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. 2022 Nov 28;191(2):974–985. doi: 10.1093/plphys/kiac540

Physiological mechanisms underlying extreme longevity in mountain pine trees

Ot Pasques 1, Sergi Munné-Bosch 2,3,✉,c,b
PMCID: PMC9922391  PMID: 36440969

Abstract

Ancient trees are life history longevity winners that mostly persist in remote and environmentally harsh mountainous areas. Here, we performed a multifeature analysis in a protected mature mountain pine (Pinus uncinata) forest to identify the morphological and physiological traits that make these trees unique. We compared the physiology of meristematic and somatic tissues (apical buds and needles, respectively) from juvenile, mature young, mature old, and mature ancient trees under cold stress and nonstress conditions. We successfully identified key morphological features of extreme longevity at the organism level, as well as various growth, vigor, stress, and dormancy markers underlying extreme longevity in old and ancient trees. Results indicated that evolution has exerted selective pressure on specific physiological traits that make trees become longevity winners (<0.1% of the tree population were ancient trees, with an average trunk diameter >100 cm and an estimated age of 700 years). Traits entailing longevity not only included apical dominance loss, epicormic growth, and modular senescence, but also an extreme plasticity in both meristematic and somatic tissues (buds and needles, respectively), as shown by various physiological markers. In conclusion, ancient trees are oddities that not only possess a unique ecological value but also show divergent physiological behaviors selected during their evolution to allow them to cope with adversities and attain long life.

Introduction

Trees that reach extreme longevity of several centuries or even millennia are rare. They are natural relics and oddities that have survived the passing of history and have an extraordinary physiological, ecological, and evolutionary value (Cannon et al., 2022). To become extremely old, a series of evolutionary and ecological events must line up. First, only certain tree species with specific genetic traits are prone to survive for a long period of time (Liu et al., 2022). In this context, gymnosperms live longer than angiosperms and tend to colonize mountainous, arid, and boreal regions (Fragnière et al., 2015). It is likely that the capacity to reach an extremely old age confers a competitive advantage to conifers compared to hardwoods (Brodribb et al., 2012). Indeed, Pinus species and several of the areas where they grow meet the requirements for extreme longevities (Piovesan and Biondi, 2021).

Ancient trees, although very difficult to identify in natural populations, still occur in places where resources are limited and where the environment presents adverse conditions. Many of these trees are found in remote regions like mountainous areas, living under very stressful environmental conditions (Piovesan and Biondi, 2021). Dry and cold environments, such as those of many mountainous regions, seem to slow down growth rates and ultimately favor the occurrence of very old trees in each population (Munné-Bosch, 2018; Liu et al., 2022). By contrast, anthropogenic disturbances, such as logging, pose a threat to the survival of long-lived trees worldwide (Lindenmayer et al., 2012). Forests at lower elevations and in accessible areas have been altered by human activity (Sandel and Svenning, 2013), so that most old trees persist in remote regions. Moreover, physiographic and local edaphic factors limit the maximum age of old trees (Piovesan and Biondi, 2021). Mountainous regions that possess cold, remote, and highly elevated areas with low population densities are generally home to most of the ancient trees of the world (Liu et al., 2022).

When trees become old, they have unique ecological functions in biodiversity conservation and the composition of a forest. They even provide unique roles when dead just through their physical presence and by providing a home to other species (Lindenmayer et al., 2012). However, the number of old trees in forests is progressively decreasing, not only because of climate change but also due to a huge direct anthropogenic pressure on forests (Lindenmayer et al., 2012). With this, the unique ecological functions and singularities of old trees are starting to disappear at all latitudes worldwide (Lindenmayer, 2009; Lindenmayer et al., 2012). Although very difficult to find in nature, due to its extremely low presence, the oldest trees give valuable information about climatic events and the evolution of climate in recent centuries (Luterbacher et al., 2016). They are also essential for the maintenance of a good forest population structure (Gibbons et al., 2008).

The capacity of a tree to cope with abiotic and biotic stresses is thought to be an essential factor favoring longevity (Munné-Bosch, 2018; Piovesan and Biondi, 2021; Cannon et al., 2022), but the difficulty of identifying very old, ancient trees in natural populations has made these studies very challenging and empirical data are still lacking, most specifically studies including cohorts with very old individuals. It has been suggested that a minimum degree of stress tolerance and resilience (capacity to recover from stress) is needed to overcome such stresses for the tree to become very old (Munné-Bosch, 2018), and that plasticity, modular growth, and regeneration are essential for extreme longevity (Van Pelt and Sillett, 2008; Munné-Bosch, 2018; Piovesan and Biondi, 2021). However, rigorous multifeature approaches for the identification of morphological and physiological markers of extreme longevity in trees are scarce. Morphological traits such as large diameter, dead tops, loss of lower limbs, and fissured bark have been useful for the identification of old trees of several species in the forests of eastern Washington, USA (Van Pelt, 2008). Protracted growth based on basal area increments has also been shown to be characteristic features of longevity in several species in the eastern United States (Johnson and Abrams, 2009). Furthermore, transcriptomic analyses of vascular cambial cells in old Ginkgo biloba trees (which can live well over one millennium) revealed that, although trees up to 600 years of age undergo less xylem generation, they exhibit no evidence of senescence (Wang et al., 2020). Unfortunately, the difficulty of performing multifeature analyses including both somatic and meristematic tissues in very old trees has made the task of demonstrating tree senescence very challenging. In this work, we aimed to study the physiological mechanisms underlying longevity in trees by performing a multifaceted study including both meristematic and somatic tissues with a particular emphasis on the spatiotemporal aspects of tree life in a protected mature mountain pine (Pinus uncinata) forest. We analyzed factors either posing threats or favoring tree longevity. Using morphological and physiological parameters, we explored unique traits underlying survival in old and ancient trees.

Results

Identifying ancient trees

The Pyrenees has historically been a mountainous region where human activity has modulated the landscapes and forest distribution for millennia. Mature mountain pine age-dated forests are mainly located in remote and protected areas of the Pyrenees, inside or near the Ordesa y Monte Perdido National Park (OMPNP) and Aigüestortes i Estany de Sant Maurici National Park (AESMNP), which have been little affected by human activity (Figure 1). To study the longevity of the ancient individuals of this species, we focused on a mature forest of the Alt Pirineu Natural Park (PNAP) in the Ribaleres area that has not been studied (Figure 1). To maximize the chances of finding individuals with the highest possible age, we selected a mature forest on a north-facing slope located at a very high altitude near the tree line (Figure 1B). Trees in remote and harsh high-elevation areas were more likely to reach extremely old ages compared to trees in areas with a south-facing slope, lower altitude, and more anthropogenic disturbances, as observed in our study (Figure 1).

Figure 1.

Figure 1

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Growth rate and geographical distribution of known age-dated mountain pine (Pinus uncinata) mature forests on north-facing slopes in protected areas of the Iberian Peninsula. A, Distribution of age-dated mountain pine forests in protected areas of the Pyrenees (RA, MV, EL, BL, TS, and CO belong to the AESMNP; SC and OR belong to the OMPNP; and PA and VM belong to the not-protected forests located in Pic d’Arnousse and Vall de Mulleres. RI corresponds to the studied forest located in the PNAP. B, Age estimation formula of the Pyrenean mountain pine trees on north-facing slopes based on the described DBH studies. NP, nonprotected area; PZ, National Park peripheric zone.

To identify ancient and old trees while causing the minimum possible damage, we used a correlation between the trunk diameter at breast height (DBH) and age to estimate tree ages without using dendrochronological methods (Figure 1). A sigmoidal curve was used to describe the tree growth rate over its complete lifespan. This model fitted rather well when assuming a decrease of the main trunk growth rate during the last period of the individual lifespan, with the highest growth rates reached once the early life stage has been surpassed. However, the sigmoidal model may have underestimated the age in old and ancient trees with extreme longevities. In our case and despite these limitations, this nondestructive approach allowed us to roughly estimate tree ages without damaging the extremely valuable ancient trees.

Of the total 1,300 individuals in the mature forest studied, 177 were randomly selected to establish the average DBH of the forest and other morphological and ecological traits. To characterize the physiological traits associated with longevity, we considered four differentiated life history stages occurring in mature forests (sensu Cannon et al., 2022). We considered trees that had not yet reached the reproductive stage as juveniles. Mature trees were defined as those that had the capacity to reproduce. In this context, we distinguished between mature young and mature old trees, the latter doubling, on average, the forest median age. Mature ancient trees were defined as the trees with the largest DBHs surpassing more than 100 cm, which is very uncommon. These trees had an estimated average age of 698 years. We established the branch perimeter, fissured bark, epicormic growth, loss of apical dominance, the presence of modular senescence (completely dead branches), and the abundance of each age range as longevity-related parameters (Figures 2 and3).

Figure 2.

Figure 2

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Longevity-related traits found in long-lived trees of a mature forest, including epicormic growth, combined with large branches, a large DBH, continuous cycles of dormancy and growth, and modular senescence. Growth plasticity with a characteristic loss of apical dominance, along with the presence of dead branches and fissured bark, are intrinsically related to all of these features in long-lived trees. Data show the mean ± SE. Different letters indicate significant differences (ANOVA, P-value < 0.05). This figure was created with Biorender.com.

Figure 3.

Figure 3

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Characterization of mature ancient and mature old trees. Mature ancient trees (A–D) and mature old trees (E and F) with longevity-related traits. Different longevity traits are presented in colored dot forms (turquoise, large DBH; yellow, epicormic growth; violet, modular senescence; orange, loss of apical dominance; pink, large branching; gray, plastic growth). G, Morphological and geographical characterization of the individuals with the 10 largest DBH. This figure was created with Biorender.com.

Ancient trees, which were outliers and unique in terms of morphology, were very rare and represented less than 0.1% of the forest trees (Figure 2). Furthermore, these trees clearly showed extreme longevity-related traits compared to mature old, mature young, and juvenile trees. The loss of apical dominance was a common feature in all the ancient trees studied, which presented the highest occurrence of epicormic growth, modular senescence, and fissured bark (Figure 2). Ancient trees also possessed the largest branches and seemed apparently to be more isolated than the other trees, although differences were not significant (Supplemental Figure 1). Mature old trees also showed age-related signs, but not as frequently as the ancient trees, presenting epicormic growth and fissured bark only in some cases (Figure 2). Their occurrence in the forest was more than 100 times that of the ancient trees, and not all the mature old trees presented a loss of apical dominance. Modular senescence, characterized by the presence of complete dead main branches along with other branches that were still alive, was also reduced in mature old trees compared to mature ancient trees. Morphological traits found in the ancient trees were almost non-existent in mature young trees, with only 25% presenting a loss of apical dominance. Mature young individuals formed most of the forest, representing more than half of the forest trees, while juvenile individuals, which were the second most represented age group in the forest, did not show any of the mentioned longevity-related traits (Figure 2).

Dormancy and modular growth

Mature ancient trees and the oldest trees from the mature old category displayed common features that were systematically repeated and interrelated (Figures 2 and3). Growth plasticity allowed an adequate response to the loss of apical dominance and the latter was reflected by epicormic growth, which, at the same time, enhanced plasticity, providing a more adaptive growth pattern in response to possible growth constraints. All this also led to another typical feature, modularity, which most likely appeared to bring clear benefits for survival, specifically when combined with dormancy cycles, as seen in ancient trees. From the 1,300 trees studied in the forest, we found 12 ancient trees. Of these, six were used to physiologically characterize them (Figure 3). These trees, with a DBH over 100 cm and an estimated age placing them among the oldest trees ever described thus far for this species (with some exceeding 700 years in age), were not easily found (even on north-facing slopes at the highest altitudes). Indeed, the morphological traits associated with longevity were an easy tool to detect them quickly, a tool even more helpful than the DBH. These particular life forms, with incredible plastic growth and modularity were visually identified with ease, which were indicated not only by the loss of apical dominance or the presence of epicormic growth but also by the exceptional deformed growth involving very unusual, twisted forms that were signs of extreme longevity. Indeed, the oldest tree in our study possessed large branches, which are associated with overdeveloped epicormic growth, a phenomenon seen in all the other individuals of this group (Figure 3). Modular senescence was clearly present in ancient trees, where only one large branch was still alive and the rest of the tree was completely dead with the presence of fissured bark (Figure 3 andSupplemental Figure 2). Loss of apical dominance was clearly observed in all these trees, producing incredible deformed forms or even developing structures with triple or even more principal stems or broken crowns with abnormally large branches (Figure 3).

Absence of damage at the meristematic and somatic levels

Under cold stress, which is the main factor limiting the growth and distribution of mountain pine trees, meristematic tissues (buds) behaved differently to somatic tissues (needles, Figure 4), showing a clear effect of cold stress on the physiology of this species (Supplemental Figures 3–5 and Supplemental Table 1). First, aging affected some stress markers like total anthocyanin (Ant) content, specifically in the buds under stress conditions (Figure 4). While juvenile trees showed the highest Ant content in buds and ancient trees the lowest during nonstress conditions, mature ancient and mature old trees accumulated the highest amounts of these pigments during cold stress, followed by mature young and juvenile trees, respectively. Thus, the buds of the oldest trees were more physiologically stressed by the cold. The abscisic acid (ABA)/gibberellin (GA) ratio, which is a dormancy index associated with longevity in trees (Pan et al., 2021), tended to increase with age except in ancient trees, which showed very similar values to that of juvenile trees. The vigor index, which can also be considered a maturation index (Valdés et al., 2002, 2004a, 2004b), expressed as the 2-isopententl adenine (2-iP)/zeatin ratio, also varied according to age (Figure 4 andSupplemental Figures 4 and 5). Ancient trees were the only ones that did not show any increase in the vigor index under cold stress (Figure 4 andSupplemental Figure 5). Jasmonoyl-isoleucine (JA-Ile) content, the active form of jasmonates (Khan et al., 2014), was higher in juvenile trees, while the content of another stress-related hormone 1-aminocyclopropane-1-carboxylic acid (ACC), the precursor of ethylene, was lower in juvenile and ancient trees under nonstress conditions (Figure 4 andSupplemental Figure 4).

Figure 4.

Figure 4

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Physiological stress, dormancy, stress-related phytohormones, and growth patterns in both meristematic (terminal buds) and somatic (needle) tissues of the different age groups of trees in a mature forest. A, Physiological stress in the buds of different age groups under noncold and cold conditions. B, Hormonal growth, dormancy, and stress in the buds of different age groups under noncold and cold conditions. C, Physiological stress in the needles of different age groups under noncold and cold conditions. D, Hormonal growth, dormancy, and stress in the needles of different age groups under noncold and cold conditions. (E–F) Heatmap of the cold-affected physiological parameters in buds (E) and needles (F) (P-value < 0.05). Higher values are presented in the blue tones, while lower values are presented in the red tones. The degree of difference is shown as a percentile of degradation in the color tone, with the darker blue tones corresponding to the highest values, the darker red tones corresponding to the lowest values, and the neutral tones corresponding to those near the average value of each parameter. Data show means ± SE of n = 12 for juvenile trees; n = 20 for mature young trees; n = 10 for mature old trees; n = 6 for mature ancient trees in (A–D). An asterisk indicates the parameters where age and interaction are significant (P-value < 0.05). All studied parameters and significances are shown in Supplemental Table 1 and Supplemental Figs. 3–5. 2-iP, 2-isopentenyl adenine; Zea, trans-zeatin. This figure was created with Biorender.com.

Somatic tissues responded differently to aging both under stress (cold) and nonstress conditions. While no age effects were observed in the Ant content in somatic tissues, needles of juvenile trees contained less Ant than those of ancient trees under nonstress conditions (Figure 4 andSupplemental Figure 3). The lipid hydroperoxide content decreased with age under nonstress conditions, with mature old and mature ancient trees showing the lowest contents. By contrast, in response to the cold, the hydroperoxide level was higher in ancient trees, being the lowest in juvenile trees. This oxidative stress marker increased under cold conditions in the ancient trees, while young and juvenile trees showed a strong reduction (Figure 4 andSupplemental Figure 3). Contents of the lipid-soluble antioxidant, γ-tocopherol, sharply increased during the cold in juvenile and ancient trees, while the relative water content (RWC) increased with snowy conditions in the mature young and mature old trees (Figure 4 andSupplemental Figure 3). In terms of growth, the only age group showing no variations in auxin (indole-3-acetic acid [IAA]) content between the changing environmental conditions was the mature ancient trees. All other age groups showed increased IAA contents during the cold (Figure 4 andSupplemental Figure 5). GA1 content seemed to be increased under cold stress as trees became older. Contrary to that, aging led to a decrease in 2-iP content in both stress and nonstress conditions (Figure 4 andSupplemental Figure 5). Aging also affected the GA3 content but had no effect on stress-related hormones in somatic tissues (Figure 4 andSupplemental Figure 5). Concerning dormancy, the ABA/GA1 ratio decreased with age under cold conditions and the ABA/GA3 ratio increased in juvenile trees under nonstress conditions. The ABA/GA4 ratio only increased in needles of mature young trees under cold conditions (Figure 4 andSupplemental Figure 4). Consequently, despite showing no differences in stress-related hormones in somatic tissues, we observed that trees with extreme longevity showed a different pattern in growth and dormancy markers compared to juvenile and mature young trees.

Singularity of ancient trees and plasticity

Ancient trees possessed great phenotypic plasticity when facing stresses compared to other mature trees. In most of the studied parameters reflecting physiological stress, hormonal growth, hormonal stress and vigor, and dormancy, age showed clear variation in terms of plasticity at both the meristematic and somatic level (Figure 5). First, the somatic tissues of ancient trees were more plastic when dealing with low temperatures. The degree of increase in the contents of photosynthetic and nonphotosynthetic pigments was greater in mature ancient trees (Figure 5). However, the variation in photoprotection per unit of absorbed light, given by the carotenoid (Car)/chlorophyll (Chl) and Ant/Chl ratios, increased less in mature ancient trees, which also showed a slight decrease in the α-tocopherol (α-toc)/Chl ratio compared to the other age groups (Figure 5). Accordingly, the highest increase in the amount of α-toc and lipid hydroperoxides (LOOH) was noted in these trees under stress conditions (Figure 5). Thus, mature ancient trees showed a more drastic and plastic, but less efficient, antioxidant, and photoprotective response to cold stress.

Figure 5.

Figure 5

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Phenotypic plasticity in the different age groups of trees of a mature forest facing cold stress conditions. The percentage variation in each parameter during cold stress conditions compared with nonstress conditions is shown. A and B, Variation and plasticity in the different tree age groups for physiological stress, vigor and dormancy, and growth and stress hormones in needles and buds, respectively. The Fv/Fm ratio (maximum efficiency of PSII), RWC, hydration, total Chl content , total Car content, the Car/Chl ratio, total Ant content, the Ant/Chl ratio, α-toc content, the α-toc/Chl ratio, and LOOH are markers of physiological stress. ABA, SA, JA, JA-Ile, and ACC are stress-related hormones. Zeatin, 2-iP, and IPA are cytokinins related to growth, as well as the auxin IAA. The 2-iP/Zea ratio is considered a vigor index, while the ABA/GA1, ABA/GA3, and ABA/GA4 ratios are considered dormancy indexes.

Although the foliar ABA content varied similarly between different ages, mature ancient trees showed the highest variation in salicylic acid (SA), jasmonic acid (JA), JA-Ile, and ACC, indicating enhanced defensive strategies against biotic and abiotic stresses (Figure 5). Concerning the growth-related hormones, these trees showed a more pronounced increase in the isopentenyladenosine (IPA) and IAA contents in the needles. In terms of dormancy, the foliar ABA/GA1 and ABA/GA3 ratios were less enhanced in mature ancient trees during cold stress (Figure 5). A very similar response occurred at the meristematic level. Buds from mature ancient trees were the only tree buds where the Chl, Car, and Ant total contents alongside the Ant/Chl ratio increased in response to the cold (Figure 5). As observed in the needles, buds of mature ancient trees also showed higher variation in the levels of jasmonates, cytokinins, and auxin (Figure 5). Furthermore, the vigor index and the ABA/GA4 ratio showed the highest increase and decrease, respectively, in buds of mature ancient trees (Figure 5). In contrast to the mature young and mature old trees, juvenile trees also possessed increased phenotypic plasticity in buds and needles when facing cold stress, not as generalized as that observed in the mature ancient trees, but quite relevant in some parameters. Juvenile trees showed higher variations in the Ant, Ant/Chl ratio, JA-Ile, IPA and the ABA/GA1 ratio content for needles, and in the α-toc, α-toc/Chl ratio, and the ABA/GA1 ratio for buds. Finally, mature young trees, which represented most of the forest in numbers, remained more stable and showed less drastic changes under cold stress (Figure 5).

Discussion

Organism lifespans can be strongly limited by aging processes. Despite that, several different developmental strategies have evolved within the plant kingdom that affect aging and lifespan (Watson and Riha, 2011). During their evolution, long-lived trees have deployed compensatory mechanisms to equilibrate the balance between growth and aging processes, by maintaining cambial cell activity, and promoting resistance-associated genes to support longevity (Wang et al., 2020). Individuals that grow slowly at the early life stages may have more possibilities of reaching larger diameters and a longer lifespan, despite being at more risk of dying young when they are small (Mencuccini et al., 2014; Bigler, 2016). Thus, the very slow growth rate of P. uncinata gives the species more chances of reaching extremely old ages (Figure 1).

In long-lived trees, meristems maintain the capacity to proliferate during the entire lifespan. Some studies have previously shown the capacity of meristematic cells to maintain telomere length during millennia in long-lived trees, allowing them to grow continuously without paying the costs of age (Watson and Riha, 2011). The capacity to maintain both telomere length and telomerase activity in different organs such as the meristems, roots, and needles may help increase the life expectancy in bristlecone pines (Pinus longaeva) (Flanary and Kletetschka, 2005). In our study, mature ancient and mature old trees did not show significant changes in their overall meristematic physiological status, which is a clear sign of senescence avoidance in mountain pines, which agrees with previous studies performed in Scots pines (Pinus sylvestris) (Mencuccini et al., 2014). The continuous capacity to maintain the replicative cell cycle, especially in meristems, facilitates and contributes to longevity (Munné-Bosch, 2020; Piovesan and Biondi, 2021). In addition, generally, the more resources invested in growth, the fewer resources invested in preventing stress or damage, which threatens longevity (Cichon, 1997). Trade-offs in functional traits (Agrawal, 2020), where negative relationships between growth and defensives strategies are found phenotypically in diverse plant species, increase the cost of producing chemical and anatomical defenses over their entire lifespan in trees (Sampedro et al., 2011; Vázquez-González et al., 2020). Abiotic stresses can modulate tree mortality (Gora and Esquivel-Muelbert, 2021). Interestingly, the effect of these abiotic stresses has been shown to be size-dependent (Johnson et al., 2018). Regarding biotic stresses, defensive compounds such as constitutive monoterpenes, along with resin ducts and wood density, are more abundant in long-lived species such as bristlecone pines, thus increasing their tolerance and making them less vulnerable to biotic attacks (Bentz et al., 2016). Long-lived trees have the ability to maintain vegetative growth that, combined with resistance to diseases in sites with low competition from other organisms, promotes survival. Thus, maintaining the capacity to keep growing while enhancing defenses is key to longevity (Wang et al., 2020). Complex crown structure and modular tree structure help increase longevity in trees, avoiding senescence (Folse and Roughgarden, 2012; Brutovská et al., 2013; Thomas, 2013; Zahradníková et al., 2020). Adaptive growth is, therefore, essential in attaining extreme longevity in trees.

The remaining ancient trees are the result of a stochastic balance between factors threatening survival and those favoring longevity (Figure 6). Modular growth, plasticity (in terms of adaptive growth and death cycles), as well as the remote and growth-limiting placements enhanced the chances of reaching extreme longevities (Figures 1, 2, 3, and6). The absence of organ damage, both at the meristematic and somatic level, along with dormancy–growth cycles and adequate hormonal and antioxidant stress responses positively contributed to longevity (Figures 4 and6). In this context, along with other environmental and developmental signals, plant hormones play an important role in controlling senescence (Khan et al., 2014). Obviously, all these features have to be combined with the specific capacities of each species to reach advanced ages, which are determined genetically. On the other hand, abiotic and biotic stresses, natural disasters, intraspecific competition, and human disturbances are the major limiting factors regarding longevity. As we have seen in this study, ancient trees that still survive are longevity winners that have literally escaped death due to a unique combination of factors. First, a limited human presence combined with a slow growth rate in a noncompetitive harsh environment give mountain pine trees the chance to reach extremely old ages (Figure 1). In addition, a series of mechanisms are essential for survival over centuries. Great morphological plasticity, seen as an increased loss of apical dominance, epicormic growth, large branching, and increased modular senescence were characteristic features of the ancient and old trees (Figures 2 and3). These are part of, and result from, longevity. It appears that, as trees become older, a series of plasticity mechanisms start to increasingly develop as a consequence and just on the mere fact of being alive. That is why almost all the common traits associated with longevity were found in most of the mature ancient and mature old trees, and they might favor survival (Figures 2, 3, and6).

Figure 6.

Figure 6

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Senescence avoidance and aging tolerance mechanisms when dealing with threats to survival during the entire lifespan of mountain pine trees. This figure was created with Biorender.com.

Aging does not directly cause death, but there are longevity signs that indicate that long-lived trees pay the effects of the passing of time while avoiding senescence. We observed that ancient trees were more physiologically stressed, both at the meristematic and somatic level (Figure 4). Despite this, they displayed greater phenotypic plasticity in terms of developing responses against all types of stresses. Ancient trees possessed more plastic aging tolerance mechanisms than all the other age groups in terms of antioxidant and photoprotective responses against the cold or in terms of dormancy, vigor, and growth (Figure 5). This may be a sign that trees maximize the range of tools to secure survival in the more vulnerable stages of lifespan. Their scarcity, combined with their extraordinary physiological and morphological plasticity, make ancient trees unique and essential for preservation. Ancient trees may be close to death, but they are ancestral vestiges that remain alive. Thus, it is important to conserve not only these trees with unique genetic and ecological backgrounds but also the ones that will replace them in the future in the circle of life.

Materials and methods

Study area

The study was performed in the Ribaleres mature mountain pine (Pinus uncinata) forest area in the PNAP (Spain, 42° 52′ N, 1° 35′ E), which is in the Pallars Sobirà region that has the lowest human population density in Catalonia. Initially, DBH was measured in 177 randomly selected individual trees to establish the median age of the forest. Tree age groups were divided into juvenile trees, mature young trees, mature old trees, and mature ancient trees, following Cannon et al., (2022), except for ancient trees, for which we selected the oldest individuals among the studied population. A total of 48 individuals were selected for detailed physiological characterization, geolocalized, and labeled according to their DBH and morphology to study both physiological and morphological parameters. These individuals included six mature ancient trees, 10 mature old trees, 20 mature young trees, and 12 juvenile trees. The study was conducted in a protected forest where P. uncinata trees delimit the tree line. The understory is formed of alpenrose (Rhododendron ferrugineum) alternating with European blueberry (Vaccinium myrtillus) in some places.

Tree characterization

For each of the 48 trees, the number of juveniles, mature young, and mature old trees that were at a distance of under 5 m and between 5 and 10 m was recorded to determine the effect that ancient and old trees had over the establishment of new trees. Furthermore, the occurrence and type of apical dominance loss, the percentage of modular senescence, and the presence or not of epicormic growth and fissured bark in the main trunk were assessed visually in situ and by taking photographs from each tree. The type of apical dominance was related to the number of main trunks that were present in the upper site of the canopy, and modular senescence was only considered when at least one of the main trunk ramifications was completely dead (we did not consider small dead isolated lateral branches in the quantification). We also recorded the height of the first branching as well as its perimeter and the number of ramifications from where the sample was collected. An even more detailed characterization was conducted in the 10 largest trees, evaluating growth plasticity, overall crown state, the presence of lichens, and the type of understory covering the soil. Furthermore, a total of 1,300 individual trees from the forest were studied to determine apical dominance and modular senescence percentages in each age group as well as to calculate the abundance of each age group.

Tree age estimation

Relating the DBH with the age of previously dendrochronologically dated P. uncinata forests from the protected areas of equiparable climatic regions of the Pyrenees (Galván et al., 2012; Hevia et al., 2018), considering the influence that altitude and aspect orientation have on the growth rate of P. uncinata, and after trying different regression formulas with different parameters, we finally opted to take into account only the populations that were on north-facing sites to better estimate the age of our studied trees. A sigmoidal regression was then viewed as the best way of estimating age from the DBH. The adjusted R2 was found to be 0.72, slightly overestimating the ages of juvenile trees and slightly underestimating the ages of ancient trees. Considering the zero damage caused to trees, we postulated that this was the most efficient nondestructive way of estimating the age of long-lived trees.

Sampling

Terminal buds and needles were sampled at the same branch site of each of the 48 trees. Samples used for physiological and biochemical analyses were collected at midday on two sampling dates. The first sampling was performed prior to the arrival of cold weather (October 6t 2021), while the second sampling was conducted after the very first cold and snowy weeks (November 20, 2021).

One random needle from each tree was used to determine the levels of stress markers (RWC, hydration, and the Fv/Fm ratio). Each needle collected in situ was individually placed in Falcon tubes that were protected from the light and immediately weighed to obtain fresh weight (FW). Afterward, Chl fluorescence was measured using a portable mini-PAM analyzer (Walz, Effeltrich, Germany) after the needle had adapted to darkness for 2 h. The Fv/Fm ratio was then calculated. After that, the same needles were individually placed into Falcon tubes containing distilled water and the turgid weight (TW) was measured 24 h later. The dry weight (DW) was obtained after overdrying the needle at 70°C for 72 h. Hydration and the RWC were then calculated as 100 × (FW − DW)/(FW) and 100 × (FW − DW)/(TW − DW), respectively.

In addition, 20 random needles and eight random buds from each tree were collected and immediately placed in liquid nitrogen in situ and transported to the laboratory, where they were stored at −80°C until analysis. All samples were collected at midday (between 12:00 and 14:00 local time).

Meteorological data

Climate data were obtained from the Servei Meteorològic de Catalunya, procured from the Saloria (NE Spain) automatic weather station. The data confirmed a decrease in temperature between the two sampling dates. In addition, relative humidity had increased, and the second sampling was conducted after several days of snow accumulation (Supplemental Figures 6–8). The second sampling was performed when there was 15–20 cm of accumulated snow.

Biochemical analyses

Stress-related phytohormones (ABA, SA, ACC, and jasmonates), growth-related hormones (IAA, IPA, Zea, 2-iP, GA1, GA3, GA4, and GA7), foliar pigments (Chl, Car, and Ant), vitamin E (α-toc, γ-tocopherol, and PC-8), and LOOH were all measured using the same methanolic extract.

After grinding the samples with liquid nitrogen, 546 μl of 0.01% (w/v) BHT in methanol + 30 μl of deuterated ABA, SA, JA, ACC, IAA, 2-iP, IPA, Zea (50 ppb) + 24 μl of deuterated GA1, GA4, and GA7 (20 ppb) were placed inside each Eppendorf tube. Afterward, the Eppendorf tubes were vortexed and placed in an ultrasonic bath for 30 min, before centrifuging the extract for 10 min at 4°C. The supernatant was collected, and the entire procedure was repeated for a re-extraction of the pellet, adding 600 μl of 0.01% (w/v) BHT in methanol this time with no deuterates. Finally, both supernatants were pooled and used for subsequent analyses.

For tocopherol analyses, the resulting extract was diluted in methanol (1:10, v/v), vortexed, and filtered before being placed in HPLC vials. For HPLC analyses, an isocratic method with n-hexane and 1,4-dioxane (95.5:4.5, v/v), a normal phase column, and fluorescence detection were used (Amaral et al., 2005). Standards (Sigma-Aldrich, Steinheim, Germany) were used for calibration.

To estimate the Chl, Car, and Ant contents, another aliquot of the resulting extract was diluted in methanol (1:5, v/v, for the buds and 1:10, v/v, for the needles), vortexed, and centrifuged before spectrophotometric analyses. Chl and Car were measured in methanolic extracts (Lichtenthaler and Wellburn, 1983), while Ant was measured in acidified methanolic extracts (Gitelson et al., 2001).

Oxylipins were measured through assessing the lipid hydroperoxide contents, which were determined using the FOX-2 assay (Bou et al., 2008), and jasmonates, a product of lipid peroxidation.

Jasmonates, including JA, its precursor 12-oxo-phytodienoic acid and its conjugated active form JA-Ile, were quantified by ultrahigh performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) (Müller and Munné-Bosch). The other stress-related phytohormones measured in this study (ABA, SA, and ACC) and growth-related hormones (IAA, 2-iP, Zea, IPA, GA1, GA3, GA4, and GA-7) were also determined by UHPLC-MS/MS (Müller and Munné-Bosch, 2011), using deuterated standards for their quantification.

Statistical analyses

A two-way ANOVA plus post hoc Tukey's test were used for data that complied with the normality of residues and homogeneity of variance. For the data that did not comply with the normality of residues, the nonparametric aligned rank transform approach was used. All statistical tests were performed using R-Studio.

Supplemental data

Supplemental Figure S1 . Number of average juvenile trees, mature young trees and mature old trees placed closer 5 m, or between 5 and 10 m from each tree age class.

Supplemental Figure S2 . View of all longevity associated signs in a same ancient tree.

Supplemental Figure S3 . Age-related changes in physiological stress markers.

Supplemental Figure S4 . Age-related changes in dormancy and stress-related hormones.

Supplemental Figure S5 . Age-related changes in growth-related hormones.

Supplemental Figure S6 . Evolution of the monthly temperatures (°C) throughout the year.

Supplemental Figure S7 . Evolution of the monthly relative humidity (%) and the monthly accumulated precipitation (mm) throughout the year.

Supplemental Figure S8 . Evolution of the monthly mean solar irradiation (RS24hm) and the monthly mean snow cover thickness (GSNOWMm) throughout the year.

Supplemental Table S1 . Statistical results and differences between all the parameters analyzed related with physiological stress, growth and vigor hormones and stress and dormancy hormones in both needles and buds.

Supplementary Material

kiac540_Supplementary_Data
Click here for additional data file. (1.1MB, pdf)

Acknowledgments

We are indebted to Marc Garriga and Oriol Grau, the director and scientific coordinator, respectively, of the Alt Pirineu Natural Park, for providing sampling permissions inside the protected area. We thank Andrea Casadesús, Laia Jené, and Celia Vincent for their support during the samplings, as well as Tania Mesa and especially Núria F. Bermejo for their support in the laboratory. We are also very grateful to the Serveis Científicotècnics of the University of Barcelona for their technical assistance. We thank Michael Maudsley for English correction of the manuscript.

Contributor Information

Ot Pasques, Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona 08028, Spain.

Sergi Munné-Bosch, Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona 08028, Spain; Research Institute in Biodiversity (IRBio), University of Barcelona, Barcelona 08028, Spain.

Author contributions

OP and SM-B designed and performed research and analyzed the data. SM-B coordinated the research. OP wrote the manuscript with the help of SM-B. All authors saw and commented on the manuscript. SM-B agrees to serve as the author responsible for contact and ensures communication.

Author responsibility

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plphys/pages/general-instructions) is: Sergi Munné-Bosch (smunne@ub.edu).

Funding

This work was supported by the Catalan Government through an ICREA Academia award and by the Spanish Government through the PID2019-110335GB-I00 grant.

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Associated Data

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Supplementary Materials

kiac540_Supplementary_Data
Click here for additional data file. (1.1MB, pdf)

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