Journal of Heredity 2011:102(5):526–536
doi:10.1093/jhered/esr056
Advance Access publication June 29, 2011
Ó The American Genetic Association. 2011. All rights reserved.
For permissions, please email: [email protected].
Adaptive Potential of Northernmost
Tree Populations to Climate Change,
with Emphasis on Scots Pine (Pinus
sylvestris L.)
OUTI SAVOLAINEN, SONJA T. KUJALA, CATHERINA SOKOL, TANJA PYHÄJÄRVI, KOMLAN AVIA, TIMO KNÜRR,
KATRI KÄRKKÄINEN, AND SHEILA HICKS
From the Department of Biology, University of Oulu, P.O. Box 3000, FIN-90014, Oulu, Finland (Savolainen, Kujala, Pyhäjärvi,
and Avia); the Biocenter Oulu, University of Oulu, Oulu, Finland (Savolainen and Kujala); the Department of Geosciences,
University of Oulu, Oulu, Finland (Sokol and Hicks); Department of Mathematics and Statistics, University of Helsinki,
Helsinki, Finland (Knürr); and the Muhos Research Centre, the Finnish Forest Research Institute, Muhos, Finland
(Kärkkäinen).
Address correspondence to Dr O. Savolainen at the address above, or e-mail: [email protected].
Abstract
The adaptive potential of the northernmost Pinus sylvestris L. (and other northern tree) populations is considered by
examining first the current patterns of quantitative genetic adaptive traits, which show high population differentiation and
clines. We then consider the postglacial history of the populations using both paleobiological and genetic data. The current
patterns of diversity at nuclear genes suggest that the traces of admixture are mostly visible in mitochondrial DNA variation
patterns. There is little evidence of increased diversity due to admixture between an eastern and western colonization
lineage, but no signal of reduced diversity (due to sequential bottlenecks) either. Quantitative trait variation in the north is
not associated with the colonizing lineages. The current clines arose rapidly and may be based on standing genetic variation.
The initial phenotypic response of Scots pine in the north is predicted to be increased survival and growth. The genetic
responses are examined based on quantitative genetic predictions of sustained selection response and compared with earlier
simulation results that have aimed at more ecological realism. The phenotypic responses of increased growth and survival
reduce the opportunity for selection and delay the evolutionary responses. The lengthening of the thermal growing period
also causes selection on the critical photoperiod in the different populations. Future studies should aim at including multiple
ecological and genetic factors in evaluating potential responses.
Key words: DNA variation, phenotypic clines, photoperiod, pollen production, range margin
In Europe, northernmost animal and plant populations have
colonized their current distribution areas during the last
10 000 years. In this short time span, they have become
genetically differentiated from the Central European and
other more southern populations (e.g., Lagercrantz and
Ryman 1990; van Rossum and Prentice 2004). Several
evolutionary factors may have led to this genetic differentiation (Pamilo and Savolainen 1999), but reciprocal
transplant experiments have shown that many populations
have become adapted to the local conditions due to
differential selection (Turesson 1922; Olsson and Ågren
2002; Savolainen et al. 2007; Leinonen et al. 2009).
Local adaptation and range expansion at the species margin
depend on an interplay between selection and gene flow
526
(Kirkpatrick and Barton 1997; Lenormand 2002). On the one
hand, gene flow provides raw material for evolution, and on
the other hand, extensive gene flow may prevent adaptation at
species margins (Haldane 1956; Garcı́a-Ramos and Kirkpatrick
1997). When there are no direct physical barriers, interspecific
interactions can also have an especially important role in
limiting adaptation and range expansion (Case et al. 2005).
Despite the importance of local adaptation, predictions
on species composition often proceed without taking
genetics into account, assuming that climatic envelopes for
the species are maintained (IPCC 2001; Kellomäki et al.
2001; Thomas et al. 2004). It seems important to include
genetic aspects because evolutionary change has also
accompanied historical range shifts (Davis and Shaw 2001).
Savolainen et al. Adaptive Potential of Northern Tree Populations
Understanding the mechanisms of previous adaptation to
new climates by migration and evolution and knowledge of the
current state of the patterns of genetic variation provide the
possibility to also examine the potential for future adaptation
(Petit et al. 2008). The role of migration and evolutionary
responses of trees to climate change at large have been
considered earlier (Davis and Shaw 2001; Saxe et al. 2001;
Savolainen et al. 2004; Aitken et al. 2008). Petit and Hampe
(2005) have emphasized the importance of responses at the
southern rear edge. Here we examine the adaptive potential of
northernmost tree populations to changing climate, often using
Scots pine (Pinus sylvestris L.) as the specific example. We first
describe the present patterns of genetic variation, next consider
the history of migration and evolution that led to the current
patterns, and last consider the potential for future changes. The
evaluation is not only based partly on our own recent work but
also on the extensive forestry research on trees in Scandinavia
and Finland.
Materials and Methods
We have earlier described sequence variation in a limited set of
genes and populations (Pyhäjärvi et al. 2007). Phenotypic
variation in timing of budset has also been studied earlier
(Garcı́a-Gil et al. 2003; Notivol et al. 2007). The sequence and
phenotypic data added here have been obtained using methods
described in these articles. Here we deal with samples from 3
populations, Norra Gullabo, Sweden (56°28’, 15°55’), Kolari,
Finland (lat 67°11’, long 24°03’), and Usinsk, Russia (66°05’,
57°30’). The sample sizes from each of these populations were
10 haploid (megagametophyte) samples per locus. The set of 10
loci, candidate genes for cold tolerance and budset, is described
in more detail in elsewhere (Pyhäjärvi et al. 2007; Wachowiak
et al. 2009; Kujala ST, Savolainen O, in preparation) The loci
and the number of nucleotides sequenced were as follows: from
Pyhäjärvi et al. (2007) and Kujala ST, Savolainen O (in
preparation) col1 (constans like 1, length 3847), gi (gigantea,
fragment 1, 402, fragment 2, 1370), phyn (phytochrome N,
6683), lp2 (s-adenosyl methionine synthetase, 1185); from
Wachowiak et al. (2009) dhn1 (dehydrin 1 1357); and from
Kujala ST, Savolainen O (in preparation) cry1 (cryptochrome 1,
4762), ft4 (flowering locus T 4, 2545), prr1 (pseudo-response
regulator 1, 4183), ztl (zeitlupe, 1182), and myb (myb-related
CCA1-like, clade II, 3113) .
Here we use these loci to compare diversity of
populations and describe their divergence. Earlier work
has shown that, in general, signals of selection at these loci
are not strong, and a set of numerous loci will have overall
patterns similar to loci presumed to be neutral (Pyhäjärvi
et al. 2007; Wachowiak et al. 2009). The analyses are based
on 10 haploid megagametophytes per locus. We also use
records of pollen transport and deposition to look at the
quantities of pollen available, its potential source, and the
timing of dispersal. Methods for monitoring pollen deposition are given in Hicks (2001) and for the timing of
pollen dispersal in Sokol C, Pessi AM, Huusko A, Hicks S,
Kubin E, Heino S (in preparation).
Current Patterns of Genetic Variation and
Adaptation
Scots pine has the widest distribution range of all pine species
and populations are found in a wide range of environmental
conditions, extending from Scotland to Eastern China and
from southern Spain to northern Scandinavia and Finland.
There is no physical barrier at the northern range limit, and
selection imposed by the environmental conditions may
determine the range in the north.
An essential aspect of climatic adaptation is the
synchronizing of growth and reproduction with favorable
seasons. Extensive studies have documented variation
between populations in traits related to the timing of growth
and pollen shedding or female strobilus maturity in Scots
pine (Heikinheimo 1949; Eriksson et al. 1980; Chung 1981;
Mikola 1982; Aho 1994; Oleksyn et al. 1998; Garcı́a-Gil et al.
2003; Andersson and Fedorkov 2004; Notivol et al. 2007),
whereas studies of the nuclear genome neutral markers have
shown very low differentiation between populations within
the continuous range of P. sylvestris (Gullberg et al. 1985;
Pyhäjärvi et al. 2007). Figure 1 shows an example of variation
of family means in the timing of setting the terminal bud in
first-year seedlings. The southern Finnish population has
much within-population variation for the timing of budset
but is highly differentiated from other populations. For the
other populations, the population means (and the ranges of
family means) are shown. Interestingly, the differentiation is
higher between southern Finland and the north than
southern Finland and the south; for 5-degree latitude
difference to the south, the mean budset difference between
populations is 11 days, to the north, the difference is 17 days.
The cline is thus at its steepest in the north. Many other
species of conifers have similar extensive clines, as for
instance Sitka spruce (Picea sitchensis) in Canada (Mimura and
Aitken 2007; Mimura and Aitken 2010).
This pattern of quantitative trait variation is consistent
with evidence of local adaptation showing that native
populations perform better than transferred ones (Savolainen
et al. 2007). Southern populations transferred to the north
suffer increased mortality. Northern populations grow and
survive better in more southern conditions but do not
outperform the local southern populations. The pattern of
local adaptation holds for most of the range from southern
Sweden northward, but right at the northern range the pattern
seems to break down (Savolainen et al. 2007). Northern
populations of Scots pine and many other tree species are
limited by cold temperatures (Eriksson et al. 1980; Rehfeldt
et al. 2002; Reich and Oleksyn 2008). A lack of ability to adapt
to the more northern conditions may have helped to shape
the current northern edge of the distribution range.
Colonization of the North
During the ice age, pine populations were found in the
Iberian and the Italian peninsulas as well as in the Balkans
(Cheddadi et al. 2006), but fossil evidence suggests that
527
Journal of Heredity 2011:102(5)
Figure 1. Histogram of family means of timing of budset in first-year seedlings of Scots pine (Pinus sylvestris) in a southern
Finnish population (Punkaharju) compared with means (dots) and ranges (horizontal arrows) of other populations. Seeds were
germinated in early June and grown in a common garden experiment in a greenhouse with close to ambient temperature and day
length in 2008 at Haapastensyrjä (Southern Finland). The latitude of origins of populations is indicated as the position relative to
right y axis. For locations of the populations, see Figure 2.
populations were probably also found north of these areas
in Central Europe (Willis and van Andel 2004). It is known
from the pollen assemblages preserved in lake sediments
that in Fennoscandia, when the ice of the last ice age began
melting, the newly revealed land along the retreating ice
margin was first colonized by a pioneer vegetation of herbs
and dwarf shrubs. These were quickly followed by tree
birches, and it was into this birch-dominated landscape that
Scots pine spread (Donner 2005). Scots pine is able to grow
on a wide range of substrates and eventually outshades birch
so that it was able to occupy the majority of the areas
formerly covered only by birch and also to form extensive
forests. Around 10 000 years ago, the last remnant of the ice
sheet was situated over northern Sweden and, to the east of
it, there was an extensive body of water, the Ancylus lake
(Figure 2). Together they formed an effective barrier to
migration, especially to northern Sweden. Migration was
possible only via the land areas of Finland to the east of the
Ancylus lake or along the narrow coastal strip of Norway,
which had become ice free at an early stage in the
deglaciation. Similar early ice-free areas also existed in the
far north of Norway, Finland, and Russia, and there is some
evidence to suggest that Scots pine was sparsely present in
this area more than 10 000 years ago (Seppä 1996). On the
basis of the available fossil pollen data, therefore, different
parallel postglacial migration routes for Scots pine can be
hypothesized: from southern Fennoscandia/Karelia northward on the eastern side of the Bothnian Bay, northward
along the Norwegian coast, and westward via from the Kola
peninsula. These different migration routes would have met
in northern Sweden.
528
By looking at the dates of the first arrival of pine from
pollen diagrams in Finland, Sweden, and Norway, it is
evident that there is a difference of around 2450 years
between its first appearance in southern Finland (Donner
et al. 1978) and in northern Finland (Eronen et al. 1999) and
of about 3170 years between its first appearance in southern
Norway (Eide et al. 2006) and in the western coast of
northern Norway (Vorren et al. 1996): distances of 860 and
1300 km, respectively. This would suggest a migration rate
of around 0.4 km per year. This is a very rapid rate
compared with recent estimates of migration rates in North
American trees that acknowledge the existence of populations close to the ice (,100 m/year) (McLachlan et al. 2005;
Petit et al. 2008). This is also somewhat faster than any
migrations seen in the last 1000 years (Juntunen et al. 2006).
The Scots pine calculations are based on the difference
between just 2 pairs of pollen diagrams, but virtually all the
available fossil evidence supports a rapid expansion of pine
in the early postglacial. The rate of migration could have
been enhanced by the different ecological conditions in the
early postglacial because pines were colonizing a much more
open landscape and, apart from the birch, there were no
other tree species to compete with.
Genetic Traces of Colonization and
Possible Admixture
Many temperate Central European tree populations show
extensive genetic signals of admixtures between differentiated
glacial refuge populations from the Iberian and Italian
Savolainen et al. Adaptive Potential of Northern Tree Populations
Figure 2. Map showing the distribution of mitochondrial haplotypes, the locations of nuclear DNA sampling site, and origins of
the phenotypic data used in the common greenhouse experiments in Pinus sylvestris populations, as well as exemplary dates (in
calibrated years before present) of rising Pinus pollen curves (Donner et al. 1978; Seppä 1996; Vorren et al. 1996; Eronen et al.
1999; Eide et al. 2006). Possible migration routes of Scots pine are marked with arrows. The ice cap and water body represent the
Ancylus lake situation approximately 10,000 years before present. In pie diagrams, the mitochondrial haplotype frequencies are
indicated by white (type A, called AA in Naydenov et al. 2007) and black or striped (type C, called BA in Naydenov et al. 2007).
peninsulas and the Balkans (Petit et al. 2003). There have been
fewer studies of Scandinavian populations, but in Norway
spruce, there is some suggestion of a hybrid zone between
admixture lineages in Central Sweden (Lagercrantz and Ryman
1990). Here we examine the genetic traces of admixture in
northern Scots pine. Is the pattern of genetic variation in
Nordic populations consistent with colonization from 2
different, differentiated sources? Or is it more likely that the
current northern populations are derived from one source?
Second, has recent selection eliminated any historical differences of adaptive differences between colonizing lineages?
An admixture between 2 genetically diverged sources of
colonization should result in increased genetic variation at
the admixture zone and increased linkage disequilibrium at
least within closely linked nucleotide sites and in the early
phases of admixture, between the cytoplasmic and nuclear
genomes. If the differentiation between the 2 source
populations is too low, the signs of admixture can be hard
to find. In trees, which have a long juvenile phase, the
probability of diverged lineages arising is lower than, for
example, in annuals (Austerlitz et al. 2004). It is also
important to evaluate the potential influence of gene
surfing—increased genetic differentiation during a rapid
expansion (Excoffier and Ray 2008). Such effects have been
detected in North American Populus balsamifera (Keller et al.
2010). Colonization from one source could not only give
rise to reduced diversity, as seen in many other species
(Eckert et al. 2008; Muller et al. 2008; Pujol and Pannell
2008), but also increase linkage disequilibrium because of
sequential bottlenecks (Hein et al. 2005).
Results from studies on mitochondrial DNA (mtDNA)
variation (Sinclair et al. 1999; Naydenov et al. 2007;
529
Journal of Heredity 2011:102(5)
Table 1 Pairwise FST values between 3 populations of Pinus
sylvestris averaged over 10 loci
Kolari, Finland
Usinsk, Russia
Norra Gullabo, Sweden
Kolari, Finland
0.027
0.069
0.011
Table 2 Nucleotide diversity estimates (p) in 3 populations of
Pinus sylvestris
hWa
Hdb
0.0045 (0.0036–0.0059)
0.0039 (0.0029–0.0054)
0.0037 (0.0028–0.0052)
0.9012
0.8928
0.8536
Estimates are based on 10 loci.
a
Maximum posterior estimate for multilocus hW from silent sites; 95%
credibility intervals in parentheses.
b
Haplotype diversity averaged over 10 loci.
530
Mitotype
average
—
Pyhäjärvi et al. 2008) are consistent with each other and the
dual colonization model, as the western and eastern sides of
Scandinavia show different patterns (Figure 2). Unfortunately, the current level of available mtDNA polymorphism
is not very informative, and the paternally inherited
chloroplastDNA of conifers is not useful in this context
due to low differentiation (Ennos 1994).
The northern populations (indicated in Figure 2) show
rather high divergence at candidate loci for climatic
adaptation (Table 1). The Russian Usinsk population is
more highly diverged from the southern Swedish (Norra
Gullabo) population (average FST 5 0.069, 4 of 10
individual loci significantly different from zero) than
European populations in general, consistent with the idea
of somewhat diverged glacial populations. The northern
Finnish Kolari population is intermediate, slightly closer to
the Russian population. The Kolari population has the
highest nucleotide and haplotypic diversity at these 10 loci,
but the small differences between populations are not
statistically significant (Table 2). Thus, there is not only little
signal of increased diversity due to admixture but also no
sign of reduced diversity due to sequential bottlenecks.
Further, these northern populations also have roughly
similar levels of variability as the central European
populations of P. sylvestris (Pyhäjärvi et al. 2007). Linkage
disequilibrium based on fairly long gene sequences seems to
be consistently high even within the 2 colonizing lineages
(Norra Gullabo, Sweden, and Usinsk, Russia, data not
shown). Thus, we cannot detect increased linkage disequilibrium in the potentially admixed population. The withingene estimates are not likely to be informative in this case
for conclusions on admixture—we would need to have
nucleotide sites that are further apart from each other than
the length of the genes examined here.
We also examined whether the quantitative genetic
variation shows any signs of admixture. Common garden
studies of timing of budset were related to the mitochondrial DNA type of the maternal family (Table 3). This
Kolari, Finland
Norra Gullabo, Sweden
Usinsk, Russia
Table 3 Association between mitotypes and timing of budset
in northern populations of Pinus sylvestris
Population
A
C
Kolari, Finland
Uusikaupunki, Finland
Norra Gullabo, Sweden
89.40
103.20
108.03
91.22
104.01
113.50
t
P
1.54
0.78
4.83
0.14
0.44
,0.001
Average timing of budset is expressed in days from sowing. The phenotypic
data are from a greenhouse experiment conducted in 2003 and thus
different from the data in Figure 1.
comparison shows that in the far northern population, close
to the potential admixture zone, there is no association
between the mtDNA variation and the adaptive variation.
An association is seen only in the southern Swedish
population, which should not be due to recent admixture.
Thus, if the timing of budset was diverged between
2 colonizing lineages, natural selection for local adaptation
has already eliminated such divergence. A similar finding has
been made for quantitative variation in admixture zones of
oak species (Kremer et al. 2002), but in oaks, the different
maternal marker lineages still differed in nuclear marker
frequencies.
The data may be consistent with the admixture of 2
colonization lineages, but for the most part, the traces of the
distinct lineages are not clearly visible in the nuclear genes.
Instead, all the populations still retain a signal of a very ancient
population bottleneck and subsequent expansion (Pyhäjärvi
et al. 2007; Kujala ST, Savolainen O, in preparation) The most
recent expansion after the ice age may also have involved a large
population expansion, but so few generations have passed that
the genome has not yet accumulated the singleton mutations
characteristic of such expansions.
How Could Adaptation Be So Rapid?
Migration of Existing Genotypes or
Standing Genetic Variation?
As described above, the rapid colonization of northern areas
was accompanied by the generation of long clines in many
traits, as shown by common garden experiments.
Clines could in principle originate through migration of
different genotypes, each following their climatic envelopes.
Many tree species, especially as seedlings, use photoperiods
as an environmental cue for cessation of growth (Dormling
1973; Oleksyn et al. 1998; Howe et al. 2003; Böhlenius et al.
2006). The current tree populations in northern areas may
stop growth if days are shorter than 20 h. These genotypes
cannot have existed at high frequencies in populations that
could grow, survive, and reproduce in Central European
conditions. Thus, the northern populations have new
phenotypic (and genotypic) combinations of photoperiodic
reactions and, for example, cold tolerance, which must have
arisen during the colonization phase (see also Ingvarsson
et al. 2008).
Savolainen et al. Adaptive Potential of Northern Tree Populations
New genotypes and phenotypes may arise by recombination and/or by genetic changes at individual loci. The
genes that govern the variation in timing of growth clines in
trees are still poorly known, with few exceptions. phyB seems
to be involved in governing variation in the timing of
growth cessation in Populus tremula (Ingvarsson et al. 2006,
2008). This gene and many of the studied candidate genes
have shown weak clines or weak phenotypic effects in many
species (Garcı́a-Gil et al. 2003; Heuertz et al. 2006),
suggesting either that the responsible loci have not been
detected, the effects are quite small, or that the phenotypic
changes are due to correlated small changes at several loci
along the cline (Latta et al. 1998; LeCorre and Kremer
2003).
Adaptation to new environmental conditions can act on
either newly arising mutations or on variation that already
existed in the ancestral population, that is, standing genetic
variation. Selection on standing genetic variation could
promote rapid adaptation because beneficial alleles are
immediately available, and no waiting period for new
mutations is needed. These alleles can exist in considerable
frequencies thus reducing the average fixation time. Also, as
these variants can be old, they might have been ‘‘pre-tested
and approved’’ by selection in past environments (reviewed
by Barrett and Schluter 2007; Hermisson and Pennings
2005). Variants that have been favorable as Scots pine and
other tree species have colonized northern areas have most
likely existed in the Central European populations at some
low frequency, as there have been repeated expansions
during alternating climate conditions (Müller et al. 2003;
Cheddadi et al. 2005; De Carvalho et al. 2010). Thus, we can
speculate that adaptation during colonization of northern
areas could have been accelerated by selection acting on
standing genetic variation. We also presume that recombination between loci has generated new combinations of alleles
and phenotypes, which did not exist in glacial survival areas.
Possible Responses to Climate Warming:
Phenotypic Plasticity
Tree responses to climate warming are first due to
phenotypic plasticity. Some of these may be adaptive,
others are not. In the north, survival is expected to increase
(Rehfeldt et al. 2002; Reich and Oleksyn 2008) and, indeed,
height growth has already increased in northern Finland
(Pensa et al. 2006).
The warming climate has an influence not just on the
individual trees but also on the reproductive traits of
individual trees and hence on mating patterns of the
populations. Until recently, seed and pollen production in
the north have been on average very low and also highly
variable between years (Koski and Tallqvist 1978;
Savolainen 1996). During the last 10 years, the start of the
thermal growing season has been 10 days earlier than the
1971–2000 average in the far north of Finland (Finnish
Meteorological Institute). Concomitantly, male flowering of
pines since the year 2000 has started 10 days earlier than the
average of 1977–2007 (Heino S, personal communication).
Pollen deposition records by pollen traps show that there is
now also more abundant male flowering in northern Finland
(Figure 3). Because of the earlier very limited pollen
production, these changes may be more important in the
north than in more southern populations that have
produced much pollen also earlier.
The changes in pollen and seed production can have
important demographic consequences. In the warming
climate, the pollen grains and seeds produced will have
increased dispersal rates (Kuparinen et al. 2009). Seeds will
also have increased chances of establishment. This has
already contributed to range expansion observed at the
northern limit of Scots pine (Juntunen et al. 2006) and
altitudinal shifts in other northern species (Kullman 2002).
Possible Responses to Climate Warming:
Evolution within Populations
Much of the literature on climate change response examines
the potential of species to track their climatic envelopes,
without considering genetic change. Many results have
suggested that it will be very difficult to track the
environment even with the increasing dispersal rates
(Iverson et al. 2004; Kuparinen et al. 2009; Loarie et al.
2009).
In the long term, evolutionary changes will need to
accompany range changes, as has also been the case during
historical range expansion. How rapidly can trees evolve? To
provide answers in a quantitative genetics framework, we
have to make assumptions about the genetic basis of adaptive
traits. The predictions of models can vary depending on the
details of assumed traits (Hänninen 2006). It is very difficult
to predict which traits will be most important for
adaptation—for instance, new disease or insect resistance
could be critical. From the past history, we know that
adaptation to the length of the growing season has been
important. As the average annual temperature is predicted to
rise some 4 °C in the next century (Kattsov and Källen 2005),
the sites at lat 68°N in Finland are predicted to experience
growing season temperatures currently found in Helsinki
(lat 60°N). We can then consider whether the pines of the
Kolari population (lat 67.2°N) (see Figure 1) will evolve to
have the mean timing of budset of Punkaharju (lat 61.8°N)
in approximately 100 years? The populations are about
5 degrees of latitude apart and differ by 17 budset days in the
experiment shown in Figure 1. This is more than 2 times the
phenotypic standard deviation (SD) of the Kolari population.
When strong selection is applied in large experimental
populations for specific traits, large initial responses can be
obtained, until genetic variation is depleted or the
deleterious side effects of selection prevent further
advancement (Falconer and Mackay 1996). Introduced tree
populations have also shown rapid phenotypic change, but
the conditions in these experiments allow for very strong
selection, as in a plant breeder’s experiment rather than
conditions of a natural population.
531
Journal of Heredity 2011:102(5)
Figure 3. Yearly deposition of Pinus pollen at 2 monitoring stations in northernmost Finland for the period 1982 to 2004. The
amount of pollen reaching the ground is a good reflection of pollen production.
For a long-term response, theoretical considerations have
suggested that populations could track environmental changes
of a magnitude governed by the available genetic variation, the
maximum growth rate (rmax) and the strength of stabilizing
selection (rW). The critical rate of change of phenotypic
optimum
kc (relative to the phenotypic SD rP) is
qffiffiffiffiffiffiffi
kc
2rmax
5r
P
rP
rw (Lynch and Lande 1993; Lynch 1996). If it is
assumed that the maximum growth rate of a population is 0.5
and stabilizing selection is weak, then the rate is at most a few
percentage of an SD per generation (Lynch 1996). Aitken et al.
(2008) suggested that assuming weak selection but a high
maximum growth rate, a much faster response would be
possible (up to 40% of rP). Common garden–based estimates
on Scots pine indicate very strong selection on timing of budset
in Scots pine in the far north, such that even using the low
reproductive capacity of 0.5, populations might be able to
tolerate a faster changes in the phenotypic optimum (Knürr T,
Kärkkäinen K, Savolainen O, in preparation). This could
suggest rapid evolution, but the models may not be appropriate
for such strong selection. Clearly many of the parameters
governing responses are not known.
The above considerations ignored the influence of gene
flow from outside the population. In the prevailing
conditions, the lack of adaptation at range margins can be
due to asymmetric gene flow from more central populations
(Garcı́a-Ramos and Kirkpatrick 1997). The current seeming
lack of adaptation in the northernmost populations could
well be due to asymmetric migration from the more
southern populations. The female strobili become receptive
before the males, and nonlocal pollen may be available for
fertilization at this time in at least some years. The pollen
shedding in southern Finland starts more than 3 weeks
before that in northern Finland (Pessi and Pulkkinen 1994).
In the north, some pine pollen is commonly recorded by
aerobiological samplers before the local male flowering of
pine begins (Ranta et al. 2008; Ranta and Pessi 2010). Varis
et al. (2009) suggested that in at least some years this can
result in pollination by southern trees. A similar window for
532
pollination from outside the population has also been
documented on an altitudinal scale, where lowland populations may pollinate receptive females higher on the slopes
(Kärkkäinen 1991).
In the warming conditions, gene flow could aid
adaptation. Gene flow was included in computer simulations
on Scots pine and birch adaptation (Kuparinen et al. 2010).
These data (based on detailed estimates of gene flow)
showed, however, that the dispersal rate is not the most
critical parameter for evolutionary response. This work also
took into account the increased growth and survival of the
northern Scots pine. The simulations showed that higher
mortality would results in more evolutionary opportunity
and a more rapid evolutionary change. Although the
increased survival of Scots pine provides some buffering
time, it also delays the evolutionary responses.
Until now, simulations on genetics have excluded many
important genetic or evolutionary factors. The models have
so far only included mortality due to frost or reduced
growth. Genetic correlations with other adaptive traits may
also influence the results (Etterson and Shaw 2001). The
simulations have also ignored the role of the photoperiod
(see below). And finally, as many tree species in the very
north benefit from the warming climate, the fate of
individual species may depend largely on the competition
environment (Case et al. 2005).
Adaptation to Temperature and
Photoperiod
Trees and other plants have adapted to local climate
conditions by genetic differentiation with respect to their
timing of growth cessation (Mikola 1982; Howe et al. 2003).
Although adaptation is to the length of the thermal growing
season (number of days with average daily temperature .5
°C), the environmental cue for growth cessation in many
species from Drosophila to pitcher plant mosquitoes
Savolainen et al. Adaptive Potential of Northern Tree Populations
(Weiomyia smithii) and trees is frequently photoperiod
(Bradshaw and Holzapfel 2001; Böhlenius et al. 2006).
Photoperiod is important in seedlings, also in species with
predetermined growth (Aitken et al. 2008). For instance,
Mimura and Aitken (2010) recently provided empirical
evidence that in Sitka spruce, photoperiodic control of the
timing of budset is very important. Day lengths during the
growing season change rapidly in high latitudes (see
Figure 4). In this area, the climate differences between
latitudes are large (e.g. in terms of length of thermal growing
season). Day length is thus quite informative of the progress
of the season. Populations from different latitudes have
different critical photoperiods (at which growth ceases).
Trees and other species are thus adapted to a combination
of climate and the associated day length at each growing site.
To be able to respond to climate change, populations
need to evolve to have a new critical photoperiod, suited to
their new environmental conditions. Figure 4 shows these
relationships. Two curves show the day length at 2 different
latitudes, one in southern Finland (60°N) and the other in
northern Finland (68°N) during the growing season
(Forsythe et al. 1995). In this example, the current northern
Finnish populations’ (lat 68°N) growth cessation could be at
day 203 (late July), corresponding to a day length of 19 h (on
the y axis). As the climate warms (by about 4 °C), the thermal
growing season will extend at the northern site (lat 68°N).
The appropriate cessation of growth might be at day 230 (late
August), which is the current growth cessation day of
a southern (lat 60°N) population. In the south, this
corresponds to a day length of about 14 h. The northern
population will experience the new temperatures in its current
photoperiodic environment. To achieve the appropriate
growth cessation date, the northern population must evolve
to stop growth at a date corresponding to 15 h, not at the
date corresponding to 14 h. Thus, in the case of the warming
climate, the required response is less on the photoperiod axis
than on the calendar days (or temperature sum axis). This
should facilitate adaptation—the appropriate photoperiodic
reactions might be available in populations north of lat 60°N,
perhaps at lat 62°N. Note that the critical day lengths are not
those at the actual time of cessation of growth but much
earlier, closer to the middle of the summer, when differences
in day length between latitudes are even larger.
In W. smithii, the pitcher plant mosquito, a change in the
critical photoperiod of the population has already been
observed, a rare documented genetic change of local
populations in response to climate warming (Bradshaw
and Holzapfel 2001). Such changes have received very little
attention but are expected in other populations as well.
In the very northernmost areas, day length as such in the
middle of the summer may cease to be informative because
the sun does not set at all. In those areas, the growth
cessation reactions may be largely governed by light quality
as the spectral composition varies between times of day,
even if the days are 24 h long. Earlier work on Norway
spruce (Picea abies; Ekberg et al. 1979) has documented
differences between populations in sensitivity to the spectral
quality of light.
Figure 4. Relationship between the length of the growing
season (governed by temperature) and photoperiod in northern
latitudes. Day lengths along the season are shown for 2
different latitudes. The solid vertical and horizontal line show
the correspondence between date of growth cessation and the
day length at lat 68°N and the dashed vertical and horizontal
lines show the same for lat 60°N. When the climate warms, the
northern population should extend its growing season to cease
growth at the current southern growth cessation date.
However, this date translates to a different photoperiod at lat
68°N (15 h), not the same as lat 60°N (14 h). Note that the
actual critical day lengths will be at some point before growth
cessation, the figure is to illustrate this relationship. See text for
explanation.
Conclusions
The adaptation of pines and other economically important,
often cultivated plants may be aided by carefully planned
assisted migration, but other species will have to rely on the
evolution within individual populations. Evolution of small
and fragmented slowly growing populations may be limited
by available genetic variability, and they may not be able to
maintain the growth to sustainable response (Lynch 1996),
even if there is an initial response to selection.
We have here concentrated the discussion on the
northern, leading edge of the range of trees, especially with
regards to Scots pine. Many of the conclusions will hold for
other species with similar life histories in the north. For
instance, Norway spruce and Sitka spruce (P. sitchensis;
Mimura and Aitken 2007; Mimura and Aitken 2010) seem to
share many of the characteristics of Scots pine. Still,
differences in physiology between species may be important
and give rise to different responses (Hänninen 2006). The
evolutionary responses of species are expected to vary, as do
the responses in distribution ranges: not all species are
expanding their ranges northward or to higher altitudes
(Parmesan 2006; Lenoir et al. 2008).
Many species in the north are experiencing increased
survival, whereas the impacts of climate change are very
different on the trailing edge, with populations of some
533
Journal of Heredity 2011:102(5)
species dying off. The high mortality in these populations
may result in faster evolutionary responses, but the required
genetic variation might not be available (Petit and Hampe
2005).
Possible responses of trees include phenotypic plasticity
and adaptation. It is evident from the above considerations
that these responses are not independent but that the
phenotypic plasticity responses have an influence on
demography and on the opportunity for selection. Migration, another possible response (Aitken et al. 2008), has
been and will be accompanied by evolution within
populations. Interspecific interactions (Kellomäki et al.
2001; Dullinger et al. 2004; Case et al. 2005) will also
influence evolutionary changes in important ways.
Whether trees will have rapid evolutionary responses is still
an open question. Some authors suggest that rapid evolutionary
responses are possible (Berteaux et al. 2004; Hamrick 2004). So
far, careful review has shown that there are few cases of
convincingly demonstrated genetic changes in response to
climate change (Gienapp et al. 2008), notably one welldocumented case represents evolution of the photoperiodic
response (Bradshaw and Holzapfel 2001). It is clear that in any
species, many critical factors for predicting the responses are
still unknown, such as the maximum reproductive rates and
strength of selection or the role of interspecific competition.
Further, predictions made on detailed understanding of genetic
networks in different environmental conditions are so far only
available for model organisms (Wilczek et al. 2010).
Funding
The Thule Institute of the University of Oulu; the National
Population Genetics Graduate School; Biocenter Oulu; the
EU Network of Excellence Evoltree (FP6 016322); the EU
project Millennium (FP6 017008), the EU project Noveltree
(FP7 211868).
Acknowledgments
We thank Torgny Persson for providing the Usinsk seeds and Folmer
Bokma for help with Figure 4.
Berteaux D, Réale D, McAdam AG, Boutin S. 2004. Keeping pace with fast
climate change: can Arctic life count on evolution? Integr Comp Biol.
44:140–151.
Böhlenius H, Huang T, Charbonnel-Campaa L, Brunner AM, Jansson S,
Strauss SH, Nilsson O. 2006. CO/FT regulatory module controls timing of
flowering and seasonal growth cessation in trees. Science. 312:1040–1043.
Bradshaw WE, Holzapfel CM. 2001. Genetic shift in photoperiodic
response correlated with global warming. Proc Natl Acad Sci U S A.
98:14509–14511.
Case TJ, Holt RD, McPeek MA, Keitt TH. 2005. The community context of
species’ borders: ecological and evolutionary perspectives. Oikos. 108:28–46.
Cheddadi R, de Beaulieu J-L, Jouzel J, Andrieu-Ponel V, Laurent J-M, Reille
M, Raynaud D, Bar-Hen A. 2005. Similarity of vegetation dynamics during
interglacial periods. Proc Natl Acad Sci U S A. 102:13939–13943.
Cheddadi R, Vendramin GG, Litt T, Francois L, Kageyama M, Lorentz S,
Laurent JM, de Beaulieu JL, Sadori L, Jost A, et al. 2006. Imprints of glacial
refugia in the modern genetic diversity of Pinus sylvestris. Global Ecol
Biogeogr. 15:271–282.
Chung M-S. 1981. Flowering characteristics of Pinus sylvestris L. with special
emphasis on the reproductive adaptation to local temperature factor. Acta
Forest. Fenn. 169:1–68.
Davis MB, Shaw RG. 2001. Range shifts and adaptive responses to
quaternary climate changes. Science. 292:673–679.
De Carvalho D, Ingvarsson PK, Joseph J, Suter L, Sedivy C, Macaya-Sanz
D, Cottrell J, Heinze B, Schanzer I, Lexer C. 2010. Admixture facilitates
adaptation from standing variation in the European aspen (Populus tremula
L.), a widespread forest tree. Mol Ecol. 19:1638–1650.
Donner J. 2005. The Quaternary history of Scandinavia. Cambridge (UK):
Cambridge Univ. Press.
Donner JJ, Alhonen P, Eronen M, Jungner H, Vuorela I. 1978.
Biostratigraphy and radiocarbon dating of the Holocene lake sediments
of Työtjärvi and the peats in the adjoining bog Varrassuo west of Lahti in
southern Finland. Ann Bot Fenn. 15:258–280.
Dormling I. 1973. Photoperiodic control of growth and growth cessation in
Norway spruce seedlings. In Proceedings of the IUFRO, IUFRO Division
2. Working Party 2.01.4 Symposium on Dormancy in Trees; 1973 Sep 5–9;
Kórnik, Poland. p. 1–15.
Dullinger S, Dirnböck T, Grabherr G. 2004. Modelling climate-change
driven treeline shfits: relative effects of temperature increase, dispersal and
invasibility. J Ecol. 92:241–252.
Eckert CG, Samis KE, Lougheed SC. 2008. Genetic variation across
species’ geographical ranges: the central-marginal hypothesis and beyond.
Mol Ecol. 17:1170–1188.
Eide W, Birks HH, Bigelow NH, Peglar SM, Birks HJB. 2006. Holocene
forest development along the Setesdal valley, southern Norway, reconstructed
from macrofossil and pollen evidence. Veg Hist Archaeobot. 15:65–85.
References
Ekberg I, Eriksson G, Dormling I. 1979. Photoperiodic reactions in conifer
species. Holarctic Ecol. 2:255–263.
Aho M-L. 1994. Autumn frost hardening of one-year-old Pinus sylvestris (L.)
seedlings: effect of origin and parent trees. Scand J For Res. 9:17–24.
Ennos RA. 1994. Estimating relative rates of pollen and seed migration
among plant populations. Heredity. 72:250–259.
Aitken SN, Yeaman S, Holliday JA, Wang TL, Curtis-McLane S. 2008.
Adaptation, migration or extirpation: climate change outcomes for tree
populations. Evol Appl. 1:95–111.
Eriksson G, Andersson S, Eiche V, Ifver J, Persson A. 1980. Severity index
and transfer effects on survival and volume production of Pinus sylvestris in
northern Sweden. Stud. For. Suecica. 156:1–32.
Andersson B, Fedorkov A. 2004. Longitudinal differences in Scots pine
frost hardiness. Silv Genet. 53:76–80.
Eronen M, Hyvärinen H, Zetterberg P. 1999. Holocene humidity changes
in northern Finnish lapland inferred from lake sediments and submerged
Scots pine dated by tree-rings. Holocene. 9:569–580.
Austerlitz F, Dick CW, Dutech C, Klein EK, Oddou-Muratorio S, Smouse
PE, Sork VL. 2004. Using genetic markers to estimate the pollen dispersal
curve. Mol Ecol. 13:937–954.
Barrett RDH, Schluter D. 2007. Adaptation from standing genetic variation.
Trends Ecol Evol. 23:38–44.
534
Etterson JR, Shaw RG. 2001. Constraint to adaptive evolution in response
to global warming. Science. 294:151–154.
Excoffier L, Ray N. 2008. Surfing during population expansions promotes
genetic revolutions and structuration. Trends Ecol Evol. 23:347–351.
Savolainen et al. Adaptive Potential of Northern Tree Populations
Falconer DS, Mackay TFC. 1996. Introduction to quantitative genetics.
Harlow (UK): Longman.
Forsythe WC, Rykiel EJ, Stahl RS, Wu H-i, Schoolfield RM. 1995. A model
comparison for daylength as a function of latitude and day of year. Ecol
Model. 80:87–95.
Garcı́a-Gil MR, Mikkonen M, Savolainen O. 2003. Nucleotide diversity at
two phytochrome loci along a latitudinal cline in Pinus sylvestris. Mol Ecol.
12:1195–1206.
Garcı́a-Ramos G, Kirkpatrick M. 1997. Genetic models of adaptation and
gene flow in peripheral populations. Evolution. 51:21–28.
Gienapp P, Teplitsky C, Alho JS, Mills JA, Merilä J. 2008. Climate change
and evolution: disentangling environmental and genetic responses. Mol
Ecol. 17:167–178.
Gullberg U, Yazdani R, Rudin D, Ryman N. 1985. Allozyme variation in
Scotch pine (Pinus sylvestris) in Sweden. Silv Genet. 34:193–201.
Haldane JBS. 1956. The relation between density regulation and natural
selection. Proc R Soc Lond B Biol Sci. 145:306–308.
Hamrick JL. 2004. Response of forest trees to global environmental
changes. For Ecol Manag. 197:323–335.
Hänninen H. 2006. Climate warming and the risk of frost damage to boreal forest
trees: identification of critical ecophysiological traits. Tree Physiol. 26:889–898.
Heikinheimo O. 1949. Results of experiments on the geographical races of
spruce and pine. Commun Inst For Fenn. 37:1–44.
Hein J, Schierup MH, Wiuf C. 2005. Gene genealogies, variation and evolution.
A primer in coalescent theory. Oxford (UK): Oxford University Press.
Hermisson J, Pennings PS. 2005. Soft sweeps: molecular population genetics
of adaptation from standing genetic variation. Genetics. 169:2335–2352.
Kattsov VM, Källen E. 2005. Future climate change: modeling and
scenarios for the Arctic. In: Symon C, Arris L, Heal B, editors. Arctic
climate impact assessment. Cambridge (UK): Cambridge University Press.
p. 100–150.
Keller SR, Olson MS, Silim S, Schroeder W, Tiffin P. 2010. Genomic
diversity, population structure, and migration following rapid range
expansion in the Balsam Poplar, Populus balsamifera. Mol Ecol.
19:1212–1226.
Kellomäki S, Rouvinen I, Peltola H, Strandman H, Steinbrecher R. 2001.
Impact of global warming on the tree species composition of boreal forests
in Finland and effects on emission of isoprenoids. Global Change Biol.
7:531–544.
Kirkpatrick M, Barton NH. 1997. Evolution of a species’ range. Am. Nat.
150:1–23.
Koski V, Tallqvist R. 1978. Results on long time measurements of the
quantity of flowering and seed crop of forest trees. Folia Forest. 364:1–60.
Kremer A, Kleinshmit J, Cotrell J, Cundall EP, Deans JD, Ducousso A,
König A, Lowe AJ, Munro RC, Petit RJ, et al. 2002. Is there a correlation
between chloroplastic and nuclear divergence, or what are the roles of
history and selection on genetic diversity in European oaks? For Ecol
Manag. 156:75.
Kullman L. 2002. Rapid recent range-margin rise of tree and shrub species
in the Swedish Scandes. J Ecol. 90:68–77.
Kuparinen A, Katul G, Nathan R, Schurr FM. 2009. Increases in air
temperature can promote wind-driven dispersal and spread of plants. Proc
R Soc Lond B Biol Sci. 276:3081–3087.
Kuparinen A, Savolainen O, Schürr F. 2010. Increased mortality can
promote adaptation of forest trees to climate change. For Ecol Manag.
259:1003–1008.
Heuertz M, De Paoli E, Källman T, Larsson H, Jurman I, Morgante M,
Lascoux M, Gyllenstrand N. 2006. Multilocus patterns of nucleotide
diversity, linkage disequilibrium and demographic history of Norway spruce
(Picea abies (L.) Karst). Genetics. 174:2095–2105.
Lagercrantz U, Ryman N. 1990. Genetic structure of Norway spruce (Picea
abies): concordance of morphological and allozyme variation. Evolution.
44:38–53.
Hicks S. 2001. The use of annual arboreal pollen deposition values for
delimiting tree-lines in the landscape and exploring models of pollen
dispersal. Rev Palaeobot Palynol. 117:1–29.
Latta R, Linhart Y, Fleck D, Elliot M. 1998. Direct and indirect estimates of
seed versus pollen movement within a population of ponderosa pine.
Evolution. 52:61–67.
Howe GT, Aitken SN, Neale DB, Jermstad KD, Wheeler NC, Chen THH.
2003. From genotype to phenotype: unraveling the complexities of cold
adaptation in forest trees. Can J Bot. 81:1247–1266.
LeCorre V, Kremer A. 2003. Genetic variability at neutral markers,
quantitative trait loci and trait in a subdivided population under selection.
Genetics. 164:1205–1219.
Ingvarsson PK, Garcia MV, Hall D, Luquez V, Jansson S. 2006. Clinical
variation in phyB2, a candidate gene for day-length-induced growth
cessation and bud set, across a latitudinal gradient in European Aspen
(Populus tremula). Genetics. 172:1845–1853.
Leinonen P, Sandring S, Quilot B, Clauss MJ, Mitchell-Olds T, Ågren J,
Savolainen O. 2009. Local adaptation in European populations of
Arabidopsis lyrata (Brassicaceae). Am J Bot. 96:1129–1137.
Ingvarsson PK, Garcia MV, Luquez V, Hall D, Jansson S. 2008. Nucleotide
polymorphism and phenotypic associations within and around the
phytochrome B2 locus in European aspen (Populus tremula, Salicaceae).
Genetics. 178:2217–2226.
IPCC. 2001. Climate Change 2001: The scientific basis. Contribution of
working group I to the third assessment report of the Intergovernmental
Panel on Climate Change. Houghton JT, Ding Y, Griggs DJ, Noguer M,
van der Linden PJ, Dai X, Maskell K, Johnsson CA, editors. Cambridge
(UK): Cambridge University Press. p. 881.
Iverson LR, Schwartz MW, Prasad AM. 2004. How fast and far might tree
species migrate in the eastern United States due to climate change. Global
Ecol Biogeogr. 13:209–219.
Juntunen V, Neuvonen S, Sutinen R. 2006. Männyn puurajan muutokset
viimeisen 400 vuoden aikana ja metsänraja-puuraja vaihettumisvyöhykkeen
ikärakenne. Metla työraportteja. 25:25–32.
Kärkkäinen K. 1991. Itsesiitos, kukintamuuntelu ja sukusiitosheikkous
pohjoisissa mäntypopulaatioissa. Selfing, flowering variation and inbreeding
depression in northern Scots pine populations. Oulu (Finland): Department
of Genetics, University of Oulu.
Lenoir J, Gegout JC, Marquet PA, de Ruffray P, Brisse H. 2008.
A significant upward shift in plant species optimum elevation during the
20th century. Science. 320:1768–1771.
Lenormand T. 2002. Gene flow and the limits to natural selection. Trends
Ecol Evol. 17:183–189.
Loarie SR, Duffy PB, Hamilton H, Asner GP, Field CB, Ackerly DD. 2009.
The velocity of climate change. Nature. 462:U1052–U1111.
Lynch M. 1996. A quantitative-genetic perspective on conservation issues.
In: Avise JC, Hamrick JL, editors. Conservation genetics. Case histories
from nature. New York: Chapman and Hall. p. 471–501.
Lynch M, Lande R. 1993. Evolution and extinction in response to
environmental change. In: Kareiva PM, Kingsolver JG, Huey RB, editors.
Biotic interactions and global change. Sunderland (MA): Sinauer. p. 234–250.
McLachlan JS, Clark JS, Manos PS. 2005. Molecular indicators of tree
migration capacity under rapid climate change. Ecology. 86:2088–2098.
Mikola J. 1982. Bud-set phenology as an indicator of climatic adaptation of
Scots pine in Finland. Silv Fenn. 16:178–184.
Mimura M, Aitken SN. 2007. Adaptive gradients and isolation-by-distance
with postglacial migration in Picea sitchensis. Heredity. 98:224–232.
535
Journal of Heredity 2011:102(5)
Mimura M, Aitken SN. 2010. Local adaptation at the range peripheries of
Sitka spruce. J Evol Biol. 23:249–258.
Muller MH, Leppälä J, Savolainen O. 2008. Genome-wide effects of
postglacial colonization in Arabidopsis lyrata. Heredity. 100:47–58.
Müller UC, Pross J, Bibus E. 2003. Vegetation response torapid climate
change in Central Europe during the past 140,000 yr based on evidence
from the Furamoos pollen record. Quat Res. 59:235–245.
Rehfeldt GE, Tschebakova NM, Parfenova YI, Wykoff WR, Kuzmina NA,
Milyutin LI. 2002. Intraspecific responses to climate in Pinus sylvestris.
Global Change Biol. 8:912–929.
Reich PB, Oleksyn J. 2008. Climate warming will reduce growth and
survival of Scots pine except in the far north. Ecol Lett. 11:588–597.
Savolainen O. 1996. Pines beyond the polar circle: adaptation to stress
conditions. Euphytica. 92:139–145.
Naydenov KD, Senneville S, Beaulieu J, Tremblay FM, Bousquet J. 2007.
Glacial vicariance in Eurasia: mitochondrial DNA evidence from Scots pine
for a complex heritage involving genetically distinct refugia at mid-northern
latitudes and in Asia Minor. BMC Evol Biol. 7:233.
Savolainen O, Bokma F, Garcı́a-Gil MR, Komulainen P, Repo T. 2004.
Genetic variation in cessation of growth and frost hardiness and
consequences for adaptations of Pinus sylvestris to climatic changes. For
Ecol Manag. 197:79–89.
Notivol E, Garcı́a-Gil MR, Alia R, Savolainen O. 2007. Genetic variation of
growth rhythm traits in the limits of a latitudinal cline of Scots pine. Can J
For Res. 37:540–551.
Savolainen O, Pyhäjärvi T, Knürr T. 2007. Gene flow and local adaptation
in forest trees. Annu Rev Ecol Evol Syst. 37:595–619.
Oleksyn J, Tjoelker MG, Reich PB. 1998. Adaptation to changing
environment in Scots pine populations across a latitudinal gradient. Silv
Fenn. 32:129–140.
Olsson K, Ågren J. 2002. Latitudinal population differentiation in
phenology, life history and flower morphology in the perennial herb
Lythrum salicaria. J Evol Biol. 15:983–996.
Pamilo P, Savolainen O. 1999. Post-glacial colonization, drift, local
selection and conservation value of populations: a northern perspective.
Hereditas. 130:229–238.
Parmesan C. 2006. Ecological and evolutionary responses to recent climate
change. Annu Rev Ecol Evol Syst. 37:637–669.
Pensa M, Sepp M, Jalkanen R. 2006. Connections between climatic variables
and the growth and needle dynamics of Scots pine (Pinus sylvestris L.) in
Estonia and Lapland. Int J Biometeorol. 50:205–214.
Pessi A-M, Pulkkinen P. 1994. Temporal and spatial variation of airborne
Scots pine (Pinus sylvestris) pollen Grana. 33:151–157.
Petit RJ, Aguinagalde I, de Beaulieu J-L, Bittkau C, Brewer S, Cheddadi R,
Ennos R, Fineschi S, Grivet D, Lascoux M, et al. 2003. Glacial refugia:
hotspots but not melting pots of genetic diversity. Science. 300:1563–1565.
Petit RJ, Hampe A. 2005. Conserving biodiversity under climate change: the
rear edge matters. Ecol Lett. 8:461–467.
Saxe H, Cannell MGR, Johnsen B, Ryan MG, Vourlitis G. 2001. Tree and
forest functioning in response to global warming. New Phytol.
149:369–399.
Seppä H. 1996. Post-glacial dynamics of vegetation and tree-lines in the far
north of Fennoscandia. Fennia. 174:1–96.
Sinclair WT, Morman JD, Ennos RA. 1999. The postglacial history of Scots
pine (Pinus sylvestris L.) in western Europe: evidence from mitochondrial
DNA variation. Mol Ecol. 8:83–88.
Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ,
Collingham YC, Erasmus BFN, de Siqueira MF, Grainger A, Hannah L,
et al. 2004. Extinction risk from climate change. Nature. 427:145–148.
Turesson G. 1922. The genotypical response of the plant species to the
habitats. Hereditas. 3:211–350.
van Rossum F, Prentice HC. 2004. Structure of allozyme variation in nordic
Silene nutans (Caryophyllaceae): population size, geographical position and
immigration history. Biol J Linn Soc. 81:357–371.
Varis S, Pakkanen A, Galofré A, Pulkkinen P. 2009. The extent of southnorth pollen transfer in Finnish Scots pine. Silv Fenn. 43:717–726.
Vorren KD, Alm T, Mørkved B. 1996. Holocene pine (Pinus sylvestris L.)
and grey alder (Alnus incana Moench.) immigration and areal oscillations in
central Troms, northern Norway, and their palaeoclimatic implications.
Paleoclimate Res. 20:271–291.
Pujol B, Pannell JR. 2008. Reduced responses to selection after species
range expansion. Science. 321:96.
Wachowiak W, Balk P, Savolainen O. 2009. Search for nucleotide
diversity patterns of local adaptation in dehydrins and other cold-related
candidate genes in Scots pine (Pinus sylvestris L.). Tree Genet Genomes.
5:117–132.
Pyhäjärvi T, Garcı́a-Gil MR, Knürr T, Mikkonen M, Wachowiak W,
Savolainen O. 2007. Demographic history has influenced nucleotide
diversity in European Pinus sylvestris populations. Genetics. 177:1713–1724.
Wilczek AM, Burghardt LT, Cobb AR, Cooper MD, Welch SM, Schmitt J.
2010. Genetic and physiological bases for phenological responses to current
and predicted climates. Philos Trans R Soc B Biol Sci. 365:3129–3147.
Pyhäjärvi T, Salmela M, Savolainen O. 2008. Colonization routes of Pinus
sylvestris inferred from mitochondrial DNA. Tree Genet Genomes. 4:247–254.
Willis KJ, van Andel TH. 2004. Trees or no trees? The environments of
central and eastern Europe during the last glaciation. Quatr Sci Rev.
23:2369–2387.
Petit RJ, Hu FS, Dick CW. 2008. Forests of the past: a window to future
changes. Science. 320:1450–1452.
Ranta H, Pessi A-M. 2010. The Finnish pollen bulletin. Turku (Finland):
Aerobiology Unit, University of Turku, Finland.
Ranta H, Sokol C, Hicks S, Heino S, Kubin E. 2008. How do airborne and
deposition pollen samplers reflect the atmospheric dispersal of different
pollen types? An example from northern Finland. Grana. 47:285–296.
536
Received April 29, 2011; Revised May 17, 2011;
Accepted May 18, 2011
Corresponding Editor: David Rand