA. Analyses are also constrained by available data from modern genomes, either from
the same or closely related species, which can be used as a reference. The use of reference genomes
hold many advantages and can facilitate comparisons, even with genomic sequences of low quality,
10
but may introduce biases depending on their taxonomic distance to the study species (Prüfer et al.
2010).
The amount of intact DNA available from organic remains is highly dependent on their preservation,
and this puts a limit to which sub-fossil material that is suitable for analysis. As a result, obtained data
is often suffering from low DNA coverage and uneven sampling. Extremely good preservation, like
that found in permafrost or deep caves, along with improved technology have recently contributed to
the retrieval of both nuclear and mitochondrial DNA several hundred thousand years old (Meyer et al.
2013; Orlando et al. 2013). However, most remains still yield DNA in low quantities and the ones that
do, commonly fall within a timescale of tens of millennia. A similar time frame applies to radiocarbon
dating, since the signal from radioactive carbon isotopes is entirely depleted after ca. 60,000 years
(Libbey 1952).
The preservation of DNA shows a clear negative correlation with higher temperatures and as a
consequence there is a latitudinal gradient of DNA survival with more favorable conditions at higher
latitudes (Hofreiter et al. 2015). This effectively makes the retrieval of aDNA from material collected
at lower latitudes and in continents like Africa, Australia and South America more difficult. The
geographical delimitation not only excludes a vast number of species to be studied, but also excludes
large parts of the current or past range of species with wide distributions.
Even under favorable conditions, animal remains and their DNA molecules degrade over time. The
most apparent result is a continuing fragmentation of the DNA strands. This process is very much
depending on the surrounding environment and its physical, chemical and microbial composition.
These factors, together with the composition of the remains themselves, decide the rate of
fragmentation, which has proven to be twice as fast for nuclear DNA compared to mtDNA (Allentoft
et al. 2012). Degradation might also involve chemical alterations of the DNA molecules. The most
common being cytosine (C) deamination, which produces uracil (U) and leads to misincorporations of
nucleotides (C to T & G to A) during amplification (Hofreiter et al. 2001a). These nucleotide
replacements may give rise to erroneous sequences and overestimated diversity (Axelsson et al. 2008).
One way to overcome misincorporations and ensuing errors is to consistently make independent reamplifications. Another way is to treat the DNA-extract with uracil-repairing enzymes, which helps to
minimize the effects of this chemical damage (Briggs et al. 2007).
Low copy numbers after amplification, which can result from the often limited amounts of aDNA
cause yet other problems; misreads and stochastic effects in the PCR that complicate interpretation of
the data. Microsatellites are specifically affected by these uncertainties much due to their repetitive
and variable structure, and can consequently produce erroneous genotypes as one or both alleles at a
11
locus are not amplified. This failure to detect alleles, referred to as allelic dropout, often gives an
excess of estimated homozygotes, a problem which can only be avoided by confirming reamplifications.
Along with degradation, ancient remains are also susceptible to contamination of exogenous DNA,
and if the contaminating DNA originates from younger or modern material, there is a high risk of it
outweighing or obscuring the endogenous DNA within in a sample. This has to be taken into
consideration when selecting remains for aDNA analyses, and necessitates careful pre-treatment and
cleaning of the material prior to extraction. Another precaution for avoiding contamination is the use
of laboratories with sterile environments specifically designed for processing aDNA. Low yields of
endogenous DNA from ancient material has also led to evaluations of DNA content in different
skeletal remains (Adler et al. 2011). The results have generally favored more compact material, which
have been shown to provide better yields of DNA as well as protection from exogenous contaminants
(Pinhasi et al. 2015).
The nuclear DNA recovered from ancient remains can be studied in a number of ways, most of which
are not relying on complete genomes. A number of more restricted markers have commonly been used
to identify polymorphic loci and compare these between populations and individuals. The most basic
are Single Nucleotide Polymorphisms (SNPs), which constitute variants of single base pairs at specific
positions. SNPs are versatile and can be chosen from across the genome, but do only represent a
restricted and a pre-defined range of diversity. Other markers that have been extensively used for
studies in population genetics are microsatellites, which consist of sequences of short tandem repeats.
These sequences are found throughout the genome and are hotspots for mutations that occur during
replication, thus containing great variation within populations (Ellegren 2004). One of the most recent
methods developed for selective targeting of DNA, is the use of RNA-baits that can capture selected
fragments during a hybridization process, a method which can be applied both to genomic and
mitochondrial sequences (Burbano et al. 2010; Carpenter et al. 2013; Enk et al. 2014).
Stable isotope analysis
In addition to preserved DNA molecules and data from radiocarbon isotopes (14C), stable isotopes of
different accumulated elements can also be used in the study of ancient remains. Levels of stable
isotopes create a signature in tissues that can provide estimates of several factors of an animal’s
environment and ecology. Two of the most commonly used isotopes are
13
C and
15
N, which have
principally been used to characterize average diet. Estimates of diet composition may further indicate
relations between carnivores and their prey as well as resource partitioning among both carnivores and
12
herbivores (Darimont et al. 2007). The results from this type of studies are often presented in bivariate
graphs, usually showing ratios of δ13C and δ15N, where individuals appear as points. This spatial
definition within two isotope gradients can be described in terms of ecological niches – the so called
“isotopic niche space” (Newsome et al. 2007). By measuring isotopic ratios of the same tissue from
several species within a particular habitat, it is possible to characterize the isotopic (and subsequently
ecologic) niche held by these animals, especially considering their diet and trophic level (Bearhop et
al. 2004). The use of isotopic niche space can further unravel patterns below the species level, for
instance detecting specialization between and within populations (Bolnick et al. 2002; Major et al.
2007; Vander Zanden et al. 2010).
As with aDNA, the properties of the paleontological remains, like contamination and degree of
preservation, often restrict analyses of stable isotopes. Additional factors must also be taken into
account, most fundamentally being variation in isotope abundance between different environments,
which can be influenced by factors like altitude, temperature, precipitation or bedrock type (Bowen
2010). Consequently, geographical regions may differ in terms of isotope signatures, with their own
distinct composition, which also varies through time (West et al. 2010).
Data analyses
A great number of different tools are available for analyzing genetic and genomic data, from relatively
simple statistical measurements of genetic diversification to simulations of complex population
scenarios. To establish phylogenetic relationships and identifying phylogeographic patterns, the most
common approach has been to construct phylogenetic trees and networks. In aDNA studies, these have
traditionally been based on short mtDNA sequences (Leonard et al. 2000; Barnes et al. 2002), which
was also the case for most of the studies presented in this thesis. Since a majority of the samples had
directly inferred ages from radiocarbon dating, this also provided reliable connections between genetic
diversity and time, which could subsequently be applied in the analyses for estimating mutation rates.
This approach thus enables an internal calibration of the molecular clock, which otherwise has to be
estimated from divergence times based on the paleontological record (Drummond et al. 2002). The
latter method evidently presents a high degree of uncertainty and the two methods have shown
considerable disparity, with the former producing comparatively elevated rates. The observed timedependency in rates estimated using internal calibration has been well established (Ho et al. 2011),
with a number of underlying factors proposed (Penny 2005; Debruyne & Poinar 2009).
A fundament for establishing evolutionary relationships based on genetic diversity is the coalescent
theory (Hudson 1990), which describes population histories backwards in time. It follows DNA
13
sequences back to common coalescing points, which represent their most recent common ancestor.
The process can accommodate several factors affecting a population, including changes in size and
mutation rate. In software simulating the coalescent processes, different settings/priors can thus be
applied for testing a variety of population models, which will subsequently be scored according to the
fit of the output to that of the observed genetic data. The phylogenetic software BEAST (Drummond
et al. 2005), applied in all five studies, contains options for both reconstructing phylogenies and
estimating change in effective population size (Ne) over time. Along with input of genetic sequence
data, a number of coalescent priors can readily be defined and adjusted for the specific population
under study. For estimating population size changes, a set of skyline plot methods are also available,
which combine data on lineage coalescent with defined time points to create graphs of effective
population size through time (Strimmer & Pybus 2001). These function has been continuously updated
with increasingly versatile methods (Minin et al. 2008; Drummond et al. 2012; Gill et al. 2013).
In order to test different population scenarios, including splits, bottlenecks and more elaborate models,
coalescent simulations can be performed using Approximate Bayesian Computation (ABC) methods
(Beaumont 2010). Output from the simulations in the form of summary statistics is compared to those
from the observed data, producing estimates of posterior probabilities. Models are accordingly
dismissed or graded according to likelihood with different support values. The addition of temporal
data and estimated mutation rates have enabled more reliable and detailed models to be constructed,
and several software including this and other flexible functions have proven suitable for aDNA data
(Bayesian Serial SimCoal (Excoffier et al. 2000; Anderson et al. 2005), BaySICS (SandovalCastellanos et al. 2014) and DIYABC (Cornuet et al. 2008)).
Simulations and model fitting can be used for most genetic and genomic markers. However, when
applied to ta wider genomic scale, this approach becomes computationally intensive and less
straightforward. A simpler option consists of testing and comparing shared derived alleles between
four taxa, where an excess of shared alleles between two taxa indicates gene-flow. This can be
detected using D statistics, which is an approach that has been extensively used for genome-wide
comparisons of aDNA data (Green et al. 2010; Cahill et al. 2013).
Study species
The cave lion (Panthera spelaea)
Fossil remains of a lion-like cat found in Tanzania points to an African origin of lions in the late
Pliocene (5-1.8 Mya) (Turner & Antón 1997; Werdelin & Lewis 2005; Barnett et al. 2006). In Europe,
14
the earliest presence of lions dates from around 700 thousand years (kyr) BP, and represents a large
form commonly named Panthera fossilis or P. leo fossilis (Turner & Antón 1997), which constitutes
the most probable ancestor of the cave lion. In the Late Pleistocene, the cave lion’s range stretched all
across northern Eurasia, and even into North America. Here a separate population was isolated south
of the glacial ice sheets, and is referred to as the American lion (Panthera atrox) (Turner & Antón
1997; Sotnikova & Nikolskiy 2006).
The cave lion was one of the top predators among the Pleistocene megafauna. Based on its dental
characteristics, it has been described as a hypercarnivore (Wroe & Milne 2007) and stable isotope
studies have revealed that prey specialization was common (Bocherens et al. 2011). Although
decisively larger, it seems in many ways to have been a northern counterpart to its now living relative,
the modern lion (Panthera leo) (Yamaguchi et al. 2004; Christiansen 2008). Even though little is
known about its appearance and social life, some features have been revealed from Paleolithic art and
through skeletal remains (Guthrie 2005; Mazák 2010) . The most well-preserved remains have also
provided genetic material, which has confirmed their close relatedness to modern African and Asiatic
lions (Burger et al. 2004; Barnett et al. 2009). These studies, based on mitochondrial DNA, have
estimated a divergence between the cave lion and the modern lion going back ca 600 kya. However, in
terms of classification there is yet no consensus and the cave lion has either been described as a
separate species or as a subspecies (Panthera leo spelaea).
During the Pleistocene, a contact zone with modern lions existed in the Near East, but so far no signs
of genetic interchange have been discovered. Modern lions did later expand their distribution in this
region, into Anatolia and the Balkans in the early Holocene. Their presence here was even testified to
well into historical times by Greek writers like Herodotus and Aristotle (Bartosiewicz 2009). By that
time cave lions had vacated all of their former range. Along with so many other large mammals, they
went extinct at the end of the Pleistocene, around 14 kyr ago. The latest radiocarbon dated remains has
been found in Alaska, and suggests eastern Beringia as their last refuge (Stuart & Lister 2011).
The grey wolf (Canis lupus)
Wolves are iconic carnivores and the largest extant members of the canid family. Although highly
social and pack living, their reproduction within a pack is typically restricted to a dominant pair (Fox
1971). Wolves share a common ancestor with coyotes (Canis latrans), and the split between the two
species has been estimated to between 4.5 and 1.8 Mya (Nowak 2003). In the early Pleistocene,
wolves seem to have shared a common radiation with several related canids across Eurasia (Azzaroli
1983), resulting in a vast geographical distribution, which can still be observed today. The species is
15
currently spread across most of the northern hemisphere, exhibiting great variation in both size and
coat color (Wang et al. 2010), a variability which has given rise to the description of a great number of
subspecies. In contrast, their genetic structure seems to rarely conform to the proposed subspecies
divisions (Vila et al. 1999). The geographical proliferation still seems to have been accompanied by
adaptations to a wide range of environments and prey. With the use of various genetic markers, recent
studies have identified populations structured according to specific habitats (Carmichael et al. 2001;
Geffen et al. 2004), suggesting that genetic structure in wolves can arise through “isolation by
environment” (Leonard 2014; Wang & Bradburd 2014). Analyses of functional genes have further
supported this suggestion, which have been most clearly demonstrated in arctic environments
(Schweizer et al. 2015).
When mtDNA diversity alone has been studied in wolves, it has revealed little geographic structure on
a global scale (Vila et al. 1999). However, the addition of aDNA has shown a discontinuous history of
mtDNA lineages, with a distinction of two major haplogroups, one containing all samples from the
Late Pleistocene along with a small subset of modern Eurasian wolves (Leonard et al. 2007; Pilot et
al. 2010). In North America, modern wolves are conversely affiliated to the other group, together with
a majority of current populations. Interestingly, the genetic turnover in American wolves seems to
have been accompanied also by a change in phenotype, from a robust to a more gracile form (Leonard
et al. 2007).
At some point during the Late Pleistocene wolves came into contact with modern humans, and were
incorporated into their societies as the domestic dog (Canis l. familiaris). The evolutionary
relationship between wild wolf populations and different dog breeds has been the topic of several
genetic studies, often with a focus on trying to identify the location and timing of domestication (Vilà
et al. 1997; Savolainen et al. 2002; Germonpré et al. 2009; Larson et al. 2012; Thalmann et al. 2013;
Freedman et al. 2014). The results have been contradictory, with a great variation both in estimations
of time and space for such events. Some have pointed to a temporal origin of dogs around 16-11 kya
(Axelsson et al. 2013; Larson et al. 2014), while others have favored an interval up to ca. 30 kya
(Thalmann et al. 2013; Wang et al. 2013). A complicating factor to the relationship between wolves
and dogs has been the frequent hybridizations between the two, both in the wild as well as mediated
by humans (Muñoz-Fuentes et al. 2010; Godinho et al. 2011). For wolves, hybridization has been
confirmed not only with dogs, but also with coyotes (Fain et al. 2010), and several populations have
been strongly influenced by this kind of gene-flow. One example is the Eastern/Great Lakes wolf in
North America, which shows signs of both ancient and recent admixture with coyotes (Koblmüller et
al. 2009).
16
The brown bear (Ursus arctos)
The brown bear is a member of the order Carnivora, sharing a common descent with other mammalian
carnivores. In dietary terms, however, it is far from a distinct carnivore and better described as a
generalist, exploiting a wide range of nutritional sources, from grass and berries to moose calves,
salmon and carcasses (Mattson et al. 1991; Mowat & Heard 2006). The brown bear is probably the
least specialized ursid, also when it comes to choice of habitat, and has the widest distribution among
all living bear species. Its distribution was even wider in the past and has gradually been reduced as a
consequence of human expansion and hunting (Servheen et al. 1990). Some isolated populations have
gone completely extinct in historical times, like those on the British Isles and in North Africa
(Hamdine et al. 1998; O’Connor & Sykes 2010).
In the Late Pleistocene, the range of the brown bear overlapped with that of the cave bear (Ursus
spelaeus) in Europe and western Eurasia. As the name suggests, the cave bear seems to have been
more dependent on caves for winter hibernation, and many cave sites have yielded overwhelming
amounts of its remains (Rabeder et al. 2000). Paleontological studies have placed the divergence
between these two bear species at around one million years ago (García 2004; Madurell-Malapeira et
al. 2009), and while some genetic studies have supported similar estimates (Loreille et al. 2001;
Korsten et al. 2009), others have favored a split already at about three million years ago (Krause et al.
2008). The most recent split however, is that between the brown bear and the polar bear (Ursus
maritimus). The timing of this split has been contentious and was initially estimated to a mere 150 kyr
ago, based on mitochondrial DNA (Lindqvist et al. 2010). However, the mitochondrial DNA of polar
bears has proven to fall within the diversity of brown bears and introgression of both mitochondrial
and genomic DNA from polar bears have been detected in modern and ancient brown bear populations
(Edwards et al. 2011; Cahill et al. 2013, 2015). More comprehensive genomic studies have recently
established the monophyletic division between the two species (Hailer et al. 2012; Miller et al.
2012b), as well as provided a divergence time of around 400 kyr BP (Liu et al. 2014).
The phylogeography of brown bears has been well studied for several regions, often showing strong
geographical structure in mtDNA variation (Taberlet & Bouvet 1994; Miller et al. 2006; Hirata et al.
2013). One explanation for this is the moderate dispersal exhibited by female brown bears (McLellan
& Hovey 2001; Stoen et al. 2006). As a consequence, mitochondrial haplotypes often display a
marked geographical structure/clustering, since only females propagate the mitochondrial lineages.
Given its relatively stable phylogeography, the brown bear has also been used as a model species for
genetic studies on more long term changes and the colonization of new territories. The first population
17
level study on brown bears using ancient DNA was based on ancient remains from North America
(Leonard et al. 2000). The results revealed a decreasing diversity over time and no structure among the
oldest samples. A similar lack of structure has been proposed for brown bears in Europe during the
Late Pleistocene (Hofreiter et al. 2004). In contrast, the current pattern seen in Europe is highly
structured; two clades (clades 1 & 3) are clearly separated between the south-west and the north-east.
The western clade has been further divided between a western (1a) and an eastern (1b) subclade,
which are thought to represent two separate populations that survived the LGM in different glacial
refugia; the Iberian and the Italian/Balkan Peninsulas (Davison et al. 2011).
Research objectives
The aim of this thesis was to study changes in genetic diversity in large carnivores across space and
time, to assess the population dynamics behind these, and identify underlying ecological factors.
More specifically, the objectives were to:
I) Formally test a proposed bottleneck taking place in the population of Late Pleistocene cave lions,
by including more data and simulating diverse population models.
II) Better describe the global phylogeography of grey wolves and test past population scenarios by
adding and comparing mtDNA data from both modern and ancient wolves.
III) Based on the first retrieved draft genome sequence of a Late Pleistocene carnivore, investigate the
genetic relationship between an ancient wolf and modern canid populations.
IV) Reconstruct the phylogeography of European brown bears, to test a proposed scenario of current
genetic structure being the result of a re-colonization from isolated glacial refugia, and study
ecological factors behind observed dynamics.
V) Investigate the genetic consequences of an anthropogenic bottleneck in the Scandinavian brown
bear population, by comparing mitochondrial and nuclear diversity in samples from historic and
modern bears.
Summary of papers
Paper I
A previous study on the phylogeography of modern and ancient lions showed indications of a reduced
diversity in Late Pleistocene cave lions, explained as potentially the result of a demographic
bottleneck (Barnett et al. 2009). To examine the past population dynamics in the species, ancient DNA
data from 14 specimens of cave lion were added to 34 previously published sequences. After
18
extraction, two mitochondrial fragments were amplified following Barnett et al. (2009); a 143 bp long
sequence of the ATP8 gene and a 215 bp long sequence of the control region (CR). Baysian
phylogenies were constructed using MrBayes (Huelsenbeck & Ronquist 2001) and a median-joining
network was constructed. Both phylogenetic analyses displayed a division into two haplogroups,
temporally separated but overlapping to some extent; Haplogroup I contained a comparably higher
amount of variation, both in terms of haplotype and nucleotide diversity, and was only represented in
samples older than ca. 41 kyr BP. Haplogroup II on the other hand was less genetically diverse and
consisted of haplotypes radiating out from a common core haplotype (Fig. 5). From around 50 kyr BP,
this second group persisted until the last recorded specimen at the very end of the Pleistocene, and was
at this time only represented by two haplotypes (Fig. 5).
A subset of the data taken from Beringia, the most well-sampled region, was tested for different
population scenarios with serial coalescent simulations, using Bayesian Serial SimCoal (BaySSC)
(Anderson et al. 2005). Out of eight models, the three most supported were further explored with
BaySICS (Sandoval-Castellanos et al. 2014). The results favored a model of population decrease of at
least a 2-fold magnitude followed by a re-expansion. The timing of this bottleneck was inferred to
have taken place between 47-18 kyr BP, which concurs with the pattern revealed from the
phylogenetic analyses. Since no human presence in Beringia has been recorded as far back in time as
the start of this bottleneck, it seems more likely that a major environmental change was the cause
behind this demographic event. It is interesting to note that several other large mammals went through
similar declines in genetic diversity in Beringia around this time. Although a more precise synchrony
of these declines is not discernable, the period coincides with marine isotope stage (MIS) 3, well
known for repeated climate changes of considerable magnitude (Voelker 2002).
Figure 5. Control region haplotypes in the cave lion distributed in a) a median-joining network and b) a temporal
chart with distributions of haplogroups I and II indicated, and estimated extent of the bottleneck shaded.
19
Paper II
Although numerous, phylogeographic studies on wolves have predominantly been focusing on Europe
and North America (Pilot et al. 2006; Weckworth et al. 2010). By adding new samples from
geographical areas that had not been well studied previously or at all, we aimed to make a global
comparison of genetic diversity within the mitochondrial control region. Two Late Pleistocene wolf
remains collected from sites in the Taimyr Peninsula in northern Siberia were also included, which
were studied along with data from both modern and ancient wolves in order to examine temporal
changes in genetic diversity. 122 samples of contemporary wolves were analyzed from Scandinavia,
Russia, China, Siberia, Iran and North America, including six samples (two of which were of
historical age) from the previously unstudied Greenland subspecies (Canis lupus arctos). By
combining six sequentially overlapping CR-fragments and using primers applied in a previous study
(Savolainen et al. 2002), a 582 bp long alignment was created. The ancient wolf samples from Taimyr
as well as the samples from Greenland were also amplified and sequenced separately in a laboratory in
Copenhagen.
Among the sequences retrieved from the analyzed samples 15 previously undescribed haplotypes were
discovered. These were further concatenated with matching sequences of both ancient and modern
wolves from previous studies, resulting in three alignments of varying length (57-582bp), which were
used for phylogenetic and network analyses. Baysian analyses were employed using the software
BEAST (1.8.0) (Drummond & Rambaut 2007), to create a phylogeny including both modern and
ancient wolves. Measures of genetic diversity were also calculated and temporal comparisons of
haplotype diversity and abundance over time were made.
From the phylogenies and networks a wide spatial distribution of several wolf clades was revealed, but
also some showing a more restricted geographical affiliation. All ancient samples predating the
Holocene, including the two from Siberia, were distinctly grouped at basal positions in the
phylogenies (Fig. 6). These Pleistocene samples exclusively showed a close relationship to a few
clades of modern wolves, none of which are currently represented in North America. In order to
explore this temporal pattern, coalescent simulations under an approximate Bayesian framework were
performed. Three models were tested in BaySSC (Anderson et al. 2005) to expolre demographic
histories for two subsets of the data representing Eurasian and North American wolves. The output
provided support for an end-Pleistocene population bottleneck in northern North America. Since a
decrease in genetic diversity associated with the disappearance of a distinct ecomorph has been
reported in eastern Beringia at this time (Leonard et al. 2007), the simulation result lends further
support for this event.
20
Figure 6. Maximum clade credibility tree of grey wolves based on alignment A (558 bp). Late Pleistocene
samples are noted with numbers 1-10.
Paper III
In order to more thoroughly investigate the relationship between Late Pleistocene wolves and their
modern wild and domestic counterparts, further analyses were applied to one of the ancient wolf
samples originating from the Taimyr Peninsula (Paper II). Genomic libraries were constructed and
sequenced on an Illumina HiSeq 2500 platform to an average 1-fold sequencing depth of the nuclear
genome. The sequencing also yielded the mitochondrial genome, which was assembled to an average
182-fold sequencing depth. When combined with published mitochondrial genomes of modern and
ancient canids (Thalmann et al. 2013), the Siberian wolf’s position could be determined within a
Bayesian phylogeny, confirming its basal position as seen in the previous study (Paper II). SNP’s
identified in the genomic sequence retrieved from the libraries were then compared to matching sets
from both dogs and wolves, including data from SNP’s and 6 modern canid genomes (Vonholdt et al.
2010; Vaysse et al. 2011; VonHoldt et al. 2011; Freedman et al. 2014). Applying D statistics (Green
et al. 2010) to the data with an Andean fox as outgroup, revealed a symmetrical relationship of the
Siberian wolf to both modern dogs and wolves. Further analyses using admixture graph models which
21
included gene-flow between dogs and wolves, gave consistent support for the Siberian wolf
representing the basal lineage, or diverging just before the split between the lineages leading to
modern dogs and wolves (Fig. 7). Given the radiocarbon date of the Siberian wolf (ca. 35,000 years
BP) its equal distance to the two modern lineages entailed a significantly older divergence between the
ancestors of modern dogs and wolves than previously assumed. Based on demographic simulations
and the known age of the Taimyr sample, the genome-wide mutation rate was also estimated in order
to further investigate the divergence time between modern dogs and wolves. The mutation rate was
found to be substantially slower than the one assumed in an earlier study (Freedman et al. 2014),
which in turn resulted in a recalibrated split time somewhere between ca. 40-27 kyr BP. D statistics
was also used to compare the Siberian wolf´s genome to the most extensive dataset of SNP’s from
modern dogs and matching data from 15 modern day wolves (Vaysse et al. 2011). The output clearly
indicated a closer relationship between the Siberian wolf and two arctic breeds; Siberian Huskies
(p=9x10-6) and Greenland Sledge Dogs (p=1.6x10-4). Overall, these results provided a first comparison
between a Late Pleistocene carnivore and its modern relatives, based on extensive genomic data.
Although not defining a domestication event, the results further strengthens previous hypotheses of
wolf domestication having taken place earlier than 16 kya, and even before the LGM (Germonpré et
al. 2009; Ovodov et al. 2011; Druzhkova et al. 2013).
Figure 7. Simplified graphical outline of the Siberian wolf’s
relationship to modern dogs and wolves.
22
Paper IV
Mitochondrial DNA from modern European brown bears has revealed a limited diversity and a
pronounced geographic structure, with two clades occurring in the south-west (clade 1) and north-east
(clade 3). Furthermore, a geographic subdivision has been made within clade 1 (1a & 1b), which has
been proposed to be the result of a separation between different refugial populations in southern
Europe during the LGM. The post-glacial re-expansion of these populations is thought to have created
the current phylogeograhic structure, and this process has been used to exemplify the
Expansion/Contraction model of populations responding to climate change and the availability of
habitat (Hewitt 1996, 1999). However, DNA from ancient brown bear remains has cast doubts on this
model and indicated a more complex phylogeographic structure before as well as after the LGM
(Hofreiter et al. 2004; Valdiosera et al. 2007, 2008).
In order to test these hypotheses and investigate temporal changes of the mentioned mitochondrial
clades in Europe, more than 300 samples of European brown bear remains were collected and
analyzed. A short sequence from the mitochondrial control region, previously used in a majority of
studies on ancient brown bears was amplified. The confirmed sequence data was combined with
published sequences, and direct or inferred ages were obtained for 121 of the samples. Both network
and phylogenies were constructed and geographical distributions of haplotypes were chronologically
analyzed. The results showed a high diversity comprising four distinct mitochondrial clades before the
LGM in Europe. Little geographic structure could be distinguished and a significant population
turnover was identified just before the LGM. In contrast to the previous assumption of bears being
confined to traditional southern refugia during the LGM, radiocarbon dated samples from Belgium and
France confirmed the presence of bears here during this period. A Bayesian SkyGrid analysis further
revealed several fluctuations in estimated population size (Fig. 8). First a marked increase
synchronized with the warming of Greenland Interstadial 1, and later an almost 10-fold decrease,
starting in the mid-Holocene. Measurements of stable nitrogen isotopes from the remains indicate a
shift towards increasing herbivory around the LGM in Europe. This dietary shift has previously been
suggested to result from such a niche becoming available through the extinction of the more
herbivorous cave bear (Ursus spelaeus) between 30-25 kyr BP (Münzel et al. 2011; Bocherens 2015).
More available habitats in the wake of the cave bear’s extinction might also be linked to a slightly
increasing trend shown in the SkyGrid plot, starting just before 30 kyr BP (Fig. 8). Thus, Effects from
inter-specific competition and human activities may have had a greater impact on European brown
bears than climate change.
23
Figure 8. Bayesian SkyGrid plot of estimated changes in effective population size through time in European
brown bears. Highlighted in blue; the Last Glacial Maximum (LGM) and Younger Dryas (YD), in pink;
Greenland Interstadial 1 (GI-1). Inset map shows the geographical distribution of radiocarbon dated remains
from the LGM along with their haplogroup assignment.
Paper V
During the 19th Century, intensified hunting caused the Scandinavian brown bear to suffer a major
decline in population size (Fig. 3), down to an estimated 130 animals as fewest (Swenson et al. 1995).
Protection was legally established in the early 20th Century and allowed the bears to slowly recover
and re-expand. The present-day population has been the focus of a number of genetic studies, which
among other things have revealed a latitudinal division between two mitochondrial lineages that meet
at a distinct contact zone in central Scandinavia (Taberlet & Bouvet 1994; Taberlet et al. 1995). Other
studies incorporating microsatellite data have further shown the existence of three or four
geographically separate subpopulations within Sweden and relatively high levels of diversity (Waits et
al. 2000; Manel et al. 2004). However, previous studies have not been able to resolve to which degree
the demographic bottleneck in the 19th Century impacted the contemporary genetic structure and
diversity. To address this issue, we used mitochondrial and microsatellite DNA markers from
historical and modern brown bear samples to estimate genetic changes across the bottleneck.
24
A multivariate analysis along with simulations showed the same genetic structure before and after the
bottleneck, with three subpopulations in southern, central and northern Scandinavia. In terms of allele
frequencies, a significant change could however be seen in the southern subpopulation. Mitochondrial
diversity was also severely reduced, with falling haplotype numbers across the bottleneck. Except for a
decline in allelic richness in the southern subpopulation, the decline in autosomal genetic diversity was
less apparent. To test different population scenarios, we used approximate Bayesian computations on
the microsatellite data, which showed a clear support for a bottleneck affecting all subpopulations,
expressed as a sharp decline in effective population size followed by a recovery. In conclusion, we
could show that both mitochondrial and nuclear diversity was negatively affected by the bottleneck
and that this was most clearly expressed in southern Scandinavia, where bears were probably more
intensively hunted. The static structure of three subpopulations might be better confirmed by more
extensive sampling from the central and northern regions, but the data at hand suggests that the genetic
structure could have been established by historical ecological processes instead of recent
anthropogenic persecution.
Figure 9. Geographical comparison of mtDNA diversity in Scandinavian brown bears, between the
19th/early 20th Centuries and modern times. The dashed lines mark the contact zone between the two
lineages (N & S).
25
Concluding remarks
The study species, which represent three of the most proliferated families of large mammalian
carnivores, all emerged and expanded during the Pleistocene. The aDNA retrieved from their remains
revealed several marked population dynamics over time on different scales. The dynamics, as
characterized by the results, appear both similar and quite different between the three. Due to limited
sampling, the declines discerned from the data were supported in restricted geographical regions;
Beringia (cave lion), northern North America (wolf) and Europe (brown bear). Nevertheless, some
common patterns can be observed within these regions. The estimated timespan of the bottleneck
impacting cave lions in Beringia for instance (Paper I), also contained a temporal disappearance of
brown bears in the eastern parts (Alaska). The fossil record of cave lions here also display a similar
hiatus ca. 40-25 kyr BP. Wolves on the other hand, appear to have suffered a bottleneck only at the
very end of the Pleistocene in this region, as described by the simulated models in Paper II. Although
the simulations did not support a similar bottleneck in Eurasia, this might be due to a lack of ancient
Eurasian samples with high genetic coverage. However, the symmetrical relation between the Siberian
wolf at ca. 35 kyr BP and all modern wolves (Paper III), lends support to this scenario, suggesting a
widespread bottleneck having taken place at some point between 35 kyr BP and the start of the
Holocene, when wolves in North America were isolated through the inundation of the Bering land
bridge.
In Europe, cave lion remains are missing between roughly 29-19 kyr BP (Stuart & Lister 2011), which
overlaps with turnovers observed in many other species (Cooper et al. 2015), including the brown bear
(Paper IV). However, bears were evidently present in Europe throughout this period, with the only
distinguishable gap in the fossil record between ca. 32-28 kyr BP. At the end of the last glaciation,
cave lions re-expanded across their range (Paper I), but this trend lasted only for a few millennia and
was cut short by their final extinction at the end of the Pleistocene (Stuart & Lister 2011). In contrast,
European brown bears showed signs of a commencing increase around the same time (Paper IV).
In terms of genetic diversity, all three study species have been previously studied, but to different
extent. For the grey wolf and the brown bear, temporal comparisons have been possible to make with
modern populations, while the long extinct cave lion has been represented by much fewer samples, all
dated to the Late Pleistocene. Thus, a prerequisite for most of our analyses has been genetic data,
publicly
available
from
previous
studies
and
online
databases
like
GenBank
(www.ncbi.nlm.nih.gov/genbank/). The use of these datasets has also influenced the choice of
methods and genetic markers, which have been applied to produce matching data, whether of
mitochondrial or autosomal origin. This approach was specifically used for all studies except in Paper
26
III, where comparisons were also highly depending on the relatively abundant genomic data available
from modern canids.
The genetic markers have generally been targeting short mitochondrial sequences. This has imposed
certain restrictions on our produced data, especially limited resolution and support for phylogenetic
clades/haplogroups. In Paper II, where alignments of different sequence lengths were compiled, the
effects on the networks clearly illustrates this problem, as shorter sequences resulted in the merging of
haplotypes (see also Fig. 4). A similar effect can be seen when comparing the Bayesian phylogenies in
Paper II and Paper III, with significantly stronger support for the latter, based on full mitogenomes.
The use of genomic data also enabled analyses including hybridization, which was a necessary
component for establishing the relation of the Late Pleistocene wolf to modern canids (Paper III).
In spite of the restricted coverage achieved from short mtDNA sequences, these markers provided
sufficient data for many phylogeographic comparisons and estimates of population dynamics. The
output from the analyses was also highly affected by the species’ different behavior in terms of
dispersal. This is clearly exemplified by the global comparison of mtDNA diversity in wolves, which
showed little or no structure (Paper II), whereas brown bears, characterized by strong female
philopatry, displayed marked geographical patterns even on regional scales (Paper IV & V). Some
populations stood out as especially distinct among the study species and could be linked to specific
geographical regions, indicating long-term isolation. Examples were the Himalayan and Indian wolf
lineages (Sharma et al. 2004; Aggarwal et al. 2007) as well as the American lion (Panthera atrox)
(Barnett et al. 2009). Among European brown bears, clade 1e, unique to the Iberian Peninsula and
extinct today, may similarly have formed as a result of prolonged isolation. However, the opposite
pattern, with widespread haplotypes, was also common in all three species. Some haplotypes were
found across the Eurasian range, a few even co-occurring in Eurasia and North America. Wolf
populations were highly characterized by this pattern, but it could also be observed in cave lions
(haplotype B) and brown bears (clade 3).
Despite limited genetic resolution in the mtDNA datasets, several demographic scenarios were largely
supported by coalescent simulations as well as analyses using other genetic markers. In Paper V for
instance, the dramatic decrease in haplotype diversity observed across the bottleneck in southern
Scandinavia (Fig. 9) was reflected, albeit to a lesser extent, by the microsatellite data from this
subpopulation. Additional support for the decrease has also been found in a recent study, where a
similar decline was observed in Y-chromosome haplotypes in southern Norway during the same time
period (Schregel et al. 2015).
27
In some cases, other measurable changes seem to have accompanied those seen in genetic diversity:
The genetic turnover observed before the LGM in European brown bears did roughly coincide with an
increase in herbivory, as indicated by the stable isotope analyses (Paper IV). A general decrease in
body size has also been suggested for brown bears in Europe, comparing Holocene and Late
Pleistocene specimens (Marciszak et al. 2015). A more well-supported change in morphology is that
observed in Late Pleistocene wolves. Wolves in eastern Beringia have been characterized as more
robustly built compared to those of the modern population, and were genetically distinct from the
latter (Leonard et al. 2007). The disappearance of this population at the end of the Pleistocene
coincided with the bottleneck inferred in Paper II, as well as the extinction of cave lions in this region
(Stuart & Lister 2011). Like the cave lions, the Beringian wolves seem to have been adapted for
preying on the co-occurring megafauna, which likely restricted them to the mammoth-steppe habitat
that supported these species. As a consequence, this may also have rendered them less able to adapt as
this ecosystem disintegrated. The changing environment across the northern hemisphere at the end of
the Pleistocene might thus be seen as an indirect cause to the demise of both the cave lion and the
Beringian wolf. Stable isotope analyses from a recent study have also indicated a more constrained
diet in cave lions compared to wolves, and revealed a pattern of more conservative feeding niches of
carnivores in Beringia compared to Europe (Yeakel et al. 2013).
Although humans might have competed with all three study species already during the Late
Pleistocene, no anthropogenic impacts can confidently be linked to the observed declines during this
period. In the Holocene, however, both bears and wolves appear to have been affected by expanding
human populations, a process that can be traced as far back as 5,000 years ago for European brown
bears (Paper IV), and that clearly escalated as more efficient hunting techniques were invented
(Paper V).
Taken together, the recovered data from ancient remains presented in this thesis has revealed a number
of declines and changes in genetic structure, which can help to understand the evolutionary processes
in large carnivores. The results also highlight the importance of aDNA as a highly useful tool for
discovering and describing past events within populations and species, which would not have been
detected from modern material alone. These techniques also provide a means to compare past
ecosystems to modern ones, and ultimately understand the continuity in between. Ever evolving
methods and technology hold the promise for improving this understanding.
28
Svensk sammanfattning
Genom att utvinna och analysera genetiskt material från subfossila lämningar av olika djurarter kan
man undersöka en mängd aspekter av deras evolutionära historia. Den här avhandlingen undersöker
dynamik, släktskap och ekologi hos olika populationer av tre stora rovdjur; grottlejon (Panthera
spelaea), varg (Canis lupus) och brunbjörn (Ursus arctos). Resultaten är främst baserade på
mitokondrie-DNA, men även på nukleärt DNA och stabila isotoper från insamlat benmaterial. Åldern
på lämningarna har mer specifikt kunnat bestämmas med hjälp av 14C-datering och tidsskalan sträcker
sig ända till den bortre gränsen för denna metod – ca 50,000 år tillbaka i tiden. Denna senkvartära
tidsrymd innefattar både den Holocena, samt senare delen av den Pleistocena tidsepoken, en tid som
utmärktes av dramatiska klimatförändringar med låga medeltemperaturer. Genom att använda analyser
som jämför lämningarnas geografiska ursprung, den genetiska diversiteten vid olika tidpunkter samt
information om samtida ekologiska förhållanden, har avsikten varit att hitta mönster som kan visa på
kopplingar mellan populationernas dynamik och förändringar i deras miljö. Även interaktioner mellan
arter samt mänsklig påverkan har tagits upp för att uppskatta om/hur dessa faktorer inverkat. I en del
fall har vi utgått från tidigare studier, som antytt förändringar i vissa geografiska områden (Paper I)
eller slagit fast att en flaskhals inträffat (Paper V). I andra har vi mer förutsättningslöst undersökt
genetisk diversitet på en global (Paper II) eller temporal skala (Papers III & IV).
Korta mitokondrie-sekvenser från daterade prover av grottlejon från hela Eurasien analyserades i
Paper I. En tydlig förlust av genetisk diversitet som kunde tolkas som orsakad av en flaskhals testades
genom simuleringar av olika populationsmodeller, där resultaten stödde ett scenario med en långvarig
flaskhals mellan ca 47-18,000 år sedan i Beringia. Tidsintervallet tillsammans med samtida nedgångar
hos andra stora däggdjur antyder att djupgående klimatförändringar kan ha legat bakom. I Paper II
undersöktes temporal diversitet hos vargar utifrån mitokondrie-DNA. Moderna prover från hela
utbredningsområdet samt två lämningar från Sibirien analyserades. Resultaten visade lite geografisk
struktur utöver två grupperingar, där den ena innehöll alla vargar från sen Pleistocen tid. Vidare
påvisade simuleringar stöd för att en flaskhals inträffat i slutet av Pleistocen hos nordamerikanska
vargar. En av varglämningarna från Sibirien analyserades utifrån både mitokondrie- och nukleärt DNA
i Paper III. Jämförelser av det nukleära DNA:t med motsvarande data från moderna hundar och
vargar stödde ett scenario där den sibiriska vargen tillhört en population som troligen utgjordes av de
gemensamma
föregångarna
till
de
två
moderna
grupperna.
Utifrån
den
uppskattade
mutationshastigheten skilde sig de två sistnämnda genetiska linjerna förmodligen så tidigt som för
minst ca 27,000 år sedan. I Paper IV sekvenserades mitokondrie-DNA från lämningar av europeisk
brunbjörn. Flera demografiska förändringar kunde avslöjas med hjälp av 14C-dateringar och provernas
fastställda haplotyper. En minskning av diversitet kunde iakttas i samband med den senaste istiden
(LGM), samt en kraftigt minskande populationsstorlek efter mitten av Holocen. Den geografiska
29
utbredningen i västra Europa under LGM motsäger tidigare hypoteser om att brunbjörnens utbredning
skulle ha varit begränsad till enbart södra Europa under denna tid. I Paper V fokuserade vi på den
skandinaviska björnpopulationen, för att undersöka genetiska effekter av den flaskhals som inträffade
under sent 1800-tal, orsakad av intensiv och okontrollerad jakt. Jämförelser av mitokondrie-DNA och
nukleära mikrosatelliter från museimaterial respektive moderna björnar påvisade en signifikant
minskning av diversitet, framför allt i södra Skandinavien. Simuleringar gav vidare stöd för en modell
där en flaskhals påverkat alla skandinaviska björnar.
Acknowledgements
I would first of all like to thank my supervisor Professor Love Dalén for taking me on and supporting
me during the work on these and all other projects. I have also received much support from colleagues
and fellow PhD students at the departments of zoology and archaeology, but especially in the ancient
DNA group; Vendela, Elle, Edson, Patricia, Jean-Luc, George, Johanna, Matti and David - I am very
grateful for all your help and your company over the years. For valuable assistance at the Department
of Bioinformatics and Genetics and in the DNA-lab I am most grateful to; Fredrik Ronquist, Pia
Eldenäs, Jane Parker, Anna-Lena Löfberg, Martin Irestedt, Bodil Cronholm, Veronica Nyström
Edmark, Rodrigo Esparza-Salas and Keyvan Mirbakhsh. All other colleagues at NRM are
acknowledged, especially Daniella Kalthoff, Peter Mortensen and Peter Nilsson for helping out with
the bear samples from the museum.
For work on the simulations I am in much gratitude to Ludovic Orlando, Edson Sandoval-Castellanos,
Jean-Luc Tison and Yvonne Chan. I am also grateful to Pontus Skoglund, in whose hands the data
from the Taimyr-wolf turned into a great paper. For inviting me to work on the dataset gathered from
modern wolves I would like to thank Peter Savolainen at the Royal Institute of Technology (KTH) and
Cornelya Klütsch at Trent University. I would further like to express my gratitude to everyone that
have helped with and facilitated the contribution of samples for all projects, as well as all the coauthors (more thoroughly acknowledged in the papers/manuscripts). Tom Gilbert and Mikkel SindingLarsen are especially acknowledged for sharing their data on the wolf samples from Greenland.
Additionally, I would like to express my gratitude to Tom Higham and Katerina Douka at the
Research Laboratory for Archaeology and the History of Art in Oxford for all their help and for a real
good time. The group working under Michael Hofreiter in Potsdam is acknowledged, especially Axel
Barlow, Johanna Paijmans and Mick Westbury, and so are Beth Shapiro and her group for hosting me
at UCSC in Santa Cruz, US. I am grateful for financial support from Tullbergs stiftelse and
Föreningen Riksmusei Vänner. I would also like to thank my co-supervisor Kerstin Lidén and the
other members of my evaluation committee; Karl Gotthard and Lars Werdelin.
Last but not least, I want to thank family and friends for their support, especially Hani for supporting
and sticking with me ♥.
30
Contributions
Paper I
I took part in the design of the study. All laboratory work was performed by me and I helped with the
data analyses. The paper was written by me, with input from the co-authors.
Paper II
I helped to design the study and performed laboratory analyses on the two Late Pleistocene wolf
samples. I also conducted all data analyses, except for the coalescent simulations, which were done
together with Yvonne Chan. I wrote the manuscript with help from the other authors.
Paper III
This study was based on the DNA extractions I did for paper II. I further helped building the Illumina
libraries. The analyses of the mitochondrial genome were performed by me, and I also participated in
writing the paper.
Paper IV
For this manuscript I helped to design the study and to formulate hypotheses. I collected samples from
museum collections around Europe, on which I did all DNA extractions, amplifications and
sequencing. I also conducted all the computational analyses on the data, interpreted the results and
wrote the manuscript with input from the co-authors.
Paper V
I helped to design the study and to formulate hypotheses. I collected all the historical samples, and
conducted laboratory and data analyses together with George Xenikoudakis. I also took part in the
work on the Bayesian simulations as well as in interpreting the results and writing the paper.
31
References
Adler CJ, Haak W, Donlon D, Cooper A (2011) Survival and recovery of DNA from ancient teeth and
bones. Journal of Archaeological Science, 38, 956–964.
Aggarwal RK, Kivisild T, Ramadevi J, Singh L (2007) Mitochondrial DNA coding region sequences
support the phylogenetic distinction of two Indian wolf species. Journal of Zoological
Systematics and Evolutionary Research, 45, 163–172.
Allentoft ME, Collins M, Harker D et al. (2012) The half-life of DNA in bone: measuring decay
kinetics in 158 dated fossils. Proceedings. Biological sciences / The Royal Society, 279, 4724–
33.
Anderson PM, Bartlein PJ, Brubaker LB (1994) Late Quaternary History of Tundra Vegetation in
Northwestern Alaska. Quaternary Research, 41, 306–315.
Anderson CNK, Ramakrishnan U, Chan YL, Hadly EA (2005) Serial SimCoal: A population genetics
model for data from multiple populations and points in time. Bioinformatics, 21, 1733–1734.
Antón M (2013) Sabertooth. Indiana University Press.
Avise JC (2000) Phylogeography: the history and formation of species. Harvard university press.
Avise JC, Arnold J, Ball RM et al. (1987) Intraspecific Phylogeography: The Mitochondrial DNA
Bridge Between Population Genetics and Systematics. Annual Review of Ecology and
Systematics, 18, 489–522.
Axelsson E, Ratnakumar A, Arendt M-L et al. (2013) The genomic signature of dog domestication
reveals adaptation to a starch-rich diet. Nature, 495, 360–4.
Axelsson E, Willerslev E, Gilbert MTP, Nielsen R (2008) The effect of ancient DNA damage on
inferences of demographic histories. Molecular Biology and Evolution, 25, 2181–2187.
Azzaroli A (1983) Quaternary mammals and the “end-Villafranchian” dispersal event - A turning
point in the history of Eurasia. Palaeogeography, Palaeoclimatology, Palaeoecology, 44, 117–
139.
Barnes I, Matheus P, Shapiro B, Jensen D, Cooper A (2002) Dynamics of Pleistocene Population
Extinctions in Beringian Brown Bears. , 295, 2267–2270.
Barnett R, Shapiro B, Barnes I et al. (2009) Phylogeography of lions (Panthera leo ssp.) reveals three
distinct taxa and a late Pleistocene reduction in genetic diversity. Molecular Ecology, 18, 1668–
1677.
Barnett R, Yamaguchi N, Barnes I, Cooper A (2006) The origin, current diversity and future
conservation of the modern lion (Panthera leo). Proceedings of the Royal Society B-Biological
Sciences, 273, 2119–2125.
Bartosiewicz L (2009) A lion’s share of attention: archaeozoology and the historical record. Acta
Archaeologica, 60, 275–289.
Bearhop S, Adams CE, Waldron S, Fuller RA, Macleod H (2004) Determining trophic niche width: A
novel approach using stable isotope analysis. Journal of Animal Ecology, 73, 1007–1012.
Beaumont MA (2010) Approximate Bayesian Computation in Evolution and Ecology. Annual Review
of Ecology, Evolution, and Systematics, 41, 379–406.
Berger J, Stacey PB, Bellis L, Johnson MP (2001) A mammalian predator-prey imbalance: Grizzly
bear and wolf extinction affect avian neotropical migrants. Ecological Applications, 11, 947–
960.
Bocherens H (2003) Isotopic biogeochemistry and the paleoecology of the mammoth steppe fauna.
Deinsea, 9, e76.
Bocherens H (2015) Isotopic tracking of large carnivore palaeoecology in the mammoth steppe.
Quaternary Science Reviews, 117, 42–71.
Bocherens H, Drucker DG, Bonjean D et al. (2011) Isotopic evidence for dietary ecology of cave lion
(Panthera spelaea) in North-Western Europe: Prey choice, competition and implications for
extinction. Quaternary International, 245, 249–261.
Bolnick DI, Yang LH, Fordyce JA, Davis JM, Svanbäck R (2002) Measuring individual-level resource
specialization. Ecology, 83, 2936–2941.
Bowen GJ (2010) Isoscapes: Spatial Pattern in Isotopic Biogeochemistry. Annual Review of Earth and
Planetary Sciences, 38, 161–187.
32
Briggs AW, Stenzel U, Johnson PLF et al. (2007) Patterns of damage in genomic DNA sequences
from a Neandertal. Proceedings of the National Academy of Sciences, 104, 14616–14621.
Burbano HA, Hodges E, Green RE et al. (2010) Targeted Investigation of the Neandertal Genome by
Array-Based Sequence Capture. Science, 328, 723–725.
Burger J, Rosendahl W, Loreille O et al. (2004) Molecular phylogeny of the extinct cave lion Panthera
leo spelaea. Molecular Phylogenetics and Evolution, 30, 841–849.
Cahill JA, Green RE, Fulton TL et al. (2013) Genomic Evidence for Island Population Conversion
Resolves Conflicting Theories of Polar Bear Evolution. PLoS Genetics, 9.
Cahill JA, Stirling I, Kistler L et al. (2015) Genomic evidence of geographically widespread effect of
gene flow from polar bears into brown bears. Molecular Ecology, 24, 1205–1217.
Calvignac S, Hughes S (2008) Ancient DNA evidence for the loss of a highly divergent brown bear
clade during historical times. Molecular Ecology, 17, 1962–1970.
Campos PF, Willerslev E, Sher A et al. (2010) Ancient DNA analyses exclude humans as the driving
force behind late Pleistocene musk ox (Ovibos moschatus) population dynamics. Proceedings of
the National Academy of Sciences of the United States of America, 107, 5675–5680.
Carbone C, Mace GM, Roberts SC, Macdonald DW (1999) Energetic constraints on the diet of
terrestrial carnivores. Nature, 402, 286–288.
Carmichael LE, Nagy JA, Larter NC, Strobeck C (2001) Prey specialization may influence patterns of
gene flow in wolves of the Canadian Northwest. Molecular Ecology, 10, 2787–2798.
Carpenter ML, Buenrostro JD, Valdiosera C et al. (2013) Pulling out the 1%: Whole-Genome Capture
for the Targeted Enrichment of Ancient DNA Sequencing Libraries. American Journal of Human
Genetics, 93, 852–864.
Chaix L, Bridault A, Picavet R (1997) A Tamed Brown Bear (Ursus arctos L.) of the Late Mesolithic
from La Grande Rivoire (Isère, France)? Journal of Archaeological Science, 24, 1067–1074.
Chapron G, Kaczensky P, Linnell JDC et al. (2014) Recovery of large carnivores in Europe ’ s modern
human-dominated landscapes. Science, 346, 17–20.
Chauvet J-M, Brunel Deschamps E, Hillaire C (1996) Dawn of art : the Chauvet Cave : the oldest
known paintings in the world. H.N. Abrams, New York.
Christiansen P (2008) Phylogeny of the great cats (Felidae: Pantherinae), and the influence of fossil
taxa and missing characters. Cladistics, 24, 977–992.
Clark PU, Mix a. C (2002) Ice sheets and sea level of the Last Glacial Maximum. Quaternary Science
Reviews, 21, 1–7.
Cooper a, Poinar HN (2000) Ancient DNA: do it right or not at all. Science (New York, N.Y.), 289,
1139.
Cooper A, Turney C, Hughen KA et al. (2015) Abrupt warming events drove Late Pleistocene
Holarctic megafaunal turnover. Science express, 349, 1–8.
Corbett LK (1995) The dingo in Australia and Asia. Cornell Univ. Press, Ithaca.
Cornuet JM, Santos F, Beaumont MA et al. (2008) Inferring population history with DIY ABC: A
user-friendly approach to approximate Bayesian computation. Bioinformatics, 24, 2713–2719.
Dalén L, Nyström V, Valdiosera C et al. (2007) Ancient DNA reveals lack of postglacial habitat
tracking in the arctic fox. Proceedings of the National Academy of Sciences of the United States
of America, 104, 6726–6729.
Dalton R (2003) Lion man takes pride of place as oldest statue. Nature, 425, 7.
Dansgaard W, Johnsen SJ, Clausen HB et al. (1993) Evidence for general instability of past climate
from a 250-kyr ice-core record. Nature, 364, 218–220.
Darimont CT, Paquet PC, Reimchen TE (2007) Stable isotopic niche predicts fitness of prey in a wolfdeer system. Biological Journal of the Linnean Society, 90, 125–137.
Davison J, Ho SYW, Bray SC et al. (2011) Late-Quaternary biogeographic scenarios for the brown
bear (Ursus arctos), a wild mammal model species. Quaternary Science Reviews, 30, 418–430.
Debruyne R, Poinar HN (2009) Time dependency of molecular rates in ancient DNA data sets, A
sampling artifact? Systematic Biology, 58, 348–360.
Dickman A, Marchini S, Manfredo M (2013) The human dimension in addressing conflict with large
carnivores. In: Key Topics in Conservation Biology 2, pp. 110–126.
Drummond AJ, Nicholls GK, Rodrigo AG, Solomon W (2002) Estimating mutation parameters,
population history and genealogy simultaneously from temporally spaced sequence data.
33
Genetics, 161, 1307–1320.
Drummond AJ, Pybus OG, Rambaut A, Forsberg R, Rodrigo AG (2003) Measurably evolving
populations. Trends in Ecology and Evolution, 18, 481–488.
Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. Bmc
Evolutionary Biology, 7.
Drummond AJ, Rambaut A, Shapiro B, Pybus OG (2005) Bayesian coalescent inference of past
population dynamics from molecular sequences. Molecular biology and evolution, 22, 1185–92.
Drummond AJ, Suchard MA, Xie D, Rambaut A (2012) Bayesian Phylogenetics with BEAUti and the
BEAST 1.7. Molecular Biology and Evolution, 29, 1969–1973.
Druzhkova AS, Thalmann O, Trifonov VA et al. (2013) Ancient DNA Analysis Affirms the Canid
from Altai as a Primitive Dog. Plos One, 8.
Edwards CJ, Suchard M a., Lemey P et al. (2011) Ancient hybridization and an irish origin for the
modern polar bear matriline. Current Biology, 21, 1251–1258.
Ellegren H (2004) Microsatellites: simple sequences with complex evolution. Nature reviews.
Genetics, 5, 435–445.
Enk JM, Devault AM, Kuch M et al. (2014) Ancient whole genome enrichment using baits built from
modern dna. Molecular Biology and Evolution, 31, 1292–1294.
Excoffier L, Novembre J, Schneider S (2000) SIMCOAL: A general coalescent program for the
simulation of molecular data in interconnected populations with arbitrary demography. Journal
of Heredity, 91, 506–509.
Fain SR, Straughan DJ, Taylor BF (2010) Genetic outcomes of wolf recovery in the western Great
Lakes states. Conservation Genetics, 11, 1747–1765.
Firestone RB, West a, Kennett JP et al. (2007) Evidence for an extraterrestrial impact 12,900 years
ago that contributed to the megafaunal extinctions and the Younger Dryas cooling. Proceedings
of the National Academy of Sciences of the United States of America, 104, 16016–16021.
Flueck W (2000) Population regulation in large northern herbivores: evolution, thermodynamics, and
large predators. Zeitschrift fuer Jagdwissenschaft, 46, 139–166.
Fox M (1971) Behaviour of wolves dogs and related canids. Dogwise Publishing.
Freedman AH, Gronau I, Schweizer RM et al. (2014) Genome Sequencing Highlights the Dynamic
Early History of Dogs. PLoS Genetics, 10.
García N (2004) New results on the remains of Ursidae from Untermassfeld: Comparisons with Ursus
dolinensis from Atapuerca and other early and middle Pleistocene sites. In: Late Neogene and
Quaternary biodiversity and evolution: Regional developments and interregional correlations.
Conference, p. 112e113.
Geffen E, Anderson MJ, Wayne RK (2004) Climate and habitat barriers to dispersal in the highly
mobile grey wolf. Molecular Ecology, 13, 2481–2490.
Germonpré M, Sablin M V., Stevens RE et al. (2009) Fossil dogs and wolves from Palaeolithic sites in
Belgium, the Ukraine and Russia: osteometry, ancient DNA and stable isotopes. Journal of
Archaeological Science, 36, 473–490.
Gill MS, Lemey P, Faria NR et al. (2013) Improving Bayesian Population Dynamics Inference: A
Coalescent-Based Model for Multiple Loci. Molecular Biology and Evolution, 30, 713–724.
Godinho R, Llaneza L, Blanco JC et al. (2011) Genetic evidence for multiple events of hybridization
between wolves and domestic dogs in the Iberian Peninsula. Molecular Ecology, 20, 5154–5166.
Goudie AS (2013) The human impact on the natural environment: past, present, and future. John
Wiley & Sons.
Green RE, Krause J, Briggs AW et al. (2010) A Draft Sequence of the Neandertal Genome. Science,
328, 710–722.
Guthrie RD (2001) Origin and causes of the mammoth steppe: a story of cloud cover, woolly mammal
tooth pits, buckles, and inside-out Beringia. Quaternary Science Reviews, 20, 549–574.
Guthrie RD (2005) The Nature of Paleolithic Art. University of Chicago Press.
Hailer F, Kutschera VE, Hallstrom BM et al. (2012) Nuclear Genomic Sequences Reveal that Polar
Bears Are an Old and Distinct Bear Lineage. Science, 336, 344–347.
Hallowell AI (1926) Bear ceremonialism in the northern hemisphere. American Anthropologist, 28, 1–
175.
Hamdine W, Thevenot M, Michaux J (1998) Recent history of the brown bear in the Maghreb.
34
Comptes Rendus de l’Academie des Sciences - Serie III: Sciences de la Vie, 321, 565–570.
Heinrich H (1988) Origin and consequences of cyclic ice rafting in the Northeast Atlantic Ocean
during the past 130,000 years. Quaternary Research, 29, 142–152.
Hewitt GM (1996) Some genetic consequences of ice ages, and their role, in divergence and
speciation. Biological Journal of the Linnean Society, 58, 247–276.
Hewitt G (1999) Post-glacial re-colonization of European biota. Biological Journal of the Linnean
Society, 68, 87–112.
Higuchi R, Bowman B, Freiberger M, Ryder OA, Wilson AC (1984) DNA sequences from the
quagga, an extinct member of the horse family. Nature, 312, 282–284.
Hirata D, Mano T, Abramov A V et al. (2013) Molecular phylogeography of the brown bear (Ursus
arctos) in Northeastern Asia based on analyses of complete mitochondrial DNA sequences.
Molecular biology and evolution, 30, 1644–52.
Ho SYW, Lanfear R, Bromham L et al. (2011) Time-dependent rates of molecular evolution.
Molecular Ecology, 20, 3087–3101.
Hofreiter M (2007) Pleistocene Extinctions: Haunting the Survivors. Current Biology, 17.
Hofreiter M, Barnes I (2010) Diversity lost: are all Holarctic large mammal species just relict
populations? BMC biology, 8, 46.
Hofreiter M, Jaenicke V, Serre D, von Haeseler A, Pääbo S (2001a) DNA sequences from multiple
amplifications reveal artifacts induced by cytosine deamination in ancient DNA. Nucleic Acids
Research, 29, 4793–4799.
Hofreiter M, Münzel S, Conard NJ et al. (2007) Sudden replacement of cave bear mitochondrial DNA
in the late Pleistocene. Current Biology, 17, R122–R123.
Hofreiter M, Paijmans JLA, Goodchild H et al. (2015) The future of ancient DNA: Technical
advances and conceptual shifts. BioEssays, 37, 284–293.
Hofreiter M, Serre D, Poinar HN, Kuch M, Paabo S (2001b) Ancient DNA. Nature Reviews Genetics,
2, 353–359.
Hofreiter M, Serre D, Rohland N et al. (2004) Lack of phylogeography in European mammals before
the last glaciation. Proceedings of the National Academy of Sciences of the United States of
America, 101, 12963–12968.
Hofreiter M, Stewart J (2009) Ecological change, range fluctuations and population dynamics during
the Pleistocene. Current Biology, 19, R584–R594.
Horn S, Prost S, Stiller M et al. (2014) Ancient mitochondrial DNA and the genetic history of
Eurasian beaver ( Castor fiber ) in Europe. Molecular Ecology, 23, 1717–1729.
Hudson RR (1990) Gene genealogies and the coalescent process. Oxford Surveys in Evolutionary
Biology, 7, 1–44.
Huelsenbeck JP, Ronquist F (2001) MRBAYES: Bayesian inference of phylogenetic trees.
Bioinformatics, 17, 754–755.
Hunter L (2011) Carnivores of the World. Princeton University Press, Princeton, New Jersey.
Hänni C, Laudet V, Sakka M, Bègue A, Stéhelin D (1990) Amplification of mitochondrial DNA
fragments from ancient human teeth and bones. C.R.Acad.Sci.Paris, t.310, Série III, 365–370.
Jansson S-B (1985) Erikskrönikan. Tiden.
Keis M, Remm J, Ho SYW et al. (2013) Complete mitochondrial genomes and a novel spatial genetic
method reveal cryptic phylogeographical structure and migration patterns among brown bears in
north-western Eurasia. Journal of Biogeography, 40, 915–927.
Kellert SR, Black M, Rush CR, Bath AJ (1996) Human culture and large carnivore conservation in
North America. Conservation Biology, 10, 977–990.
Kennett JP (1990) The younger dryas cooling event: an introduction. Paleoceanography, 5, 891–895.
KoblmÜller S, Nord M, Wayne RK, Leonard JA (2009) Origin and status of the Great Lakes wolf.
Molecular Ecology, 18, 2313–2326.
Koch PL, Barnosky AD (2006) Late Quaternary Extinctions: State of the Debate. Annual Review of
Ecology, Evolution, and Systematics, 37, 215–250.
Korsten M, Ho SYW, Davison J et al. (2009) Sudden expansion of a single brown bear maternal
lineage across northern continental Eurasia after the last ice age: A general demographic model
for mammals? Molecular Ecology, 18, 1963–1979.
Krause J, Unger T, Noçon A et al. (2008) Mitochondrial genomes reveal an explosive radiation of
35
extinct and extant bears near the Miocene-Pliocene boundary. BMC Evolutionary Biology, 8,
220.
Kurtén B (1968) Pleistocene mammals of Europe. Transaction Publishers.
Kyle DG (2014) Animal spectacles in ancient Rome: Meat and meaning. Sport in the Greek and
Roman Worlds: Greek athletic identities and Roman sports and spectacle. Volume 2, 2, 269.
Ladle RJ, Whittaker RJ (2011) Conservation biogeography. John Wiley & Sons.
Lagerholm VK, Sandoval-Castellanos E, Vaniscotte A et al. Range shifts or extinction? Ancient DNA
and distribution modelling reveal past and future responses to climate warming in cold-adapted
birds. In: In prep.
Larson G, Bradley DG, Andersson L (2014) How Much Is That in Dog Years. The Advent of Canine
Population.
Larson G, Karlsson EK, Perri A et al. (2012) Rethinking dog domestication by integrating genetics,
archeology, and biogeography. Proc Natl Acad Sci USA, 109, 8878–83.
Leonard JA (2014) Ecology drives evolution in grey wolves. Evolutionary Ecology Research, 16,
461–473.
Leonard J a, Wayne RK, Cooper a (2000) Population genetics of ice age brown bears. Proceedings of
the National Academy of Sciences of the United States of America, 97, 1651–4.
Leonard JA, Vila C, Fox-Dobbs K et al. (2007) Megafaunal extinctions and the disappearance of a
specialized wolf ecomorph. Current Biology, 17, 1146–1150.
Libbey WF (1952) Radiocarbon dating. University of Chicago Press.
Lindqvist C, Schuster SC, Sun Y et al. (2010) Complete mitochondrial genome of a Pleistocene
jawbone unveils the origin of polar bear. Proceedings of the National Academy of Sciences, 107,
5053–5057.
Liu S, Lorenzen ED, Fumagalli M et al. (2014) Population genomics reveal recent speciation and
rapid evolutionary adaptation in polar bears. Cell, 157, 785–794.
Loreille O, Orlando L, Patou-Mathis M et al. (2001) Ancient DNA analysis reveals divergence of the
cave bear, Ursus spelaeus, and brown bear, Ursus arctos, lineages. Current Biology, 11, 200–203.
Lowe JJ, Walker MJC (2014) Reconstructing quaternary environments. Routledge.
Lönnberg E (1929) Björnen i Sverige: 1856-1928. Almqvist et Wiksell.
Lönnberg E (1935) Handlingar i björnfrågan 1935. Almqvist & Wiksell, Uppsala.
MacPhee RDE (1997) The 40,000-year plague: humans, hyperdisease, and first-contact extinctions.
Natural change and human impact in Madagascar, 169–217.
Madurell-Malapeira J, Alba D, Moy-Sol S (2009) Carnivora from the late early pleistocene of Cal
Guardiola (Terrassa, Valls-Peneds Basin, Catalonia, Spain). Journal of Paleontology, 83, 969–
974.
Major HL, Jones IL, Charette MR, Diamond a. W (2007) Variations in the diet of introduced Norway
rats (Rattus norvegicus) inferred using stable isotope analysis. Journal of Zoology, 271, 463–468.
Manel S, Bellemain E, Swenson JE, François O (2004) Assumed and inferred spatial structure of
populations: the Scandinavian brown bears revisited. Molecular ecology, 13, 1327–31.
Marciszak A, Stefaniak K, Mackiewicz P, Ridush B (2015) Ursus arctos L., 1758 from Bukovynka
Cave (W Ukraine) in an overview on the fossil brown bears size variability based on cranial
material. Quaternary International, 357, 136–148.
Margulies M, Egholm M, Altman WE et al. (2005) Genome sequencing in microfabricated highdensity picolitre reactors. Nature, 437, 376–80.
Martin PS, Steadman DW (1999) Prehistoric extinctions on islands and continents. In: Extinctions in
near time, pp. 17–55. Springer.
Matthiessen P (1987) Wildlife in America. Viking Pr.
Mattson DJ, Blanchard BM, Knight RR (1991) Food habits of Yellowstone grizzly bears, 1977–1987.
Canadian Journal of Zoology, 69, 1619–1629.
Mazák JH (2010) Geographical variation and phylogenetics of modern lions based on craniometric
data. Journal of Zoology, 281, 194–209.
McLellan BN, Hovey FW (2001) Natal dispersal of grizzly bears. Canadian Journal of Zoology, 79,
838–844.
Mech LD, Boitani L (2010) Wolves: behavior, ecology, and conservation. University of Chicago
Press.
36
Meyer M, Fu Q, Aximu-Petri A et al. (2013) A mitochondrial genome sequence of a hominin from
Sima de los Huesos. Nature, 505, doi:10.1038/nature12788.
Meyer M, Kircher M (2010) Illumina sequencing library preparation for highly multiplexed target
capture and sequencing. Cold Spring Harbor Protocols, 5.
Miller W, Schuster SC, Welch AJ et al. (2012a) Polar and brown bear genomes reveal ancient
admixture and demographic footprints of past climate change. Proceedings of the National
Academy of Sciences of the United States of America, 109, E2382–90.
Miller W, Schuster SC, Welch AJ et al. (2012b) Polar and brown bear genomes reveal ancient
admixture and demographic footprints of past climate change. Proceedings of the National
Academy of Sciences of the United States of America, 109, E2382–90.
Miller CR, Waits LP, Joyce P (2006) Phylogeography and mitochondrial diversity of extirpated brown
bear (Ursus arctos) populations in the contiguous United States and Mexico. Molecular Ecology,
15, 4477–4485.
Minin VN, Bloomquist EW, Suchard MA (2008) Smooth skyride through a rough skyline: Bayesian
coalescent-based inference of population dynamics. Molecular biology and evolution, 25, 1459–
1471.
Moritz C, Dowling TE, Brown WM (1987) Evolution of animal mitochondrial DNA: relevance for
population biology and systematics. Annual Review of Ecology and Systematics, 18, 269–292.
Mowat G, Heard DC (2006) Major components of grizzly bear diet across North America. Canadian
Journal of Zoology, 84, 473–489.
Muñoz-Fuentes V, Darimont CT, Paquet PC, Leonard JA (2010) The genetic legacy of extirpation and
re-colonization in Vancouver Island wolves. Conservation Genetics, 11, 547–556.
Münzel SC, Stiller M, Hofreiter M et al. (2011) Pleistocene bears in the Swabian Jura (Germany):
Genetic replacement, ecological displacement, extinctions and survival. Quaternary
International, 245, 225–237.
Newsome SD, Del Rio CM, Bearhop S, Phillips DL (2007) A niche for isotopic ecology. Frontiers in
Ecology and the Environment, 5, 429–436.
Nowak RM (2003) Wolf evolution and taxonomy. Wolves: Behavior, ecology, and conservation, 239–
258.
Nowak C, Domokos C, Dutsov A, Frosch C (2014) Molecular evidence for historic long-distance
translocations of brown bears in the Balkan region. Conservation Genetics, 15, 743–747.
O’Connor TP, Sykes NJ (2010) Extinctions and Invasions: A Social History of British Fauna
[Elektronisk resurs]. Oxbow Books.
O’Regan H (2002) From bear pit to zoo. British archaeology, 12–19.
Orlando L, Ginolhac A, Zhang GJ et al. (2013) Recalibrating Equus evolution using the genome
sequence of an early Middle Pleistocene horse. Nature, 499, 74–+.
Ovodov ND, Crockford SJ, Kuzmin Y V. et al. (2011) A 33,000-Year-Old incipient dog from the
Altai Mountains of Siberia: Evidence of the earliest domestication disrupted by the last Glacial
Maximum. PLoS ONE, 6.
Pacher M, Stuart AJ (2009) Extinction chronology and palaeobiology of the cave bear (Ursus
spelaeus). Boreas, 38, 189–206.
Palkopoulou E, Mallick S, Skoglund P et al. (2015) Complete genomes reveal signatures of
demographic and genetic declines in the woolly mammoth. Current Biology, 25, 1395–1400.
Pasanen-Mortensen M, Pyykönen M, Elmhagen B (2013) Where lynx prevail, foxes will fail limitation of a mesopredator in Eurasia. Global Ecology and Biogeography, 22, 868–877.
Pastoureau M, Holoch G (2011) The bear : history of a fallen king. The Belknap Press of Harvard
University Press, Cambridge.
Penny D (2005) Relativity for molecular clocks. Nature, 436, 183–184.
Pentikäinen J, Tolley C (2007) Golden king of the forest : the lore of the northern bear. Etnika,
Helsinki.
Pilot MM, Branicki W, Jedrzejewski WW et al. (2010) Phylogeographic history of grey wolves in
Europe. BMC evolutionary biology, 10, 104.
Pilot M, Jedrzejewski W, Branicki W et al. (2006) Ecological factors influence population genetic
structure of European grey wolves. Molecular ecology, 15, 4533–4553.
Pinhasi R, Fernandes D, Sirak K et al. (2015) Optimal Ancient DNA Yields from the Inner Ear Part of
37
the Human Petrous Bone. PloS one, 10, e0129102.
Pohja-Mykrä M, Vuorisalo T, Mykrä S (2005) Hunting bounties as a key measure of historical
wildlife management and game conservation: Finnish bounty schemes 1647–1975. Oryx, 39,
284–291.
Prugh LR, Stoner CJ, Epps CW et al. (2009) The Rise of the Mesopredator. BioScience, 59, 779–791.
Prüfer K, Stenzel U, Hofreiter M et al. (2010) Computational challenges in the analysis of ancient
DNA. Genome biology, 11, R47.
Pääbo S (1985) Molecular cloning of Ancient Egyptian mummy DNA. Nature, 314, 644–645.
Rabeder G, Nagel D, Pacher M (2000) Der Höhlenbär. Thorbecke.
Ray JC, Hunter L, Zigouris J (2005) Setting Conservation and Research Priorities for Larger African
Carnivores. Wildlife Conservation Society, 24, 203.
Ripple WJ, Beschta RL (2004) Wolves and the Ecology of Fear: Can Predation Risk Structure
Ecosystems? BioScience, 54, 755.
Ripple WJ, Estes JA, Beschta RL et al. (2014) Status and ecological effects of the world’s largest
carnivores. Science, 343, 1241484.
Rode KD, Robbins CT, Nelson L, Amstrup SC (2015) Can polar bears use terrestrial foods to offset
lost ice-based hunting opportunities? Frontiers in Ecology and the Environment, 13, 138–145.
Sandoval-Castellanos E, Palkopoulou E, Dalén L (2014) Back to BaySICS: A user-friendly program
for Bayesian statistical inference from coalescent simulations. PLoS ONE, 9.
Savolainen P, Zhang YP, Luo J, Lundeberg J, Leitner T (2002) Genetic evidence for an East Asian
origin of domestic dogs. Science, 298, 1610–1613.
Sawyer S, Krause J, Guschanski K, Savolainen V, Pääbo S (2012) Temporal patterns of nucleotide
misincorporations and DNA fragmentation in ancient DNA. PLoS ONE, 7.
Schregel J, Eiken HG, Grøndahl FA et al. (2015) Y chromosome haplotype distribution of brown
bears (Ursus arctos) in Northern Europe provides insight into population history and recovery.
Molecular Ecology, 24, 6041–6060.
Schweizer RM, Robinson J, Harrigan R et al. (2015) Targeted capture and resequencing of 1040 genes
reveal environmentally driven functional variation in gray wolves. Molecular Ecology, n/a–n/a.
Servheen C, Darling LM, Archibald WR (1990) The status and conservation of the bears of the world.
Shackleton NJ, Opdyke ND (1973) Oxygen isotope and palaeomagnetic stratigraphy of Equatorial
Pacific core V28-238: Oxygen isotope temperatures and ice volumes on a 105 year and 106 year
scale. Quaternary Research, 3, 39–55.
Shapiro B, Drummond AJ, Rambaut A et al. (2004) Rise and fall of the Beringian steppe bison.
Science, 306, 1561–1565.
Sharma DK, Maldonado JE, Jhala Y V, Fleischer RC (2004) Ancient wolf lineages in India.
Proceedings. Biological sciences / The Royal Society, 271 Suppl , S1–S4.
Sinclair ARE, Mduma S, Brashares JS (2003) Patterns of predation in a diverse predator-prey system.
Nature, 425, 288–290.
Sotnikova M, Nikolskiy P (2006) Systematic position of the cave lion Panthera spelaea (Goldfuss)
based on cranial and dental characters. Quaternary International, 142-143, 218–228.
Stewart JR (2009) The evolutionary consequence of the individualistic response to climate change.
Journal of Evolutionary Biology, 22, 2363–2375.
Stewart JR, Lister AM, Barnes I, Dalén L (2010) Refugia revisited: individualistic responses of
species in space and time. Proceedings. Biological sciences / The Royal Society, 277, 661–671.
Stewart JR, Stringer CB (2012) Human evolution out of Africa: the role of refugia and climate change.
Science (New York, N.Y.), 335, 1317–21.
Stiller M, Baryshnikov G, Bocherens H et al. (2010) Withering away-25,000 years of genetic decline
preceded cave bear extinction. Molecular Biology and Evolution, 27, 975–978.
Stoen OG, Zedrosser A, Saebo S, Swenson JE (2006) Inversely density-dependent natal dispersal in
brown bears Ursus arctos. Oecologia, 148, 356–364.
Strimmer K, Pybus OG (2001) Exploring the Demographic History of DNA Sequences Using the
Generalized Skyline Plot. Mol. Biol. Evol, 18, 2298–2305.
Stuart AJ (1999) Late Pleistocene Megafaunal Extinctions. In: Extinctions in Near Time (ed MacPhee
RDE), pp. 257–269. Kluwer Academic/Plenum Publishers, New York.
Stuart AJ, Kosintsev PA, Higham TFG, Lister AM (2004a) Pleistocene to Holocene extinction
38
dynamics in giant deer and woolly mammoth. Nature, 431, 684–689.
Stuart a J, Kosintsev P a, Higham TFG, Lister a M (2004b) Pleistocene to Holocene extinction
dynamics in giant deer and woolly mammoth. Nature, 431, 684–689.
Stuart AJ, Lister AM (2011) Extinction chronology of the cave lion Panthera spelaea. Quaternary
Science Reviews, 30, 2329–2340.
Swenson JE, Wabakken P, Sandegren F et al. (1995) The near extinction and recovery of brown bears
in Scandinavia in relation to the bear management policies of Norway and Sweden. Wildlife
Biology, 1, 11–25.
Svensson A, Andersen KK, Bigler M et al. (2006) The Greenland Ice Core Chronology 2005, 15-42
ka. Part 2: comparison to other records. Quaternary Science Reviews, 25, 3258–3267.
Taberlet P, Bouvet J (1994) Mitochondrial DNA polymorphism, phylogeography, and conservation
genetics of the brown bear Ursus arctos in Europe. Proceedings of the Royal Society of London B. Biological Sciences, 255, 195–200.
Taberlet P, Swenson JE, Sandegren F, Bjarvall A (1995) Localization of a contact zone between two
highly divergent mitichondrial DNA lineages of the Brown bear (Ursus arctos) in Scandinavia.
Conservation Biology, 9, 1255–1261.
Terborgh J, Lopez L, Nuñez P et al. (2001) Ecological meltdown in predator-free forest fragments.
Science (New York, N.Y.), 294, 1923–1926.
Thalmann O, Shapiro B, Cui P et al. (2013) Complete Mitochondrial Genomes of Ancient Canids
Suggest a European Origin of Domestic Dogs. Science, 342, 871–874.
Treves A, Karanth KU (2003) Special Section: Human-Carnivore Conflict: Local Solutions with
Global Applications. In: Conservation Biology, pp. 1489–1490.
Turner A, Antón M (1997) The big cats and their fossil relatives: an illustrated guide to their
evolution and natural history. Columbia University Press.
Waits L, Taberlet P, Swenson JE, Sandegren F, Franzén R (2000) Nuclear DNA microsatellite
analysis of genetic diversity and gene flow in the Scandinavian brown bear (Ursus arctos).
Molecular ecology, 9, 421–431.
Valdiosera CE, García N, Anderung C et al. (2007) Staying out in the cold: glacial refugia and
mitochondrial DNA phylogeography in ancient European brown bears. Molecular ecology, 16,
5140–8.
Valdiosera CE, García-Garitagoitia JL, Garcia N et al. (2008) Surprising migration and population
size dynamics in ancient Iberian brown bears (Ursus arctos). Proceedings of the National
Academy of Sciences of the United States of America, 105, 5123–5128.
Van Valkenburgh B, Hayward MW, Ripple WJ, Meloro C, Roth VL (2015) The impact of large
terrestrial carnivores on Pleistocene ecosystems. Proceedings of the National Academy of
Sciences, 1–6.
Van Valkenburgh B, Hertel F (1993) Tough times at la brea: tooth breakage in large carnivores of the
Late Pleistocene. Science, 261, 456–459.
Wang IJ, Bradburd GS (2014) Isolation by environment. Molecular Ecology, 23, 5649–5662.
Wang X, Tedford RH, Antón M (2010) Dogs: their fossil relatives and evolutionary history. Columbia
University Press.
Wang GD, Zhai W, Yang HC et al. (2013) The genomics of selection in dogs and the parallel
evolution between dogs and humans. Nat Commun, 4, 1860.
Vartanyan SL, Garutt VE, Sher a. V. (1993) Holocene dwarf mammoths from Wrangel Island in the
Siberian Arctic. Nature, 362, 337–340.
Vaysse A, Ratnakumar A, Derrien T et al. (2011) Identification of genomic regions associated with
phenotypic variation between dog breeds using selection mapping. PLoS Genetics, 7.
Weckworth B V, Talbot SL, Cook JA (2010) Phylogeography of wolves (Canis lupus) in the Pacific
Northwest. Journal of Mammalogy, 91, 363–375.
Werdelin L, Lewis ME (2005) Plio-Pleistocene Carnivora of eastern Africa: Species richness and
turnover patterns. Zoological Journal of the Linnean Society, 144, 121–144.
West JB, Bowen GJ, Dawson TE, Tu KP (2010) Isoscapes: Understanding movement, pattern, and
process on earth through isotope mapping.
Vigne JD (1988) Les mammifères post-glaciaires de Corse. Etude archéozoologique. Supplément à
Gallia Préhistoire, 26, 1–337.
39
Vila C, Amorim I, Leonard J et al. (1999) Mitochondrial DNA phylogeography and population history
of the grey wolf canis lupus. Molecular ecology, 8, 2089–103.
Vilà C, Savolainen P, Maldonado JE et al. (1997) Multiple and ancient origins of the domestic dog.
Science (New York, N.Y.), 276, 1687–1689.
Willerslev E, Davison J, Moora M et al. (2014) Fifty thousand years of Arctic vegetation and
megafaunal diet. Nature, 506, 47–51.
Voelker AHL (2002) Global distribution of centennial-scale records for Marine Isotope Stage (MIS) 3:
a database. Quaternary Science Reviews, 21, 1185–1212.
Wolff EW, Chappellaz J, Blunier T, Rasmussen SO, Svensson A (2010) Millennial-scale variability
during the last glacial: The ice core record. Quaternary Science Reviews, 29, 2828–2838.
VonHoldt BM, Pollinger JP, Earl DA et al. (2011) A genome-wide perspective on the evolutionary
history of enigmatic wolf-like canids. Genome Research, 21, 1294–1305.
Vonholdt BM, Pollinger JP, Lohmueller KE et al. (2010) Genome-wide SNP and haplotype analyses
reveal a rich history underlying dog domestication. Nature, 464, 898–902.
Wroe S, Milne N (2007) Convergence and remarkably consistent constraint in the evolution of
carnivore skull shape. Evolution, 61, 1251–1260.
Yamaguchi N, Cooper A, Werdelin L, Macdonald DW (2004) Evolution of the mane and group-living
in the lion (Panthera leo): a review. Journal of Zoology, 263, 329–342.
Yeakel JD, Guimaraes PR, Bocherens H, Koch PL (2013) The impact of climate change on the
structure of Pleistocene food webs across the mammoth steppe. Proceedings of the Royal Society
B-Biological Sciences, 280.
Vander Zanden HB, Bjorndal K a, Reich KJ, Bolten AB (2010) Individual specialists in a generalist
population: results from a long-term stable isotope series. Biology Letters, 6, 711–714.
Zazula GD, Froese DG, Telka AM, Mathewes RW, Westgate J a (2003) Plants , bugs , and a giant
mammoth tusk : Paleoecology of Last Chance Creek , Yukon Territory. Yukon Exploration and
Geology 2002, 251–258.
Zimov SA, Zimov NS, Tikhonov AN, Chapin FS (2012) Mammoth steppe: a high-productivity
phenomenon. Quaternary Science Reviews, 57, 26–45.
40