Download The evolutionary ecology of senescence

Functional Ecology 2008, 22, 371–378
doi: 10.1111/j.1365-2435.2008.01418.x
The evolutionary ecology of senescence
Blackwell Publishing Ltd
P. Monaghan1,*, A. Charmantier2, D. H. Nussey3 and R. E. Ricklefs4
1
Division of Environmental and Evolutionary Biology, Institute of Biomedical and Life Sciences, Graham Kerr Building,
University of Glasgow, Glasgow G12 8QQ, UK; 2Centre d’Ecologie Fonctionnelle et Evolutive, CNRS U.M.R. 5175, 1919,
route de Mende, 34293 Montpellier cedex 5, France; 3Institute of Evolutionary Biology, University of Edinburgh, Kings’
Buildings, West Mains Road, Edinburgh EH9 3JT, UK; and 4Department of Biology, University of Missouri-St. Louis, One
University Boulevard, St. Louis, MO 63130, USA
Summary
1. Research on senescence has largely focused on its underlying causes, and is concentrated on
humans and relatively few model organisms in laboratory conditions. To understand the
evolutionary ecology of senescence, research on a broader taxonomic range is needed, incorporating
field, and, where possible, longitudinal studies.
2. Senescence is generally considered to involve progressive deterioration in performance, and it is
important to distinguish this from other age-related phenotypic changes. We outline and discuss the
main explanations of why selection has not eliminated senescence, and summarise the principal
mechanisms thought to be involved.
3. The main focus of research on senescence is on age-related changes in mortality risk. However,
evolutionary biologists focus on fitness, of which survival is only one component. To understand the
selective pressures shaping senescence patterns, more attention needs to be devoted to age-related
changes in fecundity.
4. Both genetic and environmental factors influence the rate of senescence. However, a much clearer
distinction needs to be drawn between life span and senescence rate, and between factors that alter
the overall risk of death, and factors that alter the rate of senescence. This is particularly important
when considering the potential reversibility and plasticity of senescence, and environmental effects,
such as circumstances early in life.
5. There is a need to reconcile the different approaches to studying senescence, and to integrate
theories to explain the evolution of senescence with other evolutionary theories such as sexual and
kin selection.
Key-words: ageing, antagonistic pleiotropy, disposable soma, evolution, lifespan, mortality,
mutation accumulation, oxidative stress
Organisms change during their lifetimes in many ways, sometimes permanently as with most aspects of body growth and
development, but sometimes temporarily, as with seasonal
leaf loss and replacement, growth and regression of gonads,
pre-migratory and pre-hibernation accumulation of fat reserves, or development of thicker fur or down in response to
decreases in temperature. The predictability and reversibility
of such change is of great interest to biologists, and we seek
to understand how change is controlled and what fitness
advantages it confers. Changes that occur in old age, generally
referred to as ageing or senescence, are particularly fascinating,
since these progressive and irreversible changes impair rather
than improve performance, with apparently negative effects
*Correspondence author. E-mail: [email protected]
on fitness. Understanding the evolution and persistence of
senescence therefore poses a particular challenge.
The typical route followed in biological research is to
observe a natural process and then try to understand and
explain it by investigations under controlled conditions, often
in the laboratory. In this respect, research on senescence has
followed an unusual path since, in many animal taxa, it was
first studied in captive or laboratory conditions. The subsequent
emphasis on the mechanisms responsible for impairment
of performance in old age has been due, in part, to the great
interest in whether we might intervene to slow or reverse
senescence in humans. With this aim in mind, the majority of
studies have focused on model species in laboratory conditions.
These studies have greatly increased our knowledge and understanding of senescence, providing considerable insight into
© 2008 The Authors. Journal compilation © 2008 British Ecological Society
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P. Monaghan et al.
the genetic and cellular mechanisms (Kirkwood & Austad
2000; Bonsall 2006). This approach, however, is not appropriate
for understanding the evolutionary ecology of senescence.
Field and laboratory studies on a broader range of organisms
are needed to understand biological variation in the processes
contributing to senescence.
Accordingly, the papers in this special feature on the
‘Evolutionary Ecology of Senescence’ are intentionally biased
towards investigations of senescence in natural conditions
and/or non-model species. The papers focus on a number of
new developments in the study of senescence likely to be of
particular interest to ecologists. The importance of the
comparative approach in both evolutionary and mechanistic
studies is demonstrated by Ricklefs (2008), while Nussey
et al. (2008) discuss the challenges facing field ecologists
seeking to accurately measure senescence rates in free-living
populations. The great advantages of data from longitudinal
studies of known individuals are highlighted. Münch et al.
(2008) review a remarkable body of emerging work on senescence and its causes in the honey bee (Apis mellifera), a species
in which the life spans of genetically identical individuals vary
by an order of magnitude or more. They show how novel
insights can be gained by studying a non-model species that
has a particularly interesting and relevant life-history pattern.
Mangel (2008) links environmental variation with senescence
patterns by developing a general life-history model linking
early life conditions to degenerative disease in later life. He
provides a quantitative framework that can be used to assess
costs and benefits of exposure to environmental stressors in
early life. Wilson et al. discuss and illustrate how a quantitative
genetic approach can be used to examine the genetic basis of
senescence rates and their evolution in wild populations. Their
approach provides a fertile testing ground for evolutionary
theory outside the laboratory. Finally, Bonduriansky et al.
(2008) examine the largely unexplored links between the evolution of senescence and the evolution of sexual strategies. In
this introductory paper, we discuss these and related issues more
broadly. We also highlight and discuss some areas of controversy, and how these might be resolved by further research.
What is senescence?
This might seem a straight forward enough question, but in
fact the terms ‘ageing’ and ‘senescence’ are used in various
ways. There is obviously a distinction between age-related
phenotypic change, which includes many developmental and
maturational processes, and ‘ageing’ in the mature organism.
In the individual, senescence is generally thought of as an
inevitable, irreversible accumulation of damage with age that
leads to loss of function and eventual death. This too is how
the term ageing is generally used. Thus, for simplicity, the
terms ageing and senescence are treated as synonymous in
this special feature. We preferentially use the latter here,
because there are phenotypic changes associated with advancing age, such as greying of the hair in many mammals, which
might not in themselves impair performance in any way.
Indeed, in some species of primates such as the gorilla
(Gorilla gorilla gorilla), such greying is associated with an
increase in performance, when so-called ‘silver backs’ gain
mating or resource acquisition advantages (Margulis, Whitham
& Ogorzalek 2003). Are these apparently trivial phenotypic
changes, albeit age-related, not in fact ‘senescent’ or are they
harbingers, or side effects, of deterioration at other levels in
the body? To answer such questions, we need a closer integration
of studies of mechanisms with studies of fitness consequences.
How might senescence have evolved?
Senescence has captured the attention of evolutionary
biologists for more than a century (Finch 1990; Kirkwood &
Rose 1991; Charlesworth 2000; Hughes & Reynolds 2005).
The German biologist August Weissman, who developed the
germ plasm theory of inheritance distinguishing germ line
and somatic cell lineages, proposed in 1882 that senescence
benefits the population by removing old, unproductive
individuals (Weissman 1889). However, since senescence as
explained by Weissman cannot benefit the individual, it
should be selected against except in the special circumstances
where kin or group selection can pertain. Moreover, because
Weissman’s hypothesis presupposes the existence of senescence,
it cannot explain its origin.
Currently, there are three main, albeit related, theories
for the evolution of senescence. The first can be traced to
Haldane (1941) and Medawar (1952), who suggested that,
because individuals die of causes that are not connected to
senescence (termed extrinsic factors), the force of selection
declines with age in proportion to Fisher’s reproductive value
(Fisher 1930), which measures the contribution of an individual
to future generations. Medawar supposed that deleterious
mutations expressed at older ages would accumulate in
populations and reduce the survival and reproductive success
of older individuals. Williams extended this idea in a second
theory by proposing the existence of antagonistically
pleiotropic genes that have deleterious effects in old age, but
are nonetheless favoured because of their contributions to the
survival and fecundity of younger individuals (Williams
1957). According to this second hypothesis, senescence is
considered as a consequence of positive selection on genetic
factors that happen to have negative effects later in life.
Both of the above theories have been refined somewhat
since they were first put forward. Notably, Hamilton (1966)
clarified the nature of selection on genes expressed at different
ages. He pointed out that reproductive value is not the
appropriate measure of the strength of selection because this
parameter reflects only an individual’s contribution to future
generations and not the contribution from the gene pool as a
whole. Indeed, in the absence of senescence, the reproductive
value of an individual alive at any age (its expectation of
future reproduction) is constant, providing of course its
environmental circumstances remain the same. Therefore,
changes in reproductive value with age cannot explain the
evolution of senescence. Rather, even in the absence of senescence, the decline in the proportion of individuals remaining
alive at progressively older ages, as a consequence of extrinsic
© 2008 The Authors. Journal compilation © 2008 British Ecological Society, Functional Ecology, 22, 371–378
Evolutionary ecology of senescence 373
mortality factors, provides sufficient explanation for the
decline in the strength of selection with age. This is because, at
least for those species that reach a fixed adult size, the greater
the proportion of individuals experiencing the positive or
negative effects of a particular trait, the stronger will be the
selective forces. Thus, Medawar’s mutation accumulation
theory posits that, because there are so few individuals alive
in older age classes as a result of non-senescence-related
mortality factors, there is only very weak selection against
mutations that do not have detrimental effects until old age.
The antagonistic pleiotropy idea posits that, because more
individuals are alive in younger age classes, mutations that
produce positive fitness benefits in young individuals are
favoured by selection even when they are detrimental in old
individuals. The decline in the strength of selection with age
can be offset to some extent in species that grow and increase
in fecundity throughout their adult lives, such as turtles and
some fish, in which case selection to postpone senescence
can persist into very old age (Vaupel et al. 2004); in a few
extreme cases, such as Hydra vulgaris, organisms seem to
show negligible senescence and apparently indefinite life span
(Martinez 1998).
The third theory for the evolution of senescence, developed
by Kirkwood and termed the ‘disposable soma theory’, is
centred on trade-offs in the allocation of limiting resources
to self-maintenance and other activities, particularly
reproduction (Kirkwood 1977, 2002; Kirkwood & Holliday
1979). In this theory, decline in function results from unrepaired
damage to molecules, cells, and tissues as a result of life
processes, particularly the harmful byproducts of normal
metabolism and the stress imposed by reproduction and other
factors; this damage therefore accumulates with age (Westendorp & Kirkwood 1998; Sgro & Partridge 1999). Kirkwood
emphasises that the rate of accumulation of such damage is
influenced by various biochemical mechanisms that prevent
or repair damage, such as antioxidants and DNA repair
enzymes. These mechanisms carry costs for the individual in
terms of deployment of resources that might otherwise have
been allocated to provisioning offspring or avoiding environmental causes of mortality, such as predation, inclement
weather, and food shortages. Accordingly, the expected rate
of deterioration of an individual reflects an optimized balance
between resource allocation to self-maintenance and to other
competing activities (Kirkwood 2005).
The disposable soma theory posits that there is no point in
maintaining the soma beyond an age that the individual can
reasonably expect to attain in its particular environment.
Thus, individuals that live in a safer environment have a
longer expectation of life and selection should increase
allocations towards better prevention and repair mechanisms.
Kirkwood’s hypothesis is based on conflicting demands,
which can occur within a life-history stage or across different
life-history stages; where the latter occurs, investment
patterns that confer early life benefits are likely to be favoured
by selection. The disposable soma theory can be seen as a
phenotypic version of antagonistic pleiotropy; its emphasis
is on the age-related consequences of resource allocation
trade-offs rather than the antagonistic consequences of the
expression of a gene at different ages.
Thus, we have three different explanations of why selection
to maximize individual fitness has not acted to eliminate
senescence. The mutation accumulation theory suggests that
the forces of selection against senescence are simply too weak,
which is perhaps the least convincing. The antagonistic
pleiotropy theory suggests that senescence is a consequence
of an unfortunate link between the benefits that some traits
provide to young organisms and their negative consequences
late in life. The disposable soma theory suggests that while
damage is inevitable, the rate of senescence is a consequence
of the extent to which selection or individual circumstances
favour the allocation of resources to repair. These three
evolutionary processes are not mutually exclusive and they may
well operate to a variable extent in different species. There is
some empirical evidence in support of each (Kirkwood &
Austad 2000) and Wilson et al. (2008) provide a short review
of the testing of these hypotheses.
What causes senescence?
To distinguish between these evolutionary theories of senescence, and/or identify the circumstances under which they
apply, we need to know more about the proximate processes
responsible for organism senescence and how these are
influenced by genetic and environmental factors. Many
mechanisms have been identified as contributing to agerelated deterioration in function (Nemoto & Finkel 2004),
and it is not our intention to review these fully here (see also
papers by Ricklefs and Münch 2008). One process that is
widely believed to play an important role is the accumulation
of oxidative damage, now termed the free radical theory
(Harman 1956; Beckman & Ames 1998; Finkel & Holbrook
2000; Nemoto et al. 2004). The normal oxidative production
of ATP by the mitochondria produces as a byproduct various
reactive oxygen species (ROS) that can oxidize a variety of
macromolecules, including lipids, proteins and DNA, and
interfere with cell and tissue function (Finkel & Holbrook 2000;
Barja 2004). Such oxidative damage is a strong candidate
for senescence-related changes in individuals (Stadtman 1992;
Hamilton et al. 2001; Kujoth et al. 2007). The production of
ROS in the mitochondria can be reduced by altering
membrane proton gradients (Brand 2000; Balaban, Nemoto
& Finkel 2005), but this results in reduced efficiency in
producing ATP and increased overall energy requirement
(Serra et al. 2003; Speakman et al. 2004; Humphries et al. 2005).
There appears to be no simple connection between ROS
production and life span (Perez-Campo et al. 1998; Barja 2004),
and the production of ROS can be balanced to some extent
by the maintenance of systems to prevent their damaging
effects. These include the ROS scavenging antioxidant
enzymes and other antioxidants (Sohal, Mockett & Orr
2002). However, these mechanisms presumably require energy
and nutrient allocation, and potentially interfere with the
roles of ROS as signalling molecules and in defence against
pathogens. Balancing the generation of free radicals and
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374 P. Monaghan et al.
defence against oxidative stress appears to be an important
mechanism underpinning life-history trade-offs. Thus, the
metabolic processes of organisms, and their pattern of energy
expenditure, are likely to be very important in influencing
senescence. Many of the genes that appear to play a role in
influencing senescence and life span regulate mitochondrial
function and metabolic parameters, and responses to oxidative stress. The insulin–IGF-1 pathway, which is involved in
nutritional signalling and metabolic regulation, appears to be
of particular importance, and is relatively well conserved
across taxa (Gems & Partridge 2001;Tatar, Bartke & Antebi
2003; Nemoto et al. 2004).
Another potentially important mechanism that influences
senescence, and could underlie life-history trade-offs involving
life span, is telomere attrition (Blackburn 1991; Monaghan
& Haussmann 2006; Haussmann et al. 2007). Telomeres
are regions of non-coding highly repetitive DNA that cap the
ends of chromosomes, enabling cells to distinguish chromosome
ends from chromosome breaks. Because some DNA is lost at
the ends of chromosomes with each replication cycle, telomeres
also enable cell lines to undergo the repeated replications
necessary to build an organism and maintain its tissues
without loss of coding sequences. When telomere length
in nuclear chromosomes declines to a certain point, DNA
replication ceases and the cell enters a state of replicative
senescence. Such cells either die, or remain in tissues; in the
latter case, they can secrete substances that cause further
damage. Furthermore, the genome tends to become unstable
when telomere length is short, which is associated with many
negative effects (Campisi 2005). Studies of the links between
cellular and organism senescence are still relatively few (Herbig et al. 2006). Comparative studies of telomere dynamics
are also very limited. Studies in wild birds have suggested a
correlation between the potential longevity of individuals and
telomere loss (Haussmann et al. 2003; Pauliny et al. 2006;
Haussmann et al. 2007). Most telomere loss occurs early in
life, and the rate of loss appears to be linked to growth rate
(Hall et al. 2004). Thus, telomere loss could mediate the
trade-off between growth rate and senescence (Blount et al.
2003), but more work is needed on the links between cellular and organism senescence (Monaghan & Haussmann
2006).
Genes, senescence and evolution
To understand the evolution of senescence, we do of course
need to know about its genetic basis. Genetic research on
senescence has tended to follow one of two paths. Molecular
gerontologists have sought to identify candidate genes
associated with longevity in model study systems (Kenyon
et al. 1993). At the same time, evolutionary biologists have used
artificial selection and quantitative genetic techniques to test
for age-specific genetic effects consistent with either mutation accumulation or antagonistic pleiotropy (Rose 1984;
Charlesworth & Hughes 1996). Both approaches have yielded
great insight into the process of senescence. Molecular work
has identified numerous genes associated with increased
longevity in humans, fruit flies and nematode worms and has
pinpointed metabolic pathways that are likely to play a
crucial role in driving variation in longevity and senescence
patterns (Kenyon et al. 1993; Lin, Seroude & Benzer 1998;
Suh et al. 2008; Nemoto et al. 2004). However, the significance
of many of these mutations to senescence in natural populations is unclear. Artificial selection and quantitative genetic
breeding experiments on laboratory fruit flies have yielded
compelling evidence for age-specific gene action consistent
with both mutation accumulation and antagonistic pleiotropy
(Rose & Charlesworth 1980; Rose 1984; Charlesworth &
Hughes 1996; Snoke & Promislow 2003). One challenge in the
emergence of an inter-disciplinary approach to senescence is
the reconciliation of these two approaches both to classical
model systems and to a wider range of systems both inside
and outside the laboratory. The increasing availability of
advanced genomic technologies and interest in the application
of quantitative genetic and quantitative trait locus (QTL)
mapping techniques to non-model study systems is likely to
facilitate such an integration (e.g. Wilson et al. 2008; Slate
2005). Approaches such as QTL mapping could help link
specific regions of the genome with variation in longevity,
senescence rates and trade-offs across life stages in any study
system, and tie together ultimate evolutionary processes
and more proximate genetic and molecular mechanisms
underpinning senescence.
Developing our theoretical understanding of how natural
selection acts on senescence rates is another important area
in need of further research. The very fundament of the
evolutionary theory of senescence – the expectation that the
force of natural selection should inevitably weaken with age
(Hamilton 1966) – has been questioned recently by theoreticians on the basis that, as mentioned already, in systems
where size or fecundity increase through adulthood, the onset of
senescence can be substantially or perhaps even indefinitely
delayed (Baudisch 2005; Baudisch 2008). Theoreticians have
also recently challenged Williams’ classic theoretical prediction
that reduction in mortality factors that are age- and conditionindependent should lead to selection for slower senescence
(Williams & Day 2003; Reznick et al. 2004; Williams et al.
2006). Williams’ prediction, although widely accepted and
tested, is of course dependent on the validity of separating
intrinsic (senescence-related) and extrinsic (non-senescencerelated) mortality risks (Abrams 1993; Williams & Day 2003).
Such a separation might be possible in laboratory studies in
which an age-independent hazard can be experimentally
applied, but how applicable is this to natural populations? On
the face of it, such a distinction seems improbable in the wild,
since, for example, vulnerability to disease or predators seems
likely vary with age (Williams & Day 2003). Interestingly, comparison of age-related mortality patterns in birds in captivity
and in the wild does not support this, since the rate of
senescence remains similar despite the absence of important
extrinsic mortality factors ‘such as predation’ in captive
conditions (see Ricklefs 2008). This highlights our need to
know more about the causes of death, and how vulnerability
to these causes does or does not change with environmental
© 2008 The Authors. Journal compilation © 2008 British Ecological Society, Functional Ecology, 22, 371–378
Evolutionary ecology of senescence 375
circumstances and with age. Rather than trying to separate
causes of mortality into intrinsic and extrinsic mortality
factors, it might be more fruitful to consider the extent to which
any one factor has senescence-dependent and senescenceindependent components. The number of predators in an
area might be age- and condition-independent, but how
fast you can run away from them is not. The inclusion of a
condition-dependent environmental hazard alters the rate of
age specific deterioration early and late in life, and we need
now to focus on more detailed analyses of changes in the rate
of senescence across the lifetime, and indeed also on the timing
of its onset, which has received little theoretical and empirical
consideration.
More interaction with theories of the evolution of senescence and other areas of evolutionary theory is also needed.
There is currently only a very limited theoretical literature
linking either kin (Bourke 2007) or sexual selection (Bonduriansky 2008) to the evolution of senescence. Bonduriansky
et al., review of the latter subject reveals remarkable theoretical
and empirical gaps: theoretical predictions remain unclear
and data with which to test them scarce. For example, although
potentially fundamental to the theories of senescence
evolution, links between the intensity of sexual selection and
senescence are still largely undescribed and theoretical
predictions unresolved. Should higher sexual competition
result in more rapid senescence due to a ‘live fast, die young’
trade-off, or, conversely, should it result in slower senescence
because of stronger selection on high performance individuals?
The questions and discussion presented in Bonduriansky
et al.’s paper will undoubtedly stimulate multiple experimental
tests in the near future.
Environmental effects on senescence
Given the diversity of mechanisms that underlie the process
of senescence, it is not surprising that environmental influences are important in its expression (see Münch et al. and
Mangel 2008). Generation of free radicals, for example, will
be influenced by the pattern of energy expenditure, and the
effectiveness of antioxidant defences influenced by dietary
factors. Levels of environmental stressors, such as food
availability, temperature, predators and competitors will also
vary. A well-documented and robust environmental effect
on senescence in laboratory studies is the increased life span
associated with reduced food intake. Based on experimental
results with calorie and diet restriction, Masoro (1998)
developed the hormesis hypothesis (see Mangel 2008),
which states that longer life under these conditions results
from the effect of any number of mild caloric and nutritional
stresses that bring protective and repair mechanisms into play.
The hormesis hypothesis is similar to Wingfield et al.’s ideas
about the effects of stress realised through the hypothalamic–
pituitary–adrenal (HPA) axis, mediated by glucocorticoid
secretions (Boonstra 1994, 2005; Wingfield et al. 1998). Thus,
mild stresses induce protective mechanisms that enhance
immediate survival but might also extend life more generally
by altering the rate of senescence (Gems & Partridge 2008).
Chronic severe stress has the opposite effect, possibly through
continuously elevated metabolism and mobilization of energy
reserves. Processes that improve resistance to stress, such as
the expression of heat shock proteins, might reduce damage
generation and accumulation, and thereby have life-extending
effects (Ogburn et al. 1998; Kapahi, Boulton & Kirkwood 1999;
Fabrizio et al. 2001; Ogburn et al. 2001; Zera & Harshman
2001; Lithgow & Walker 2002). However, in addition to the
effects on senescence, we also need to know effects on other
fitness-related parameters such as reproductive output.
Furthermore, the distinction between factors that alter the
risk of death, as opposed to the rate of senescence, is very
important in this context (see below).
It is becoming increasingly clear that environmental
circumstances and events during growth and development,
experienced directly or as a result of maternal effects, can
have long-term consequences for the pattern of degeneration
later in life (Metcalfe & Monaghan 2001), Mangel (2008)
provides a life-history approach to modelling the costs and
benefits of early life effects in relation to the adult environment,
likely to be generally applicable. Studies in wild populations
are increasingly finding such links across life-history stages
(Reid et al. 2003; Nussey et al. 2007; Keller, Reid & Arcese
2008). There are many mechanistic pathways through which
such a link could occur – antagonistically pleiotropic effects
creating a trade-off between rates of growth and senescence,
for example. Alternatively, sustaining a high early growth rate
might have damaging effects that do not manifest themselves
until later in life. Environmentally induced variation in the
pattern of growth is known to alter many aspects of the
phenotype, including antioxidant defences (Blount et al. 2003),
telomere dynamics (Hall et al. 2004; Monaghan et al. 2006;
Houben et al. 2008) and stress responses (McEwen 2007), all
of which can influence senescence rates.
Clearly, both genetic and environmental factors are likely
to influence the pattern of senescence, and to a variable extent
in different organisms. Dissecting these effects is an important focus for future interdisciplinary studies.
Identifying and measuring senescence
Recognising and measuring deterioration in performance in
animals pose formidable difficulties, especially in the wild
(Nussey et al. 2008). At the individual level, we tend to look for
phenotypic changes with age that are linked to reduced fecundity and increased mortality risk. Such phenotypic changes
can be difficult to recognise and might be minimal in some
taxa (see Ricklefs 2008). At the population level, however, agerelated changes in average fecundity and survival probabilities
with age are often used as measures of senescence, but can
lead to senescence being misidentified or missed altogether.
Longitudinal studies of known individuals can get round
some of the problems, but are difficult and time consuming
(Nussey et al. 2008). Many studies of senescence therefore
focus on age at death. However, the distinction between life
span and senescence raises important considerations for evolutionary ecologists.
© 2008 The Authors. Journal compilation © 2008 British Ecological Society, Functional Ecology, 22, 371–378
376
P. Monaghan et al.
First, age at death by itself does not measure senescence.
Variation in average age at death amongst populations or
species can arise solely as a consequence of variation in the
extrinsic mortality factors such as predation or disease risk,
and need not be related to variation in the rate of senescence.
It is also important to realise that there can be intrinsic, but
still non-senescence-related, factors that alter life expectancy.
Such factors, which might be environmentally induced, could
alter vulnerability (sometimes called ‘frailty’) over the short
or long term, producing differences in life span that are not
due to differences in the rate of senescence. For example,
phenotypic effects of early life conditions might elevate the
risk of death at all ages, but the rate of senescence itself might
be unchanged. The timing of the onset of senescence, rather
than its progression, could also change, thereby affecting
longevity (Hulbert et al. 2004). This kind of effect has recently
been found in Drosophila: flies subjected to dietary restriction
exhibit an immediate drop in the risk of death, but the agerelated increase still proceeds at the same pace. Interestingly,
this is not the case with changes in temperature. Reducing
temperature does seems to reduce the subsequent accumulation
of damage, resulting in the flies growing old more slowly in the
cold (Hulbert et al. 2004).
An additional point to bear in mind here is that we might also
see age-specific changes in the risk of death due to variation in
factors other than the rate of damage accumulation. Such
changes can then appear to be age-related when they are not, for
example, when increasing age and changing environmental
conditions are confounded. It is important therefore, if
possible, to study more than one cohort in the wild. It is also
possible that the risk of death might change with age, without
being due to senescence if individuals take on new roles or
occupy different environments with age, which expose them
to higher disease or predation levels. Changes in investment
patterns with age could also mean a higher risk of death. For
example, changes in the environment or the onset of sexual
maturity might mean that an organism has to allocate more
resources to, say, foraging or thermoregulation at the expense
of, say, immune function. Alternatively reduced cognitive
ability as a consequence of poor growth conditions, as has
been found in zebra finches (Fisher, Nager & Monaghan
2006), might not affect mortality risk until an individual has
the increased demand of dependent offspring. Such effects
can increase the risk of death in mature individuals, but not as
a consequence of accumulated damage. In some cases, such
altered mortality risk could be reversible, but not where it is a
consequence of permanent phenotypic change. The apparent
reversibility of senescence in the honey bee challenges the
view that senescence is caused by the accumulation of irreversible damage. However, it could also be due to an associated
change in risk of death for other reasons, as suggested above
(see Münch et al. 2008).
To understand and evaluate such effects, we need more
information on causes of mortality and how these change in
relation to behaviour, environment and intrinsic state. It is
also important to realise that life span might be terminated
by intrinsic factors without senescence having to occur. In
addition to the traditional view of senescence as a progressive
decline resulting from damage accumulation, which is how we
usually think of senescence, it is also possible that age at death
could be controlled by particular pleiotropic genes that act
like time bombs, suddenly putting an end to life by triggering
a catastrophic failure in key organ systems. In such species,
senescence might hardly be evident at all. As highlighted by
Ricklefs (2008), it is surprising how little understanding we
have of causes of death in natural populations, or indeed even
in captive animals, that would allow us to say whether the
grim reaper slowly engulfs the organism, or suddenly
ambushes it.
While changes in life span need not imply changes in rate of
senescence, conversely we cannot assume that faster senescence will necessarily be manifest as a reduction in the average
life span of a population since it is often the case that very few
individuals in the wild live long enough to suffer senescent
declines. Finally, and very importantly, to understand the
fitness consequences of, and hence the evolutionary ecology of,
senescence, we need to combine studies of age-specific
mortality patterns with studies of age-specific fecundity. There is
increasing evidence of progressive deterioration in fecundity
with age within individuals and many more longitudinal
studies are needed (see Nussey et al. 2008).
Where do we go from here?
A consensus amongst all the papers in this special feature is
the need for more studies in natural conditions involving a
broader taxonomic range of organisms. More interspecific
comparisons are likely to generate new insights into both the
evolution and the mechanisms of senescence. As highlighted
recently by Partridge & Gems (2007), extrapolating results
from controlled laboratory conditions has its limits, especially
for processes affecting life-history traits highly influenced by
environmental conditions. Studies in the wild also provide the
opportunity to study organisms that are difficult to maintain
in the laboratory. We can identify species with exceptional life
spans, such as many birds, of which the medical community is
unaware, but whose physiology might reveal new approaches
to slowing senescence in humans. There is a surprising lack of
information on senescence in plants, which surely offer many
interesting avenues for studying the evolution of senescence
(Thomas 2002; Munne-Bosch 2007); most studies at present
focus on seasonal leaf loss, and not on senescence rate and
life-history trade-offs in the plant itself. Furthermore, there
have recently been major improvements in how data from
natural populations can be used in studies of senescence, and
there remain many promising avenues to pursue in this area.
Some of the processes identified in the laboratory as being of
great importance, at least to life span, but possibly also to
senescence rate, such as food intake, metabolism and oxidative
stress, need to be studied in a wider range of organisms and in
natural populations; in addition to their effects on longevity,
we need to know the consequences for other important fitness
parameters such as fecundity, and fitness-related traits such
as immune function. We have progressed from descriptive
© 2008 The Authors. Journal compilation © 2008 British Ecological Society, Functional Ecology, 22, 371–378
Evolutionary ecology of senescence 377
studies answering the question ‘Do wild animals display
reproductive and actuarial senescence?’ to sophisticated
methods analysing longitudinal datasets over long time scales
and enabling individual variation and environmental factors
to be investigated. The question ‘Why does senescence
occur?’ remains a challenge. However, recent attempts to test
evolutionary theories of senescence while integrating them in
a wider life-history perspective are providing new insights.
The use of long-term datasets in exploring evolutionary
processes has posed new methodological challenges, such as
the problem of individual detection probability, revealing key
issues that need to be solved. A number of fundamental issues
also remain to be resolved, only some of which we have
discussed above. Field based genetic studies of the causes of
senescence need to be integrated with evolutionary theory,
since this will enable us to evaluate the importance of the three
different explanations of the evolution of senescence in
different taxa and environments. Without doubt, the study of
senescence offers a fertile ground for future research, and one
that will bring together mechanistic and evolutionary
approaches, and field and laboratory studies.
Acknowledgements
We thank Charles Fox and two anonymous referees for comments on this introductory paper, and all the other authors for contributing such interesting
papers to this special feature.
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Received 18 March 2008; accepted 6 April 2008
Handling Editor: Charles Fox
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