Journal of Ecology 2014, 102, 555–565
doi: 10.1111/1365-2745.12219
No signs of meristem senescence in old Scots pine
~ ate3, Josep Pen
~ uelas4,5, Laura Rico4,5
Maurizio Mencuccini1,2*, Marta On
-Bosch3
and Sergi Munne
1
School of GeoSciences, University of Edinburgh, Edinburgh EH9 3JN, UK; 2ICREA at CREAF, Cerdanyola del
s, 08193 Catalonia, Spain; 3Departament de Biologia Vegetal, Facultat de Biologia, Universitat de Barcelona,
Valle
Avinguda Diagonal 645, E-08028 Barcelona, Spain; 4CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB,
s, 08193 Catalonia, Spain; and 5CREAF, Cerdanyola del Valle
s, 08193 Catalonia, Spain
Cerdanyola del Valle
Summary
1. Ageing and senescence in plants remain poorly understood. Although meristem totipotency may allow
woody perennials to be immortal, relative growth and photosynthetic rates typically decline with age.
2. Trees of ages between 129 and 534 years were selected in one of the oldest extant populations of Scots
pine. Apical branches were propagated by grafting onto homogeneous juvenile rootstock to eliminate the effects
of size and environmental variability and isolate those due to age. The hormonal profile of leaves and seeds
along with markers of the physiological status of leaves and their pattern of DNA cytosine methylation were
measured 15 years after grafting.
3. The percentage of total methylated loci in nuclear DNA increased with increasing meristematic age. However, only very few significant relationships were found between levels of phyto-hormones, pigments or physiological markers either in leaves or seeds and age of the meristem. In addition, shoots grafted from old trees
grew as fast as those from younger trees and produced the same number of germinable seeds.
4. Synthesis. We conclude that changes in DNA methylation can occur in old trees. The lack of apparent physiological deterioration in the grafted plants suggests that meristem senescence is not the main factor triggering
whole-plant ageing in Scots pine.
Key-words: ageing, DNA methylation, growth, reproduction, Scotland, Scots pine, senescence,
size-related processes
Introduction
Rather little is known about the occurrence of ageing (defined
here as the deterioration of physiological performance that is
not under control of an endogenous biological clock) and
senescence (the deterioration in performance that depends
directly on endogenous molecular processes, e.g. Hamilton
1966) in perennial plants, with large woody plants such as
trees infrequently studied (Finch 1990; Roach 1993; Bond
2000; Munne-Bosch 2007; Pe~nuelas & Munne-Bosch 2010;
Thomas 2012; Salguero-Gomez, Shefferson & Hutchings
2013). Perennial plants are sometimes taken as examples of
organisms which can potentially escape the evolution of
senescence, as a consequence of their capacity for modular
growth as a result of the meristems being contained inside
individual buds which remain only slightly differentiated over
time. It has been argued that modularity may result in large
size-related increases in reproductive potential with age (e.g.
Finch 1990; Vaupel et al. 2004; Munne-Bosch 2008).
Because natural selection acts most effectively during the
reproductive phase of an organism, the intensity of its action
against deleterious mutations favouring senescence in old
*Correspondence author. E-mail: [email protected]
plants should depend on the potential for continued reproductive capacity (Medawar 1952; Williams 1957; Vaupel et al.
2004; Baudisch 2005). Perennial plants, and especially trees,
have a prolonged capacity for modular growth and can therefore increase their reproductive output exponentially over time
(e.g. Harper 1977). They are therefore ideal candidates for
organisms that may potentially achieve extremely long lifespans.
However, modularity and indeterminate growth can have
complex effects, which may even act in the direction of
favouring the evolution of senescence. For example, in longlived clonal plants, continued vegetative reproduction of meristems by mitosis escapes the selection bottleneck imposed by
sexual reproduction and may result in the accumulation of
somatic mutations both in the vegetative tissues and in the
replicating meristems, with the potential of forming mutating
germlines (Ally, Ritland & Otto 2010). Provided that these
mutations did not negatively impact the physiological performance of the ramet, reproductive senescence could occur in
long-lived clonal organisms simply as a result of accumulated
somatic mutations (cf., Finch 1990; Silvertown, Franco &
Perez-Ishiwara 2001).
Senescence manifests itself as a complex series of morphological, physiological and behavioural events that affect the
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society
556 M. Mencuccini et al.
vigour and vitality of organisms (e.g. Carranza et al. 2004;
Chen et al. 2005; Reimers, Holmengen & Mysterud 2005;
Angelier et al. 2007; Munne-Bosch & Lalueza 2007; O~
nate
& Munne-Bosch 2010). Arguably, declines in survival and in
reproductive capacity must be traced back to the relevant
physiological processes that result from the mutational or the
molecular changes underlying senescence (Ricklefs & Finch
1995).
In general, it is widely accepted that perennial species suffer age-related physiological deteriorations which result in the
slowdown of, for example, growth rates and photosynthetic
rates (e.g. Day, Greenwood & Dıaz-Sala 2002; Thomas 2002;
Matsuzaki et al. 2005; Martınez-Vilalta, Vanderklein &
Mencuccini 2007; Munne-Bosch 2007). However, using
approaches based on the vegetative propagation of meristems
from donor trees of different ages (e.g. via rooted cuttings or
grafting), some studies have questioned whether these
changes are truly age-related. Instead, they have suggested
that maturational changes, such as reduced vegetative growth,
changes in leaf morphology or changes in different hormones
are rather consequences of changes in the environment external to the meristem itself, like increased size and complexity
of the plant (e.g. Mencuccini et al. 2005; Bond et al. 2007;
Vanderklein et al. 2007; O~nate & Munne-Bosch 2008, 2009;
Abdul-Hamid & Mencuccini 2009; Greenwood, Day &
Schatz 2010).
The potentially complex interplay between age and size is
illustrated in the diagram of Fig. 1. The three major molecular
processes which may underlie the action of an endogenous
biological clock (i.e. telomere shortening, accumulating
somatic mutations and changed DNA methylation levels) can
interact, on their own or jointly with the concurrent sizerelated changes driven by modifications in the water, carbon
and nutrient economy of the plant. In turn, these interactions
may alter fundamental physiological processes and the regulation of growth and development. It should be possible to document the occurrence of both of these processes by the
changes in the underlying balance of hormones and pigments.
Details on some of these molecular processes are beginning
to be unravelled by recent studies, in particular in relation to
DNA methylation (Bossdorf, Richards & Pigliucci 2008).
Cytosine methylation (Finnegan et al. 1998) likely represents
a mechanism of regulation of gene expression (Holliday &
Plug 1975). In both angiosperms and gymnosperms, the
extent of DNA methylation changes during ageing and maturation (Theiss & Follmann 1980; Diaz-Sala et al. 1995;
Lambe et al. 1997; Fraga, Ca~nal & Rodrıguez 2002; Fraga,
Rodrıguez & Ca~nal 2002). In Arabidopsis thaliana, individuals with an abnormally low amount of DNA methylation
showed severe phenotypic abnormalities during development
(Finnegan, Peacock & Dennis 1996; Ronemus et al. 1996).
Based on these considerations, we hypothesized that
changes in meristematic age occurring across a series of
grafted trees of Scots pine would relate to changes in (a) leaf
DNA methylation, (b) the performance of the major physiological pathways and (c) the hormonal balances controlling the
processes of growth and development. We also hypothesized
Fig. 1. Schematic diagram of the conceptual framework employed in
this paper to identify the biochemical processes and the links between
meristematic tree age and size, plant growth and reproduction. Various potential causes of ageing, triggered either by endogenous molecular mechanisms (labelled ‘Biological Clocks’) or by exogenous
processes acting at the whole-organismal level (labelled ‘Size-related
Effects’) are highlighted inside the rectangles at the top of the diagram. Either alone, or in combination, these various processes are
hypothesized to determine the appearance of senescence symptoms
(i.e. reductions in growth, survival or reproduction), as shown at the
bottom of the diagram. The age-related changes in these demographic
parameters are assumed to occur via changes in two main classes
of processes, those related to physiological competence and those
regulating growth and development. Irrespective of this distinction,
evidence of these changes should be available in measurements of
hormone and pigment concentrations and of other physiological indicators (middle of the diagram).
that the differences in growth and reproductive effort
observed across the sampled grafts would relate to pigment
and hormonal concentrations.
Materials and methods
STUDY SITE AND POPULATION
Donor trees (the ortets) were sampled at Glen Loyne (Scotland, UK,
57°09′ N, -5°05′ W) to the south of the Cluanie Lodge, in Invernessshire in the Scottish Highlands. At Glen Loyne, trees are sparsely
scattered across about 2 km2 on the southern side of the glen to the
west of Loch Loyne and span an altitudinal range of 250–390 m. At
the time of sampling, this Scots pine woodland was approaching
extinction, with only few scattered individuals remaining from the original Caledonian pinewood. Glen Loyne contains some of the oldest
known Scots pine trees (more than 550 years of age). The population
showed little evidence of natural regeneration, and seed production
was very low and of low quality, possibly as a result of self-pollination (Bartholomew, Malcolm & Nixon 2001). In 1995, apical shoots
(the ramets) taken from about 100 donor trees (between three and five
ramets per ortet) were grafted onto Rannoch rootstock. After 4 years
of nursery acclimation, the grafts were planted as an ex situ seed
orchard in 1999 at Lauder Hill (Scottish Borders, 55°43′ 00″ N,
2°46′ 45″ W, 270–290 m a.s.l.), with a north-westerly aspect and
moderate exposure. The ramets from the various ortets were planted
with a random design across the orchard interspersed with silver birch
(Betula pendula L.), rowan (Sorbus aucuparia L.) and other local
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
Ageing in trees 557
broadleaves. The ramets were planted with a spacing of 3 9 3 m2
and given their size very little, if any, competition was taking place at
the time of sampling.
and tapped to release seeds. The cones were then torn apart to determine total seed content. Full and empty seeds per cone were counted,
and full seeds were tested for germinability under standard controlled
conditions (e.g. Goslin 2006).
FIELD SAMPLING
Field work was carried out in 2010, with sampling times in May and
August for the leaf material and December for the reproductive material. One to three ramets from 27 ortets were selected out of the available 100 ortets, based on the known age distribution of the original
donor trees in Glen Loyne and given the available time and resources.
When more than one ramet was sampled for each ortet, samples were
aggregated, because equal replication could not be obtained across all
ortets.
GROWTH
To estimate investment in growth, stem diameter was measured with
a precision calliper to the nearest 1 mm above the bulging in the collar caused by grafting. Total height was measured with a graduated
pole pruner to the nearest 5 cm. Height growth during the last 4 years
was also measured in the same manner.
CONE AND SEED MATERIAL
To estimate investment in reproduction, all cones in their final year of
development were collected from the crowns of the selected ramets in
December. After drying at 35 °C for 2 days, the cones were shaken
STRATEGY FOR BIOCHEMICAL ANALYSES
A diagram is given (Fig. 2) to clarify our approach to the biochemical
analysis. Based on the structure presented in Fig. 1, we identified a
set of seven processes related to physiological competence and the
regulation of growth and development that are most likely to be
involved in ageing (dotted and dashed rectangles at the centre), and
for each of these processes, we identified the most important physiological and biochemical pathways (pigments and hormones) to be
measured (continuous-line rectangles beneath). We also isolated DNA
methylation as the most likely candidate molecular process for an
endogenous biological clock regulating the ageing process (top
ellipse) and characterized the relationships between these biochemical
pathways, growth, reproductive effort and age (bottom ellipses). We
acknowledge that the physiology underlying all of these processes is
vastly more complicated than it is represented in Fig. 2. However,
our categorization is consistent with accepted physiological knowledge (e.g. Taiz & Zeiger 2010).
SAMPLING FOR BIOCHEMICAL ANALYSES
Sampling of tissue for biochemical analyses took place at three times
of the year. The May leaf samples were taken when their elongation
Fig. 2. Diagram for the implementation of the conceptual framework of Fig. 1 into a framework of testable hypotheses. The processes of genome
DNA Methylation, reduced Physiological Competence and altered Regulation of Growth and Development (the three ellipses at the top of the diagram) are linked to the changes taking place in Growth and Reproduction as well as to whole-plant Ageing as measured by the age of the meristems of the grafted plants (bottom three ellipses). The classes of processes of Physiological Competence and Regulation of Growth and
Development are broken down into seven types of physiological processes (shown inside the dashed and the dotted rectangles). The dashed rectangle delimitates those processes that are hypothesized to be linked primarily to Growth, the dotted rectangle those that are primarily linked to
Reproduction. Those processes delimited by both types of rectangles are hypothesized to be linked to both Growth and Reproduction. The variables inside the ellipses and the dashed/dotted rectangles are considered as latent variables that cannot be measured directly. The continuous-line
rectangles beneath the ellipses and the dashed/dotted rectangles contain the measured outcome variables that allow estimates of the relevant latent
variables.
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
558 M. Mencuccini et al.
had begun, and therefore, they could be considered foliar primordia.
The August leaf samples were completely developed and fully
expanded. In the text, they are referred to as young leaves (in May)
and mature leaves (in August). As mentioned above, mature cones
were sampled in December. Leaf material was collected from the
fourth whorl of the canopy to reduce intraramet variability. Both vegetative and reproductive samples were taken at around midday to
minimize time-related variability in the physiological markers. The
leaf samples for biochemical analyses were collected and immediately
frozen in liquid nitrogen and later stored at 80 °C in the laboratory
until they were analysed.
the same recognition sequence. Both enzymes recognize the same
sequence 5′-CCGG-3′ when it is un-methylated but differ in their sensitivity to methylated strands. HpaII is sensitive to methylation of the
internal cytosine at both strands, whereas MspI is sensitive to methylation of the external cytosine. Hence, the comparison of EcoRI+MspI/EcoRI+HpaII profiles allowed the identification of four
types of DNA methylation status: Non-methylated loci (1/1), Fully
methylated loci (1/0), Hemi-methylated loci (0/1) or Hyper-methylated
loci (0/0).
DATA ANALYSIS
HORMONAL ANALYSES
Samples of leaves from each clone were split into separate units for
subsequent analysis. A subsample taken at random was employed to
determine leaf water content, leaf area (using a standard leaf area
metre) and dry mass following drying in the oven at 80 °C for 48 h.
The ratio of leaf area to mass was employed to calculate the specific
leaf area (SLA).
To determine the age-related changes in the processes described in
Fig. 2, concentrations of the cytokinins, zeatin, zeatin riboside, isopentenyladenosine, isopentenyladenine and dihydrozeatin riboside, the
auxin, indole-3-acetic acid (IAA), the ethylene precursor, 1-aminocyclopropane-1-carboxylic acid, together with abscisic acid, jasmonic
acid, salicylic acid and gibberellins 4 and 24 were determined following M€
uller & Munne-Bosch (2011) (Appendix S1 in Supporting
Information for more details). The analyses of a- and c-tocopherols
were carried out as described in Amaral et al. (2005) (Appendix S1
for more details).
CHLOROPHYLL AND CHLOROPHYLL FLUORESCENCE
ANALYSES
Samples were extracted in 80% (v/v) acetone and assayed spectrophotometrically to estimate chlorophyll contents. Specific absorption coefficients reported by Lichtenthaler & Wellburn (1983) were used. The
maximum efficiency of PSII photochemistry (Fv/Fm), an indicator of
photoinhibition of the photosynthetic apparatus, was calculated from
chlorophyll fluorescence data obtained with a portable fluorimeter
Mini-PAM (Walz, Effeltrich, Germany) from leaves maintained at
least 1 h in darkness, by using the equations described by van Kooten
& Snel (1990).
ISOLATION OF DNA AND METHYLATION-SENSITIVE
AMPLIFICATION POLYMORPHISM (MSAP) ANALYSIS
Methylation-sensitive amplification polymorphism analysis followed a
modified version of the original protocol published by Reyna-Lopez,
Simpson & Ruiz-Herrera (1997), as detailed in the Appendix S1.
METHYLATION PATTERNS ANALYSIS
To determine the presence (1) or absence (0) of fragments where
DNA methylation occurred, digestions using the Escherichia coli
endonuclease restriction enzyme EcoRI and one of the two enzymes
of the isoschizomer pair MspI/HPaII were carried out for each genotype tested (Salmon et al. 2008; cf., Table S1). Only those fragments
with a relative abundance > 0.5% were considered in subsequent
analyses. Isoschizomers are pairs of restriction enzymes specific to
A general linear model (GLM) was employed to determine the significance of the linear relationships between each of the available hormonal and physiological measures and meristematic age for the two
sampling dates for leaves and the one sampling date for seeds. For
leaves, the GLM accounted for the repeated-measure nature of the
data set and tested for the significance of both meristem age and the
two sampling dates (as an intercept shift). Percentage seed germination was analysed using linear regression on the arcsine-transformed
values.
Carrying out multiple independent regression analyses runs the risk
of inflating type I errors, but the efficacy of available corrections (e.g.
Bonferroni’s correction) is still debated in the literature (e.g. Curtin &
Schulz 1998; Pemeger 1998), especially for cases in which outcome
variables are correlated among themselves. For example, in the
extreme case when a number of outcome variables are correlated
among themselves with r = 1, knowledge of the outcome of a single
test would be sufficient to know the outcome of the other tests, and
carrying out multiple tests should not therefore incur penalization by
Bonferroni’s correction. The results of these tests based on a GLM
should thus be viewed as preliminary to the multivariate technique
presented below.
To allow for the multi-collinear nature of the measurements, correct for multiple comparisons and for the tendency of many of the
hormonal measures to nest logically around latent variables, representing the various classes of biochemical processes highlighted in Fig. 2,
we employed a multivariate technique called Regularized Generalised
Canonical Correlation Analysis (RGCCA, Tenenhaus & Tenenhaus
2011), as implemented in the library RGCCA available in R 2.15.1 (R
Development Core Team 2011). RGCCA combines elements of classical canonical correlation analysis with those of partial least square
path modelling. It can be employed to model linear relationships
among blocks of variables, whereby each block can be considered a
latent variable that is itself a linear function of the observed variables
(in our case measurements of hormonal and pigment concentrations,
DNA methylation, Growth, Reproduction). In classical canonical correlation analysis, one deals with two matrices (typically one of the
environmental variables and one of the biological outcome variables)
and seeks to find the best (linear) combinations of variables from both
matrices that maximize the correlation coefficient between these two
new (latent) variables. In RGCCA, one can define any number of
latent variables (or blocks), not only two, and one can specify any
number of structural relationships among the various blocks of variables in the same way as in structural equation modelling.
We grouped our physiological and molecular measurements
according to the group structure given in Fig. 2, whereby the seven
classes of processes inside the dotted and dashed rectangles (e.g.
Photo-Protection from Oxidative Stress, Photosynthetic Potential,
Induced Defenses) represent the latent variables estimated by the measured variables listed inside the continuous-line rectangles directly
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
Ageing in trees 559
below them. By way of example, one could decide a priori that
among the seven classes of processes listed in Fig. 2, those delimited
by the dashed rectangle should be related to Growth only, those
delimited by the dotted rectangle should be related to Reproduction
only and those delimited by both types of rectangle should be related
to both Growth and Reproduction. Indeed, this is the assumption we
made in our subsequent analyses. Conversely, all seven processes
could be related to Age. RGCCA was then employed to test whether
these relationships were significant. Note also that capitalized names
such as ‘Growth’ are employed to refer to the latent variables
employed in the RGCCA analysis, where non-capitalized names such
as ‘growth’ refer to the underlying biological process.
We used RGCCA to explore the following hypotheses: (a) that differences in growth and reproduction across the 27 ortets could be
explained by the changes in the physiological processes given in
Fig. 2, (b) that changes in DNA methylation acting either via the various physiological processes measured by our metabolites or via alternative physiological pathways (which were not quantified) explained
the variability in the growth and reproduction of the ramets, and
finally (c) that DNA methylation, the various physiological processes,
growth or reproduction changed significantly with donor tree age.
Further details on the analysis are given in the Appendix S1. For (a),
we tested the significance of the hypothesized direct links between
Reproduction, Growth and the various processes listed in Fig. 2). For
(b), we tested the significance of the links either between DNA methylation, physiological processes and Growth and/or Reproduction, or
between DNA methylation and Growth and/or Reproduction directly.
For (c), we tested the significance of all possible links with Age.
Model goodness of fit was calculated using the concept of AVE,
the average variance explained at the various hierarchical levels. Note
that, because of the optimization schemes employed, RGCCA allows
quantifying the relationships among blocks of variable up to a sign;
in other words, one can estimate the values of the correlation coefficients, but not their signs, which need to be derived from the exploration of the relationships among original variables and block variables.
All coefficients are therefore given without a sign in the Results section. As elaborated in the Appendix S1, the 95% and 99% confidence
intervals of the correlation coefficients among blocks of variables and
within individual blocks of variables were obtained by a bootstrapping technique, by random permutation of the values of each variable
in the data set 1000 times.
In addition to the transformations mentioned above, the values of
number of cones, total number of seeds per cone and number of full
seeds per cone and the concentrations of jasmonic acid, gibberellins,
zeatin, zeatin riboside were also log-transformed to satisfy homogeneity of variance.
Results
VEGETATIVE GROWTH AND REPRODUCTIVE OUTPUT
The donor trees sampled at Glen Loyne spanned more than
400 years in age, from 129 to 534 years (in 2010), with a
mean of 384 years. Height of the grafted trees ranged from
2.5 to 5.2 m and trunk diameter from 5.4 to 11.6 cm. None
of the growth parameters measured was significantly related
to meristematic age using GLM (Fig. S1a–c).
With regard to reproductive vigour, number of cones per
tree and number of seeds per cone (either total or full seeds)
also did not vary significantly as a function of meristem age
(Fig. S1d, e). However, the arcsine-transformed percentage of
seed germination decreased significantly with meristem age
(R2 = 0.41, P < 0.05, Fig. S1f; note the n = 15 for this
analysis, as not all ramets had enough seeds for analysis).
Because we collected all the cones from our sample trees, we
could calculate the total number of germinable seeds per tree.
This variable did not show any trend with age, with the total
number of germinable seeds per plant being instead a very
strong positive function of tree diameter (P < 0.01, data not
shown).
None of the pigment or hormone concentrations varied significantly with meristematic age using GLM (Tables 1 and 2),
with one exception represented by the gibberellin GA24
(P = 0.03), which declined with age, although with an extremely small percent of explained variance (R2 = 0.09). In contrast, the majority of the variables measured on leaves
showed significant changes from the May (leaf primordial) to
the August (mature leaves) sampling times.
CHANGES IN DNA METHYLATION WITH AGE
Four types of methylation-sensitive polymorphism were found
in the MSAP bands at the CCGG sequence, that is, no methylation, hemi-methylation (outer cytosine methylated in one
strand), full methylation (inner cytosine methylation in both
strands) and hyper-methylation (the presence of methylation
of both cytosines in both strands of DNA).
Taking into account all DNA samples examined, the incidence of DNA methylation was up to 70% of all loci
obtained in the present study, with the percentages of full
methylation (22.69 1.39 and 19.49 0.64, for young and
mature leaves, respectively) and hyper-methylation (40.23 2.25 and 30.15 1.24) of CCGG being higher than the
Table 1. Results of general linear model analyses of physiological
outcome variables against meristem age and time of sampling
t-test
Physiological markers
Fv/Fm
Chl a + b
Chl a/b
Car
Car/Chl
a-toc
c-toc
Tot Meth
Hyper Met
Age
P
Time
1.7
0.1
1.2
0.9
1.3
0.5
0.3
2.4
1.1
13.2
15.3
1.4
7.9
23.5
13.0
2.6
3.4
Age
Time
R2
0.10
0.93
0.24
0.39
0.21
0.65
0.60
0.02‡
0.28
0.00†
0.00†
0.17
0.00†
0.00†
0.00†
0.78
0.83
0.06
0.56
0.92
0.78
0.01
0.20
0.21
0.01†
0.00†
The values of t-tests, probability levels P and percent of explained
variance R2 are given for the maximum efficiency of photosystem II
photochemistry (Fv/Fm), chlorophyll a and b (Chl a + b) levels and
Chl a/b ratio, total carotenoids (Car), Car/Chl ratio, a- and c-tocopherol (toc) and DNA total (Tot Meth) and hyper-methylation (Hyper
Meth) levels in leaves at two stages of development, May and August
(c-toc was measured only for the May samples). Columns labelled
‘age’ refer to tests against meristem age, those labelled ‘time’ to tests
against time of sampling.
†
Significant difference at P ≤ 0.01.
‡
Significant difference at P ≤ 0.05.
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
560 M. Mencuccini et al.
Table 2. Results of general linear model analyses of hormonal and pigment outcome variables against meristem age and time of sampling
t-test
Regression against age for full
seeds
P
R2
Hormones and pigments
Z
ZR
IPA
2iP
DHZR
IAA
ACC
SA
JA
GA4
GA24
ABA
Age
0.4
0.5
1.4
1.0
0.6
0.2
0.9
0.2
0.6
1.5
2.2
0.7
Time
0.6
2.2
0.6
1.7
3.8
1.9
7.2
1.6
1.0
2.8
0.4
3.4
Age
Time
0.69
0.62
0.17
0.32
0.54
0.83
0.36
0.86
0.58
0.15
0.03‡
0.45
0.55
0.03‡
0.57
0.10
0.00†
0.06
0.00†
0.12
0.31
0.01†
0.71
0.00†
0.01
0.09
0.04
0.07
0.23
0.07
0.52
0.05
0.03
0.17
0.09
0.20
F-test
P
R2
0.00
0.00
0.17
0.48
0.14
0.56
0.69
1.44
0.02
0.19
0.22
0.00
0.97
0.94
0.69
0.50
0.71
0.46
0.41
0.25
0.88
0.66
0.65
0.96
0.00
0.00
0.00
0.03
0.00
0.03
0.04
0.07
0.00
0.01
0.01
0.00
Left columns refer to analysis on leaves, right columns to analyses on seeds. The values of t-tests, probability levels P and percent of explained
variance R2 are given for the cytokinins, zeatin (Z), zeatin riboside (ZR), isopentenyladenosine (IPA), 2-isopentenyladenine (2iP) and dihydrozeatin riboside (DHZR), the auxin, indole-3-acetic acid (IAA), the ethylene precursor, 1-aminocyclopropane-1-carboxylic acid (ACC), salicylic acid
(SA), jasmonic acid (JA), the gibberellins 4 and 24 (GAs) and abscisic acid (ABA) levels in leaves at two stages of development, May and
August and in full seeds. Columns labelled ‘age’ refer to tests against meristem age, those labelled ‘time’ to tests against time of sampling.
‡
Significant difference at P ≤ 0.05.
†
Significant difference of at least P ≤ 0.01.
percentages
of
hemi-methylation
(9.98 0.86
and
16.97 0.69). The sum of percent methylation levels and the
hyper-methylation levels only of the fragments were both
higher in young leaves than in mature ones in the GLM
(P < 0.01, Table 1). A positive relationship was also found
between meristem age and percentage of total methylated loci
(Table 1 and Fig. 3 top panel, R2 = 0.20, P < 0.05), although
such relationship was much stronger for the mature leaves
than for the leaf primordia (data not shown).
PIGMENT AND HORMONAL PATTERNS IN RELATION TO
AGE, GROWTH AND REPRODUCTION
Because of limitations to our sample size, the three dates
(May and August for leaves, December for seeds) were analysed separately while pooling all physiological measurements
(hormones and pigments) into a single group for each date.
RGCCA showed several significant relationships among the
different variables (Fig. 4). All three groups of hormonal and
pigment measurements carried out in May and August on
leaves and December on seeds were significantly related to
each other and to the latent variables of Growth and Reproduction, which in turn were related to each other (all at least
P < 0.05, i.e. none of the bootstrapped 95% confidence intervals contained the value of 0). In contrast, none of the DNA
Methylation measurement dates related to any of the measurements of hormonal and pigment concentrations nor to Growth
or Reproduction directly. Age did not relate to any of the biochemical variables and was only mildly related to one of the
DNA Methylation dates (Fig. 4 and Table 3), in contrast with
what found using GLM (Fig. 3 and Table 1).
When the measurements of hormonal and pigment concentration were instead pooled across the three dates but
separated according to the biochemical processes highlighted
in Fig. 2, different patterns were obtained (Fig. 5). In this
case, the latent variable of DNA Methylation was significantly
related to the latent variables of Induction of Chemical
Defenses against Herbivores and Pathogens (r = 0.58,
P < 0.05) and the combined group of Organ-Level Senescence, Cell Division and Transition to Reproduction
(r = 0.62, P < 0.05). Note that the three processes of Organlevel Senescence, Cell Division and Transition to Reproduction were grouped together here to simplify the analysis, since
the hormonal pathways controlling them consisted to a large
degree of the cytokinins (Fig. 2). A different analysis in
which they were kept separated showed largely similar patterns. In turn, the same processes that were related to DNA
Methylation also appeared to be significantly related to
Reproduction, Growth or both of them (all at least P < 0.05).
Again, as in the previous model, age did not relate to any of
the biochemical processes (with the exception of Induction of
Chemical Defenses and Initiation of Reproductive Structures)
and, especially, it did not relate to Growth or Reproduction
(the relationship with DNA Methylation was mildly significant, Table 3).
Overall, the goodness of fit of the models was of intermediate quality. The two alternative models showed similar overall
global AVE (global AVE is an overall index of variance
explained by the model, Appendix S1), with slightly higher
value for the model pooling across hormonal/pigment groups
for the three separate dates (AVE = 0.21) than for the model
pooling over the three dates but separating the measurements
into biochemical processes (AVE = 0.20). The most heterogeneous blocks (Transition to Reproduction, Photo-protection,
Investment in Defense against Herbivores and Pathogens,
Organ-Level Senescence) had relatively low or low average
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
Ageing in trees 561
Fig. 3. Relationships between meristematic age of the grafted trees
(X axis) and (a) percentage of the DNA CCGG sequences that were
methylated, that is, in which either full methylation, hemi-methylation
or hyper-methylation was found; (b) percentage of the DNA CCGG
sequences that were hyper-methylated, that is, in which the cytosines
on both DNA strands were found to be methylated. See text for further details. The two parallel lines in a) refer to the results of the general linear model (GLM) analysis which tested for the effect of both
age (as continuous variable) and time of sampling (May vs. August
as a repeated measure). The symbols NS in b) refer to the non-significance of the GLM analysis for the hyper-methylation levels.
variance explained (AVE < 0.4) while the blocks of Methylation, Growth and Reproduction had generally higher AVEs.
The model always converged to the final solution in < 10
iterations.
Discussion
PIGMENT/HORMONAL CONCENTRATIONS DRIVE
CHANGES IN GROWTH AND REPRODUCTION
A comprehensive biochemical analysis (including DNA methylation) was conducted in relation to age in a series of grafted
Scots pine trees. We analysed these data using both a standard GLM and a multivariate technique (RGCCA). The
RGCCA model’s goodness of fit, as assessed by the global
AVEs, may seem relatively low (global AVE of about 0.20);
however, this primarily reflects the complex and interacting
nature of the molecular processes investigated in a field situation and the difficulty of constraining hormones and pigments
with distinct functions and pathways in a limited set of physiological processes.
Fig. 4. Multivariate path diagram resulting from Regularized Generalised Canonical Correlation Analysis. Global DNA methylation levels
and hormonal and pigment levels were grouped according to the date
of sampling (May and August for leaves and December for cones and
seeds only). Each ellipse represents a block component or, in other
terms, a latent variable whose coefficients are estimated via the correlation matrix of the measured variables belonging to that block and
the matrices of the other blocks. Thin lines connect latent variables
which were assumed a priori to be related to each other. Bold lines
indicate those relationships that were found to be significant (the correlation coefficients are given by the side of the line; *P < 0.05;
**P < 0.01). For each latent variable, the rectangle labelled AVE
(average variance explained) indicates the variance of that block of
variables explained by the latent variable itself. Two other indices of
model quality, inner model AVE and outer model AVE are also given
(Appendix S1 for further information).
The RGCCA analyses showed that differences in growth
and reproduction were significantly related to hormonal/pigment patterns reflecting measures of Photosynthetic Potential
(leaf area, chlorophyll content, SLA) and Organ-level Senescence and Cell Division and Expansion (cytokinins and IAA).
Similarly, the relationships between Reproduction and hormones such as gibberellins are well established and are supported by a large body of literature (e.g. Taiz & Zeiger 2010;
and literature mentioned therein). Slightly more surprising
was the fact that Growth did not relate to traits linked to
Photo-Protection or Induction of Chemical Defenses (e.g.
Loehle 1997). In Scots pine, the defense system is largely
based on the constitutive and induced production of oleoresins, which are terpenoid-rich compounds. Induced production
of resin ducts is controlled by methyl jasmonate mediated by
ethylene production (Hudgins & Franceschi 2004), two pathways we characterized by the levels of jasmonic acid and
1-aminocyclopropane-1-carboxylic acid (ACC), the ethylene
precursor.
DNA methylation was not related to Growth, Reproduction,
or to any of the hormonal levels of either young or mature
leaves (Fig. 4), but, when the biochemical processes were
separated into different groups (Fig. 5), significant relationships emerged with the latent variables of Induction of Chemical Defenses (as measured by the jasmonic acid, salicylic
acid and ethylene pathways) and of Organ Senescence, Cell
Division & Expansion and Transition to Reproduction (as
measured by the cytokinins, abscisic acid and IAA) (Fig. 5).
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
562 M. Mencuccini et al.
Table 3. Correlation coefficients and probability levels for the relationships between the various block components of the RGCCA
analysis and meristematic age of the donor trees. The analyses at the
top are referred to the model of Fig. 4, which are grouped according
to the timing of sampling (May, August and December). The analyses
at the bottom are referred instead to the model of Fig. 5, where the
variables are organized according to the groups of biochemical functions carried out by the various compounds
Correlations with
age
Block components from RGCCA analysis
Model pooling across all hormones/pigments
DNA methylation of new leaves
DNA methylation of mature leaves
Hormones/pigments of new leaves
Hormones/pigments of mature leaves
Hormones/pigments of seeds
Reproduction
Growth
Model pooling across sampling dates
DNA Methylation
Photo-Protection
Photosynthetic Potential
Induction Chemical Defenses
Organ Senescence/Cell Division &
Expansion/Transition to Reproduction
Initiation of Reproductive Structures
Reproduction
Growth
r
P
0.19
0.34
0.25
0.31
0.03
0.31
0.24
ns
–†
ns
ns
ns
ns
ns
0.37
0.24
0.11
0.48
0.13
–†
ns
ns
–‡
ns
0.47
0.31
0.24
–‡
ns
ns
ns, non-significant difference; RGCCA, Regularized Generalised
Canonical Correlation Analysis.
Significance levels were determined by a bootstrapping technique (see
Appendix S1 for further information).
†
Significant difference at P ≤ 0.10.
‡
Significant difference at P ≤ 0.05.
Fig. 5. Multivariate path diagram resulting from Regularized Generalised Canonical Correlation Analysis. Hormonal and pigment levels
were grouped according to the biochemical processes that they help
regulate. Boxes, thin lines, bold lines, boxes labelled AVE and coefficients in the figure have the same meaning as in Fig. 4.
While these pathways are of physiological interest, the lack
of significant direct links between DNA Methylation and
Growth or Reproduction suggests that DNA methylation has,
at best, only indirect effects on these processes. Finally, both
models of Figs 4 and 5 showed a significant interaction
between Growth and Reproduction, suggesting that genetic
differences may have existed across clones affecting both
processes.
FEW RELATIONSHIPS BETWEEN AGE AND PIGMENT/
HORMONAL CONCENTRATIONS
Age did relate to two hormonal patterns in the RGCCA,
Induction of Chemical Defenses (as measured by the jasmonic
acid, salicylic acid and ethylene pathways) and Initiation of
Reproductive Structures (via increased gibberellin levels in
leaves). The link with Induction of Chemical Defenses suggests a role for an ontogenetic control of the level of chemical
defenses in trees (e.g. Boege & Marquis 2005; Webber &
Woodrow 2009). The relationship between age and Initiation
of Reproductive Structures suggests the existence of agerelated patterns in gibberellins, which have been shown to be
involved in regulating the transition of meristematic buds
from the vegetative to the reproductive state in several conifers
(Haffner et al. 1991; Valdes et al. 2002; Valdes, Fernandez &
Centeno 2003, 2004).
Very strikingly, age was not linked to differences in
Growth or Reproduction. In our experiment, age is not confounded with size, environmental conditions or degree of
competition among trees. We found a highly significant
reduction in percent seed germinability with age in the few
ramets with seeds (Fig. S1f) but the total number of germinable seeds per tree did not relate to age and increased instead
with size. This suggests that overall reproductive output did
not decline with age. In addition, a Bonferroni’s correction
applied to the relationship of germinability with age would
have raised no significance. Reduced seed germinability had
already been reported for the donor trees in Glen Loyne and
attributed to lack of pollination among the widely scattered
isolated trees (Bartholomew, Malcolm & Nixon 2001). Our
results suggest that there may also be an ageing component to
this decline, but this will need confirmation. Since no other
variable linked to either growth and reproduction was found
to be related to tree age, our findings support the theory that
many of the age-related patterns in growth, reproduction and
biochemical properties reported in the literature are primarily
size-related and have little ontogenetic basis. Dendro-ecological research on hundreds of Scots pine trees at several Scottish valleys very close to the original Glen Loyne population
employed here and with similar ages (Fish et al. 2010) likewise excluded the occurrence of senescence in these populations. Tree ring data from recently dead trees showed a
progressive reduction in relation to tree size, but ring width in
the years preceding mortality did not suddenly decline.
SIGNIFICANCE OF THESE FINDINGS FOR THE ECOLOGY
OF SENESCENCE IN WOODY PERENNIALS
A relationship between meristem age and a biomarker of ageing (DNA methylation) is reported here for centenarian trees,
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
Ageing in trees 563
suggesting the possibility that woody perennials may be able
to track time not only via increased rates of somatic mutations
in clonal species (Ally, Ritland & Otto 2010), but also via
epigenomic changes in the degree of global DNA methylation. Further studies are required to determine how significant
this pattern is. Although our analyses showed a significant
relationship with meristem age, the scatter of the data was
large, especially for the young leaves, and the relationship in
the RGCCA is non-significant at the standard P < 0.05. If a
Bonferroni’s correction had been applied to the GLM relationship between DNA methylation and age, a corrected significance level would indeed have been about P < 0.10. In
future studies, it may be preferable to target the analysis of
DNA methylation to specific DNA regions, as opposed to
attempting a global analysis, as done here, as this may
increase the significance levels found. Genes involved in
induced defenses against herbivores and pathogens would
seem to be ideal candidates, on the basis of the results presented here. Overall, it seems unlikely that the observed
changes with age in the methylation levels of mature leaves
indicate that a process of genetic deterioration is taking place
in the old pines. They more likely represent a mechanism of
ontogenetic control of the genes and of plant biochemistry.
The range of ages spanned by our sample covers most of
the lifespan of Scots pine, excluding the first century of life,
but including the vast majority of the later life (the maximum
known age for Scots pine is 750 years, Kirchhefer 2001),
with a span of more than 400 years between youngest and
oldest ramet. The lack of trees older than about 550 years is
a concern, but those individuals are extremely rare. The lack
of trees younger than 100 years may also be a problem, in
that our analysis only covered one specific developmental
phase of this tree, although separating the developmental processes leading to sexual maturation from those related to
senescence is also a challenge (e.g. Mencuccini et al. 2005,
2007; Martınez-Vilalta, Vanderklein & Mencuccini 2007;
Vanderklein et al. 2007). An obvious but unavoidable limitation of our study is the lack of a longitudinal perspective. It
is possible that the lack of senescence symptoms in our
grafted trees may have resulted from a progressive decrease
in the average frailty of our cohort, because of progressive
thinning of senescing individuals (e.g. Vaupel, Manton &
Stallard 1979; Vaupel 1990). Many of the native pinewoods
of Scotland suffered extensive clearance during the 18th and
19th centuries that adversely affected the age structure of the
remnants of native woodland (Edwards & Mason 2006). Glen
Loyne was, in the past, also heavily managed for timber and
subjected to intensive grazing by feral and domestic animals
(Beaumont et al. 1995), and therefore, both selective and
non-selective factors will have influenced the genetic composition of the remnant trees.
Specifically remarkable is the lack of any ontogenetic effect
on growth, leaf structure (SLA, area of a leaf) and leaf photosynthesis, suggesting that, if a distinction exists in woody
perennials between soma and germline, this results in ontogenetic reductions only in the latter (Ally, Ritland & Otto 2010;
these results). Also, while we did not find any declining
trends in total germinable seeds with meristematic age, we
did find a significant link between Age and Initiation of
Reproductive Structure (mediated by changes in gibberellin
levels). In addition, we also found a significant link between
Age and Induction of Chemical Defenses, which might suggest a reduced capacity for allocation to the plant’s defense
system with age (Boege & Marquis 2005). Therefore, while
the overall reproductive output does not decline with age in
old Scots pine, it remains unclear whether we should expect
that mortality rates should increase with age.
Plant senescence is frequently defined as the occurrence of
age-specific reductions in fertility or survival (e.g. review by
Salguero-G
omez, Shefferson & Hutchings 2013), whereas
ageing is frequently employed to indicate the mere passing of
chronological time. This population ecology definition does
not discriminate between various causes of physiological performance reductions in plants. Hamilton (1966) spoke of
accumulation of alleles with negative side effects later in life,
assuming therefore that these intrinsic processes have a clear
genetic basis, but this is far from clear. In many species, it
has been shown that size changes results in changes in reproductive capacity and increased growth rates; therefore, raising
the possibility that senescence processes have more to do with
size or stage transitions than age per se (e.g. Caswell 2012;
Caswell & Salguero-G
omez 2013; Shefferson & Roach 2013;
Tuomi et al. 2013). In trees (and possibly other plant groups),
an additional complication occurs, in that a progressive reduction in photosynthetic performance and growth efficiency has
been reported to occur frequently in the largest individuals.
The causes of these reductions are not entirely clear, but
probably result from a combination of increased hydraulic
resistance in tall trees (Mencuccini & Grace 1996; Ryan &
Yoder 1997) and increased respiratory burdens in organisms
with large living biomass (Yoda et al. 1965; Ryan, Binkley
& Fownes 1997). Re-invigoration of meristems by coppicing,
cutting, pruning, grafting or in-vitro propagation are wellknown techniques to reduce these burdens and return growth
rates to their maximum values and, along similar lines, plant
shrinkage and sectoriality have been shown to have important
physiological and ecological consequences (Salguero-G
omez
& Casper 2010, 2011). These techniques are sometimes
referred to as promoting rejuvenation, but in many cases (with
the notable exception of in-vitro propagation), it is likely that
the genetic developmental program has not been modified at
all (Mencuccini et al. 2005; Chen et al. 2012). Therefore, our
results call for a re-evaluation of the classical definition of
senescence as being driven only by age changes. Baudisch
et al. (2013) showed senescence to be a relatively rare phenomenon among angiosperms, occurring largely only in the
phanerophytes (woody shrubs and trees), that is, the organisms that by definition have not only the longest lifecycles,
but also the largest sizes. Our experiment was primarily
designed to disentangle the relative effects of age and size in
affecting senescence processes. While our results cannot be
employed to argue in favour or against the occurrence of negative or negligible senescence in Scots pine, they are entirely
compatible with the evidence by Baudisch et al. (2013).
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
564 M. Mencuccini et al.
Conclusions
The effects of age per se on physiology, growth and reproduction of Scots pine were isolated by grafting trees of ages
varying by more than 400 years onto homogeneous juvenile
rootstock. By doing so, we documented the existence of a
complex network of biochemical processes linking DNA
methylation with growth and reproduction. Very few of the
structural, morphological and physiological variables that we
measured were related to meristematic age. A significant relationship between meristematic age and the DNA methylation
level of leaves was found. Coupled with earlier observations
in this same species (Mencuccini et al. 2005, 2007; MartınezVilalta, Vanderklein & Mencuccini 2007; Vanderklein et al.
2007), our findings suggest that changes in DNA methylation
do not result in physiological deterioration in Scots pine.
Therefore, although a putative ontogenetic biomarker was
present in the leaves, no evidence of senescence in either
growth or in reproduction was found.
Acknowledgements
We are indebted to Luis Lopez-Sangil and Sheldon Goss for help during sampling and to Colin Edwards (Forest Research) for background information on
Glen Loyne. We are very grateful to the Serveis Cientıfico-Tecnics (Universitat
de Barcelona) for technical assistance. Arthur Tenenhaus helped in understanding RGCCA and provided the code to estimate the confidence intervals of the
correlation coefficients. This work was supported by the Spanish Government
(Projects MONTES CSD2008-00040, BFU2012-32057, PRI-AIBNZ-20110833, CGL2010-17172 and BFU2009-07294) and by the Catalan Government
project SGR 2009-458. Support for the research of SM was also received
through the prize ICREA Academia, funded by the Generalitat de Catalunya.
M. O~
nate held a FPI fellowship from the Spanish Government during studies.
MM is indebted to NERC grant NERC NE/I017749/1 for financial support.
References
Abdul-Hamid, H. & Mencuccini, M. (2009) Age- and size-related changes in
physiological characteristics and chemical composition of Acer pseudoplatanus and Fraxinus excelsior trees. Tree Physiology, 29, 27–38.
Ally, D., Ritland, K. & Otto, S.P. (2010) Aging in a long-lived clonal tree.
PLOS Biology, 8, e1000454.
Amaral, J.S., Casal, S., Torres, D., Seabra, R.M. & Oliveira, B.P. (2005)
Simultaneous determination of tocopherols and tocotrienols in hazelnuts by a
normal phase liquid chromatographic method. Analytical Sciences, 21, 1545–
1548.
Angelier, F., Weimerskirch, H., Dano, S. & Chastel, O. (2007) Age, experience
and reproductive performance in a long-liver bird: a hormonal perspective.
Behavioural Ecology and Sociobiology, 61, 611–621.
Bartholomew, A., Malcolm, D.C. & Nixon, C.J. (2001) The Scots pine population at Glen Loyne, Inverness-shire: present condition and regenerative
capacity. Scottish Forestry, 55, 141–148.
Baudisch, A. (2005) Hamilton’s indicators of the force of selection. Proceedings of the National Academy of Sciences of the United States of America,
102, 8263–8268.
Baudisch, A., Salguero-Gomez, R., Jones, O.R., Wrycza, T., Mbeau-Ache, C.,
Franco, M. & Colchero, F. (2013) The pace and shape of senescence in angiosperms. Journal of Ecology, 101, 596–606.
Beaumont, D., Dugan, D., Evans, G. & Taylor, S. (1995) Deer management
and tree regeneration in the RSPB reserve at Abernethy forest. Our Pinewood Heritage (ed. J.R. Aldhous), pp. 186–195. Forestry Commission, Royal
Society for the Protection of Birds and Scottish Natural Heritage, Edinburgh,
UK.
Boege, K. & Marquis, R.J. (2005) Facing herbivory as you grow up: the ontogeny of resistance in plants. Trends in Ecology and Evolution, 20, 441–448.
Bond, B.J. (2000) Age-related changes in photosynthesis of woody plants.
Trends in Plant Science, 5, 349–353.
Bond, B.J., Czarnomski, N.M., Cooper, C., Day, M.E. & Greenwood, M.S.
(2007) Developmental decline in height growth in Douglas fir. Tree Physiology, 27, 441–453.
Bossdorf, O., Richards, C.L. & Pigliucci, M. (2008) Epigenetics for ecologists.
Ecological Letters, 11, 106–115.
Carranza, J., Alarcos, S., Sanchez-Prieto, C.B., Valencia, J. & Mateos, C.
(2004) Disposable-soma senescence mediated by sexual selection in an ungulate. Nature, 432, 2215–2218.
Caswell, H. (2012) Matrix models and sensitivity analysis of populations classified by age and stage: a vec-permutation matrix approach. Theoretical Ecology, 5, 403–417.
Caswell, H. & Salguero-Gomez, R. (2013) Age, stage, and senescence in
plants. Journal of Ecology, 101, 585–595.
Chen, G.H., Wang, Y.J., Wang, X.M., Zhou, J.N. & Liu, R.Y. (2005) Effect of
aging on species-typical behaviors in senescence-accelerated mouse. Physiology & Behaviour, 85, 536–545.
Chen, Y.-T., Shen, C.H., Lin, W.D., Chu, H.A., Huang, B.L., Kuo, C.I., Yeh,
K.W., Huang, L.C. & Chang, I.F. (2012) Small RNAs of Sequoia sempervirens during rejuvenation and phase change. Plant Biology, 15, 27–36.
Curtin, F. & Schulz, P. (1998) Multiple correlations and Bonferroni’s correction. Biological Psychiatry, 44, 775–777.
Day, M.E., Greenwood, M.S. & Dıaz-Sala, C. (2002) Age- and size-related
trends in woody plant shoot development: regulatory pathways and evidence
for genetic control. Tree Physiology, 22, 507–513.
Diaz-Sala, C., Rey, M., Boronat, A., Besford, R. & Rodriguez, R. (1995) Variations in the DNA methylation and polypeptide patterns of adult hazel (Corylus avellana L.) associated with sequential in vitro subcultures. Plant Cell
Repords, 15, 218–221.
Edwards, C. & Mason, W.L. (2006) Stand structure and dynamics of four
native Scots pine (Pinus sylvestris L.) woodlands in northern Scotland.
Forestry, 79, 261–277.
Finch, C.E. (1990) Longevity, Senescence, and the Genome. University of Chicago Press, Chicago, IL.
Finnegan, E.J., Peacock, W.J. & Dennis, E.S. (1996) Reduced DNA methylation in Arabidopsis thaliana results in abnormal plant development. Proceedings of the National Academy of Sciences of the United States of America,
93, 8449–8454.
Finnegan, E.J., Genger, R.K., Peacock, W.J. & Dennis, E.S. (1998) DNA methylation in plants. Annual Review of Plant Physiology and Plant Molecular
Biology, 49, 223–247.
Fish, T., Wilson, R., Edwards, C., Mills, C., Crone, A., Kirchhefer, A.J., Linderholm, L., Loader, N.J. & Woodley, E. (2010) Exploring for senescence
signals in native Scots pine (Pinus sylvestris L.) in the Scottish Highlands.
Forest Ecology and Management, 260, 321–330.
Fraga, M.F., Ca~nal, M.J. & Rodrıguez, R. (2002) Phase-change related epigenetic and physiological changes in Pinus radiata D. Don. Planta, 4, 672–678.
Fraga, M.F., Rodrıguez, R. & Ca~nal, M.J. (2002) Genomic DNA methylation–
demethylation during aging and reinvigoration of Pinus radiata. Tree Physiology, 22, 813–816.
Goslin, P.G. (2006) Tree seeds. The Encyclopedia of Seeds: Science, Technology and Uses (eds M. Black, J.D. Bewley & P. Halmer), pp. 725–731. CAB
International, Wallingford.
Greenwood, M.S., Day, M.E. & Schatz, J. (2010) Separating the effects of tree
size and meristem maturation on shoot development of grafted scions of red
spruce (Picea rubens Sarg.). Tree Physiology, 30, 459–468.
Haffner, V., Enjalric, F., Lardet, L. & Carron, M.P. (1991) Maturation of
woody plants: a review of metabolic and genomic aspects. Annales des Sciences Forestieres, 48, 615–630.
Hamilton, W.D. (1966) Moulding of senescence by natural selection. Journal
of Theoretical Biology, 12, 12–45.
Harper, J.L. (1977) Population Biology of Plants. Academic Press, London, UK.
Holliday, R. & Plug, J.E. (1975) DNA modification mechanism and gene activity during development. Science, 187, 226–232.
Hudgins, J.W. & Franceschi, V.R. (2004) Methyl jasmonate induces traumatic
resin ducts, terpenoid resin biosynthesis, and terpenoid accumulation in developing xylem of Norway spruce stems. Plant Physiology, 129, 1003–1018.
Kirchhefer, A.J. (2001) Reconstruction of summer temperatures from tree-rings
of Scots pine (Pinus sylvestris L.) in coastal northern Norway. Holocene, 11,
41–52.
van Kooten, O. & Snel, J.F.H. (1990) The use of chlorophyll fluorescence nomenclature in plant stress physiology. Photosynthesis Research, 25, 147–150.
Lambe, P., Mutambel, H.S.N., Fouche, J.-G., Deltour, R., Foidart, J.-M. & Gaspar, T. (1997) DNA methylation as a key process in regulation of organogenic totipotency and plant neoplastic progression? In Vitro Cellular &
Developmental Biology-Plant, 33, 155–162.
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565
Ageing in trees 565
Lichtenthaler, H.K. & Wellburn, A.R. (1983) Determinations of total carotenoids and chlorophylls a and b of leaf extracts in different solvents.
Biochemical Society Transactions, 11, 591–592.
Loehle, C. (1997) Optimal defensive investment in plants. Oikos, 49, 199–208.
Martınez-Vilalta, J., Vanderklein, D. & Mencuccini, M. (2007) Tree height and
age-related decline in growth in Scots pine (Pinus sylvestris L.). Oecologia,
150, 529–544.
Matsuzaki, J., Norisada, M., Kodaira, J., Suzuki, M. & Tange, T. (2005) Shoots
grafted into the upper crowns of tall Japanese cedar (Cryptomeria japonica
D. Don) show foliar gas exchange characteristics similar to those of intact
shoots. Trees, 19, 198–203.
Medawar, P. (1952) An Unsolved Problem of Biology. Lewis, London.
Mencuccini, M. & Grace, J. (1996) Hydraulic conductance, light interception
and needle nutrient concentration in Scots pine stands (Thetford, UK) and
their relations with net aboveground primary production. Tree Physiology,
16, 459–468.
Mencuccini, M., Martınez-Vilalta, J., Vanderklein, D., Hamid, H.A., Korakaki,
E., Lee, S. & Michiels, B. (2005) Size-mediated ageing reduces vigour in
trees. Ecology Letters, 8, 1183–1190.
Mencuccini, M., Martınez-Vilalta, J., Hamid, H.A., Korakaki, E. & Vanderklein, D. (2007) Evidence for age- and size-mediated controls of tree growth
from grafting studies. Tree Physiology, 27, 463–473.
M€
uller, M. & Munne-Bosch, S. (2011) Rapid and sensitive hormonal profiling
of complex plant samples by liquid chromatography coupled to electrospray
ionization tandem mass spectrometry. Plant Methods, 7, 1–11.
Munne-Bosch, S. (2007) Aging in perennials. Critical Reviews in Plant Sciences, 26, 123–138.
Munne-Bosch, S. (2008) Do perennials really senesce? Trends in Plant Science,
13, 216–220.
Munne-Bosch, S. & Lalueza, P. (2007) Age-related changes in oxidative stress
markers and abscisic acid levels in a drought-tolerant shrub, Cistus clusii
grown under Mediterranean field conditions. Planta, 225, 1039–1049.
O~
nate, M. & Munne-Bosch, S. (2008) Meristem aging is not responsible for
the age-related changes in growth and abscisic acid levels in the Mediterranean shrub, Cistus clusii. Plant Biology, 10, 148–155.
O~
nate, M. & Munne-Bosch, S. (2009) Influence of plant maturity, shoot reproduction and sex on vegetative growth in the dioecious plant, Urtica dioica.
Annals of Botany, 104, 945–956.
O~
nate, M. & Munne-Bosch, S. (2010) Loss of flower bud vigour in the Mediterranean shrub, Cistus albidus L. at advanced developmental stages. Plant
Biology, 12, 475–483.
Pemeger, T.V. (1998) What is wrong with Bonferroni adjustments. British
Medical Journal, 136, 1236–1238.
Pe~
nuelas, J. & Munne-Bosch, S. (2010) Potentially immortal? New Phytologist,
187, 564–567.
R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Reimers, E., Holmengen, N. & Mysterud, A. (2005) Life-history variation of
wild reindeer (Rangifer tarandus) in the highly productive North Ottadalen
region. Norway Journal of Zoology, 265, 53–62.
Reyna-L
opez, G.E., Simpson, J. & Ruiz-Herrera, J. (1997) Differences in DNA
methylation patterns are detectable during the dimorphic transition of fungi
by amplification of restriction polymorphisms. Molecular Genetics and Genomics, 253, 703–710.
Ricklefs, R.E. & Finch, C.E. (1995) Aging: A Natural History. Scientific American Library, New York, NY, USA.
Roach, D.A. (1993) Evolutionary senescence in plants. Genetica, 91, 53–64.
Ronemus, M.J., Galbiati, M., Ticknor, C., Chen, J. & Dellaporta, S.L. (1996)
Demethylation-induced developmental pleiotropy in Arabidopsis. Science,
273, 654–657.
Ryan, M.G., Binkley, D. & Fownes, J.H. (1997) Age-related decline in forest
productivity: patterns and processes. Advances in Ecological Research, 27,
213–262.
Ryan, M.G. & Yoder, B.J. (1997) Hydraulic limits to tree height and tree
growth. BioScience, 47, 235–242.
Salguero-G
omez, R. & Casper, B.B. (2010) Keeping plant shrinkage in the
demographic loop. Journal of Ecology, 98, 312–323.
Salguero-G
omez, R. & Casper, B.B. (2011) A hydraulic explanation for sizespecific plant shrinkage: developmental hydraulic sectoriality. New Phytologist, 189, 229–240.
Salguero-G
omez, R., Shefferson, R.P. & Hutchings, M.J. (2013) Plants do not
count… or do they? New perspectives on the universality of senescence.
Journal of Ecology, 101, 545–554.
Salmon, A., Clotault, J., Jenczewski, E., Chable, V. & Manzanares-Dauleux,
M.J. (2008) Brassica oleracea displays a high level of DNA methylation
polymorphism. Plant Sciences, 174, 61–70.
Shefferson, R.P. & Roach, D.A. (2013) Longitudinal analysis in Plantago:
strength of selection and reverse-age reveal age-indeterminate senescence.
Journal of Ecology, 101, 577–584.
Silvertown, J., Franco, M. & Perez-Ishiwara, R. (2001) Evolution of senescence
in iteroparous perennial plants. Evolutionary Ecological Research, 3, 393–
412.
Taiz, L. & Zeiger, E. (2010) Plant Physiology. Sinauer Associates, Sunderland,
MA, 782 pp.
Tenenhaus, A. & Tenenhaus, M. (2011) Regularized generalized canonical correlation analysis. Psychometrika, 76, 275–284.
Theiss, G. & Follmann, H. (1980) Methylcytosine formation in wheat embryo
DNA. Biochemical Biophysical Research Communications, 94, 291–297.
Thomas, H. (2002) Ageing in plants. Mechanisms of Ageing and Development,
123, 747–753.
Thomas, H. (2012) Senescence, ageing and death of the whole plant. New Phytologist, 197, 696–711.
Tuomi, Y., Crone, E.E., Gremer, J.R., Jakalaniemi, A., Lesica, P., Pedersen, B.
& Ramula, S. (2013) Prolonged dormancy interacts with senescence for two
perennial herbs. Journal of Ecology, 101, 566–576.
Valdes, A.E., Fernandez, B. & Centeno, M.L. (2003) Alterations in endogenous
levels of cytokinins following grafting of Pinus radiata support ratio of cytokinins as an index of ageing and vigour. Journal of Plant Physiology, 160,
1407–1410.
Valdes, A.E., Fernandez, B. & Centeno, M.L. (2004) Hormonal changes
throughout maturation and ageing in Pinus pinea. Plant Physiology & Biochemistry, 42, 335–340.
Valdes, A.E., Centeno, M.L., Espinel, S. & Fernandez, B. (2002) Could plant
hormones be the basis of maturation indices in Pinus radiata? Plant Physiology & Biochemistry, 40, 211–216.
Vanderklein, D., Martınez-Vilalta, J., Lee, S. & Mencuccini, M. (2007) Plant
size, not age, regulates growth and gas exchange in grafted Scots pine trees.
Tree Physiology, 27, 71–79.
Vaupel, J.W. (1990) Relatives risks: frailty models of life history risks. Theoretical Population Biology, 37, 220–234.
Vaupel, J.W., Manton, K.G. & Stallard, E. (1979) The impact of heterogeneity
in individual frailty on the dynamics of mortality. Demography, 16, 439–454.
Vaupel, J.W., Baudisch, A., D€olling, M., Roach, D.A. & Gampe, J. (2004) The
case for negative senescence. Theoretical Population Biology, 65, 339–351.
Webber, B.L. & Woodrow, I.E. (2009) Chemical and physical plant defence
across multiple ontogenetic stages in a tropical rain forest understorey tree.
Journal of Ecology, 97, 761–771.
Williams, G.C. (1957) Pleiotropy, natural selection, and the evolution of senescence. Evolution, 11, 398–411.
Yoda, K., Shinozaki, K., Ogawa, H., Hozumi, K. & Kira, T. (1965) Estimation
of the total amount of respiration in woody organs of trees and forest communities. Journal of Biology, Osaka City University, 16, 15–26.
Received 26 January 2013; accepted 16 January 2014
Handling Editor: Roberto Salguero-Gomez
Supporting Information
Additional Supporting Information may be found in the online version of this article:
Appendix S1. Additional methodological details and results.
Table S1. Description of the Methylation-Sensitive Amplification
Polymorphism analysis (MSAP) to detect the methylation state of
genomic DNA by differential cleavage of the restriction site (CCGG)
and by the restriction isoschizomer pair HpaII and MspI.
Figure S1. Relationship between meristematic age (X axis) and various other growth and reproductive parameters of the grafted trees.
© 2014 The Authors. Journal of Ecology © 2014 British Ecological Society, Journal of Ecology, 102, 555–565