# Are forest trees genetically resilient?

Antoine Kremer, Jun Chen, Martin Lascoux

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Antoine Kremer, Jun Chen, Martin Lascoux. Are forest trees genetically resilient?. 2024. hal-04775124

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1 Are forest trees genetically resilient?

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3 Antoine Kremer¹, Jun Chen², Martin Lascoux³

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5 ¹UMR BIOGECO, INRAE, Université de Bordeaux, Cestas 33612, France

6 ²College of Life Sciences, Zhejiang University, Hangzhou 310058, China

7 ³Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala SE-75236, Sweden

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9 Authors for correspondence: Antoine.Kremer@inrae.fr, Martin.Lascoux@ebc.uu.se

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12 Keywords: Forest trees, genetic resilience, Quaternary, local adaptation, gene flow, effective population size

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Abstract

Forest trees are foundation species of many ecosystems and are challenged by global
environmental changes. We assemble genetic facts and arguments supporting or undermining
resilient responses of forest trees to those changes. Genetic resilience is understood here as
the capacity of a species to restore its adaptive potential following environmental changes
and disturbances. Importantly, the data come primarily from temperate tree species with
large distributions and consider only marginally species with small distributions. We first
examined historical trajectories of trees during repeated climatic changes. Species that
survived the Pliocene-Pleistocene transition and underwent the oscillations of glacial and
interglacial periods were equipped with life history traits enhancing persistence and
resilience. Evidence of their resilience also comes from the maintenance of large effective
population sizes across time and rapid microevolutionary response to recent climatic events.
We then review genetic mechanisms and attributes shaping resilient responses. Usually
invoked constraints to resilience, such as genetic load or generation time and overlap, have
limited consequences or are offset by positive impacts. Conversely, genetic plasticity, gene
flow, introgression, genetic architecture of fitness-related traits and demographic dynamics
strengthen resilience by accelerating adaptive responses. Finally, we address the limitations
of this review and highlight critical research gaps.

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36 **Introduction**

37 All organisms have experienced repeated climate changes and environmental disturbances
38 during their evolutionary history and this constitutes a natural testing ground of their
39 resilience. Resilience is a broadly used word these days and a definition is in order here to
40 avoid misunderstandings. We extend Holling's broad definition of ecosystem resilience
41 (Holling, 1973) and of the forest resilience concepts (Anderson-Teixeira et al., 2013; Nikinmaa
42 et al., 2020) to the genetic level of forest trees, as the capacity of a woody species to withstand
43 or to recover from adverse ecological conditions and disturbances by maintaining its adaptive
44 potential. Such constraints can be generated by either extreme events (e.g. earthquakes, frost
45 spells, droughts, windstorms, pest outbreaks) or result from steadily increasing stress due to
46 biotic or abiotic continuous directional changes. Whatever the cause, a resilient species would
47 be more likely to avoid extinction during adverse ecological periods and recover and thrive as
48 more favourable conditions return. Importantly, our understanding of resilience does not
49 assume return to the pre-disturbance state of the species, but its capacity to evolve and
50 eventually adapt to post-disturbance conditions. Evolutionary trajectories leading to
51 resilience thus encompass genetic rescue by natural means and adaptation and bring into play
52 genetic as well as demographic processes. Concerns about resilience are today raised most
53 often for trees in the context of climate change (Dymond et al., 2014; Nikinmaa et al., 2024).

54 It has become common place to state that trees, in general, and forest trees, in particular, are
55 ill-equipped to face climate change, the main argument being that their long generation-time
56 will prevent them from adapting fast enough to rapid climate change (Aitken et al., 2008;
57 Bisbing et al., 2021), although earlier reports supported rapid microevolution (Petit & Hampe,
58 2006; Kremer, 2006). Concerns were further reinforced by reports of increasing forest tree
59 mortalities following repeated drought events (Allen et al., 2015; Changenet et al., 2021;
60 George et al., 2022). In this review, we attempt to assemble genetic facts and arguments
61 supporting or undermining resilient responses of trees primarily on species of the Northern
62 Hemisphere.

63 It is important to state outright that we are in no way questioning the need to take urgent
64 actions against ongoing climate change. Also, it is worth stressing that, while emphasis is on
65 resilience to climatic change, forest trees also have to be resilient to a host of biotic factors.
66 As a matter of fact, as witnessed by the ash dieback in Europe or the chestnut blight dieback
67 of the American chestnut, some of the greatest recent threats experienced by forest trees did
68 not come from climate change but from the spread of diseases and pests. However, genetic
69 characteristics of trees that allow for rapid adaptation to climate change should also facilitate
70 adaptation to biotic agents of selection.

71 Our review proceeds in two steps. In a first part we will draw lessons from the past. Trees have
72 experienced dramatic and repeated climatic changes during the late Pleistocene at different
73 time scales (Rull, 2020; Huntley et al., 2023) and their trajectories have been well
74 reconstructed using complementary disciplines such as palynology, phylogeography and
75 population genetics (Petit et al., 2005; Gavin et al., 2014; Birks & Tinner, 2016; De Lafontaine
76 et al., 2018; Milesi et al., 2024). What does the evolutionary history of individual tree species
77 tell us? Were forest trees particularly vulnerable during adverse climatic periods? Can one
78 observe shared features of tree responses to climatic changes, or, instead, were those
79 responses to climate change primarily idiosyncratic? We will focus on species of the Northern
80 hemisphere and, more specifically, on Europe as it was strongly affected by glaciation and
81 since this is the part of the world we are most familiar with, but we will also consider other
82 geographic areas, especially when those offer an interesting contrast with Europe.
83 Importantly, we mostly did not consider large groups of tree species, such as insect pollinated
84 tropical trees which often have limited distributions, and to which some of our conclusions
85 may not apply. With a few exceptions (Eucalypts and acacias sensu largo), these species
86 remain understudied in view of their ecological importance.

87 In a second part, we will revisit conclusions inferred from contemporary studies of key genetic
88 mechanisms either constraining or shaping resilient responses across spatio-temporal scales.
89 Large genetic surveys have been conducted during the last decades in widely distributed tree
90 species highlighting contrasting distribution of neutral and adaptive diversity across ecological
91 gradients (Alberto et al., 2013; Leites & Benito Garzon, 2023). Similarly, genetic and genomic
92 studies, both intensive and comparative, conducted in breeding and natural populations have
93 enriched our understanding of the genetic, mating and dispersal systems of trees and their
94 functioning in different ecological settings (Austerlitz et al., 2004; González-Martínez et al.,
95 2006; Savolainen et al., 2007). What have we learned from different species about the factors
96 that may have triggered or limited resilience? Which evolutionary processes are at stake
1. Lessons from the past

100 1.1. Legacies of the Pleistocene

101 Woody floras underwent severe climatic and macroecological events since the late Pliocene.
102 In the northern hemisphere, these climatic fluctuations resulted in a succession of extinctions
103 followed by repeated sequences of extreme demographic expansions and contractions of the
104 remaining species. At the Pliocene-Pleistocene transition (around 2.58 million years ago
105 (Mya)) the climate in the northern hemisphere changed dramatically with the onset of the
106 glacial-interglacial periods, resulting in large-scale extinction of trees, especially in Europe
107 (Rull, 2020). The modern flora represents less than 30% of the tree genera present during the
108 Tertiary (Latham & Ricklefs, 1993; Eiserhardt et al., 2015) and species that went extinct were
109 widespread before their disappearance (Magri et al., 2017). During and following these
110 extinctions, the remnant species retracted and expanded their distributions in response to the
111 oscillations of glacial and interglacial periods.

112 While extinctions selectively eliminated cold sensitive species (Svenning, 2003), an additional
113 selective filtering took place in the aftermath of extinction. Post extinction scenarios involve
114 replacement and diversification dynamics associating expansion of pre-existing species,
115 evolution of new taxa and invasion by non-local species (Jablonski, 2001; Jablonski, 2008). In
116 the case of the Plio-Pleistocene (5 Mya to about 12 kya) extinction of trees, replacement
117 dynamics with pre-existing species sharing invasiveness attributes dominated. Indeed,
118 surviving species rapidly colonized southern Europe, as the overall forested area had only
119 slightly decreased during the extinction (Magri et al., 2017), thus suggesting expansion of pre-
120 existing local species. These new species shared invasiveness attributes such as prolificity,
121 competitive ability, dispersal (Lamarque et al., 2011) that facilitated the replacement of the
122 extinct species. Indeed tree genera (Carya, Tsuga, Liquidambar, Cathaya, ..) that disappeared
123 from Europe during the Gelasian-Calabrian (2.8 Mya to 0.8 Mya) were predominantly replaced
124 during the Mid Pleistocene by species such as Quercus, Fagus, Betula, Carpinus, Pinus and
125 Picea, that still occupy most of Central and Northern Europe today (Combourieu-Nebout et
126 al., 2015; Magri et al., 2017).
During extinctions and afterwards, these genera were further reinforced by additional selective drivers triggered by orbitally forced range dynamics (ORD, (Dynesius & Jansson, 2000)). ORD refer to the succession of expansion/retraction range changes due to recurrent sequences of glacial-interglacial cycles. More than fifteen sequences paved the Pleistocene with frequent (periodicity of 41 kya) and with low climatic amplitude cycles during the early phase (2.6 Mya to 1.8 Mya), gradually followed by less frequent (periodicity 100ka) but with high amplitude cycles since the mid Pleistocene (Head & Gibbard, 2015). ORD selective drivers increased with the severity and the amplitude of the latter cycles and favored fast colonizing, vagile and generalist species (Dynesius & Jansson, 2000; Jansson & Dynesius, 2002). High vagility, fertility and colonizing ability lead to increased migration rates and thereby facilitate demographic expansion. Low specialization also facilitates site capture and rapid establishment in new suitable habitats. Both vagility and broad niche contribute ultimately to the wide distribution of species. These inferences are supported by palynological records of the last interglacial period that also highlight high migration velocities (Giesecke et al., 2017; Giesecke & Brewer, 2018). According to these authors, tree migration was «faster than the predicted mean velocity of climate change (Loarie et al., 2009)» reconstructed for the same period. Evidence of selection for rapid establishment and site capture comes from present monitoring of tree recovery in agriculture abandoned field land or other degraded areas. In these studies, the woody communities colonizing new areas are predominantly composed of early successional species and establishment is extremely rapid, typically within a few decades (Wright & Fridley, 2010; Rehounková et al., 2018).

Finally, there are two additional and more recent historical facts that reinforce the hypothesis of selection for climatic resilience during the Pleistocene (2.58 Mya to 11,650 ya) extinction and the subsequent ORD episodes. First, extinctions were rare during the most recent glacial-interglacial cycles-during the Middle (1.25 Mya to c. 129 kya) and Late Pleistocene (from c. 129 kya and c. 11,700 ya), i.e. after the extinction crisis of the early Pleistocene (close to 2.58 Mya), which affected relictual genera such as Zelkova (Jasinska et al., 2022) or Pterocarya (Corrado & Magri, 2011). Second, surviving species to the extinction and to ORD episodes demonstrated resilient responses during abrupt and short climatic changes that occurred within the interglacial periods. There are at least four reported abrupt changes reported during the current interglacial period (Bölling (warming), Alleröd (warming) /Bölling-Alleröd,
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14,700 ya – 12,900 ya), Older Dryas (cooling, c. 14,000 ya) and Younger Dryas (cooling, (c.

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12,900 ya–11,650 ya)), with large climatic amplitude over a few hundred years (Peteet, 2000).

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Very rapid vegetation responses including local disappearance and substitution of local woody

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species, were observed, followed by rapid recovery of the original species (Tinner & Lotter,

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2001; Cole, 2010). In summary, a large body of biogeographical data support the sorting of

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species equipped with life history traits enhancing persistence and resilience during the early

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and late Pleistocene as a result of extinctions and ORD episodes.

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## 1.2. Maintenance of the effective population size across time

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Another source of evidence about the resilience of forest trees to past climate change comes

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from recent studies inferring change in effective population size ($N_e$) over time (see Box 1 and

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(Nadachowska-Brzyska et al., 2015) for estimation of $N_e$, and for what $N_e$ is and what it is not).

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Many studies have estimated changes in $N_e$ over time in forest trees using one of the methods

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mentioned in Box 1. Of particular interest are comparative studies. Estimates of $N_e$ obtained

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for seven major European forest tree species with StairwayPlot2, showed a continuous

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increase over time (Figure 1, Milesi et al., 2024). For some species, for instance *Quercus*

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*petraea* and *Fagus sylvatica*, this time period extended very far back in time (up to 15 Mya in

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*Quercus petraea*). And they both had a very large current $N_e$, especially *Quercus petraea*

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(800,000). Interestingly, $N_e$ trajectories could be clustered into three groups, suggesting that

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they were not entirely determined by environmental factors. Scots pine was part of these

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seven species and was analysed independently by Bruxaux et al. (2024) who, using a large,

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rangewide sampling, also observed an overall increase in estimates of $N_e$ obtained with

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StairwayPlot 2 over a period of 1 Mya. As for *Quercus* and *Fagus*, recent $N_e$ was generally very

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large ($5 \times 10^5-10^6$). In oaks, a large and rather stable $N_e$ does not seem to be specific to *Q.*

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*petraea* as a similar pattern was also observed in other oak species, in North America (*Q.*

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*lobata*; Sork et al., 2022) and East Asia (*Q. acutissima*; Fu et al., 2022). Helmstetter et al. (2020)

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also estimated temporal changes in $N_e$ with the StairwayPlot2 method on three palm and four

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Annonaceae species from West Africa tropical forests. Again, $N_e$ trajectories were strongly

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species dependent, suggesting that they were not entirely determined by environmental

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factors. Interestingly, the $N_e$ of the three palm species, all of which had large $N_e$ (up to
500,000), increased continuously over the time period under which $N_e$ values were estimated.

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Finally, Bai et al. (2018) used PSMC to estimate the change in $N_e$ for 11 temperate *Juglans*

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(walnut) species. As in the two previous studies the different species did not react similarly to
the climatic oscillations following the early Pleistocene cooling and species-specific factors
seemed to have played a prominent role. However, in this case, most species exhibited a
decline in N<sub>e</sub>, but there was a large variation in the importance of N<sub>e</sub> decline. In summary,
these widely distributed species tree species appear to have been very resilient to past
environmental changes, as suggested by the maintenance of their large effective population
size. Finally, it should be pointed out that, another indirect source of evidence for the
maintenance of fairly large long-term N<sub>e</sub> and weak random genetic drift is the large number
of shared polymorphisms observed across related species, even in species that diverged long
time ago and are today found on different continents (e.g. Chen et al., 2010).

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1.3. Rapid tree microevolution

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A long-standing question and nowadays recurrent concern about the resilience of forest trees
is the pace of microevolution in response to on-going climate change. Considerable research
has been conducted in common gardens (a.k.a. provenance tests) of trees highlighting
extensive genetic differentiation between populations for quantitative traits, some of which
might be related to fitness (Langlet, 1971; Wright, 1976). One century of provenance tests
research has amply confirmed that tree populations are locally adapted across different
biomes of the Northern hemisphere (Leites & Benito Garzon, 2023). Notably, trees exhibit
striking genetic clines for growth and phenological traits along climatic gradients
(Morgenstern, 1996; Sáenz-Romero et al., 2019) suggesting adaptive responses to climatic
changes. Provenance research corresponds to synchronic approaches to assess genetic
variation. Provenance tests afford estimates of population differentiation between extant
populations, but they do not provide assessment of the rate of microevolution resulting in
population differentiation (Hendry & Kinnison, 1999). While most temperate European tree
populations are in place since several millennia (Giesecke et al., 2017; Giesecke & Brewer,
2018), no genetic diachronic approach allowed the estimation of the time frame needed to
achieve local adaptation. Did trees evolve gradually over several generations during the post-
glacial period or did adaptation proceed over much shorter periods as short temporal pulses?
There is indirect evidence that trees were able to adapt gradually. For instance, Li et al. (2022)
analyzed a contact zone separating the two main genetic clusters of Scandinavian populations
of Norway spruce. Under the Last Glacial Maximum (18,000 ya) Scandinavia was covered by
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ice. As the ice melted away, trees (and other organisms) recolonized Scandinavia from both
the North and the South leading to the current contact zone. The latter matches very closely
the border between the two main Köppen climate regions of Scandinavia suggesting that the
contact zone was shaped and maintained by selection, something that was confirmed by
selection tests (Li *et al.* (2022)). Because the trees recolonized Scandinavia some 8000-12000
ya, and assuming a generation time of at least 50 years, these data suggest that the pattern
of local adaptation to the main climatic regions and the establishment of the contact zone
took place over, at most, a few hundred generations. Of course, part of this pattern of local
adaptation likely also reflects some levels of pre-adaptation in the trees that recolonized
Scandinavia.

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Were trees also able to adapt during shorter time scales? Longitudinal temporal monitoring
of genetic changes in trees remain an experimental challenge due to their long generations
and has been discarded in the past. Access to ancient DNA has overcome these constraints,
but fails for the time being to recover data at the level of whole populations (Wagner *et al.*,
2018; Wagner *et al.*, 2024). Dendroecological studies based on tree ring analysis, although
retrospective, do not take into consideration the temporal demographic changes (mortalities)
as they are conducted on surviving trees. Furthermore, they do not allow separating genetic
from plastic responses to environmental changes. Despite experimental constraints to track
temporal evolutionary changes, there are a few emerging results that indicate that adaptive
processes are active at ecological time scales (a few centuries). A first series of data provide
estimates of population differentiation between populations that were recently separated
from their known common source population. Typical examples of such cases correspond to
population transfers by human intervention, as the introduction of North American species in
Europe during the last two centuries (Krumm & Vitkova, 2016). When the introduced
populations were compared to their source populations in common garden experiments,
significant genetic differences of fitness related traits suggested that natural selection was the
most parsimonious explanation to the recent divergence observed (Daubree & Kremer, 1993;
Kremer & Hipp, 2020). Although these differences were detected between modern extant
populations, the very recent divergence provide evidence that adaptive evolution can occur
over a very few generations.

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More recent diachronic approaches combining genomic and phenotypic surveys have confirmed these conclusions. In two recent studies (Saleh et al., 2022; Caignard et al., 2024), temporal genetic changes were assessed in multi-centennial oak trees during the transition between the Little Ice Age (1450-1850) and the Anthropocene warming (1850-today) (Box 2). The Little Ice Age was a cold period with repeated extreme winters documented by historical reports of tree mortalities and damages (Fagan, 2002). Temperatures increased afterwards by more 1.5°C to present times (Pfister & Wanner, 2021). Significant temporal genetic changes were found during the transition between the cold Little Ice Age and the Anthropocene warming at the genomic and phenotypic level (Box 2). There are three lessons to be learned from this retrospective analysis regarding the pace of microevolution. First, evolution was rapid as changes were detectable on an ecological timescale. Second, evolutionary changes fluctuated in response to climatic transition as the direction of genetic changes switched in opposite direction between the Little Ice Age and the Anthropocene warming. Third, the genomic imprint of genetic changes was distributed over the whole genome with limited allelic frequency shifts at a large number of SNPs. Furthermore evidence of rapid and directional genetic changes was underpinned by diachronic observations conducted over two successive generations in oaks at contemporary time scales (Alexandre et al., 2020). Taken together, these findings suggest that adaptation is tracking very closely climatic changes and could thereby contribute to tree resilience to environmental changes.

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## 2. Lessons from the present

### 2.1. Limited impacts of genetic load and inbreeding depression

Inbreeding and inbreeding depression can severely decrease the adaptive potential of a species. Many surveys have shown that long-lived perennials, such as forest trees, have higher levels of inbreeding depression than annuals and shrubs (Lesaffre & Billiard, 2021). Indirect estimates of the measure of inbreeding depression ($\delta \equiv 1-w_i/w_o$ where $w_i$ and $w_o$ are the fitness of inbred and outbred individuals), amounted respectively to 0.24 for short-lived herbaceous, to 0.53 for long-lived herbaceous and to 0.66 for woody species (Duminil et al. 2009). Inbreeding depression is particularly high and well documented in conifers (Williams & Savolainen, 1996). It is still disputed whether inbreeding depression is higher in long-lived
perennials than in annuals because they accumulate more somatic mutations or because inbreeding depression is expressed across multiple life stages, but recent surveys of genome-wide molecular variation indicate that long-lived outcrossing perennials tend to accumulate more deleterious mutations than short-lived ones (Chen et al. 2017). These authors calculated 0- and 4-fold pairwise nucleotide site diversity, $\pi_0$ and $\pi_4$, respectively. 0-fold nucleotide diversity is a proxy of nonsynonymous changes in protein coding sequences while 4-fold pairwise nucleotide site diversity, is a proxy of synonymous diversity. The former is assumed to be under selection while the latter evolves under neutrality. Those pairwise nucleotide diversities were then used to calculate the ratio of 0-4 fold nucleotide diversity, $\pi_0/\pi_4$, which provides a good measure of the efficiency of selection in purging deleterious mutations. In trees (outcrossing long-term perennials), estimates of $\pi_0/\pi_4$ were significantly higher than the value observed in outcrossing annuals and at similar level to selfing annuals and selfing short-term perennials (Figure 2).

Since, under the nearly neutral theory (Ohta & Gillespie 1996), $\pi_0/\pi_4$ decreases with effective population size, one might have expected to observe relatively low values in trees. Independently of its source and causes of its maintenance, the high genetic load observed in many forest tree species should limit their evolutionary potential, particularly in marginal populations where the genetic load is expected to be higher than in central ones. However, this is not observed in broadly distributed tree species, such as Quercus petraea or Picea abies, where the ratio $\pi_0/\pi_4$ varies little across populations (James et al., 2023). This may be a consequence of gene flow linking marginal and central populations and/or of the fact that the current values of $\pi_0/\pi_4$ are more closely associated to the deeper part of gene genealogies, which is shared across populations than to the most recent part, that is more population specific. At any rate, it appears that the adaptive response and resilience of many forest trees have not been badly affected by the presence of the high genetic load observed across the species range. Possibly, the very large number of offspring produced during a tree's lifetime and the strong selection at the seedling stage combine to make the genetic load bearable.

## 2.2. Mixed effects of overlapping and long generation intervals

Long and overlapping generations have mixed effects on the resilience of trees. When forest stands are renewed either by natural means or by human interventions under even or uneven management regimes, seedlings are produced by open matings between adult trees.
However, the age of parent trees varies between seed trees and pollinating trees. The former are composed by the oldest trees of the population just prior to their removal after natural death or by artificial cutting, while the latter are part of all surrounding trees producing pollen which are trees of different ages starting from sexual maturity. As a result the age at reproduction, for seed trees and pollen trees, exceeds the age at first breeding and the generation interval is no longer the age when parent trees first reproduce, but becomes the average age of parent trees at the birth of their offspring (Bijma & Wool Williams, 1999). While generation time has rarely been estimated precisely in trees (Petit & Hampe, 2006), this, nonetheless, means that generation interval in many temperate forest trees may exceed 100 years. Thus, generation times of most tree species outpace by far the IPCC time frame of climatic predictions, and the predicted genetic changes needed to meet climate requirements exceed the known rate of past microevolution. This is why long generation interval is recurrently claimed as a major limitation of tree evolution to match the velocity of climate change (Kremer, 2007; Aitken et al., 2008). Evolutionary constraints generated by this reduced generation turnover have been highlighted in simulation studies under climate change scenarios (Kuparinen et al., 2010), where the rate of evolutionary change in two target species (*Betula pendula* and *Pinus sylvestris*) deviated continuously from the rate of climatic change, leading to an increasing adaptational lag. Under the simulation assumptions, the removal of adult trees changed this trend and facilitated adaptive evolution to climate change. Furthermore, long generation time in trees is accompanied by overlapping generations which also have evolutionary consequences in the context of climate change, especially when combined with long generation times. More generally, there are at least five evolutionary consequences of long and overlapping generations. Some are potentially positive, and other negative for tree resilience. Let us start with the negative effects. (i) Overlapping generations lead to a decrease in effective population size, *N*<sub>e</sub>, compared to the effective size expected under the classical Wright-Fisher model with non-overlapping generations (Caballero 2020; Nunney 1993; Wakeley 2009). Under neutrality, Nunney (1993) concluded that, under fairly general conditions, when the average generation time in an age-structured population is lengthened then *N*<sub>e</sub> approaches N/2, where N is the number of adults. So, everything else being equal, overlapping generations should lead to a lower genetic diversity than would have been observed had the species been an annual following the Wright-Fisher model. (ii) Long generation time implies that generation turnover is limited and thus recombination cycles
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which promote new allelic associations prone to selection are reduced. (iii) Generation
overlap implies crossings between parent trees belonging to different age cohorts and thus
generates temporal gene flow. Under continuous directional climatic variation with time,
fitness of age-structured cohorts is likely to vary linearly with age, older trees exhibiting lower
fitness than younger cohorts (Caignard et al., 2024). Thus, temporal gene flow will increase
the adaptational lag due to the maintenance of long generation intervals

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However, generation overlap can also have positive effects. (i) First, generation overlap can act as a reservoir of genetic variation, as multiple age cohorts that underwent different selection regimes during their lifetime are maintained. This temporal variation can create ecological niches even in the absence of spatial variation in selection pressure and lead to a so-called "storage effect" that contributes to the maintenance of genetic variation (Ellner & Hairston Jr, 1994; Svardal et al., 2015). Under fluctuating selection, this will increase the overall genetic variation of the population (Ellner & Hairston Jr, 1994; Yamamichi et al., 2019) and thus enhance selection responses. (ii) Second, generation overlap and long generations decrease the effect of drift during colonization (Austerlitz et al. 2000). During colonization, overlapping generations will basically reduce founder effects. Because of the length of the juvenile phase, a newly established population will grow through the arrival of new migrants. This will increase the number of founders and therefore decrease the founder effect (Austerlitz et al., 2000). Interestingly, both simulations (Austerlitz et al., 2000) and experimental data in long lived semelparous species (species that reproduce once in their lifetime and then die) (Liu et al., 2024), indicate that it is really the overlapping generation and not only the long generation times that lead to this effect: the semelparous species *Puya raimondii* stays in a rosette form until it reaches around 60 years and produces a massive inflorescence and, shortly after that, dies. In contrast to what is observed in most forest tree species, a recent genomic study showed that drift in such species is very strong – at any rate much stronger than in its relative, *P. macrura*, which is iteroparous – and population differentiation very pronounced (Liu et al., 2024).

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## 2.3. Genetic architecture of fitness related traits facilitates rapid evolution

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The genetic dissection of fitness related traits in trees has considerably improved our
understanding of how adaptive variation builds up and evolves in natural populations and
contributes to their resilience. Genetic dissection breaks down phenotypic traits into the

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number, frequency, effect size and genomic distribution of genes resulting in the genetic architecture of traits. Three major results have emerged from studies linking genetic architecture to adaptive variation in trees. First, QTL (Quantitative Trait Loci) detection in segregating populations and GWAS (Genome-Wide Association Studies) in natural populations confirmed that most adaptive traits are controlled by a large number of genes, typically amounting to several hundreds, leading to a polygenic architecture (Hall et al., 2016). Second, the genetic variation of adaptive traits fuelling local adaptation builds on minor contribution of variation at each single gene and a much larger contribution of the covariation among the different genes (Le Corre & Kremer, 2003; Le Corre & Kremer, 2012). And third, the multiple associations of different genes contributing to adaptive traits, generate genetic redundancy, i.e. the occurrence of different associations resulting to the same phenotype (Yeaman, 2015; Laruson et al., 2020). To sum up, it is not only the cumulative contribution of single gene effects, but also the contribution of the multiple combinatory associations of genes that underpin adaptive variation. While the former contribution has been supported by numerous results in breeding and natural tree populations, the latter contribution was inferred on the basis of the contrasting observed differentiation between adaptive traits and their underlying genes in trees (Kremer & Le Corre, 2012). The polygenic architecture of adaptive traits, the combinatory effects, and genetic redundancy lead to important consequences on tree population evolution. First, large evolutionary changes in adaptive trait values can be triggered by the standing variation of numerous loci, each one of small effect (Sella & Barton, 2019; Höllinger et al., 2023). Second, effective selection on standing genetic variation can occur over a limited number of generations (Kremer & Le Corre, 2012; Ehrlich et al., 2021). Third, polygenic architecture and genetic redundancy facilitate the maintenance of variation of adaptive traits (Laruson et al., 2020; Bataillon et al., 2022). As a result, adaptive traits with polygenic redundant architecture enhance genetic resilience. Just as functional redundancy insures community resilience at the species level (Biggs et al., 2020), genetic redundancy may trigger genetic resilience at the population level as variable combinations of redundant alleles offer multiple opportunities to reach optimal fitness at short time scales (Ehrlich et al., 2021). Finally, besides genetic redundancy of the architecture of adaptive traits, there is a second level of redundancy that may be considered concerning resilience, which is redundancy at the genome level. While the evolution of the genome of flowering plants is paved by multiple
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phases of genome and gene duplications (Wang *et al.*, 2012), recent whole genome sequences of oak species have highlighted the increased duplication of defence related genes (Plomion *et al.*, 2018; Sork *et al.*, 2022). Enrichment of resistance genes was interpreted as a means to withstand variable biotic selection pressures to which long-lived species such as trees are exposed.

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## 2.4. Synergistic contributions of plastic and genetic effects to adaptive evolution

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Phenotypic plasticity, defined as the capacity of a given genotype to respond differently to environmental conditions has received much attention in trees that are exposed to repeated ecological changes over their lifetime (Chambel *et al.*, 2005). Empirical assessments of plastic responses of trees have mostly been investigated at the population level in multisite common garden experiments (Park & Rodgers, 2023), starting with the discovery of widespread genotype*environment (GE) interactions in most economically important species (Li *et al.*, 2017). Implicitly, the presence of GE interactions unveiled the underlying different responses of populations to site conditions, that are called norms of reaction and modelled as linear (Gregorius & Kleinschmit, 2001) or quadratic functions (Wang *et al.*, 2006) to environmental variables. The slopes (coefficients of the norm of reactions) are the key parameters accounting for the plastic response of the traits. Lessons gained from the assessments of the norms of reaction in multisite common garden experiments can be summarized in four major outcomes. First, the slopes of the norms of reaction at the species or population level are non-zero for most adaptive traits (Chambel *et al.*, 2005; Leites & Benito Garzon, 2023). Second, population differences exist indicating genetic differentiation of plastic responses (Rehfeldt *et al.*, 2002; Sáenz-Romero *et al.*, 2019). Third, genetic variation of plastic responses is maintained within populations (Marchi *et al.*, 2022). Taken together these results indicate that plasticity in trees has a genetic basis and can evolve. However, despite significant differences among populations, the level of genetic differentiation in plasticity among populations remains low and amounts to the magnitude observed for neutral traits in the only known experiment where intra and inter population genetic variation of plasticity were assessed (Soularue *et al.*, 2023). Maintenance of genetic variation and low genetic differentiation among populations of the slope of the norms of reaction suggest that past evolution has generated a «generalist» type response in trees maintained in all populations. Evolution towards an optimum plastic response, where genotypes can reach optimal fitness in all environments, is also predicted by theory for long-lived species experiencing large spatio-temporal environmental heterogeneity and composed of populations connected by extensive gene flow (Scheiner, 2013; Hendry, 2016). The «generalist» type of response increases the ability of populations to persist under
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a wide range of environmental disturbances and thus contribute to their resilience (Ghalambor *et al.*, 2007).

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Finally, empirical results suggest that plastic and genetic variation contribute synergistically to phenotypic evolution of adaptive traits. Covariation of plastic and genetic effects in the same direction is expected when plastic responses to environmental changes ultimately result in increased fitness thus contributing to the persistence of the species under altered conditions (« Baldwin effect », Crispo, 2008). Under this scenario, plasticity first leads to phenotypic changes followed later by genetic changes, but alternative scenarios may occur as well (Crispo, 2008). Whatever the evolutionary sequence in trees, experimental results show that positive covariation of plastic and genetic effects of adaptive traits are more frequent in extant tree populations than negative covariation (Kremer *et al.*, 2014, Box 3). Several contemporary studies of variation in tree growth illustrate the positive covariation of plastic and genetic effects. Large scale surveys of tree growth using increment cores conducted *in situ* indicated steady increase of growth during recent decades due to higher atmospheric CO2 concentration and nitrogen deposits (Maes *et al.*, 2019). Temporal genetic changes assessed in age-structured oak cohorts spanning the last two centuries (Caignard *et al.*, 2024), and genetic changes predicted over two successive generations (Alexandre *et al.*, 2020) showed similar trend for tree growth. In this example phenotypic changes, combining plastic and genetic responses, and genetic changes *per se* covary in the same direction. Monitoring of trait variation conducted *in situ* and in genetic tests (common gardens) exhibit mostly positive covariation of plastic and genetic effects (Box 3). Thus, both sources of variation amplify synergistically phenotypic responses to environmental changes and contribute more efficiently to persistence following perturbations.

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**2.5. Sustained local adaptation despite widespread gene flow within species**

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Most temperate forest trees are anemophilous and able to disperse pollen over long distances. Documented extreme effective pollen dispersal –although rare- may reach hundreds of kilometres and, in Europe, are of the same magnitude as predicted shifts of climate during this century (Kremer *et al.*, 2012). In some species gene flow can also take place by seed as well as via pollen, and in some tree species, e.g. *Sorbus aucuparia*, seed flow may even be more important than pollen flow (Bacles et al. 2004). Under such circumstances, whether gene flow would facilitate or constrain adaptation to ongoing climate change has been a pressing issue that has been addressed recently by theoretical and experimental approaches (Savolainen *et al.*, 2007). From a theoretical standpoint, gene flow generates
conflicting evolutionary trends (Lopez et al., 2008). On the one hand, gene flow homogenizes allele frequencies among populations across space and increases the lag between the extant genetic value of populations and their expected optimal value, thus generating migration load. On the other hand, gene flow increases the standing genetic variation within populations and enhances their response to natural selection. Recent experimental results at a very local scale suggest that the latter effects of gene flow are dominating in ecological settings of closely located populations (Scotti et al., 2023). Notably, adaptive divergence of nearby populations at individual SNPs is not prevented by extensive gene flow that connects close populations. In four conifers with contrasting life history traits, genomic differentiation correlated to local adaptation was maintained between close populations growing under contrasting environmental conditions. Fine scale comparisons of immigrant with local gene pools indicated indeed that within population genetic variation was increased by gene flow and enhanced adaptive differentiation (Gauzere et al., 2020). In the same vein, the ratio π₀/π₄, which measures the efficiency of selection in purging deleterious mutations did not vary across populations in six European forest tree species (James et al., 2023), contrary to expectations that marginal populations would show a higher value than core populations. Altogether these experimental results suggest that gene flow does not constrain adaptive differentiation when divergent selection is strong. Note, however, that the strong short-term response to selection observed at a very local scale may not necessarily translate into high evolutionary rate when large time periods are considered (Messer et al., 2016). A possible explanation is pervasive fluctuating selection as recently suggested by Saleh et al. (2022) in oaks and shown in *Mimulus* by (Kelly, 2022). In the latter, out of 1.8 M SNPs, 1796 SNP showed significant fluctuating selection and 40 significant directional selection, the rest behaving neutrally. Conversely, pollen flow may even amplify adaptation by introducing preadapted genes from distant populations into target populations under a directional shifting climate. Theory shows that in an heterogeneous environment changing linearly in space and time mimicking climate change along a geographic gradient, pollen dispersal will shift the ecological niche of a species to match the moving environmental change, and accelerate the shift for species dispersing pollen at long distances (Aguilée et al., 2016). Although we are lacking experimental results supporting these predictions, beneficial effects of pollen flow are likely to overcome negative effects, considering in addition that airborne pollen production of many tree taxa is stimulated by climatic change (Ziello et al., 2012).
An extreme case of local adaptation in spite of gene flow is provided by Scots pine (Pinus sylvestris). Scots pine has one of the largest natural ranges among forest trees extending from Scotland in the west to Russian Pacific Coast in the east and from the Iberian and Balkans mountain ranges in the south to the Barents Sea to the north. A recent rangewide genomic survey showed that genetic differentiation is weak and genetic diversity high and strikingly uniform across the range (Bruxaux et al., 2024). Similarly, the ratio π₀/π₄, was consistently high and barely varied across populations. Nonetheless, decades of common garden studies (aka provenance tests in the forestry literature) have repeatedly shown evidence of local adaptation. However, in the case of Scots pine, different factors underlie local adaptation in different parts of the range, with temperature playing a major role in the central part of the range, drought-related variables in Spain and photoperiod in Scandinavia (Leites and Benito Garzon 2023). Those regional patterns of local adaptation may, at least in part, explain the weak signal of genotype-environment association detected by Bruxaux et al. (2024) at the range level and, importantly, together with extensive gene flow maintaining the connections among populations, may have contributed to the maintenance of genetic diversity at the species level.

## 2.6. Frequent hybridization in trees enhances adaptive introgression

Both hybridization and introgression have occurred frequently in forest trees and hybridization was found to be positively correlated with perenniality (Mitchell et al., 2019). Hybridization between different species and ensuing generations of backcrossing, i.e. introgression, is one of the most efficient genetic mechanisms to quickly introduce vast amount of genetic variation into the genome of a given species (Soltis, 2013). While the importance of hybridization and introgression in plant species has been recognized for nearly a century, a systematic understanding of both processes in plants has only started over the last decades. A first indication of the importance of hybridization and introgression in plant species was revealed by frequent conflict between chloroplastic and nuclear DNA, and between different nuclear genomic regions when reconstructing phylogenetic trees. However, only recently did the development of large-scale genomic sequencing allowed us to gain a global picture of the importance of historical gene flow on the evolution of whole group of species, such as *Ficus* (Gardner et al., 2023), *Fagaceae* (Zhou et al., 2022), *Salix* and *Populus* (Sanderson et al., 2023), and *Picea* (Karunarathne et al., 2024). Even rare introgressed alleles
can contribute to increase the number of adaptive mutations, that may be in short supply because of small N<sub>e</sub> or low mutation rate. Studies in *Quercus* (Leroy *et al.*, 2020; Fu *et al.*, 2022) have revealed that adaptive introgressed alleles were common across the genome of widely-distributed European and Asian oaks, and that their proportion was influenced by genetic drift and environmental factors (Figure 3). Introgression was affected by genetic divergence between pairs of populations and also by the similarity of the environments in which they live—populations occupying similar ecological sites tended to share the same introgressed regions. Fu *et al.* (2022) further pointed out that i) adaptive introgression did not affect the genes themselves but instead the cis-regulatory elements regulating their expression leading to similar expression profiles of closely related species in the same environment, and that ii) although recombination facilitates the integration of introgressed alleles, suppression of recombination is necessary for the maintenance of adaptive introgressed alleles. Suarez-Gonzalez *et al.* (2016) also identified linked adaptive introgression signals near a telomeric region in two *Populus* species. The suppressed recombination rate may help improve the efficacy of natural selection or reduce the so called ‘segregating load’ by preventing breaking down co-adapted parental alleles (Moran *et al.*, 2021). In summary, while the exact mechanisms underlying adaptive introgression remain to be deciphered, introgression, by increasing the level of genetic diversity and bringing new adaptive alleles, will contribute to the resilience of forest trees.

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## 2.7. Demographic dynamics boost genetic rescue

We have so far focused on genetic factors. As resilience was primarily viewed as an important evolutionary property it made sense to focus on those. However, resilience is also intrinsically a demographic property. And, while we have shown above that empirical genetic and evolutionary evidence indicates that tree populations are prone to resilience, our understanding of how resilience is ultimately achieved remains limited. We are still lacking sufficient historical monitoring across generations to grasp the ecological and genetic mechanisms that triggered the recovery of populations to extreme environmental changes.

The question arises of how tree populations are maintained after repeated sequences of extreme climatic events that may have lethal consequences. The increased occurrence of
extreme climatic events has stimulated worldwide monitoring of tree mortalities (Allen et al., 2015). These reviews concentrated mostly on the abiotic causal drivers of mortality, rather than on the subsequent demographic changes in tree populations. Regional studies confirmed that increasing mortalities followed severe drought episodes in Europe (Senf et al., 2020; George et al., 2022). Reported mortality statistics described extreme spatial and temporal variation. Extant observed mortalities are the consequence of the background mortality pre-existing in the population and the die-off generated by the extreme event, which have different temporal dynamics. Even die-off mortalities exhibit extreme spatio-temporal variation due to tree diversity, and microecological variation. Thus, forest stands undergoing dieback are characterized by the simultaneous persistence of dying and surviving trees, a situation that may subsist over years or decades.

Overall individual tree mortality, and tree population decline following extreme events is a temporal gradual process (Changenet et al., 2021). The Tree Decline Recovery Seesaw model (Whyte et al., 2016) nicely illustrates the long duration during which tree populations maintain a decline status characterized by the coexistence of dying and surviving trees. One-off total tree mortalities are thus exceptions that may occur after fire or gale events but are unlikely the result of other biotic or abiotic events, including recent extreme droughts (as in 2003 or 2018-2019 (Senf et al., 2020)). Canopy opening, resulting from the mortality of adult trees, favors recruitment resulting from open crossing between surviving trees (Martínez-Vilalta & Lloret, 2016). The time period during which partial mortalities will persist under steady state, thus increases opportunities for genetic rescue to proceed by facilitating the renewal of the population. Long distance pollen flow may prevent the break-down of genetic diversity in the recruited seedlings, and thus maintain the adaptive potential in the new generation. Ultimately, as the adult cohort may still be under a steady state decline, the juvenile cohort originating from the surviving adult trees will develop and undergo selective screening under natural selection. Two cohorts following different evolutionary dynamics may then inhabit the same forest: the adult cohort undergoes steady decline while the juvenile cohort, given the higher expected selection intensity in the higher density among the seedlings, undergoes more rapid adaptive shifts to cope with the ongoing environmental changes. The coexistence of both cohorts over longer periods will reinforce the self-replacement as the seedlings may benefit from additional seeding years. In some cases, the two cohorts may be composed of
different species and lead to replacement of the pre-existing species (Cerioni et al., 2024).

However, self-replacement dynamics have also been observed following severe droughts (Margalef-Marrase et al., 2022) but their genetic consequences remain poorly investigated.

Such scenarios combining early expansion of new recruits benefiting from pre-existing genetic diversity will contribute to important adaptive shifts to the ongoing stress episode, while the adult cohort may progressively disappear ("silver-lining" scenario, Coleman&Wernberg, 2020).

## 3. Conclusion

In the present article we have reviewed what is known about forest tree response to past climate changes and showed that species that did survive the Pliocene-Pleistocene transition had biological properties that helped them to survive the oscillations of glacial and interglacial periods that ensued. An important conclusion of this review is that resilience is a hallmark of the northern temperate zone's trees, very likely due to their long history of surviving, even flourishing, through major environmental changes. Even under shorter time periods repeated perturbations and disturbances expose trees to non-equilibrium conditions triggering evolutionary resilient responses, that have been poorly investigated so far. Our evolutionary perspective on trees has been dominated by the ultimate stable climax view of ecological systems, which are unlikely to apply to forest trees inevitably exposed during their lifetime to disturbance regimes. Eventually such disturbance regimes may have led to some of the adaptive processes that we have outlined in the second part of this review.

While we still have a far from complete understanding of the evolutionary mechanisms contributing to forest tree resilience, some salient features have started to emerge. In particular, one key attribute of forest trees contributing to resilience appears to be their ability to combine large populations connected through extensive gene flow with pronounced local adaptation. This combination of features may have, in turn, enabled forest tree species to maintain high genetic diversity and survive their generally high genetic load. Even factors such as long and overlapping generations time may not have only negative consequences on resilience, and the "storage effect" observed under fluctuating selection could also have contributed to the maintenance of genetic diversity. One practical implication of the present review is that gene flow in forest trees is not something we need to worry about as it did not erase local adaptation and may even have contributed to it (Le Corre and Kremer 2012). Finally
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rapid adaptive responses to new selection pressures are indeed expected in populations
combining high levels of standing genetic variation and polygenic architecture of fitness, and
exposed to strong selection intensities (Kremer & Le Corre, 2012; Le Corre & Kremer, 2012).

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As we highlighted in our review tree species share these attributes, and encounter severe
selection intensities during the juvenile phase, thus demonstrating their high evolutionary
potential (Box 4).

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However, our review highlights the lack of understanding of the temporal frames at which
these mechanisms are operating in tree populations. As far as possible, we have distinguished
short term and long-term processes, as inferred from population genetics or synchronic
monitoring in common garden experiments. Temporal dynamics (allochronic approaches) are
needed to grasp the pace at which resilience builds up in comparison to the strength and
velocity of environmental changes. Yet, we illustrated in a case study that microevolutionary
changes could occur rapidly during the transition between the Little Ice Age and the
Anthropocene warming. Ancient DNA studies (a few millennia back in time) in trees may be a
new avenue to explore temporal dynamics at various time scales. While they are still in their
infancy technical breakthroughs will undoubtedly usher a new era in evolutionary biology of
forest trees as it did in humans. A second limitation of our review comes from the focus on
tree species sharing particular attributes, such as wide and continuous distribution, allogamy
and longevity. Because they also share economic importance, their genetics, genomics and
evolutionary biology have been more intensely studied, and were thus preferentially prone
for a review. It may well be that species with contrasting attributes (e.g., scattered vs narrow
distribution, autogamy vs obligate outcrossing, short vs very long lifespan) behave differently.

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Comparative studies that span these life history traits and emergent attributes of species are
needed to gauge the generality of our conclusions. Finally, we have put a bit more emphasis
on genomic studies than on quantitative genetics simply because those allow easier historical
inferences, not because we believe that quantitative genetics is not relevant. On the contrary,
quantitative genetics is certainly going to play a central role in our efforts to understand the
resilience of forest trees. Decades-long breeding programs and provenance tests, national
forest surveys provide a vast trove of comparative data ready to be analysed. Responding to
the urgent conditions presented by ongoing climate change and environmental degradation

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demand that we keep working with these data to understand tree adaptive capacity and
resilience even as we establish new experiments tailored to our evolving questions and needs.

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Finally our conclusions open new avenues to be explored for operational adaptive management in temperate forests. Among the various mechanisms and properties contributing to resilience that we have highlighted, some are intrinsic to species or evolutionary legacies and can hardly be shaped by human interventions, but others can be refined or manipulated through silvicultural practices. For example, the efficiency of natural selection could readily be improved by increasing the density of seedlings during natural seeding by accumulating seedlings over multiple years of fruiting. Thinning operations following early signals of mortalities due to extreme events should avoid clear cuttings or replacement by new species, but, instead, should facilitate renewal by natural regeneration of the declining species. It is out of the scope of this review to go through all potential applications. Instead, the results presented here should be viewed as a modest stepping stone towards more scientifically-based decisions in the management and conservation of tree species.

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**Acknowledgements:** We would like to thank Richard Ennos, Andrew Hipp, Rémy Petit and Outi Savolainen for constructive comments and suggestions on an earlier version of the paper, and Tongzhou Tao for help with drawing Figure 2. ML thanks FORMAS, the Swedish Research Council for sustainable development (Grant Formas 2020-01456) and the Swedish Energy Agency through the Project Tree for ME for support. This study was also supported by the European Research Council through an Advanced Grant (project TREEPEACE # FP7-339728) to AK.

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<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

**Figure 1.** Genetic resilience of seven common European tree species. (A) Change in effective population size ($N_e$) through time (million years ago, Mya), inferred with Stairway Plot 2 (lines, with one-sample-per-population). The median changes in $N_e$ are reported. (B) A zoom-in of (A) focusing on the 0–1.8 Mya period. Blue shaded rectangles delineate periods of glacial advance. (C) Species can be grouped based on their $N_e$-trajectories. Heatmap based on Kendall's correlation coefficients computed from changes in $N_e$ through time between each pair of species. The order of species along the x-axis is the same as that along the y-axis. Blue and red colors represent negative and positive correlation values, respectively. Adapted from Milesi et al. (2024).
<figure><img src="image_5.png" /><figcaption>**Figure 2.** The ratio $\pi_0/\pi_4$, where $\pi_0$ is nucleotide diversity at 0-fold sites (non synonymous) and $\pi_4$ is nucleotide diversity at 4-fold sites (synonymous), differs between combinations of mating system and lifespan. Each dot corresponds to a species. Box limits indicate the range of the central 50% of the data, and the central line marks the median value. The ratio $\pi_0/\pi_4$ is as high in long-term perennials as in annual selfers, suggesting that they accumulate deleterious mutations at the same rate. STP, short-term perennial; LTP, long-term perennial. The list of the species used to draw the Figure is given in additional file piNpiS.xlsx.</figcaption></figure>

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<figure><img src="image_6.png" /><figcaption>**Figure 3.** Distribution of adaptive introgressed SNPs across the genome and their association with environmental factors.</figcaption></figure>

a. Distribution of the number of SNPs under diversifying selection in windows of introgression for *Q. acutissima* 12 chromosomes. The y axis represents the coordinates of chromosomes and the x axis represents the 12 chromosomes.

b. Density distribution of introgression windows with significant evidence of introgression on Chr.9–12. The x axis shows the coordinates of each chromosome that was equally divided into 512 bins and the y axis gives the number of 10 kb sliding windows with significant evidence of introgression. Introgression is estimated by $f_d$, which quantifies the proportion of genomic regions affected by introgression (Martin *et al.* 2005). Each distribution curve corresponds to a population whose name is given at the start of the curve.

c. All four main introgressed regions in Chr.9–12 are enriched with SNPs with frequency significantly associated with environmental/geographical factors (written in bold-face, aligned vertically with each major introgression peak represented in panel b and c). The size of the dots represents mean Bayesian Factor (BF) across all significant SNPs in the window.

Figure adapted from Fu et al. (2022).
1107

1108 **Box 1 Estimating effective population size**

1109

1110 Classically, the effective size of a population, $N_e$, is defined as the size of an idealized
1111 population, typically a so-called Wright-Fisher population, that would produce the same rate
1112 of genetic drift as the population of interest (Wakeley 2009). As pointed out by (Waples, 2022)
1113 this definition is technically correct but its rather abstract nature hides the simpler
1114 dependency of $N_e$ on three main demographic parameters: the number of potential parents,
1115 and the mean and variance in the number of offspring per parent (see also (Caballero, 2020)
1116 ch. 5). These three main parameters will, in turn, be influenced by population structure and
1117 selection. The effective population size will rarely be equal to the census number and it is
1118 therefore important to be aware that estimates of $N_e$ only provide indirect information on
1119 past changes in census number. However, $N_e$ is directly related to genetic variation and to the
1120 efficacy of selection, and is therefore indicative of the evolutionary potential of a species.
1121 There are various approaches to reconstruct changes in $N_e$ over time. They differ primarily in
1122 the source of information they are using and this, in turn, determines the time scale on which
1123 inference can be made. Methods based on linkage disequilibrium will retrieve information on
1124 past $N_e$ over a few hundred generations (GONE, Santiago et al. 2020), while methods based
1125 on the site frequency spectrum (StairwayPlot2 (Liu & Fu, 2020), Fitcoal (Hu et al. 2023)), or on
1126 the distribution of heterozygosity along the genome (PSMC (Li & Durbin, 2011), MSMC2,
1127 Schiffels and Wang 2020, SMC++ (Terhorst et al. 2017) will retrieve $N_e$ trajectories across much
1128 deeper times but will have a low resolution for more recent ones. Finally, it is worth stressing
1129 that all these methods do not explicitly consider population structure. Nor do they consider
1130 introgression from other species. So, while the resulting estimates of $N_e$ are good estimates
1131 of the evolutionary potential of the species at a given point in time they should be interpreted
1132 cautiously in term of demography.

1133
1134 Box 2 Microevolutionary changes during climate transitions

1135 Assessments of temporal genetic changes in forest trees over successive generations are very
1136 rare given the time constraints imposed by long-lived species. In a recent study, genome wide
1137 allelic frequency changes (Δ) were assessed in four different age structured cohorts in sessile
1138 oak (Quercus petraea) even-aged managed forests to track temporal changes during the
1139 transition from the cold period of the Little Ice Age to the warming Anthropocene (from 1680
1140 to 2008). The experiment was repeated in three different forests (Saleh et al., 2022). Under
1141 even-aged silvicultural regimes, natural selection is strongest at the juvenile stage, when more
1142 that 95% of seedlings are eliminated. These age-driven demographic dynamics were the
1143 rationale for using a retrospective monitoring of evolutionary changes based on age
1144 structured cohorts, despite the lack of access to discrete separate generations. To separate
1145 stochastic genetic changes from one cohort to the next (due to genetic drift or other
1146 demographic causes) from systematic changes due to natural selection, covariations of Δ
1147 values were examined over different time periods (for example between Δ<sub>1680-1850</sub> and Δ<sub>1850-1960</sub>.
1148 Under stochastic sources of variation, the covariations (r) are expected to be zero, while
1149 similar systematic sources as natural selection will raise positive values, and opposing sources
1150 will generate negative values (Buffalo & Coop, 2019). The results showed temporal genome-
1151 wide allelic frequency changes of the same sign during the cold period (r<sub>cold</sub> positive) and in
1152 the warm period (r<sub>warm</sub> positive), the two periods being considered separately (Saleh et al.,
1153 2022). Conversely covariations were negative when comparing Δ values between cold and
1154 warm periods (r<sub>cold,warm</sub> negative). These results were further confirmed at the phenotypic level
1155 in common garden experiments in which open pollinated progenies originating from the
1156 different age structured cohorts were compared. In particular genetic changes of height
1157 growth and phenology related traits were reoriented between the cold and warm period
1158 (Caignard et al., 2024). Overall, these results show that microevolutionary changes can occur
1159 over ecological time frames in trees, and that the direction of evolution can change with
1160 climate change.

<figure><img src="image_7.png" /></figure>

1161

1162
1163 Box 3 Positive covariation of plastic and genetic effects in trees

1164 Covariation of plastic and genetic effects can be assessed in trees by comparing genetic and phenotypic
1165 clines in common gardens and *in natura*. When different populations stemming from different
1166 geographic origins are compared under common garden conditions, most adaptive traits exhibit
1167 continuous population variation along some ecological gradient of their origins (Morgenstern, 1996;
1168 Leites & Benito Garzon, 2023). This pattern, called genetic cline, is the consequence of past divergent
1169 selection along the ecological gradient. Genetic clines can be compared to phenotypic clines, resulting
1170 from observations of the same traits made *in natura* along the same ecological gradient, and which
1171 are mostly shaped by plastic responses (Conover & Schultz, 1995; Conover *et al.*, 2009). When both
1172 clines are oriented along the same direction, cogradian variation ensues (Conover *et al.*, 2009) and
1173 plastic effects amplify adaptive genetic variation. However, when the two clines are in opposite
1174 directions, countergradient variation occurs (Conover *et al.*, 2009) and plastic effects then offset
1175 genetic effects. We illustrate co- and counter-gradient variation for growth (panel a and b) and seed
1176 weight (panel c and d) in sessile oak (Caignard *et al.*, 2021) along an elevational gradient in the French
1177 Pyrénées. Height growth and seed weight were assessed in oak stands at various altitudes (panel a and
1178 c). The same traits were measured on offsprings collected on the same trees and raised in a common
1179 experiment (panel b and d). Both traits show clinal genetic and phenotypic variation, but positive
1180 covariation (cogradian) for height growth, and negative covariation (countergradient variation) for
1181 seed weight. The comparison of genetic and phenotypic clines for various adaptive traits (including
1182 growth, phenology, physiology and morphology) in oaks and eucalyptus showed that co-gradient
1183 variation was over-represented (Kremer *et al.*, 2014) in comparison to counter gradient variation.
1184 Reported examples of counter gradient variation were interpreted as the consequence of
1185 compensation between environmental and genetic sources of variation (Caignard *et al.*, 2021).

1186
Figure adapted from Caignard *et al.*, 2021

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>
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Box 4 Evolvability and evolutionary potential of oaks

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Fitness of an adult tree can be assessed by the number of surviving descendants it produces (as a male or female parent) in the next generation and having reached the same age as the parent tree. Its estimation *in situ* therefore requires access to two successive generations in the same population, and the reconstruction of the genetic relatedness between the trees of the two generations based on parentage analysis. Its measurement in the forest is therefore laborious and handicapped by the experimental constraints linked to the forest context. The mean standardized genetic variance of fitness within a population provides an estimate of the evolvability of this population, which corresponds to its evolutionary potential (Hansen *et al.*, 2011; Hansen *et al.*, 2019). It measures the expected increase in fitness resulting from the response to selection on all adaptive traits, which can be interpreted as a component of resilience. Recently, fitness assessments of adult trees in a mixed forest of pedunculate oak (*Q. robur*) and sessile oak (*Q. petraea*) were carried out (Alexandre *et al.*, 2020) and their evolvabilities compared to measurements available in other plant and animal species that were compiled in a review (i.e. 82 estimates, (Hendry *et al.*, 2018)). The attached graph, adapted from Hendry *et al.*, 2018, positions the values obtained for the two oaks (arrows) as compared to the distribution observed for the 82 values in plants and animals (distribution in grey). This example illustrates the remarkable evolutionary capacities of trees in comparison to other animal or plant species, suggesting that they are prone to resilience.

Figure adapted from (Hendry *et al.*, 2018) and (Alexandre *et al.*, 2020)

<figure><img src="image_12.png" /></figure>

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