Translator Disclaimer
1 January 2009 A Bird's-Eye View of Aging: What's in it for Ornithologists?
Author Affiliations +

ORGANISMAL AGING, OR senescence, can be defned as a progressive, irreversible loss of function that results in declines in fertility and survival. This defnition restricts “aging” to age-related deterioration that occurs after organisms reach maturity, including processes that can be detrimental to reproductive success and, hence, relevant to ftness tradeoffs. The biology of aging, or “biogeron-tology,” is broadly focused on understanding basic processes responsible for variation in animal life spans and aging patterns, including evolutionary forces as well as physiological and molecular mechanisms (Finch 1990, Rose 1991, Kirkwood and Aus-tad 2000). Much of the research in this field is couched in terms of preventing aging-related disease or extending human life span, and most biogerontological researchers use short-lived, inbred laboratory model species for which molecular tools are very well developed (e.g., mice, flies, and roundworms) rather than wild,aging, there is also intense interest in animals, including many bird species, that are exceptionally long-lived for their body sizes or metabolic rates and that may have interesting physiological or molecular mechanisms for long-term maintenance of somatic integrity and reproductive capacity. Along with a push to adopt longer-lived, outbred animal models for aging studies, there is growing appreciation of the utility of comparative and evolutionary approaches to understanding basic aging processes (Austad 2001, Holmes et al. 2003a, Buffen-stein 2005, Hulbert et al. 2007, Holmes and Kristan 2008).

“Bird studies offer a richresource for exploring thebiochemical and molecularmechanisms that underlie variationin aging and longevity withinand between species, as wellas the genetic, developmental,and physiological bases oflife-history tradeoffs.”

Improvements in marking and monitoring techniques now furnish a wealth of demographic data from wild bird populations that are very valuable for addressing predictions of evolutionary aging and life-history theory. Various researchers are seeking reliable physiological correlates of senescence-related changes in birds (Monnier et al. 1999, Holmes and Aus-tad 2004, Monaghan and Haussmann 2006, Palacios et al. 2007), refining clinical immune assays and other aging “biomarkers” for application to studies in both wild and captive populations. Bird studies offer a rich resource for exploring the biochemical and molecular mechanisms that underlie variation in aging and longevity within and between species, as well as the genetic, developmental, and physiological bases of life-history tradeoffs. Research is already underway that is geared specifically toward the discovery of “anti-aging” mechanisms in birds and other extremely long-lived animals that hold special promise as animal models. However, although great potential exists for dialogue across disciplines, much of the biogerontological literature that would be useful for facilitating innovative, interdisciplinary research on avian aging and related areas remains unfamiliar or inaccessible to ornithologists.

Avian biologists are currently making exciting research contributions that are directly relevant to the field of aging (reviewed in Holmes and Ottinger 2006, Monaghan et al. 2008, Ricklefs 2008). But communication and collaboration between ornithologists—particularly those working with wild birds in the field- and more biomedically oriented researchers of aging are still rare. Here, we highlight some central research issues in the biology of aging that are of particular relevance to avian biology as a whole. We review recent findings that could be particularly interesting for ornithologists working in aging and related areas. We discuss the importance of developing more meaningful proximate measures of avian aging, and identify some aging measures and “bio-markers” that have special promise for bird studies. Finally, we suggest ways to build a more comparative and ecologically based “avian biogerontology,” integrating research priorities of ornithologists, comparative zoologists, and biogerontologists.

Avian Aging and Longevity: An Overview

The biology of aging is focused on how “ultimate,” evolutionary forces shape variation in life spans and aging patterns between and within groups of animal species, as well as on the “proximate” physiological, cellular, and molecular mechanisms underlying these patterns. Central questions in the field currently include why some kinds of animals, such as birds or bats, live longer and age more slowly than others with similar body sizes and metabolic rates, and whether diverse animal taxa share key genes or metabolic pathways that shape life spans and aging rates (Kirkwood and Austad 2000, Promislow et al. 2006, Ricklefs 2008).

Comparative explanations for the wide variation in animal life spans and aging patterns include a long-standing idea that animal life spans are constrained primarily by their metabolic rates and resulting cellular wear and tear. This idea is typically referred to as the “rate of living” theory. This proximate, mechanistic theory was based on a strong, positive correlation between body size and maximum documented species longevities within vertebrate classes, coupled with a strong, inverse, relationship between species life spans and basal metabolic rates (Pearl 1928, Austad and Fischer 1991, Speakman 2005a). Currently, a more robust theoretical scenario for the evolution of variation in life span is provided by evolutionary senescence and life-history theory (Stearns 1992, Kirkwood and Austad 2000, Promislow et al. 2006, Monaghan et al. 2008, Ricklefs 2008). Tenets of this body of theory include the central concept of adaptive, genetically based tradeoffs between current and future survival and reproduction. Animal populations subject to higher mortality from predation, disease, or accident generally are expected to evolve more rapid maturation rates, earlier reproductive investment, and higher fecundity. A corollary prediction of this tenet is that in the absence of higher mortality risk, natural selection should favor organisms with slower aging rates and adaptations that ensure long-term somatic maintenance (Williams 1957, Edney and Gill 1968, Partridge and Barton 1993, Kirkwood and Austad 2000, Martin 2001). Evolutionary and more mechanistic ideas for explaining basic aging processes are continually being integrated, and proximate developmental, metabolic, and oxidative processes undoubtedly play major roles in organismal senescence.

Fig. 1.

Comparison of relationships between maximum documented species life spans and basal metabolic rates for birds (upper line) versus mammals (lower line). Although birds have higher metabolic rates, on average, than mammals of similar body mass, many avian species live longer and age more slowly. For birds, n = 108 species; for mammals, n = 267. (Reproduced from Hulbert et al. [2007] with permission of A. Hulbert and American Physiological Society.)

f01_01.eps

Birds as exceptionally long-lived animals.—Birds exhibit a wide range of life spans and aging patterns (Bennett and Owens 2002, Gill 2007). In general, however, avian species live 1.5 times longer than similar-sized mammals, on average, despite much higher (2–3 times) mass-specific metabolic rates and lifetime oxygen expenditures (3–4 or more times higher) (Figs. 1 and 2; reviewed in Holmes and Austad 1995b, Speakman 2005a, Ricklefs 2008). Maximum species longevities derived from banding records for wild bird populations show that even small songbirds often survive for more than five years in the wild, and that reproductive senescence in many birds occurs at under half the rate of that in similar-sized rodents in captivity (Newton 1989; Holmes et al. 2001, 2003b; Brunet-Rossinni and Austad 2006; Ricklefs 2008). Avian species that mature and reproduce extremely slowly—including seabirds (some with documented life spans of ≥50 years)—are among the longest-lived homeotherms for their size. Slow aging and long life spans in avian species are generally correlated with slow declines in reproductive success (e.g., Pugesek and Diem 1983, Ottinger et al. 1995, Nisbet et al. 1999).

Taken in comparative context, observations about the apparently slow aging rates of birds are intriguing to biogerontologists—and may also be of greater significance to ornithologists than is generally recognized. In the field of aging, there is a continual search for animal model strains or species that appear to be particularly resistant to aging and aging-related diseases. A growing number of specific “longevity assurance” genes have been identified in inbred laboratory animals over the past two decades,and there is an intense effort underway to identify the biochemical and physiological processes controlled by these genes. Some exceptionally long-lived laboratory strains of worms, flies, and mice that possess genes for slow aging also have demonstrably enhanced defenses against certain stressors and types of cellular and molecular damage and, in particular, against damage caused by normal oxidative metabolism. There is also great interest in developing additional animal model species and systems for investigating aging processes, including wild, outbred animals like birds, bats, snakes, fishes, and mole-rats (Brunet-Rossinni and Austad 2004, Buffenstein 2005, Gerhard 2007, Bronikowski 2008).

Fig. 2.

Comparison of loge (lifetime energy expenditures [kj/g] of tissue) for (A) mammal (n = 249) and (B) bird (n = 164) species. Birds tend to have higher average metabolic rates for their body masses, than mammals and to expend more energy over the course of a lifetime. (Reproduced from Speakman [2005a] with permission of author and The Company of Biologists.)

f02_01.eps

It has been suggested that the apparently slow aging rates seen in homeotherms that fly (birds and bats) are an evolutionary correlate of low adult mortality rates afforded by efficient modes of escape from predators and accidental death (Williams 1957;Edney and Gill 1968; Partridge and Barton 1993; Ricklefs 1998, 2008; Kirkwood and Austad 2000). Long life spans and slow aging in birds could, alternatively, be a result of the metabolic demands and intensity of selection for flight performance, rather than a straightforward outcome of life-history evolutionary forces (Speakman 2005a, Hulbert et al. 2007, Ricklefs 2008). In either case, the basic biology of aging in birds is worthy of more focused research.

Demographic Patterns and the Measurement of Avian Aging

Demographic measurement of aging.—Detecting and measuring rates of senescence in captive or free-living animals, including birds, depends on the collection of data on age-specific rates of survival or reproduction from mature adults. Long-term, longitudinal studies of large numbers of individuals in wild bird populations have provided a great deal of data suitable for testing ideas from evolutionary aging and life-history theory, including predictions about tradeoffs between reproduction and long-term survival (Newton 1989, Promislow 1991, Stearns 1992, Newton and Rothery 1997, Bennett and Owens 2002, Roff 2002, Monaghan et al. 2008, Ricklefs 2008). Usually, relatively few individuals of a given population reach extreme old ages in the wild, but gradual increases in mortality and declines in reproduction consistent with senescence have now been documented for many avian populations (Ricklefs 1998, Holmes et al. 2001, Ricklefs and Scheuerlein 2003, Brunet-Rossinni and Austad 2006). An increasing number of studies of relatively shorter-lived songbirds and grouse show quite strong declines in survival and reproductive success among birds in older age classes (Wiebe and Martin 1998, Sandercock et al. 2005a, Brommer et al. 2007, Keller et al. 2008). Conventional analytical approaches to demographic studies of aging typically include calculation of age-specific probabilities of death or infertility using survivorship, mortality, or morbidity plots (Fig. 3; Finch 1990, Tatar et al. 1996, Pletcher 1999, Kirkwood and Austad 2000, Bronikowski and Promislow 2005). In studies of wild bird populations, senescence is generally inferred from statistically reliable age-related declines in adult survival or reproductive success, after discounting effects on these traits attributable to specific diseases or terminal illness.

For the most part, the proximate mechanisms responsible for patterns of “demographic senescence,” or aging-related changes in various vital rates in wild bird populations, remain undetermined. But a few studies of seabirds and raptors have documented declines in the foraging success of very old individuals compared with that of middle-aged birds (Newton and Rothery 1997, Reed et al. 2008). Age-related variation in various parameters relevant to animals' health, condition, or specific aging-related physiological syndromes (e.g., fertility declines, changes in immune measures, cardiovascular function, or accumulated products of oxidative damage to cells) can also be used to test the hypothesis that senescence is actually occurring. Given adequate numbers of known-age individuals in a range of age classes, demographic analyses of senescence patterns can be useful for (1) testing the hypothesis that reliable aging-related declines are occurring in adult survival, reproduction, or other specific functional measures; (2) comparing patterns of aging-related declines of different physiological systems such as immunocompetence or stress responses; and (3) comparing aging patterns between closely related taxa, populations, or experimental groups across different environmental types and conditions (Promislow 1991, Rose 1991, Stearns 1992, Roff 2002, Ricklefs 2008, Wilson 2008, Bears et al. 2009).

Fig. 3.

Declining survivorship consistent with aging in wild populations of (A) European Barn Swallow and (B) Collared Flycatcher. Survival rates that fall below the dashed lines reflect age-related increases in mortality consistent with aging. Data from both populations represent band-recapture records from thousands of individuals. (Reproduced from Holmes and Austad [2004] with permission of the authors and Highwire Press [adapted from original data from Møller and Szép 2002 and L. Gustafsson pers. comm.].)

f03_01.eps

Detecting avian aging in the wild: Probability can obscure ability.—Variability in ecological factors or stochastic trends present statistical and other kinds of challenges to gathering the demographic data needed for senescence studies in the wild. Avian aging studies must consider that adult birds often show age-related increases in reproductive success before they reach prime reproductive maturity and undergo subsequent senescence; thus, the performance of old birds is most appropriately compared with that of middle- or prime-aged birds. Declining survivorship with age produces smaller numbers of individuals in older age classes, resulting in increased statistical variance in estimates of vital rates at the oldest ages. Older age classes may not be phenotypically or genetically representative of the entire populations under study but may consist of subsamples of adult individuals, depending on whether or how longevity traits covary with other demographic traits and on the presence or strength of tradeoffs at different ages (Rose 1991, Kirkwood and Austad 2000, Keller et al. 2008, Ricklefs 2008). Another challenge to detection and measurement of senescence is that aging processes may drive steady declines in physiological function of individuals, whereas stochastic, ecological processes such as predation, disease, or extreme weather can abruptly remove individuals from populations for reasons not related directly to senescence. Alternatively, relaxation of harsh ecological or environmental conditions may actually improve the apparent fitness of senescent individuals as measured by other functional capacities (Laaksonen et al.2002).

Detecting senescence using survival data for birds may be particularly complicated by aging patterns wherein individuals have prolonged good health and performance followed by a catastrophic death, which makes it difficult to detect diminished function and intrinsic aging processes (Ricklefs 2008). Thus, ecological studies of aging may require many years or many study sites to acquire sufficiently large samples for assessing both the ability and the probability of reproductively mature individuals to survive and reproduce as they age (e.g, Brommer et al. 2007). Discrepancies between ability and probability of survival and reproduction of senescent individuals may also vary with species life-history type, such that declines in ability may be more easily discerned in raptors and pelagic seabirds with specialized foraging or other behaviors that require exceptionally high physical performance, and less apparent in herbivorous or omnivorous birds with preda-tion-driven life histories that may show gradual or no declines in performance. Further field studies are needed to determine the role of life-history type in shaping patterns of senescence and the key mechanisms involved (e.g., declines in performance of individuals or selective removal by predators). These studies could be most productively done on populations of bird species that exhibit strong life-history variation or are subject to particularly variable ecological conditions (Martin 2001, Martin and Wiebe 2004).

Avian reproductive aging.—In birds, reproductive vital rates show great variation among species in pattern of onset and degree of apparent senescent declines (Martin 1995). For example, White-tailed Ptarmigan (Lagopus leucura), and many other birds, show a strong pattern of senescence in the timing of egg-laying with consequent declines in clutch size, but no declines in either nest failure or the probability of replacing a clutch after failure of the first attempt as birds shift from prime breeding to older age classes (Sandercock et al. 2005a). Other aging-related reductions in fecundity may be compensated for by improvements in another trait (e.g., older birds are able to raise proportionately more of the offspring they hatch); thus, parental experience can compensate for reduced ability to produce eggs (Wiebe and Martin 1998, Velando et al. 2006). There can also be great variability among individuals in the onset and strength of senescence, possibly attributable to strong cohort effects, early breeding experience, population density, or environmental variation (Rockwell et al. 1985, Wilson et al. 2007, Nussey et al. 2008, Reed et al. 2008). In general, relationships among individual fitness, reproductive success, and senescence in birds are likely to be inherently complex, and the predicted tradeoffs between reproductive investment and longevity remain difficult to assess in natural populations that may or may not exhibit stable population characteristics. These complexities notwithstanding, longitudinal field studies of vital rates in birds, in concert with measurement of physiological or other functional aging measures, can provide invaluable opportunities for examining these processes in natural populations of vertebrates.

Reproductive senescence has been well characterized in domestic poultry and includes changes in ovarian function, declines in gamete production, and changes in reproductive hormone ti-ters, parental care behaviors, and numbers of offspring fledged per breeding episode (reviewed in vom Saal et al. 1994, Holmes et al. 2003b). Age-related changes in reproduction, reproductive endocrinology, and mating behaviors can be particularly sensitive bio-markers of aging. In domestic Japanese Quail (Coturnix japonica), for example, changes in courtship behavior are under the control of gonadotropin-releasing hormone (GnRH) secreted by the hypothalamus; hence, changes in GnRH and these behaviors can be used to accurately forecast later reproductive declines in males (Ottinger 2001, Ottinger et al. 2004). As in mammals, patterns of reproductive senescence in birds often differ substantially from patterns of survivorship. But for the reasons stated above, it is generally easier to measure declines in reproductive function than declines in survival. Elucidation of senescence patterns is further complicated by the fact that declines in reproduction are presumably driven only by intrinsic factors, whereas declines in survival are considered to be influenced by either intrinsic or extrinsic factors or both.

Many demographic studies have documented aging-related changes in reproduction in wild birds, but relatively few studies have focused intensively on the physiological basis of these changes (for an exception, see Ottinger et al. 1995). Newton and Rothery (2002), for example, concluded that old female Eurasian Sparrowhawks (Accipiter nisus) raised fewer offspring because they were less effective at feeding and protecting their young, given that most nestling mortality was attributable to nestling starvation and depredation. Saino et al. (2002) reported some effects of maternal age and senescence on indicators of offspring quality in Barn Swallows (Hirundo rustica), including nestling body mass, morphology, and T-cell-mediated immunity. The ability to sustain reproduction may vary with species and life-history type, such that very old individuals of herbivorous species raising pre-cocial young can maintain reproduction or mitigate declines via behavioral compensation or increased experience. On the other hand, species that must meet the higher demands of feeding altri-cial young may show more dramatic patterns of reproductive senescence, especially when provisioning of offspring requires high levels of physical performance or specialized foraging skills.

Other phenotypic correlates of aging in wild and captive birds.—In both wild and captive bird populations, aging-related phenotypic variation or changes have been documented for an assortment of other measures, including higher parasite loads, declines in immune function, changes in telomere dynamics, and the accumulation of molecular oxidative damage. Documented clinical signs of aging in captive birds (pets or zoo animals) include fertility loss, osteoarthritis, kidney disease, diabetes, and cancers (Holmes and Austad 1995a, Ricklefs 2000b, Ricklefs et al. 2003, Ottinger et al. 2004, Holmes and Ottinger 2006). Again, particularly interesting to biogerontologists is the fact that even small songbird species appear to exhibit senescence and lose reproductive potential much more slowly than laboratory rodents, which suggests that birds may be particularly resistant to some kinds of deteriorative processes. Although quantifcation of aging-related changes using clinical aging “biomarkers” in birds is still relatively rare, some measures like these are now being adopted for use in studies of captive and wild birds.

Potential contributions of ecological field studies of birds.—Recent reviews of the ecology and evolution of senescence in vertebrates call for field studies that can contribute particular insights into relationships between environmental conditions or gradients and patterns of lifetime fitness, longevity, and senescence (Monaghan et al. 2008, Nussey et al. 2008, Ricklefs 2008). Some songbirds show remarkable within-species shifts from fast to slow life histories across elevational or geographic gradients; some congeneric grouse species, as well, exhibit striking life-history variation between and within species (Sandercock et al. 2005b, Wilson 2008, Bears et al. 2009). If individuals in some populations of a species live longer than those in others, then such questions arise as which vital rates are modified to achieve differences in life spans, and how much do ecological factors such as predation risk or environmental variation modulate these demographic responses. Although longevity may be generally linked to slower aging or lower vital rates, aging rates may not be uniform among adult age classes. Species that show significant life-history shifts across environmental or geographic gradients provide an ideal opportunity to examine how frequently and how strongly patterns of longevity and senescence are linked, and whether these are related to different reproductive investment patterns or to direct environmental effects on reproductive rates. More generally, there is the intriguing question of how bird populations achieve these life-history shifts, particularly when the mortality is age-independent in large part and presumably attributable to extrinsic factors.

Global warming and the effects of increasing climate variability on different-aged cohorts of breeding birds are a concern for which senescence could be particularly relevant, because populations and species with slow and fast life histories may vary in their vulnerability to environmental perturbation, perhaps depending on whether the patterns of warming influence annual survival or reproduction of individuals (Sandercock et al. 2005b, Wilson 2008). For example, climate warming in winter or severe episodes of weather during the breeding season that depress breeding success may have disproportionate effects on populations with fast life histories, whereas other environmental stressors that in-fluence survival will be expected to have greater effects on populations with high survival. However, if birds that live longer have more prolonged good health until shortly before they die (Ricklefs 2008), they may be more resistant to increasingly severe environmental stress, at least in the short term.

KEY PROXIMATE MECHANISMS IMPLICATED IN AGING

The ability to target specific genes that control aging patterns in laboratory animals has facilitated the identification of key metabolic processes, cell-signaling pathways, and transcription factors that are likely to underlie differences in life span (Tatar et al. 2003, Partridge et al. 2005, Sonntag et al. 2005, Carter and Sonntag 2006). Genes for longevity and slow aging are of particular interest and have been identified in laboratory mice, fruit flies, round-worms, and yeast (Brown-Borg et al. 1996, Hekimi and Guarente 2003, Johnson 2006a, Pinkston et al. 2006). For example, alterations in single genes (e.g., daf-1 and age) can increase population life spans in roundworms more than seven-fold, and some genes like these are remarkably well conserved across eukaryote taxa.

“Aging genes” also play key roles in regulating apoptosis (adaptive, programmed cell death) and preventing tumorigenesis and cancer (Campisi 2001, Krtolica et al. 2001). Some are associated with homeostatic responses to particular stressors, including heat, cold, oxidative processes, and food restriction. Much current research is focused on the relationship between aging and oxida-tive damage to cells and macromolecules and on understanding how key aspects of mitochondrial function and energy metabolism are controlled by genes for long life span. Once again, this focus makes long-lived homeothermic vertebrates (e.g., birds, bats, and mole-rats) a particular target as animal models, and the development of molecular tools for use of these species is of growing interest.

Oxidative damage.—Reactive oxygen species (ROS) are unstable oxygen molecules generated by mitochondria during oxi-dative metabolism. The production of ROS at higher rates by organisms with high metabolic rates and lifetime oxygen expenditures is a central prediction of the free-radical and oxidative-damage theories of aging (Harman 1956, Martin et al. 1996, Beck-man and Ames 1998). This proximate prediction drives much current research geared toward a better understanding of the cellular and molecular mechanisms that underlie organismal senescence. Reactive oxygen species and their byproducts are implicated in a growing assortment of aging-related diseases and associated damage to specifc tissues, cellular structures, and macromolecules (Martin et al. 1996, Yu and Yang 1996, Finkel and Holbrook 2000, Van Remmen and Richardson 2001, Muller et al. 2007). The long life spans of many avian species despite high metabolic rates and lifetime oxygen expenditures (Figs. 1 and 2) make aging in birds particularly intriguing in this context. Some authors have suggested that birds either have better cellular defenses against oxidative damage or produce fewer ROS during oxidative metabolism than shorter-lived mammals of comparable size and weight (Holmes and Austad 1995a, b; Barja 1998; Hulbert et al. 2007).

Caloric restriction, carbohydrate metabolism, and growth factors.—Another active research area in biogerontology concerns relationships between aging and caloric intake, somatic growth rates, insulin signaling, and other processes regulating cell growth and proliferation. Specifc genes and metabolic pathways that control growth, development, and aging via growth hormone (GH) and insulin-like growth factor (IGF-1) are now implicated in a number of aging-related diseases (e.g., diabetes, cardiovascular disease, and infammatory syndromes) and linked to genes for life-span variation in inbred mice, worms, and flies (Brown-Borg et al. 1996, Flurkey et al. 2001, Tatar et al. 2003, Partridge et al. 2005, Sonntag et al. 2005). In humans and laboratory animals, IGF-1 is a nonspecific regulator of cell proliferation and growth; it is secreted primarily by the liver under the influence of GH. Normal aging-related decreases in GH and IGF-1 have been shown to be correlated in some species with declines in lean body mass, bone density, immune function and cognition, and various other functional declines.

Experimental caloric restriction (CR) while simultaneously controlling for nutritional quality and micronutrient intake has been shown to be a reliable intervention in aging in a wide range of vertebrate and invertebrate species. Reduction of caloric intake of 20–30% below normal (ad libitum feeding) extends the normal life span in laboratory rodents 30–40%, and retards onset of a wide array of aging-related diseases (Weindruch and Walford 1988, Masoro 2001, Partridge et al. 2005). The anti-aging effects of CR may occur in part through altered carbohydrate and insulin metabolism, as well as via specific changes in transcription pathways regulated by IGF-1 and GH. Short-term food restriction has also been shown to reduce egg production and alter reproductive endocrinology in poultry species (Holmes et al. 2003b, Ottinger et al. 2005), but the effects of long-term CR on avian aging over the full course of the lifespan remain unexplored.

The effects of CR are likely a result of physiological and evolutionary tradeoffs between investment in reproduction and long-term somatic maintenance, and between dormancy states and long-term survival during environmental stress. This idea has been subjected to few direct tests using outbred animal models (Martin 1995a, Kirkwood and Austad 2000, Austad and Kristan 2003, Tatar et al. 2003, Ricklefs 2008). Although avian laboratory models (e.g., quail, Domestic Chicken [Gallus gallus domesticus], and songbirds) have long been a mainstay of developmental biology and neuroendocrinology, little research has directly addressed relationships among nutrition, development, growth, carbohydrate metabolism, and aging processes in birds. Given our common interests in evolutionary and developmental tradeoffs, there is potentially a great deal of intellectual common ground to be shared by biogerontologists and bird biologists interested in the nutritional and endocrine bases of evolutionary tradeoffs (reviewed in Monaghan et al. 2008; see, e.g., Alonso-Alvarez et al. 2007).

AGING BIOMARKERS AND AVIAN SENESCENCE

Field ornithologists obviously need robust, noninvasive methods for determining the concordance between age-related physiological changes and chronological ages of birds in the wild. Concurrently, biogerontologists are striving to develop reliable biomarkers of physiological senescence, other age-related functional changes, and disease susceptibility (Cristofalo 1988, Miller 2001, Butler et al. 2004, Johnson 2006b). Ideal measures of senescence, or aging biomarkers, would reliably predict an organism's future life expectancy or risk of mortality from intrinsic, aging-related causes (Table 1) or serve as a measure of the deterioration of particular functions or physiological systems. In addition, good biomarkers should allow repeated and non-invasive measurements without afFecting the survival of individuals.

Aging measures currently used in work with laboratory animals include clinical blood parameters, incidence of pathological lesions, cellular markers of cancer and infLammation, and specifIc byproducts of oxidative metabolism and glycosylation implicated in disease states. Although many of these measures have been shown to correlate with changes in mortality, no biomarker or combination of these measures, other than mark-recapture and monitoring methods, has been found that can accurately reflect an individual bird's chronological age, even in the laboratory.

Table 1.

Ideal characteristics of an aging biomarker (adapted from Harper et al. 2004).

t01_01.gif

Despite the lack of a single measure of aging that can meet an ideal set of criteria, parameters have been identified that show biologically meaningful, reasonably reliable variation with age in inbred laboratory animals under controlled conditions; some of these are potentially very useful to bird biologists. They include clinical measures of immune function, cardiovascular health and inflammation; cumulative oxidative damage to macromolecules (including nuclear and mitochondrial DNA); changes in reproduction and endocrine function (Cristofalo 1988; Meites 1988; Hamilton et al. 2001; Harper et al. 2003, 2004; Chaudhuri et al. 2006; Bentley and Muttukrishna 2007); and measures of physiological performance, strength, or frailty.

Some measures of functional aging are more meaningful for comparisons between species than for comparing individuals within a population or species (Harper et al. 2004, Speakman 2005a). Within species, even in highly inbred strains of animals maintained under pathogen-free conditions, there is much individual variation in rates of aging; offspring from a single litter or breeding attempt can have very different “agedness” profiles at a given chronological age (reviewed in Finch and Kirkwood 2000). Aging-related death and disease rates can be affected dramatically by nutritional status, infectious diseases, exercise, and other factors, as well as reproductive activity and effects of sampling error for older age classes (reviewed in Weindruch and Wal-ford 1988, Finch 1990, Finch and Kirkwood 2000, Masoro and Austad 2005, Conn 2006). In laboratory studies, caloric restriction strongly influences aging and results in statistically reliable changes in aging biomarkers at the population level. Hence, nutritional and other forms of environmental variability are likely to be powerful influences on intrinsic aging rates in the wild, as well as in captivity.

Different physiological and functional systems are expected to have evolved under different selection pressures and constraints and, therefore, to sometimes show different rates and patterns of aging-related deterioration (Martin et al. 1996, Bronikowski and Promislow 2005, Promislow et al. 2006). To complicate things further, aging-related changes in health or condition (e.g., specific aspects of mobility or physiological function) in inbred laboratory animals may not be generalizable to outbred, free-living animals in natural environments that impose selection via predation, disease, and variation in food availability (Lithgow and Walker 2002, Austad and Kristan 2003, Baldal et al. 2006). Some aspects of aging in outbred, free-living animal populations may, in fact, more closely resemble aging in humans than that in inbred laboratory animals that are protected against disease and stress (Partridge et al. 2005,Lithgow 2006, Holmes and Kristan 2008, Monaghan et al. 2008, Ricklefs 2008).

Some of the most interesting aging measures currently being used in wild bird studies include declines in survivorship or reproductive output, neuroendocrine changes, changes in telomere dynamics, and functional immune measures (summarized in Table 2). Although most must be obtained invasively, measures of the accumulation of products of oxidative damage to avian cells and molecules also show promise, both in the laboratory and in the field. In the following sections, we discuss recent research employing such measures in bird studies that should be of interest to ornithology as a whole.

Oxidative Damage and Resistance Measures

Are avian cells exceptionally resistant to oxidative damage?—Healthy animal cells are thought to employ a variety of defenses against ROS-inflicted damage, including both structural features (e.g., oxidation-resistant lipids in mitochondrial membranes) and active molecular defenses (like antioxidant enzymes and other molecules) and repair systems. Several possible mechanisms for slowing the production and accumulation of oxidative damage have been suggested to exist in bird species. These mechanisms include better constitutive or inducible ROS defenses, like antioxidants, and more efficient ways of repairing cellular damage. In addition, some researchers have suggested that avian mitochondria may be especially efficient or produce fewer ROS during oxidative metabolism, creating less potential for cellular damage in the first place (Barja et al. 1994a; Holmes and Austad 1995a, b; Brand 2000; Hulbert et al. 2007; Lambert et al. 2007).

Several labs have begun to explore putative protective mechanisms of avian cells against oxidative damage (Table 3). They have employed a variety of methods from biochemistry, toxicology, and mitochondrial physiology—assessing the survival of isolated cells with respect to oxidative damage, for example, or measuring the production of ROS by isolated respiring mitochondria. These methods usually require in-vitro approaches. With few exceptions, they use samples from a variety of tissues from a few individuals that represent only a few bird species, comparing data from a small pool of vertebrate species with markedly different maximum documented life spans. Phylogenetic methods now widely accepted in evolutionary and comparative zoology, in which traits of interest are compared in large numbers of species from diverse taxa while statistically incorporating effects of shared ancestry (i.e., “phylogenetic independent contrasts”; Bennett and Huey 1990, Harvey and Pagel 1991, Promislow 1991), have not been used until very recently for testing specific predictions of the free-radical or other mechanistic aging theories (Austad and Holmes 1999; for exceptions, see Promislow 1991; Speakman 2005a, b; Hulbert et al. 2007; Lambert et al. 2007). Despite their sometimes limited taxonomic scope, studies like those we describe below have yielded valuable and provocative results and have refined thinking about the role of oxidative metabolism in aging.

Table 2.

Promising functional measures or correlates of aging in birds.

t02_01.gif

Avian mitochondrial metabolism.—Several labs, using avian species from several different orders (Budgerigar [Melopsittacus undulatus], Rock Pigeon [Columba livia], Common Canary [Serinus canaria]), have reported that mitochondria of long-lived bird species either generate ROS more slowly or generate fewer ROS per oxygen molecule than mitochondria of short-lived laboratory rodents (e.g., Ku and Sohal 1993, Lopez-Torres et al. 1993, Barja et al. 1994a, Herrero and Barja 1998; Table 3). Some have also gathered data consistent with the idea that lower ROS production is localized to avian mitochondrial complex I (Barja and Herrero 1998, Lambert et al. 2007). Moreover, it has been suggested that avian mitochondria undergo metabolic “uncoupling” during oxidative phosphorylation, adaptively leaking protons across mitochondrial membranes and reducing ROS generation and oxidative damage (Barja 1998, Herrero and Barja 1998, Lesnefsky and Hoppel 2006, Hulbert et al. 2007). This idea has been related to in-vitro evidence of mitochondrial uncoupling in cells from ca-lorically restricted laboratory rodents (e.g., Gredilla et al. 2001; Bevilacqua et al. 2004, 2005) and of lower ROS production rates by mitochondria of mammals with longer maximum life spans (Brunet-Rossinni and Austad 2004, Lambert et al. 2007). It remains unclear, however, whether the observed species differences in in-vitro mitochondrial ROS production can be generalized to living systems, whether uncoupling is directly implicated in the aging process (Brand 2000, Lesnefsky and Hoppel 2006, Lambert and Brand 2007), and whether this type of uncoupling occurs in an adaptive context in living animals.

Antioxidant levels.—Lowered production of ROS by avian cells could, in turn, require lower antioxidant levels to protect against oxidative damage. Several studies (Table 3) have compared levels of various antioxidant enzymes, as well as nonenzy-mic antioxidants like ascorbate, in avian and mammalian tissues. Most have reported lower levels of some endogenous antioxidants (superoxide dismutase, catalase, glutathione, and glutathione peroxidase) in birds and mammals with longer life spans (Lopez-Torres et al. 1993; Barja et al. 1994a, b; Perez-Campo et al. 1998; Jaensch et al. 2001). Others, by contrast, have shown higher levels of superoxide dismutase, glutathione, and glutathione peroxidase in tissues from these same bird (vs. mammal) species (Ku and Sohal 1993, Ku et al. 1993). In the most comprehensive comparative study of endogenous antioxidant levels in birds to date, Cohen et al. (2008) measured total antioxidant capacity, antioxidant response to stress, and levels of uric acid, vitamin E, and four carotenoids in 95 avian species in relation to life-history patterns. Most of these species were passerines, and the study included tropical and temperate-zone representatives. Higher antioxidant levels were generally found to be associated with smaller body size, higher mass-specific metabolic rates, more rapid development, larger clutches, and lower survival rates. Antioxidant-life history associations also showed some differences between tropical and temperate species, but these statistical relationships were by no means straightforward. As in previous studies with fewer vertebrate species, no simple relationships emerged between levels of specific antioxidants and species' life spans or other particular life-history traits. This is consistent with the lack of evidence of predictable relationships between constitutive antioxidant levels and longevity found in similar comparative studies of mammals, even including mammalian species within a single order with very different life spans (e.g., rodents; Buffenstein et al. 2008).

Table 3.

Summary of studies comparing putative oxidative defenses in tissues of birds and mammals of similar body sizes and contrasting maximur life spans.

t03_01.gif

Abbreviations: ROS = reactive oxygen species, SOD = superoxide dismutase, GSH = glutathione, CAT = catalase, and ACEs = advanced glycoxidative end-products. References: (1) Ku and Sohal 1993,(2) Lopez-Torres et al. 1993,(3) Barja et al. 1994,(4) Herrero and Barja 1998, (5) Barjaand Herrero 1998, (6) Pamplona et al. 2005, (7) Ku et al. 1993,(8) Perez-Campo et al. 1998 (9) Jaensch et al. 2001, (10) Ogburn et al. 1998, (11) Ogburn et al. 2001, (12) Pamplona et al. 1999,(13) Liu 2004, (14) Beuchat and Chong 1998, (15) Iqbal et al. 1999, (16) Monnier et al. 1999,(17) Fallon et al. 2006, and (18) Cohen et al. 2008.

Whole-cell approaches.—Another approach to comparing resistance to oxidative damage of cells from diferent populations or species of animals involves isolating (and, in some cases, growing in culture) embryonic cells from representative individuals of long- and short-lived avian and mammalian species. Cells can then be exposed in vitro to various forms of oxidative stress (e.g., high concentrations of atmospheric oxygen, hydrogen peroxide, or paraquat). Using this approach, cells of longer-lived birds (European Starlings [Sturnus vulgaris], Common Canaries, or Budgerigars) have been reported to survive oxidative stress signifcantly longer and repair damaged DNA better than those of short-lived birds (i.e., Japanese Quail [Coturnix japonica]), laboratory rodents, or humans (Ogburn et al. 1998, 2001).

Damage to specifc macromolecules.—Specifc structural defenses against oxidative damage have also been examined in cells of some bird species. Parameters measured have included variation in structure and unsaturation levels of the fatty acids in mitochondrial membranes. In general, membrane lipids from long-lived birds have been shown to have lower levels of some markers of accumulated oxidative damage than those of shortlived mammals. This apparent resistance to damage also may be associated with lower levels of fatty-acid unsaturation and lipid peroxidation in avian membranes (Herrero and Barja 1999, Pamplona et al. 2005). Variation in fat composition in membranes of long- and short-lived vertebrates may not only enhance the stability of membrane lipids, but could underlie diferences in mito-chondrial metabolism and species diferences in rates of damage accumulation (Hulbert 2003, Hulbert et al. 2007).

Presumably, the maintenance of functional cells—and or—ganismal homeostasis as a whole-depends on sustaining the integrity of DNA. Permanent, irreparable oxidative damage could cause mutation, genomic instability, and the dysregulation of cellular and physiological processes (Beckman and Ames 1998, Hamilton et al. 2001, Cabelof et al. 2006). Hence, DNA oxidative lesions of various types have been adopted as biomarkers of aging and as clinical markers of certain diseases (i.e., cancers) or of exposure to environmental toxins. For example, 8-OH-dG (8-oxo-7,8-dehy-dro-2'-deoxyguanosine), a widely used marker of oxidative damage to nuclear and mitochondrial DNA, has been shown to accumulate with age in various tissues in humans and laboratory animals (Hamilton et al. 2001, Van Remmen and Richardson 2001, Kujoth et al. 2005). The rate of accumulation of such oxidative biomarkers can be altered reliably via caloric restriction (Ward et al. 2005, Mansouri et al. 2006).

Levels of 8-OH-dG in some tissues also have been reported to be correlated negatively with maximum potential life span in mammals and in a few bird species (reviewed in Pamplona et al. 2005, Muller et al. 2007). Liu (2004) assayed tissues from four bird species across a range of ages and found that 8-oxo-dG levels were correlated with the individuals' age in skeletal muscle and brain of captive Zebra Finches (Taeniopygia guttata). Remarkably, however, skeletal muscle of older individuals of three wild species also examined (Tree Swallow [Tachycineta bicolor], Common Tern [Sterna hirundo], and Leach's Storm-Petrel [Oceanodroma leucorhoa]) were reported to contain less detectable 8-OH-dG than that of middle-aged individuals. To our knowledge, this is the only study to explicitly address the hypothesis that this oxidative damage marker either accumulates or decreases with chronological age in birds. A key priority for ornithological researchers is additional, longitudinal characterization of promising biomarkers like this one, along with further development of less-invasive ways of obtaining tissue samples for assays.

“AGEs” and glycoxidative processes in birds.—Under normal in-vivo conditions, glucose in living cells interacts with proteins, nucleic acids, and other macromolecules in a complex series of nonenzymatic reactions. These include reactions called “glycosyl-ation” and “glycoxidation,” which can produce potentially damaging compounds known as “advanced glycosylation end-products” (AGEs). There is growing evidence that AGEs contribute to aging-related diseases and diabetes, including arthritis, kidney disease, ocular cataracts, and cardiovascular disease. Without effective mechanisms for prevention or repair, given their high metabolic rates and blood-glucose levels, birds might be expected to be more susceptible to accumulated damage from these compounds than their mammalian counterparts (Monnier 1990; Holmes and Austad 1995a, b; Austad 1997). Several recent studies on chickens suggest that birds may produce AGEs (e.g., pentosidine) at slower rates than mammals (Beuchat and Chong 1998, Iqbal et al. 1999, Monnier et al. 1999, Holmes et al. 2001, Klandorf et al. 2001, Fallon et al. 2006). Although limited in taxonomic scope, these data support the idea that birds somehow prevent AGE accumulation despite much higher blood glucose levels, and they are somewhat consistent with slower rates of accumulation of damaging DNA adducts like 8-OH-dG. With careful selection of appropriate tissues and biochemical protocols, AGE accumulation assays might be adapted for use in wild bird populations.

AVIAN IMMUNOSENESCENCE

Declines in immune function are a well-documented feature of aging in humans, domestic animals, and laboratory rodents and arguably one of the primary correlates of organismal senescence (Grubeck-Loebenstein and Wick 2002, Effros 2003, Miller et al. 2005). Aging-related deterioration of functional immunity, or “immunosenescence,” includes increased susceptibility to infectious diseases and diminished responses to immunizations, as well as increased risk of cancers and autoimmune disease. Changes in some subpopulations of T lymphocytes have been identified as predictors of longevity and, hence, as promising aging biomarkers for rodents and other mammals (Harper et al. 2004, Miller et al. 2005).

Although extensive work on the chicken has shown the avian immune system to be similar in its general features to that of mammals, little work has focused specifically on avian immu-nosenescence (Lavoie 2005). But over the past decade, a few studies have documented some age-related immune changes in wild populations of birds, using either cross-sectional or longitudinal approaches (Table 4). For the most part, these have employed one or a few simple clinical assays of humoral or cellular immune responses; we are aware of no published studies of aging-related changes in avian lymphocyte subsets. The measures currently being developed, however, show definite promise as measures of changing functional immunity and resistance to disease as wild birds age in nature.

In one such study, in conjunction with long-term field studies of Barn Swallow populations, Saino et al. (2003) vaccinated breeding adults with killed Newcastle disease virus (NDV) and monitored their ability to raise primary and secondary antibody responses during the first year of vaccination and the following breeding season. They found that older (four-year-old) breeding females showed significantly lower antibody responses during the first year of treatment; their secondary responses averaged only about one-third that of two-year-old females. In the second year after immunization, older individuals (2–6 years old) of both sexes showed a trend toward a significantly diminished secondary antibody response. Similar age-related changes in acquired humoral immunity to sheep red blood cells, a nonspecific antigen, were observed by Cichoń et al. (2003) in Collared Flycatchers (Ficedula albicollis) that were feeding nestlings, with one-year-old females showing the highest antibody titers. Titers declined with advancing age and were lowest in the oldest (5–6 years) adults.

Table 4.

Studies of aging-related immune changes in wild and outbred birds (results are for wild populations unless otherwise noted).

t04_01.gif

Abbreviations: NDV = Newcastle disease virus, NABs = natural antibodies, PHA = phytohemagglutinin, conA = concanavalin A, and LPS = lipopolysaccharide from Salmonella typhlmurlum, a B-cell mitogen.

a Captive colony.

A more comprehensive picture of age-related immune changes was obtained in a study of female Tree Swallows, in which Palacios et al. (2007) combined measures of cell-mediated acquired immunity (in vivo and in vitro) with assays for innate humoral immunity. They also performed in-vitro assays of T-cell proliferation in response to each of two mitogens, PHA and con-canavalin A. In-vitro responses to a B-cell mitogen, LPS (lipopolysaccharide from Salmonella), did not vary with age; nor did in-vivo antibody responses to immunization with sheep red blood cell antigen or two measures of innate humoral immunity. These results seem consistent with work on breeding Common Terns (Apanius and Nisbet 2003) that correlated reproductive performance and serum IgG levels but showed no apparent aging effect on immu-noglobin levels.

As these studies suggest, some aging-related immune changes may be exhibited reliably by wild birds, and in some cases these may be detectable rather early in the aging process. Other measures, however, show little aging-related change consistent with senescence in functional immunity. In humans and laboratory rodents, declining T-cell proliferative responses are an important correlate of aging; it is far from clear how these particular types of cellular responses might change with aging in any free-living vertebrate populations. It is a reasonable expectation, however, that older birds should rely and invest differentially in some forms of immunity as fitness tradeoffs and relative costs of specific immune functions change over the course of the life span.

In laboratory studies of immune aging, animals typically are maintained in pathogen-free conditions, and changes in resistance to infectious disease and other parameters relevant to fitness in free—living animals—including humans-generally are not measured (Austad and Kristan 2003, Holmes and Austad 2004, Lithgow 2006). Wild bird populations, by contrast, provide opportunities for exploring specific predictions about aging-related changes in immunity in natural environments where disease and parasites are expected to have significant effects on survivorship and reproductive success (Ricklefs and Wikelski 2002, Haussmann et al. 2003, Holmes and Austad 2004, Martin et al. 2006, Palacios et al. 2007). The progressive effects of aging, including immunosenescence, might be predicted to show stronger or earlier effects on survival or reproduction in wild birds subject to ecological pressures; this possibility has yet to be explored. Few studies, moreover, have directly compared aspects of immunity in short- vs. long-lived birds, or between species with different developmental or life-history patterns (Telia et al. 2002; Matson et al. 2006a, b).

The emerging discipline of “ecoimmunology” has generated an explosion of studies adopting clinical measures of immune function to test evolutionary hypotheses in outbred vertebrate populations. Areas of intense interest include the relationships among immune function, sexual selection, and mate choice;the stress response and nutritional status; and defenses against infectious disease and parasites (e.g., Norris and Evans 2000, Alonso-Alvarez and Telia 2001, Martin et al. 2006). An ecoim-munological framework could readily be applied to more directly address evolutionary questions about avian aging, life-history tradeoffs, and reproductive costs. This would require careful experimental integration of immunosenescence measures in wild animals with other biomarkers of aging, such as assays for oxidative damage, inflammation, specific disease states, or other physiological stressors. In addition, we need to know how immune changes in wild birds actually reflect variation in fitness and reproductive success, or how species with different life histories make tradeoffs between immunocompetence and other evolutionary priorities.

Fig. 4.

Predicted patterns of development and senescence of immune defenses in fast- and slow-living species. Dotted line stands for age at first reproduction. Shaded portion of graph represents transition from nonspecific (dark) to specific (light) immune defenses: fast-living species are predicted to rely on nonspecific defenses for most of their lives. “Stair-stepped” part of graph shows predicted variability in rate of aging-related immune declines during seasonal transitions between breeding and nonbreeding conditions: larger decrements per step show bias toward investment in reproduction with advancing age. Asterisks indicate breeding events; asterisk size represents breeding effort per event. (Reproduced from Martin et al. [2006] with permission of L Martin and Highwire Press.)

f04_01.eps

Some avian biologists have begun to integrate predictions from life-history theory with ideas about immunosenescence, suggesting that immune-system declines should vary qualitatively along a “fast-slow” continuum of life-history strategies (Lochmiller and Deerenberg 2000, Norris and Evans 2000, Telia et al. 2002, Martin et al. 2006, Matson et al. 2006a; see Fig. 4). Shorter-lived populations or species are predicted to invest less in immune defenses overall and to rely on less expensive, nonspecific immune functions rather than costly acquired defenses against particular pathogens. A vigorous discussion is in progress concerning the need for refinement and better integration of various measures of immune fitness for studies of wild vertebrates (Franceschi et al. 1999, Adamo 2004, Palacios and Martin 2006). This is an area in which studies of wild bird populations hold great promise for a more integrated approach to understanding organismal aging.

Telomere Dynamics and Avian Aging

Telomeres, which are highly repetitive nucleotide sequences located on the ends of eukaryotic chromosomes, are essential for the replication of linear DNA. In healthy tissues undergoing cell replication, telomeres are maintained by telomerase, a reverse transcriptase. Interest in aging-related changes in telomere maintenance and telomerase function arose from the observation that telomeres shorten progressively as somatic cell lines in culture (e.g., human epithelial fibroblasts) undergo repeated rounds of replication and division. These cells typically replicate a finite number of times before the population either dies out or “transforms” to become cancer cells. This loss of replicative capacity or “cellular senescence” in vitro is accompanied by telomere shortening and loss of telomerase activity, ostensibly increasing genomic instability. This phenomenon led cell biologists to the concept of a “telomere clock”—the idea that telomere shortening rates (or declining telomerase activity) provide a measure of loss of replicative capacity (and, hence, a marker of aging) in terminally differentiated animal tissues. Critical changes in telomere structure and function have been implicated in the transformation of healthy to cancerous cells in humans and rodents, and evidence is accumulating that telomere dynamics are important in these species in aging and in some aging-related diseases, such as cancer (Blackburn 1991, Has-tie et al. 2003, Kujoth et al. 2005, Wright and Shay 2005).

But there is no particular reason, a priori, to expect that telomere lengths or other aspects of telomere dynamics will reflect variation in organismal aging patterns—even between species within a vertebrate class—in a straightforward way. Telomeres of cells from adult laboratory rodents, for example, are considerably longer than those of similar cells from adult humans, and replicative senescence in rodent cells in vitro does not correlate predictably with telomere shortening as it does in human cells. However, long-lived organisms are expected to have more efficient ways of responding to stressors, preserving healthy capabilities for cell replication and preventing cancers, and these are likely to involve aspects of telomere dynamics (Shay and Wright 2001,2005; Wang et al. 2001). It is interesting, in this context, that aging-related telomere shortening rates in some tissues have been reported to correlate inversely with documented life spans of some vertebrates, including some bird species (Hauss-mann et al. 2003, Vleck et al. 2003).

Given that many birds are exceptionally long-lived for their sizes and metabolic rates, it stands to reason that they may have particularly efficient regulation of cell replication. Thus, the concept of an avian telomere clock has received considerable attention recently (reviewed in Taylor and Delany 2000). The measurement of avian telomeres can be complicated by the unusually large size of the avian telomeric genome, and there is considerable variability reported in the lengths of telomere fragments measured from different avian tissues and species (Table 5; Delany et al. 2000, Swanberg and Delany 2006). The chicken telomeric genome, the best-studied of all bird species, includes about 10× more DNA than the human telomeric genome. Avian class-Ill terminal restriction fragments (TRFs) are the largest described for telomeres of any vertebrate group, with lengths ranging from 40 kilobases to 2 megabases.

In some respects, avian telomere dynamics resemble those in human tissues more closely than those in rodent tissues. As in humans, for example (but unlike in mice), avian telomerase has been shown to be down-regulated in many organs postnatally, after tissues have completed differentiation, remaining active only in tissues with high cell turnover or particular cell lines that have undergone transformation to a precancerous state in vitro (Swan-berg and Delany 2003, Swanberg and Payne 2004). An initial comparison of erythrocytes and sperm from a few individuals for each of 18 bird species revealed no reliable relationships among TRF lengths and either the age of individuals or documented species life spans (Delany et al. 2000). But more recent cross-sectional studies including considerably larger numbers of individuals from wild populations of a number of avian species (with a wide range of documented life spans) have reported age-associated shortening of TRFs derived from erythrocytes (Haussmann et al. 2003, Vleck et al. 2003, Juola et al. 2006) (Table 5 and Figs. 5 and 6). Moreover, contrary to expectations, these authors reported that telomere fragment lengths from Leach's Storm-Petrels were positively correlated with chronological age. A later, longitudinal study of several different wild bird populations, on the other hand, reported no telomere shortening or lengthening in erythrocytes when younger birds were eliminated from the analysis (Hall et al 2004). The authors of this last study suggested that aging-related telomere shortening is likely to be overestimated in studies when subadult birds are included (age = 0; Table 5), given that tissues of younger, immature birds may not be composed of terminally differentiated cells.

Table 5.

Some key studies of avian telomere dynamics relevant to senescence.

t05_01.gif

Abbreviation: TRF = telomere restriction fragment.

a Domestic birds.

Fig. 5.

Cross-sectional examination of relationships between age and telomere (TRF) lengths (from erythrocytes) in one domestic and five wild bird populations: (A) domestic Zebra Finch, (B) Tree Swallow, (C) Adélie Penguin (Pygoscelis adeliae), (D) Common Tern, and (E) Leach's Storm-Petrel. Note that subadults are included for all but Leach's Storm-Petrel and that telomere lengths increase with age in this species. (No samples obtained from Leach's Storm-Petrels 1–9 years old; young do not return to breeding site until 3–6 years after fledging.) Lines are best-fit regressions: (A) slope = -515 ± 95 (SE) base pairs (bp) year-1, F = 29.9, df = 1 and 26, P< 0.0001, r 2 = 0.54; (B) slope =-391 ± 65 bp year-1, F = 23.3, df= 1 and 47, P< 0.0001, r 2 = 0.34; (C) slope = -235 ± 48 bp year-1, F = 23.9, df = 1 and 21, P < 0.0001, r 2 = 0.55; (D) slope = -57 ± 7 bp year-1, F = 67.0, df = 1 and 43, P < 0.0001, r 2 = 0.61; (E) slope = +75 + 10 bp year-1, F = 59.7, df = 1 and 32, P < 0.0001, r 2 = 0.66. (Reproduced from Haussmann et al. [2003] with permission of M. Haussmann and the Royal Society.)

f05_01.eps

Fig. 6.

Cross-sectional comparisons of telomere lengths (from erythrocytes) as a function of age in two wild seabird populations: (A) European Shag and (B) Wandering Albatross. Although telomere length appears to decline with age with youngest age classes are included, no significant associations were detected between telomere length and age in adults. For European Shags, r = -0.08, P = 0.54, n = 63; for Wandering Albatrosses, r = -0.08, P = 0.52, n = 61. (Reprinted from Hall et al. [2003] with permission of P. Monaghan and the Royal Society.)

f06_01.eps

It is important to recognize that telomere lengths (and any aging-related changes in TRFs) are expected to vary substantially among tissues with different cell-turnover rates. Terminal restriction fragments could fail to reflect either organism age or tissue age (i.e., number of cell replications) in cell lines that are not terminally differentiated (e.g., germ cells, some blood cells, or in tissues from young animals that are still undergoing development). Telomere lengths from a given tissue type can also vary considerably among individuals, even in inbred laboratory animal populations, as well as with organismal health, nutritional state, and history, including exposure to oxidative or other stressors (Levy et al. 1998, Hastie et al. 2003, Shay and Roninson 2004).

Despite the complexity of these issues, and the as-yet-unexplored variability of telomere genomes and dynamics among avian species, the data on telomeres and telomerase activity from wild bird populations are provocative. This emerging area merits additional, careful study and critical analysis—particularly in the context of other aging-related functional changes and fitness tradeoffs (see, e.g., Monaghan and Haussmann 2006). Evolution is expected to produce an array of defenses against molecular stress and damage; the telomere shortening typical of replicative senescence in humans, for example, may represent one, but not the only, kind of adaptation whereby longer-lived species preserve genomic integrity (Shay and Wright 2001). The influence of environmental conditions (e.g., stress and food availability) on telomere dynamics within a species is of particular interest to ornithologists. More controlled, longitudinal studies—both in captivity and in the wild, and using a range of tissue types from a variety of bird species—will be needed to clarify the significance of age-related changes in telomere dynamics and telomerase activity in birds with different aging patterns.

Future Directions in “Avian Biogerontology”

Major research priorities for the biology of aging include the identification of molecular, physiological, and evolutionary mechanisms that allow, as well as prevent, organismal senescence, and that promote sustained somatic maintenance and reproduction in exceptionally long-lived species—including many birds. A better understanding of the generality of basic aging mechanisms in a wide taxonomic range of model organisms has obvious utility for intervention in diseases of aging. Current research priorities of avian and evolutionary biologists are quite compatible with those of more medically oriented biogerontologists, given their common strong focus on the roles of genes and the environment in creating and maintaining healthy, integrated animal phenotypes. Below, we summarize several areas we view as potentially ripe for cooperation and shared research contributions by ornithologists and biogerontologists.

Evolutionary aging and life—history theory.-Biogerontology and ornithology have a common investment in evolutionary theory as a framework for understanding the “fast-slow” continuum of development, maturation, and [in] aging patterns seen among living organisms, including the laboratory species commonly used in studies of basic aging processes (Rose 1991, Martin et al. 1996, Reznick et al. 2004, Reznick 2005). For several decades, studies of wild bird populations have focused on the effects of specific ecological variables on life-history evolution and life span, including predation, food supply, latitude, altitude, extreme cold, and migration patterns (e.g., Ricklefs 1973, 1990, 2000a; Botkin and Miller 1974; T. E. Martin 1987; K. Martin 1995; Wiebe and Martin 1998; Ricklefs and Scheuerlein 2003; Møller et al. 2005; Sandercock et al. 2005b; Møller 2006; Dobson and Jouventin 2007; Wilson 2008; Bears et al. 2009). Despite demonstrations that many birds undergo some form of aging in the wild, however, it is unknown how aging-related deterioration varies across populations in relation to environmental conditions and whether such deterioration contributes in a significant way to changes in fitness or lifetime reproductive success. More comprehensive studies of aging-related immune changes in wild, breeding birds should lead to a clearer understanding of how specific aspects of immunity and other physiological functions actually reflect variation in condition or stress resistance and how species with different life histories make tradeoffs between immunocompetence, reproduction, and other evolutionary priorities. Avian ecoimmunology holds particular promise for a more integrated approach to understanding senescence in nature, and this discipline is stimulating the adoption of clinical measures of immune function for testing hypotheses from life-history and sexual-selection theory using both captive and wild populations of birds.

Biogerontologists have expressed particular interest in very long-lived birds, like seabirds, that inhabit insular habitats and are subject to very low mortality rates (Finch 1990; Ricklefs 1990; Holmes and Austad 1995a, b; Ricklefs and Finch 1995; Holmes 2003). Recent seabird studies have shown little appreciable change in immune function or reproductive endocrinology in older breeding birds (Ottinger et al. 1995; Nisbet et al. 1999, 2002; Apanius and Nisbet 2003) but suggest the intriguing possibility that older birds may compensate for declines in physiological condition with increases in reproductive effort (Velando et al. 2006, Torres and Velando 2007, Keller et al. 2008) or enhanced physiological resistance to stress (Angelier et al. 2007; but see Heidigger et al. 2008). Apart from being intrinsically interesting from ecological or evolutionary standpoints, sustained low rates of reproduction with little apparent aging-related loss of fertility in birds could have implications for understanding basic mechanisms of human reproductive aging and infertility.

Physiological tradeoffs and reproductive costs.—A particularly strong focus of avian biology now centers on potential costs of reproduction accrued from exposure to steroid sex and stress hormones and the relationships between antioxidant defenses, fitness, and reproductive success. Although genetic and physiological tradeoffs are sometimes considered in studies of basic aging processes, a rigorous evolutionary perspective is often lacking; this is arguably one of the most important shortcomings of standard biogerontological approaches currently (Partridge et al. 2005, Lithgow 2006). Sustained fertility and slow, healthy aging are expected to be related in evolutionary terms, and genes responsible for variation in life span probably also control, in many cases, key aspects of reproduction (Kirkwood and Austad 2000, Partridge et al. 2005). Consideration of reproductive costs and the possible evolutionary tradeoffs (e.g., antagonistic pleiotropy) among fertility, somatic fitness, and longevity are relevant to a number of current aging-related medical priorities, including human reproductive aging issues and cancers (Stearns et al. 2008).

Energy metabolism, oxidative stress, and nutrition.—Currently, a primary focus of biogerontology is the relationship between aging and oxidative stress and damage to cells and macro-molecules, and how key aspects of energy metabolism and growth rates are related to life span. Ornithologists are likewise engaged in studies of the relationships among nutritional status (particularly in relation to antioxidants), hormonal infuences, growth rates, and such fitness parameters as immune function and stress resistance (see, e.g., Alonso-Alvarez and Tella 2001; Metcalfe and Monaghan 2001, 2003; Blount et al. 2003; Alonso-Alvarez et al. 2006, 2007; Criscuolo et al. 2008). Researchers increasingly recognize the importance of studies like these to the biology of aging generally, their implications for human health and developmental biology, and the potential for interdisciplinary collaboration in exploring these issues.

Sexual selection, sexual conflict, and mate choice.—The biology of aging has distinct implications for addressing theoretical questions about sexual conflict, mate choice, and the evolution of mating systems, given that there are strong correlates of sex differences in aging and mortality patterns in many animals, including humans (e.g., Promislow et al. 1992, Promislow 2004, Clutton-Brock and Isvaran 2007). Sex differences in the roles of steroid hormones in long-term health, including immune function, susceptibility to parasites and disease, and the ability to combat oxidative and other stresses have direct clinical relevance. For example, Bonduriansky et al. (2008) suggested that sexual selection and male reproductive strategies may result in elevated mortality and weakened selection on life span in males compared with females. Currently, however, there is little direct discussion or collaboration among evolutionary biologists, behavioral ecologists, and biogerontologists in addressing these issues.

Comparative approaches to studies of basic aging processes.—Comparative approaches of various kinds have long provided important insights into the basic processes underlying senescence in both wild and captive studies (reviewed in Austad and Holmes 1999, Holmes and Kristan 2008). Although natural populations typically show patterns of survival and reproductive investment consistent with predicted survival-fecundity tradeoffs, the mechanisms responsible for these aging patterns remain elusive. For example, rates of aging-related mortality in field studies of birds are often highly correlated with mortality resulting from extrinsic age-independent causes, such as predation, harsh weather, or habitat conditions, rather than from the predicted causes of intrinsic (aging-related) mortality, such as cancer or cardiovascular failure (Ricklefs 2008). Furthermore, in captivity, where resources are plentiful, the life spans of birds and mammals appear to be unrelated to investment in reproduction (Ricklefs and Cadena 2007). More field studies using comparative approaches are needed to determine the cause of death in natural populations and to characterize variation in rates of aging within and across populations, and we need more detailed longitudinal studies of individual health and reproductive success in relation to age at death (Monaghan et al. 2008, Nussey et al. 2008). Such comparative studies should help to quantify differences in aging rates between different physiological systems and reveal how each contributes to fitness at different life-history stages (Promislow et al. 2006). Although multispecies comparisons of aging and life span have long been used by biogerontologists, phylogenetic statistical approaches have been applied only recently for addressing comparative questions about proximate aging mechanisms (Haussmann et al. 2003; Speakman 2005a, b; Hulbert et al. 2007; Lambert et al. 2007). In addition, clinical and genetic markers, as well as other variables, should prove useful for identifying phenotypic traits that contribute to the probability of longevity (Møller and Szép 2002, Priest et al. 2002, Saino et al. 2002, Møller 2006).

Value of reliable aging biomarkers in avian conservation biology.—The development of aging biomarkers for avian populations has wide potential application for both diagnosis and prescription in ecology, conservation, and management. Such biomarkers would allow greater insight into the relationships and the ecological importance between senescence and other cohort effects in response to environmental gradients or stressors. Where population life histories vary with altitude or latitude, intensive, long-term longitudinal studies could be used to assess potential effects of climate change on particular age cohorts. Current field techniques often can distinguish only two or a few “cohorts” of adults—first-time breeders and all older birds—making it difficult to diagnose effects of overhunting or other elevated mortality factors.

Improved physiological or molecular measures of aging might eventually allow earlier diagnosis of populations or cohorts of birds in peril, if such measures refected environmentally altered patterns of actuarial or physiological senescence that are actually correlated with reduced vital rates. For declining populations of threatened species, such as the Horned Lark subspecies Eremophila alpestris strigata in Washington state (Pearson et al. 2008), such aging bio-markers might be particularly useful. Reliable, biologically meaningful measures of cellular or molecular damage, specific functional declines, or other signs of physiological stress in known-age individuals might eventually be employed to weigh the relative contributions of habitat loss or degradation to intrinsic aging-related changes, as opposed to “normal,” extrinsic mortality forces. In critically endangered populations, such as the Northern Spotted Owl (Strix occidentalis caurina) in British Columbia, where all remaining birds in the populations are older, a biomarker that could measure reproductive senescence would have wonderful efficacy for identifying those individuals in the best condition to set up a captive breeding program. For threatened species, many of which are long-lived, we might save valuable time and maximize successful breeding attempts in captivity if we could develop biomarker for separating ‘chronologically old’ from ‘physiologically old’ individuals.

ACKNOWLEDGMENTS

We are very grateful for comments on the manuscript from C. Col-beck, K. Loeb Belinsky, R. Ricklefs, and an anonymous reviewer. We thank S. Sealy and R. Earles for valuable editorial input. Figure 1 was reproduced with permission from A. Hulbert and the American Physiological Society. Figure 2 was reproduced with permission from J. Speakman and The Company of Biologists. Figure 3 was reproduced with permission from D. Holmes, S. Austad, and Highwire Press, and adapted from original data from Møller and Szép (2002) and L. Gustafsson (pers. comm.). Figure 4 was reproduced with permission from L. Martin and Highwire Press. Figure 5 was reproduced with permission from M. Haussmann and the Royal Society. Figure 6 was reproduced with permission of P. Monaghan and the Royal Society.

LITERATURE CITED

  1. S. A. ADAMO 2004. How should behavioural ecologists interpret measurements of immunity? Animal Behaviour 68:1443–1449. Google Scholar

  2. C. Alonso-Alvarez , S. Bertrand, G. Devevey, J. Prost, B. Faivre , O. Chastel , and G. Sorci . 2006. An experimental manipulation of life-history trajectories and resistance to oxida-tive stress. Evolution 60:1913–1924. Google Scholar

  3. C. Alonso-Alvarez , S. Bertrand, B. Faivre , O. Chastel , and G. Sorci . 2007. Testosterone and oxidative stress: The oxidation handicap hypothesis. Proceedings of the Royal Society of London, Series B 274:819–825. Google Scholar

  4. C. Alonso-Alvarez , and J. L. Tella . 2001. Effects of experimental food restriction and body-mass changes on the avian T-cell-mediated immune response. Canadian Journal of Zoology 79:101–105. Google Scholar

  5. F. Angelier, B. Moe, H. Weimerskirch, and O. Chastel. 2007. Age-specifc reproductive success in a long-lived bird: Do older parents resist stress better? Journal of Animal Ecology 76:1181–1191. Google Scholar

  6. V. Apanius , and I. C. T. Nisbet . 2003. Serum immunoglobulin G levels in very old Common Terns, Sterna hirundo. Experimental Gerontology 38:761–764. Google Scholar

  7. V. Apanius , and I. C. T. Nisbet . 2006. Serum immunoglobulin G levels are positively related to reproductive performance in a long-lived seabird, the Common Tern (Sterna hirundo). Oecolo-gia 147:12–23. Google Scholar

  8. S. N. Austad 1996. The uses of intraspecific variation in aging research. Experimental Gerontology 31:453–463. Google Scholar

  9. S. N. Austad 1997. Birds as models of aging in biomedical research. ILAR Journal Online 38:137–141. [Online.] Available at  dels.nas.edu/ilar_n/ilarjournal/38_3/38_3Birds.shtml.  Google Scholar

  10. S. N. Austad 2001. An experimental paradigm for the study of slowly aging organisms. Experimental Gerontology 36:599–605. Google Scholar

  11. S. N. Austad, and K. E. Fischer. 1991. Mammalian aging, metabolism, and ecology: Evidence from the bats and marsupials. Journals of Gerontology 46:B47–B53. Google Scholar

  12. S. N. Austad , and D. J. Holmes . 1999. Evolutionary approaches to probing aging mechanisms. Pages 437–452 in Methods in Aging Research ( B. P. Yu, Ed.). CRC Press, Boca Raton, Florida. Google Scholar

  13. S. N. Austad, and D. M. Kristan. 2003. Are mice calorically restricted in nature? Aging Cell 2:201–207. Google Scholar

  14. E. A. Baldal , W. Baktawar , P. M. Brakefield , and B. J. Zwaan . 2006. Methuselah life history in a variety of conditions, implications for the use of mutants in longevity research. Experimental Gerontology 41:1126–1135. Google Scholar

  15. G. Barja 1998. Mitochondrial free radical production and aging in mammals and birds. Annals of the New York Academy of Sciences 854:224–238. Google Scholar

  16. G. Barja, S. Cadenas, C. Rojas, M. López-Torres, and R. Pérez-Campo. 1994a. A decrease in free radical production near critical targets as a cause of maximum longevity in animals. Comparative Biochemistry and Physiology B 108:501–512. Google Scholar

  17. G. Barja, S. Cadenas, C. Roja, R. Perez-Campo, and M. Lopez-Torres. 1994b. Low mitochondrial free radical production per unit of O2 consumption can explain the simultaneous presence of high longevity and high aerobic metabolic rate in birds. Free Radical Research 21:317–328. Google Scholar

  18. G. Barja , and A. Herrero . 1998. Localization at complex I and mechanism of the higher free radical production of brain non-synaptic mitochondria in the short-lived rat than in the longevous pigeon. Journal of Bioenergetics and Biomembranes 30:235–243. Google Scholar

  19. H. Bears, K. Martin, and G. C. White. 2009. Breeding in high-elevation habitat results in shift to slower life-history strategy within a single species. Journal of Animal Ecology: in press (DOI: 10.1111/j.1365-2656.2008.01491). Google Scholar

  20. K. B. Beckman , and B. N. Ames . 1998. The free radical theory of aging matures. Physiological Reviews 78:547–581. Google Scholar

  21. A. F. Bennett , and R. B. Huey . 1990. Studying the evolution of physiological performance. Pages 251–284 in Oxford Surveys in Evolutionary Biology, vol. 7 (D. J. Futuyma and J. Antonovics, Eds.). Oxford University Press, Oxford, United Kingdom. Google Scholar

  22. P. M. Bennett , and I. P. F. Owens . 2002. Evolutionary Ecology of Birds. Life Histories, Mating Systems and Extinction. Oxford University Press, Oxford, United Kingdom. Google Scholar

  23. G. R. Bentley , and S. Muttukrishna . 2007. Potential use of bio-markers for analyzing interpopulation and cross-cultural variability in reproductive aging. Menopause 14:668–679. Google Scholar

  24. C. A. Beuchat , and C. R. Chong . 1998. Hyperglycemia in hummingbirds and its consequences for hemoglobin glycation. Comparative Biochemistry and Physiology A 120:409–416. Google Scholar

  25. L. Bevilacqua, J. J. Ramsey, K. Hagopian, R. Weindruch, and M.-E. Harper. 2004. Effects of short- and medium-term calorie restriction on muscle mitochondrial proton leak and reactive oxygen species production. American Journal of Physiology: Endocrinology and Metabolism 286:E852–E861. Google Scholar

  26. L. Bevilacqua, J. J. Ramsey, K. Hagopian, R. Weindruch, and M. E. Harper. 2005. Long-term caloric restriction increases UCP3 content but decreases proton leak and reactive oxygen species production in rat skeletal muscle mitochondria. American Journal of Physiology: Endocrinology and Metabolism 289: E429–E438. Google Scholar

  27. E. H. Blackburn 1991. Structure and function of telomeres. Nature 350:569–573. Google Scholar

  28. J. D. Blount , N. B. Metcalfe, K. E. Arnold, P. F. Surai , G. L. Devevey , and P. Monaghan . 2003. Neonatal nutrition, adult antioxidant defences and sexual attractiveness in the Zebra Finch. Proceedings of the Royal Society of London, Series B 270:1691–1696. Google Scholar

  29. R. Bonduriansky , A. Maklakov , F. Zajitschek , and R. Brooks . 2008. Sexual selection, sexual conflict and the evolution of ageing and lifespan. Functional Ecology 22:443–453. Google Scholar

  30. D. B. Botkin , and R. S. Miller . 1974. Mortality rates and survival of birds. American Naturalist 108:181–192. Google Scholar

  31. M. D. Brand 2000. Uncoupling to survive? The role of mitochondrial inefficiency in ageing. Experimental Gerontology 35:811–820. Google Scholar

  32. J. E. Brommer , A. J. Wilson , and L. Gustafsson . 2007. Exploring the genetics of aging in a wild passerine bird. American Naturalist 170:643–650. Google Scholar

  33. A. M. Bronikowski 2008. The evolution of aging phenotypes in snakes. AGE 30:169–176. Google Scholar

  34. A. M. Bronikowski , and D. E. L. Promislow . 2005. Testing evolutionary theories of aging in wild populations. Trends in Ecology and Evolution 20:271–273. Google Scholar

  35. H. M. Brown-Borg , K. E. Borg , C. J. Meliska , and A. Bartke . 1996. Dwarf mice and the ageing process. Nature 384:33. Google Scholar

  36. A. K. Brunet-Rossinni , and S. N. Austad . 2004. Ageing studies on bats: A review. Biogerontology 5:211–222. Google Scholar

  37. A. K. Brunet-Rossinni , and S. N. Austad . 2006. Senescence in wild populations of mammals and birds. Pages 243–266 in Handbook of the Biology of Aging ( E. J. Masoro and S. N. Austad, Eds.). Academic Press, Burlington, Massachusetts. Google Scholar

  38. R. Buffenstein 2005. The naked mole-rat: A new long-living model for human aging research. Journal of Gerontology 60A:1369–1377. Google Scholar

  39. R. Buffenstein , Y. H. Edrey , T. Yang , and J. Mele . 2008. The oxidative stress theory of aging: Embattled or invincible? Insights from non-traditional model organisms. AGE 30:99–109. Google Scholar

  40. R. N. Butler, R. Sprott, H. Warner, J. Bland, R. Feuers, M. Forster, H. Fillit, S. M. Harman, M. Hewitt, and others. 2004. Biomarkers of aging: From primitive organisms to humans. Journals of Gerontology A. Biological Sciences and Medical Sciences 59A:B560–B567. Google Scholar

  41. D. C. Cabelof, J. J. Raffoul, Y. Ge, H. Van Remmen, L. H. Matherly, and A. R. Heydari. 2006. Age-related loss of the DNA repair response following exposure to oxidative stress. Journal of Gerontology 61A:427–434. Google Scholar

  42. J. Campisi 2001. From cells to organisms: Can we learn about aging from cells in culture? Experimental Gerontology 36:607–618. Google Scholar

  43. C. S. Carter , and W. Sonntag . 2006. Growth hormone, insulinlike growth factor-I, and the biology of aging. Pages 534–569 in Handbook of the Biology of Aging, 6th ed. ( E. J. Masoro and S. N. Austad, Eds.). Academic Press, New York. Google Scholar

  44. A. R. Chaudhuri , E. M. de Waal, A. Pierce, H. Van Remmen , Ward W. F. , and A. Richardson . 2006. Detection of protein carbonyls in aging liver tissue: A fuorescence-based proteomic approach. Mechanisms of Ageing and Development 127:849–861. Google Scholar

  45. M. J. Chutter , I. Blackburn, D. Bonin, J. B. Buchanan, D. Cunnington, L. Feldes, A. Harestad, D. Heppner, L. Kiss , S. Leech , and others. 2007. Guidance and some components of action planning for the Northern Spotted Owl (Strix occiden-talis caurina) in British Columbia. British Columbia Ministry of Environment, Victoria. Google Scholar

  46. M. Cichon , J. Sendecka , and L. Gustafsson . 2003. Age-related decline in humoral immune function in Collared Flycatchers. Journal of Evolutionary Biology 16:1205–1210. Google Scholar

  47. T. H. Clutton-Brock , and K. Isvaran . 2007. Sex differences in ageing in natural populations of vertebrates. Proceedings of the Royal Society of London, Series B 274:3097–3104. Google Scholar

  48. A. A. Cohen , K. J. McGraw, P. Wiersma, J. B. Williams, W. D. Robinson, T. R. Robinson , J. D. Brawn , and R. E. Ricklefs . 2008. Interspecifc associations between circulating antioxidant levels and life-history variation in birds. American Naturalist 172:178–193. Google Scholar

  49. P. M Conn . 2006. Handbook of Models for Human Aging. Academic Press, New York. Google Scholar

  50. F. Criscuolo , P. Monaghan , L. Nasir , and N. B. Metcalfe . 2008. Early nutrition and phenotypic development: ‘Catch-up’ growth leads to elevated metabolic rate in adulthood. Proceedings of the Royal Society of London, Series B 275:1565–1570. Google Scholar

  51. V. J. Cristofalo 1988. Cellular biomarkers of aging. Experimental Gerontology 23:297–307. Google Scholar

  52. M. E. Delany , A. B. Krupkin , and M. M. Miller . 2000. Organization of telomere sequences in birds: Evidence for arrays of extreme length and for in vivo shortening. Cytogenetics and Cell Genetics 90:139–145. Google Scholar

  53. F. S. Dobson , and P. Jouventin . 2007. How slow breeding can be selected in seabirds: Testing Lack's hypothesis. Proceedings of the Royal Society of London, Series B 274:275–279. Google Scholar

  54. E. B. Edney , and R. W. Gill . 1968. Evolution of senescence and specific longevity. Nature 220:281–282. Google Scholar

  55. R. B. Effros 2003. Genetic alterations in the ageing immune system: Impact on infection and cancer. Mechanisms of Ageing and Development 124:71–77. Google Scholar

  56. J. A. Fallon , R. L. Cochrane , B. Dorr , and H. Klandorf . 2006. Interspecies comparison of pentosidine accumulation and its correlation with age in birds. Auk 123:870–876. Google Scholar

  57. C. E. Finch 1990. Longevity, Senescence, and the Genome. University of Chicago Press, Chicago, Illinois. Google Scholar

  58. C. E. Finch , and T. B. L. Kirkwood . 2000. Chance, Development, and Aging. Oxford University Press, New York. Google Scholar

  59. C. E. Finch , M. C. Pike , and M. Witten . 1990. Slow mortality rate accelerations during aging in some animals approximate that of humans. Science 249:902–905. Google Scholar

  60. T. Finkel , and N. J. Holbrook . 2000. Oxidants, oxidative stress and the biology of ageing. Nature 408:239–247. Google Scholar

  61. K. Flurkey , J. Papaconstantinou , R. A. Miller , and D. E. Harrison . 2001. Lifespan extension and delayed immune and collagen aging in mutant mice with defects in growth hormone production. Proceedings of the National Academy of Sciences USA 98:6736–6741. Google Scholar

  62. C. Franceschi , S. Valensin, F. Fagnoni , C. Barbi , and M. Bonafè . 1999. Biomarkers of immunosenescence within an evolutionary perspective: The challenge of heterogeneity and the role of antigenic load. Experimental Gerontology 34:911–921. Google Scholar

  63. G. S. Gerhard 2007. Small laboratory fish as models for aging research. Ageing Research Reviews 6:64–72. Google Scholar

  64. F. B. Gill 2007. Ornithology, 3rd ed. F.H.Freeman, New York. Google Scholar

  65. R. Gredilla , A. Sanz , M. Lopez-Torres , and G. Barja . 2001. Caloric restriction decreases mitochondrial free radical generation at complex I and lowers oxidative damage to mitochondrial DNA in the rat heart. FASEB Journal 15:1589–1591. Google Scholar

  66. B. Grubeck-Loebenstein , and G. Wick . 2002. The aging of the immune system. Advances in Immunology 80:243–284. Google Scholar

  67. M. E. Hall , L. Nasir,, F. Daunt, E. A. Gault, J. P. Croxall , S. Wanless , and P. Monaghan . 2004. Telomere loss in relation to age and early environment in long-lived birds. Proceedings of the Royal Society of London, Series B 271:1571–1576. Google Scholar

  68. M. L. Hamilton , Z. Guo, C. D. Fuller, H. Van Remmen, W. F. Ward, S. N. Austad, D. A. Troyer , I. Thompson , and A. Richardson . 2001. A reliable assessment of 8-oxo-2-deoxy-guanosine levels in nuclear and mitochondrial DNA using the sodium iodide method to isolate DNA. Nucleic Acids Research 29:2117–2126. Google Scholar

  69. D. Harman 1956. Aging: A theory based on free radical and radiation chemistry. Journal of Gerontology 11:298–300. Google Scholar

  70. J. M. Harper , A. T. Galecki , D. T. Burke , and R. A. Miller . 2004. Body weight, hormones and T cell subsets as predictors of life span in genetically heterogeneous mice. Mechanisms of Ageing and Development 125:381–390. Google Scholar

  71. J. M. Harper , N. Wolf, A. T. Galecki , S. L. Pinkosky , and R. A. Miller . 2003. Hormone levels and cataract scores as sex-specifc, mid-life predictors of longevity in genetically heterogeneous mice. Mechanisms of Ageing and Development 124:801–810. Google Scholar

  72. P. H. Harvey , and M. D. Pagel . 1991. The Comparative Method in Evolutionary Biology. Oxford University Press, Oxford, United Kingdom. Google Scholar

  73. P. Hastie, J. Campisi, J. Hoeijmakers, H. van Steeg, and J. Vijg. 2003. Aging and genome maintenance: Lessons from the mouse? Science 299:1355F.H.1359. Google Scholar

  74. M. F. Haussmann , D. W. Winkler, C. E. Huntington, D. Vleck, C. E. Sanneman , D. Hanley , and C. M. Vleck . 2005. Cell-mediated immunosenescence in birds. Oecologia 145:270–275. Google Scholar

  75. M. F. Haussmann , D. W. Winkler, K. M. O'Reilly, C. E. Huntington , I. C. T. Nisbet , and C. M. Vleck . 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proceedings of the Royal Society of London, Series B 270:1387–1392. Google Scholar

  76. M. F. Haussmann , Winkler D. W., Huntington C. E. , I. C. T. Nisbet , and C. M. Vleck . 2007. Telomerase activity is maintained throughout the lifespan of long-lived birds. Experimental Gerontology 42:610–618. Google Scholar

  77. B. J. Heidinger , E. D. Ketterson , and I. Nisbet . 2008. Changes in adrenal capacity contribute to a decline in the stress response with age in a long-lived seabird. General and Comparative Endocrinology 156:564–568. Google Scholar

  78. S. Hekimi , and L. Guarente . 2003. Genetics and the specifcity of the aging process. Science 299:1351–1354. Google Scholar

  79. A. Herrero , and G. Barja . 1998. H2O2 production of heart mitochondria and aging rate are slower in canaries and parakeets than in mice: Sites of free radical generation and mechanisms involved. Mechanisms of Ageing and Development 103:133–146. Google Scholar

  80. A. Herrero , and G. Barja . 1999. 8-oxo-deoxyguanosine levels in heart and brain mitochondrial and nuclear DNA of two mammals and three birds in relation to their different rates of aging. Aging (Milano) 11:294–300. Google Scholar

  81. D. J. Holmes 2003. Aging in birds. Pages 201–219 in Aging in Organisms ( H. Osiewacz, Ed.). Kluwer Press, Amsterdam. Google Scholar

  82. D. J. Holmes, and S. N. Austad. 1995a. Birds as animal models for the comparative biology of aging: A prospectus. Journal of Gerontology A 50:B59–B66. Google Scholar

  83. D. J. Holmes, and S. N. Austad. 1995b. The evolution of avian senescence patterns: Implications for understanding primary aging processes. American Zoologist 35:307–317. Google Scholar

  84. D. J. Holmes, and S. N. Austad. 2004. Declining immunity with age in the wild? Evidence from bird populations. Science of Aging Knowledge Environment 2004:pe22. Google Scholar

  85. D. J. Holmes , R. Flückiger , and S. N. Austad . 2001. Comparative biology of aging in birds: An update. Experimental Gerontology 36:869–883. Google Scholar

  86. D. J. Holmes , and D. M. Kristan . 2008. Comparative and alternative approaches and novel animal models for aging research. AGE 30:63–73. Google Scholar

  87. D. Holmes , and M. A. Ottinger . 2006. Domestic and wild bird models for the study of aging. Pages 351–365 in Handbook of Models for Human Aging ( P. Conn, Ed.). Academic Press, New York. Google Scholar

  88. D. J. Holmes, M. A. Ottinger, R. E. Rickleffs, and C. E. Finch. 2003a. SOSA-2: Introduction to the Proceedings of the Second Symposium on Organisms with Slow Aging. Experimental Gerontology 38:721–722. Google Scholar

  89. D. J. Holmes, S. L. Thomson, J. Wu, and M. A. Ottinger. 2003b. Reproductive aging in female birds. Experimental Gerontology 38:751–756. Google Scholar

  90. A. J. Hulbert 2003. Life, death and membrane bilayers. Journal of Experimental Biology 206:2303–2311. Google Scholar

  91. A. J. Hulbert , R. Pamplona , R. Buffenstein , and W. A. Buttemer . 2007. Life and death: Metabolic rate, membrane composition, and life span of animals. Physiological Reviews 87:1175–1213. Google Scholar

  92. M. Iqbal, L. L. Probert, N. H. Alhumadi, and H. Klandorf. 1999. Protein glycosylation and advanced glycosylated endprod-ucts (AGEs) accumulation: An avian solution? Journals of Gerontology A 54:B171–B176. Google Scholar

  93. S. Jaensch , L. Cullen , L. Morton , and S. R. Raidal . 2001. Nor-mobaric hyperoxic stress in budgerigars: Non-enzymic antioxi-dants. Comparative Biochemistry and Physiology C 128:181–187. Google Scholar

  94. T. E. Johnson 2006a. For the special issue: The nematode Caenorhabditis elegans in aging research. Experimental Gerontology 41:887–889. Google Scholar

  95. T. E. Johnson 2006b. Recent results: Biomarkers of aging. Experimental Gerontology 41:1243–1246. Google Scholar

  96. F. A. Juola , M. F. Haussmann , D. C. Dearborn , and C. M. Vleck . 2006. Telomere shortening in a long-lived marine bird: Cross-sectional analysis and test of an aging tool. Auk 123:775–783. Google Scholar

  97. L. F. Keller , J. M. Reid , and P. Arcese . 2008. Testing evolutionary models of senescence in a natural population: Age and inbreeding effects on fitness components in song sparrows. Proceedings of the Royal Society of London, Series B 275:597–604. Google Scholar

  98. T. B. L. Kirkwood, and S. N. Austad. 2000. Why do we age? Nature 408:233–238. Google Scholar

  99. H. Klandorf , D. S. Rathore, M. Iqbal , X. Shi , and K. Van Dyke . 2001. Accelerated tissue aging and increased oxidative stress in broiler chickens fed allopurinol. Comparative Biochemistry and Physiology C 129:93–104. Google Scholar

  100. A. Krtolica , S. Parrinello, S. Lockett , P.-Y. Desprez , and J. Campisi . 2001. Senescent fibroblasts promote epithelial cell growth and tumorigenesis: A link between cancer and aging. Proceedings of the National Academy of Sciences USA 98:12072- 12077. Google Scholar

  101. H.-H. Ku , U. T. Brunk , and R. S. Sohal . 1993. Relationship between mitochondrial superoxide and hydrogen peroxide production and longevity of mammalian species. Free Radical Biology and Medicine 15:621–627. Google Scholar

  102. H.-H Ku , and R. S. Sohal . 1993. Comparison of mitochondrial pro-oxidant generation and anti-oxidant defenses between rat and pigeon: Possible basis of variation in longevity and metabolic potential. Mechanisms of Ageing and Development 72:67–76. Google Scholar

  103. G. C. Kujoth , A. Hiona, T. D. Pugh, S. Someya, K. Panzer, S. E. Wohlgemuth, T. Hoffer, A. Y. Seo, R. Sullivan , W. A. Jobling , and others. 2005. Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian aging. Science 309:481–484. Google Scholar

  104. T. Laaksonen , E. Korpimäki , and H. Hakkarainen . 2002. Interactive effects of parental age and environmental variation on the breeding performance of Tengmalm's Owls. Journal of Animal Ecology 71:23–31. Google Scholar

  105. A. J. Lambert , H. M. Boysen, J. A. Buckingham, T. Yang, A. Podlutsky, S. N. Austad, T. H. Kunz , R. Buffenstein , and M. D. Brand . 2007. Low rates of hydrogen peroxide production by isolated heart mitochondria associate with long maximum lifespan in vertebrate homeotherms. Aging Cell 6:607–618. Google Scholar

  106. A. J. Lambert , and M. D. Brand . 2007. Research on mitochondria and aging, 2006–2007. Aging Cell 6:417–420. Google Scholar

  107. E. Lavoie 2005. Avian immunosenescence. AGE 27:281–285. Google Scholar

  108. E. J. Lesnefsky , and C. L. Hoppel . 2006. Oxidative phosphorylation and aging. Ageing Research Reviews 5:402–433. Google Scholar

  109. T. Levy , I. Agoulnik, E. N. Atkinson, X. W. Tong, H. M. Gause, A. Hasenburg, I. B. Runnebaum, E. Stickeler, V. J. Mobus , A. L. Kaplan , and D. G. Kieback . 1998. Telomere length in human white blood cells remains constant with age and is shorter in breast cancer patients. Anticancer Research 18:1345–1349. Google Scholar

  110. G. J. Lithgow 2006. Why aging isn't regulated: A lamentation on the use of language in aging literature. Experimental Gerontology 41:890–893. Google Scholar

  111. G. J. Lithgow , and G. A. Walker . 2002. Stress resistance as a determinate of C. elegans lifespan. Mechanisms of Ageing and Development 123:765–771. Google Scholar

  112. W. Liu 2004. DNA oxidative damage in birds: Measuring, analyzing and comparing. Ph.D. dissertation, Iowa State University, Ames. Google Scholar

  113. R. L. Lochmiller, and C. Deerenberg. 2000. Trade-offs in evolutionary immunology: Just what is the cost of immunity? Oikos 88:87–98. Google Scholar

  114. M. Lopez-Torres , R. Perez-Campo, C. Rojas , S. Cadenas , and G. Barja . 1993. Maximum life span in vertebrates: Relationship with liver antioxidant enzymes, glutathione system, ascorbate, urate, sensitivity to peroxidation, true malondialdehyde, in vivo H2O2, and basal and maximum aerobic capacity. Mechanisms of Ageing and Development 70:177–199. Google Scholar

  115. G. A. Lozano , and D. B. Lank . 2003. Seasonal trade-offs in cell-mediated immunosenescence in ruffs (Philomachus pugnax). Proceedings of the Royal Society of London, Series B 270:1203- 1208. Google Scholar

  116. A. Mansouri , F. L. Muller, Y. Liu, R. Ng, J. Faulkner, M. Hamilton, A. Richardson, T.-T. Huang , C. J. Epstein , and H. Van Remmen . 2006. Alterations in mitochondrial function, hydrogen peroxide release and oxidative damage in mouse hind-limb skeletal muscle during aging. Mechanisms of Ageing and Development 127:298–306. Google Scholar

  117. G. M. Martin , S. N. Austad , and T. E. Johnson . 1996. Genetic analysis of ageing: Role of oxidative damage and environmental stresses. Nature Genetics 13:25–34. Google Scholar

  118. K. Martin 1995. Patterns and mechanisms of age-dependent reproduction and survival in birds. American Zoologist 35:340–348. Google Scholar

  119. K. Martin 2001. Wildlife in alpine and sub-alpine habitats. Pages 285–310 in Wildlife-Habitat Relationships in Oregon and Washington ( D. H. Johnson and T. A. O'Neil, Eds.). Oregon State Press, Corvallis. Google Scholar

  120. K. Martin , and K. L. Wiebe . 2004. Coping mechanisms of Alpine and Arctic breeding birds: Extreme weather and limitations to reproductive resilience. Integrative and Comparative Biology 44:177–185. Google Scholar

  121. L. B. Martin II , Z. M. Weil , and R. J. Nelson . 2006. Refining approaches and diversifying directions in ecoimmunology. Integrative and Comparative Biology 46:1030–1039. Google Scholar

  122. T. E. Martin 1987. Food as a limit on breeding birds: A life-history perspective. Annual Review of Ecology and Systematics 18:453–487. Google Scholar

  123. T. E. Martin 1995. Avian life history evolution in relation to nest sites, nest predation, and food. Ecological Monographs 65:101–127. Google Scholar

  124. E. J. Masoro 2001. Dietary restriction: an experimental approach to the study of biology and aging. Pages 396–422 in Handbook of the Biology of Aging, 5th ed. ( E. J. Masoro and S. N. Austad, Ed.). Academic Press, New York. Google Scholar

  125. E. J. Masoro , and S. N. Austad . 2005. Handbook of the Biology of Aging, 6th ed. Academic Press, New York. Google Scholar

  126. K. D. Matson, A. A. Cohen, K. C. Klasing, R. E. Ricklefs, and A. Scheuerlein. 2006a. No simple answers for ecological immunology: Relationships among immune indices at the individual level break down at the species level in waterfowl. Proceedings of the Royal Society of London, Series B 273:815–822. Google Scholar

  127. K. D. Matson, B. I. Tieleman, and K. C. Klasing. 2006b. Capture stress and the bactericidal competence of blood and plasma in five species of tropical birds. Physiological and Biochemical Zoology 79:556–564. Google Scholar

  128. J. Meites 1988. Neuroendocrine biomarkers of aging in the rat. Experimental Gerontology 23:349–358. Google Scholar

  129. N. B. Metcalfe, and P. Monaghan. 2001. Compensation for a bad start: Grow now, pay later? Trends in Ecology and Evolution 16:254–260. Google Scholar

  130. N. B. Metcalfe , and P. Monaghan . 2003. Growth versus lifes-pan: Perspectives from evolutionary ecology. Experimental Gerontology 38:935–940. Google Scholar

  131. R. A. Miller 2001. Biomarkers of aging: Prediction of longevity by using age-sensitive T-cell subset determinations in a middle-aged, genetically heterogeneous mouse population. Journal of Gerontology 56A:B180–186. Google Scholar

  132. R. A. Miller , S. B. Berger, D. T. Burke, A. Galecki, G. G. Garcia , J. M. Harper , and A. A. Sadighi Akha . 2005. T cells in aging mice: Genetic, developmental, and biochemical analyses. Immunological Reviews 205:94–103. Google Scholar

  133. A. P. Møller 2007. Senescence in relation to latitude and migration in birds. Journal of Evolutionary Biology 20:750–757. Google Scholar

  134. A. P. Møller , F. de Lope , and N. Saino . 2005. Reproduction and migration in relation to senescence in the Barn Swallow Hirundo rustica: A study of avian ‘centenarians.’AGE 27:307–318. Google Scholar

  135. A. P. Møller , and T. Szép . 2002. Survival rate of adult Barn Swallows Hirundo rustica in relation to sexual selection and reproduction. Ecology 83:2220–2228. Google Scholar

  136. P. Monaghan , A. Charmantier , D. H. Nussey , and R. E. Rick-lefs . 2008. The evolutionary ecology of senescence. Functional Ecology 22:371–378. Google Scholar

  137. P. Monaghan, and M. F. Haussmann. 2006. Do telomere dynamics link lifestyle and lifespan? Trends in Ecology and Evolution 21:47–53. Google Scholar

  138. V. M. Monnier 1990. Nonenzymatic glycosylation, the Maillard reaction and the aging process. Journal of Gerontology A 45: B105–B111. Google Scholar

  139. V. M. Monnier , J. F. Fogarty , C. S. Monnier , and D. R. Sell . 1999. Glycation, glycoxidation, and other Maillard reaction products. Pages 657–681 in Methods in Aging Research ( B. P. Yu, Ed.). CRC, Boca Raton, Florida. Google Scholar

  140. F. L. Muller , M. S. Lustgarten, Y. Jang , A. Richardson , and H. Van Remmen . 2007. Trends in oxidative aging theories. Free Radical Biology and Medicine 43:477–503. Google Scholar

  141. I. Nanda , D. Schrama, W. Feichtinger, T. Haaf , M. Schartl , and M. Schmid . 2002. Distribution of telomeric (TTAGGG)n sequences in avian chromosomes. Chromosoma 111:215–227. Google Scholar

  142. I. Newton 1989. Lifetime Reproduction in Birds. Academic Press, London. Google Scholar

  143. I. Newton , and P. Rothery . 1997. Senescence and reproductive value in sparrowhawks. Ecology 78:1000–1008. Google Scholar

  144. I. Newton , and P. Rothery . 2002. Age-related trends in different aspects of the breeding performance of individual female Eurasian Sparrowhawks (Accipiter nisius). Auk 119: 735–748. Google Scholar

  145. I. C. T. Nisbet , V. Apanius , and M. S. Friar . 2002. Breeding performance of very old Common Terns. Journal of Field Ornithology 73:117–124. Google Scholar

  146. I. C. T. Nisbet , C. E. Finch, N. Thompson, E. Russek-Cohen , J. A. Proudman , and M. A. Ottinger . 1999. Endocrine patterns during aging in the Common Tern (Sterna hirundo). General and Comparative Endocrinology 114:279–286. Google Scholar

  147. K. Norris , and M. R. Evans . 2000. Ecological immunology: Life history trade-offs and immune defense in birds. Behavioral Ecology 11:19–26. Google Scholar

  148. D. H. Nussey , T. Coulson , M. Festa-Bianchet , and J.-M. Gail-lard . 2008. Measuring senescence in wild animal populations: Towards a longitudinal approach. Functional Ecology 22:393–406. Google Scholar

  149. C. E. Ogburn, S. N. Austad, D. J. Holmes, J. V. Kiklevich, K. Gollahon, P. S. Rabinovitch, and G. M. Martin. 1998. Cultured renal epithelial cells from birds and mice: Enhanced resistance of avian cells to oxidative stress and DNA damage. Journal of Gerontology A 53:B287–B292. Google Scholar

  150. C. E. Ogburn, K. Carlberg, M. A. Ottinger, D. J. Holmes G. M. Martin, and S. N. Austad. 2001. Exceptional cellular resistance to oxidative damage in long-lived birds requires active gene expression.Journal of Gerontology 56A:B468–B474. Google Scholar

  151. T. H. O'Hare , and M. E. Delany . 2005. Telomerase gene expression in the chicken: Telomerase RNA (TR) and reverse transcrip-tase (TERT) transcript profiles are tissue-specifc and correlate with telomerase activity. AGE 27:257–266. Google Scholar

  152. M. A. Ottinger 1991. Neuroendocrine and behavioral determinants of reproductive aging. Critical Reviews in Poultry Biology 3:131–142. Google Scholar

  153. M. A. Ottinger 2001. Quail and other short-lived birds. Experimental Gerontology 36:859–868. Google Scholar

  154. M. A. Ottinger, M. Mobarek, M. Abdelnabi, G. Roth, J. Proudman, and D. K. Ingram. 2005. Effects of calorie restriction on reproductive and adrenal systems in Japanese Quail: Are responses similar to mammals, particularly primates?Mechanisms of Ageing and Development 126:967–975. Google Scholar

  155. M. A. Ottinger , M. Abdelnabi, Q. Li, K. Chen, N. Thompson, N. Harada , C. Viglietti-Panzica , and G. C. Panzica . 2004. The Japanese Quail: A model for studying reproductive aging of hypothalamic systems. Experimental Gerontology 39:1679–1693. Google Scholar

  156. M. A. Ottinger , I. C. T. Nisbet , and C. E. Finch . 1995. Aging and reproduction: Comparative endocrinology of the Common Tern and Japanese Quail. American Zoologist 35:299–306. Google Scholar

  157. M. A. Ottinger , N. Thompson, Y. Fan, G. C. Panzica , C. Viglietti-Panzica , and Q. Li . 1997. Gonadotropin-releasing hormone (cGnRh-1) and neuropeptide systems refect endocrine and behavioral changes during reproductive aging. Pages 91–100 in Perspectives in Avian Endocrinology ( S. Harvery and R. J. Etches, Eds.). Arrowsmith, Bristol, United Kingdom. Google Scholar

  158. M. G. Palacios , J. E. Cunnick , D. W. Winkler , and C. M. Vleck . 2007. Immunosenescence in some but not all immune components in a free-living vertebrate, the Tree Swallow. Proceedings of the Royal Society of London, Series B 274:951–957. Google Scholar

  159. M. G. Palacios , and T. E. Martin . 2006. Incubation period and immune function: A comparative field study among coexisting birds. Oecologia 146:505–512. Google Scholar

  160. R. Pamplona , M. Portero-Otin, J. R. Requena, S. R. Thorpe , A. Herrero , and G. Barja . 1999. A low degree of fatty acid unsaturation leads to lower lipid peroxidation and lipoxidation-derived protein modification in heart mitochondria of the longevous pigeon than in the short-lived rat. Mechanisms of Ageing and Development 106:283–96. Google Scholar

  161. R. Pamplona , M. Portero-Otin, A. Sanz, V. Ayala , E. Vasileva , and G. Barja . 2005. Protein and lipid oxidative damage and complex I are lower in the brain of budgerigar and canaries than in mice. Relation to aging rate. AGE 27:267–280. Google Scholar

  162. L. Partridge , and N. H. Barton . 1993. Optimality, mutation and the evolution of ageing. Nature 362:305–311. Google Scholar

  163. L. Partridge, D. Gems, and D. J. Withers. 2005. Sex and death: What is the connection? Cell 120:461–472. Google Scholar

  164. A. Pauliny , R. H. Wagner, J. Augustin , T. Szép , and D. Blomqvist . 2006. Age-independent telomere length predicts fitness in two bird species. Molecular Ecology 15:1681–1687. Google Scholar

  165. R. Pearl 1928. The Rate of Living. Knopf, New York. Google Scholar

  166. S. F. Pearson, A. F. Camfield, and K. Martin. 2008. Streaked Horned Lark (Eremophila alpestris strigata) fecundity, survival, population growth and site fidelity: Research progress report. [Online.] Washington Department of Fish and Wildlife, Wildlife Science Division, Olympia. Available at  southsoundprairies.org/documents/STHLfecunditysurvivalpopgrowthandsitefdelity_2008.pdfGoogle Scholar

  167. R. Perez-Campo , M. López-Torres, S. Cadenas , C. Rojas , and G. Barja . 1998. The rate of free radical production as a determinant of the rate of aging: Evidence from the comparative approach. Journal of Comparative Physiology B 168:149–158. Google Scholar

  168. J. M. Pinkston , D. Garigan , M. Hansen , and C. Kenyon . 2006. Mutations that increase the life span of C. elegans inhibit tumor growth. Science 313:971–975. Google Scholar

  169. S. D. Pletcher 1999. Model fitting and hypothesis testing for age-specific mortality data. Journal of Evolutionary Biology 12:430–439. Google Scholar

  170. M. Portero-Otín , J. R. Requena, M. J. Bellmunt , V. Ayala , and R. Pamplona . 2004. Protein nonenzymatic modifications and proteasome activity in skeletal muscle from the short-lived rat and long-lived pigeon. Experimental Gerontology 39:1527–1535. Google Scholar

  171. N. K. Priest , B. Mackowiak , and D. E. L. Promislow . 2002. The role of parental age effects on the evolution of aging. Evolution 56:927–935. Google Scholar

  172. D. E. L. Promislow 1991. Senescence in natural populations of mammals: A comparative study. Evolution 45:1869–1887. Google Scholar

  173. D. E. L. Promislow 2004. Mate choice, sexual conflict, and evolution of senescence. Behavior Genetics 33:191–201. Google Scholar

  174. D. E. L. Promislow , K. M. Fedorka , and J. M. S. Burger . 2006. Evolutionary biology of aging: Future directions. Pages 217–242 in Handbook of the Biology of Aging ( E. J. Masoro and S. N. Austad, Ed.). Academic Press, New York. Google Scholar

  175. D. E. L. Promislow , R. D. Montgomerie , and T. E. Martin . 1992. Mortality costs of sexual dimorphism in birds. Proceedings of the Royal Society of London, Series B 250:143–150. Google Scholar

  176. B. H. Pugesek , and K. L. Diem . 1983. A multivariate study of the relationship of parental age to reproductive success in California gulls. Ecology 64:829–839. Google Scholar

  177. T. E. Reed, L. E. B. Kruuk, S. Wanless, M. Frederiksen, E. J. A. Cunningham, and M. P. Harris. 2008. Reproductive senescence in a long-lived seabird: Rates of decline in late-life performance are associated with varying costs of early reproduction. American Naturalist 171:E89–E101. Google Scholar

  178. D. N. Reznick 2005. The genetic basis of aging: An evolutionary biologist's perspective. Science of Aging Knowledge Environment 2005:pe7. Google Scholar

  179. D. N. Reznick , M. J. Bryant, D. Roff , C. K. Ghalambor , and D. E. Ghalambor . 2004. Effect of extrinsic mortality on the evolution of senescence in guppies. Nature 431:1095–1099. Google Scholar

  180. R. E. Ricklefs 1973. Fecundity, mortality, and avian demography. Pages 366–435 in Breeding Biology of Birds D. S. Farner, Ed.). National Academy of Science, Washington, D.C  Google Scholar

  181. R. E. Ricklefs 1990. Seabird life histories and the marine environment: Some speculations. Colonial Waterbirds 13:1–6. Google Scholar

  182. R. E. Ricklefs 1998. Evolutionary theories of aging: Confirmation of a fundamental prediction, with implications for the genetic basis and evolution of life span. American Naturalist 152:24–44. Google Scholar

  183. R. E. Ricklefs 2000a. Density dependence, evolutionary optimization, and the diversification of avian life histories. Condor 102: 9–22. Google Scholar

  184. R. E. Ricklefs 2000b. Intrinsic aging-related mortality in birds. Journal of Avian Biology 31:103–111. Google Scholar

  185. R. E. Ricklefs 2008. The evolution of senescence from a comparative perspective. Functional Ecology 22:379–392. Google Scholar

  186. R. E. Ricklefs , and C. D. Cadena . 2007. Lifespan is unrelated to investment in reproduction in populations of mammals and birds in captivity. Ecology Letters 10:867–872. Google Scholar

  187. R. E. Ricklefs, and C. E. Finch. 1995. Aging: A Natural History. Scientific American Library, New York. Google Scholar

  188. R. E. Ricklefs, and A. Scheuerlein. 2003. Life span in the light of avian life histories. Population and Development Review 29 (Supplement):71–98. Google Scholar

  189. R. E. Ricklefs , A. Scheuerlein , and A. Cohen . 2003. Age-related patterns of fertility in captive populations of birds and mammals. Experimental Gerontology 38:741–745. Google Scholar

  190. R. E. Ricklefs , and M. Wikelski . 2002. The physiology/life-history nexus. Trends in Ecology and Evolution 17:462–468. Google Scholar

  191. R. F. Rockwell , C. S. Findlay , and F. Cooke . 1985. Life history studies of the Lesser Snow Goose V.: Temporal effects on age-specifc fecundity. Condor 87:142–143. Google Scholar

  192. D. A. Roff . 2002 Life History Evolution. Sinauer Associates, Sunderland, Massachusetts. Google Scholar

  193. M. R. Rose 1991. Evolutionary Biology of Aging. Oxford University Press, New York. Google Scholar

  194. B.-E. Sæther 1988. Pattern of covariation between life-history traits of European birds. Nature 331:616–617. Google Scholar

  195. N. Saino , R. Ambrosini , R. Martinelli , and A. P. Møller . 2002. Mate fidelity, senescence in breeding performance and reproductive trade-offs in the Barn Swallow. Journal of Animal Ecology 71:309–319. Google Scholar

  196. N. Saino , R. P. Ferrari, M. Romano , D. Robelini , and A. P. Møller . 2003. Humoral immune response in relation to senescence, sex and sexual ornamentation in the Barn Swallow (Hirundo rustica). Journal of Evolutionary Biology 16:1127–1134. Google Scholar

  197. B. K. Sandercock, K. Martin, and S. J. Hannon. 2005a. Demographic consequences of age-structure in extreme environments: Population models for Arctic and Alpine Ptarmigan. Oecologia 146:13–24. Google Scholar

  198. B. K. Sandercock, K. Martin, and S. J. Hannon 2005b. Life history strategies in extreme environments: Comparative demography of Arctic and Alpine Ptarmigan. Ecology 86:2176–2186. Google Scholar

  199. J. W. Shay , and I. B. Roninson . 2004. Hallmarks of senescence in carcinogenesis and cancer therapy. Oncogene 23:2919–2933. Google Scholar

  200. J. W. Shay , and W. E. Wright . 2001. Aging. When do telomeres matter? Science 291:839–840. Google Scholar

  201. J. W. Shay , and W. E. Wright . 2005. Senescence and immortalization: Role of telomeres and telomerase. Carcinogenesis 26:867–874. Google Scholar

  202. W. E. Sonntag , C. S. Carter, Y. Ikeno, K. Ekenstedt, C. S. Carlson, R. F. Loeser, S. Chakrabarty, S. Lee, C. Bennett , R. Ingram , and others . 2005. Adult-onset growth hormone and insulin-like growth factor I deficiency reduces neoplastic disease, modifes age-related pathology, and increases life span. Endocrinology 146:2920–2932. Google Scholar

  203. J. R. Speakman 2005a. Body size, energy metabolism and lifespan. Journal of Experimental Biology 208:1717–1730. Google Scholar

  204. J. R. Speakman 2005b. Correlations between physiology and lifes-pan-Two widely ignored problems with comparative studies. Aging Cell 4:167–175. Google Scholar

  205. S. C. Stearns 1992. The Evolution of Life Histories. Oxford University Press, New York. Google Scholar

  206. S. C Stearns , R. M. Nesse , and D. Haig . 2008. Introducing evolutionary thinking to medicine. Pages 3–14 in Evolution in Health and Disease, 2nd ed. ( S. C. Stearns and J. C. Koella, Eds.). Oxford University Press, New York. Google Scholar

  207. S. E. Swanberg, and M. E. Delany. 2003. Dynamics of telomere erosion in transformed and non-transformed avian cells in vitro. Cytogenetics and Genome Research 102(1–4):318–25. Google Scholar

  208. S. E. Swanberg , and M. E. Delany . 2006. Telomeres in aging: Birds. Pages 339–349 in Handbook of Models for Human Aging ( P. M. Conn, Ed.). Academic Press, Burlington, Massachusetts. Google Scholar

  209. S. E. Swanberg , W. S. Payne, H. D. Hunt , J. B. Dodgson , and M. E. Delany . 2004. Telomerase activity and differential expression of telomerase genes and c-myc in chicken cells in vitro. Developmental Dynamics 231:14–21. Google Scholar

  210. M. Tatar , A. Bartke , and A. Antebi . 2003. The endocrine regulation of aging by insulin-like signals. Science 299:1346–1351. Google Scholar

  211. M. Tatar , D. E. L. Promislow , A. A. Khazaeli , and J. W. Curt-singer . 1996. Age-specifc patterns of genetic variance in Drosophila melanogaster. II. Fecundity and its genetic covariance with age-specifc mortality. Genetics 143:849–858. Google Scholar

  212. H. A. Taylor , and M. E. Delany . 2000. Ontogeny of telomerase in chicken: Impact of downregulation on pre- and postnatal telo-mere length in vivo. Development, Growth, and Diferentiation 42:613–621. Google Scholar

  213. J. L. Tella, A. Scheuerlein, and R. E. Ricklefs. 2002. Is cell-mediated immunity related to the evolution of life-history strategies in birds? Proceedings of the Royal Society of London, Series B 269:1059–1066. Google Scholar

  214. R. Torres , and A. Velando . 2007. Male reproductive senescence: The price of immune-induced oxidative damage on sexual attractiveness in the Blue-footed Booby. Journal of Animal Ecology 76:1161–1168. Google Scholar

  215. H. Van Remmen , and A. Richardson . 2001. Oxidative damage to mitochondria and aging. Experimental Gerontology 36:957–968. Google Scholar

  216. A. Velando , H. Drummond , and R. Torres . 2006. Senescent birds redouble reproductive effort when ill: Confrmation of the terminal investment hypothesis. Proceedings of the Royal Society of London, Series B 273:1443–1448. Google Scholar

  217. R. N. Venkatesan , and C. Price . 1998. Telomerase expression in chickens: Constitutive activity in somatic tissues and down-regulation in culture. Proceedings of the National Academy of Sciences USA 95:14763–14768. Google Scholar

  218. C. M. Vleck , M. F. Haussmann , and D. Vleck . 2003. The natural history of telomeres: Tools for aging animals and exploring the aging process. Experimental Gerontology 38:791–795. Google Scholar

  219. F. S. vom Saal , C. E. Finch , and J. F. Nelson . 1994. Natural history and mechanisms of reproductive aging in humans, laboratory rodents, and other selected vertebrates. Pages 1213–1314 in The Physiology of Reproduction ( E. Knobil and J. D. Neill, Eds.). Raven Press, New York. Google Scholar

  220. E. Wang , C. Autexier , and E. Chen . 2001. Apoptosis and aging. Pages 246–266 in Handbook of the Biology of Aging ( E. J. Masoro and S. N. Austad, Eds.). Academic Press, San Diego, California. Google Scholar

  221. W. F. Ward, W. Qi, H. Van Remmen, W. E. Zackert, L. J. Roberts II, and A. Richardson. 2005. Efects of age and caloric restriction on lipid peroxidation: Measurement of oxidative stress by F2-isoprostane levels. Journal of Gerontology 60A:847–851. Google Scholar

  222. R. Weindruch , and R. L. Walford . 1988. The Retardation of Aging and Disease by Dietary Restriction. Charles C. Tomas, Springfield, Illinois. Google Scholar

  223. K. L. Wiebe , and K. Martin . 1998. Age-specific patterns of reproduction in White-tailed and Willow ptarmigan Lagopus leucurus and L.lagopus. Ibis 140:14–24. Google Scholar

  224. G. C. Williams 1957. Pleiotropy, natural selection, and the evolution of senescence. Evolution 11:398–411. Google Scholar

  225. S. D. Wilson 2008. Influence of environmental variation on habitat selection, life history strategies and population dynamics of sympatric ptarmigan in the southern Yukon Territory. Ph.D.dissertation, University of British Columbia, Vancouver. Google Scholar

  226. S. Wilson , D. R. Norris , A. G. Wilson , and P. Arcese . 2007. Breeding experience and population density affect the ability of a songbird to respond to future climate variation. Proceedings of the Royal Society of London, Series B 274:2539–2545. Google Scholar

  227. W. E. Wright, and J. W. Shay. 2005. Telomere biology in aging and cancer. Journal of the American Geriatrics Society 53:S292–S294. Google Scholar

  228. B. P. Yu , and R. Yang . 1996. Critical evaluation of the free radical theory of aging: A proposal for the oxidative stress hypothesis. Annals of the New York Academy of Science 786:1–11. Google Scholar

© 2009 by The American Ornithologists' Union. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Rights and Permissions website, http://www.ucpressjournals.com/reprintInfo.asp
Donna Holmes and Kathy Martin "A Bird's-Eye View of Aging: What's in it for Ornithologists?," The Auk 126(1), (1 January 2009). https://doi.org/10.1525/auk.2009.1109
Received: 7 April 2008; Accepted: 1 October 2008; Published: 1 January 2009
JOURNAL ARTICLE
23 PAGES


SHARE
ARTICLE IMPACT
Back to Top