Do gray wolves (Canis lupus) support pack mates during aggressive inter-pack interactions?

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Do gray wolves (Canis lupus) support pack mates during aggressive inter-pack interactions? Cassidy,KA
Title Do gray wolves (Canis lupus) support pack mates during aggressive inter-pack interactions?
Authors KA Cassidy,RT McIntyre
Journal Animal cognition
Issue
Issn 1435-9456
Isbn
Doi 10.1007/s10071-016-0994-1
PMID 27193460
Volume
Pages HASH(0x2dbd798)
Keywords
Website [[Website::[1]]]
Publication Year May 2016

Abstract


For group-living mammals, social coordination increases success in everything from hunting and foraging (Crofoot and Wrangham in Mind the Gap, Springer, Berlin, 2010; Bailey et al. in Behav Ecol Sociobiol 67:1-17, 2013) to agonism (Mosser and Packer in Anim Behav 78:359-370, 2009; Wilson et al. in Anim Behav 83:277-291, 2012; Cassidy et al. in Behav Ecol 26:1352-1360, 2015). Cooperation is found in many species and, due to its low costs, likely is a determining factor in the evolution of living in social groups (Smith in Anim Behav 92:291-304, 2014). Beyond cooperation, many mammals perform costly behaviors for the benefit of group mates (e.g., parental care, food sharing, grooming). Altruism is considered the most extreme case of cooperation where the altruist increases the fitness of the recipient while decreasing its own fitness (Bell in Selection: the mechanism of evolution. Oxford University Press, Oxford 2008). Gray wolf life history requires intra-pack familiarity, communication, and cooperation in order to succeed in hunting (MacNulty et al. in Behav Ecol doi: 10.1093/beheco/arr159 2011) and protecting group resources (Stahler et al. in J Anim Ecol 82: 222-234, 2013; Cassidy et al. in Behav Ecol 26:1352-1360, 2015). Here, we report 121 territorial aggressive inter-pack interactions in Yellowstone National Park between 1 April 1995 and 1 April 2011 (>5300 days of observation) and examine each interaction where one wolf interferes when its pack mate is being attacked by a rival group. This behavior was recorded six times (17.6 % of interactions involving an attack) and often occurred between dyads of closely related individuals. We discuss this behavior as it relates to the evolution of cooperation, sociality, and altruism.


Acronyms

Acronyms
P. verreauxi => primate species where birth sex ratios are typically nearly equal (see Fedigan and Zohar 1997), or male biased, as in the closely related Verreaux’s sifaka
RNP => Ranomafana National Park

IntroductIon

  • skewed adult sex ratios mammals prediction by Fisher (1930) sex ratios.
  • skewed adult sex ratios result mortality between males and females (Clutton-Brock et al. 1977, 1982), females living longer than males.
  • studies array species support theory that male survival lower than female survival (Clutton-Brock et al. 1982; Jorgenson al. 1997; Modaferri Becker 1997; Christe et al. 2006; Bronikowski et al. 2011).
  • difference cost selected traits

  • propensity risky behavior enhances male reproductive success (Promislow 1992; Moore Wilson 2002; Setchell et al. 2005; Kraus et al. 2008).
  • Variation mortality and reproduction between sexes , sexual selection, life-history consequences (Gaillard al. 1989; Magnhagen 1991; Andersson 1994).
  • As a result, understanding sex differences life-history patterns theme disciplines (Bonduriansky et al. 2008).

  • conflict between males and females, costs effort, proposed cause of sex-specific life span mortality patterns (Arnqvist Rowe 2005; Bonduriansky et al. 2008).
  • Increased male mortality predation (Owen-Smith 1993), male-biased dispersal, movement patterns (Fedigan Zohar 1997; Kraus et al. 2008), increased requirements (Clutton-Brock et al. 1982, 1985; Bribiescas 2006), male--male competition

  • (Clutton-Brock et al. 1982), effects testosterone (Folstad Karter 1992; Roberts al. 2004) all suggested causes sex differences in survival and life span (Bonduriansky et al. 2008; Bronikowski et al. 2011).
  • without examining mortality occurs, understanding factors determining sex-specific differences limited.
  • example, faster growth rates of males (compared with females) lead stress more during juvenility (Clutton-Brock et al. 1985; Fedigan and Zohar 1997), resulting in higher juvenile mortality.
  • ``fragile male hypothesis addresses trajectories males and females predicts higher rates of male mortality during the juvenile period of development, periods resource scarcity (van Schaik and de Visser 1990; Janson van Schaik 1993).

  • hypothesis, ``high risk, high gain, predicts higher male mortality rates during adolescence and adulthood due to risky behavior (e.g., male--male competition or dispersal; Trivers 1985; Rajpurohit and Sommer 1991).
  • support this hypothesis primate species (yellow baboons, Papio cynocephalus Alberts and Altmann 1995; monkeys, Chlorocebus aethiops Fairbanks al. 2004; mouse lemurs, Microcebus murinus: Kraus et al. 2008).
  • higher average male mortality not be age , increased risk mortality during the breeding season (Hoogland al. 2006; Kraus et al. 2008) conditions (Coulson al. 2001; Bonenfant al. 2002; Toïgo Gaillard 2003).
  • environment , sex differences costs cause females reproduction years and follow bet hedging strategy (Stearns 1976, 1992; Wright 1995; Gaillard Yoccoz 2003).
  • strategy leads live slow, die old hypothesis (Bonduriansky et al. 2008), disparities between male and female growth, maturation, life span to females slowing growth development compensate unpredictability.
  • results in bloomer males (Richard et al. 2002) longer female life spans (Charnov Berrigan 1993).
  • This hypothesis suggest that mortality all ages expected higher males than in females.

  • article, investigate life-history strategies male and female Milne-Edwards sifaka (Propithecus edwardsi).
  • Understanding P. edwardsi life history evaluating sex differences in life span can add theory sex-biased traits, this species lacks characteristics proposed influence differences in male and female life spans in other species.
  • example, growth rates (Clutton-Brock et al. 1985; Fedigan and Zohar 1997) dimorphism (Promislow 1992) predicted drive mortality differences among male and female juveniles, adult life span.
  • traits not P. edwardsi (King et al. 2011).
  • P. females not follow live slow, strategy, living area resource variability (King et al. 2011) high female infant and juvenile mortality (Pochron et al. 2004).
  • Sex differences predation rates species may explain differences in male and female survival life stages (Christe et al. 2006), there is no evidence sex-biased predation P. edwardsi (Irwin al. 2009).
  • male-biased dispersal known result in higher male mortality (e.g., yellow baboons Alberts and Altmann 1995), both male and female P. edwardsi

  • disperse, no significant differences in the frequency or distance dispersal detected (Morelli et al. 2009).
  • male-biased aggression competition mating opportunities differences in life span (Clutton-Brock 2007); , P. edwardsi , both males and females both sexes (Wright 1995, 1999; Wright P, unpublished data).
  • testosterone levels do not differ between sexes (Tecot SR, Zohdy S, Jernvall J, Wright PC, preparation).

  • examine age-based sex ratios and mortality determine sex-biased survival rates and life spans P. edwardsi.
  • 15 years data collected same population as this study, Pochron et al. (2004) patterns female mortality fertility and implications group sex ratios.
  • build this work by analyzing 9 years data, investigating both males and females, studying population-wide sex ratios.
  • ``fragile male and ``high risk, high gain hypotheses predict sex-based differences mortality at different life stages, resulting in differences sex ratios and male and female life spans.
  • Given lack traits associated male and female mortality rates sex-biased longev-ity primates and other mammals, we expected that males and females similar sex ratios and life spans.
  • predicted 1) similarities growth rates and body sizes, male and female juvenile mortality rates 2) both sexes disperse competition and aggression, adult mortality similar, resulting in similar life spans.
  • Given similarities dispersal frequency distance reported this species (Morelli et al. 2009), predicted no difference in the timing dispersal lead mortality rates.
  • compare findings sex differences in survival and group transfer or dispersal other species discuss factors driving patterns.

Methods

Study site

  • Data derived long-term study (1986--pres-ent) P. Ranomafana National Park (RNP) Madagascar (lat 21°16ʹS 47°20ʹE; Wright 1992).
  • RNP consists 43 500 ha rainforest, ranges 559 1396 m elevation, average temperature 21 °C, receives average 3090 mm rain year (Tecot 2008; Wright et al. 2008).
  • climate RNP varies higher rainfall temperature months December--March than remainder year ( 1993; Hemingway 1996; Wright 2006).
  • pattern, variation distributions rain fruit unpredict-able from year to year (King et al. 2011).
  • Individuals our study members 4 groups in the area RNP known Talatakely.
  • Talatakely study site altitude 900--1100 m researchers system .

Study subjects

  • P. edwardsi both males and females adult body mass averaging 5.7 kg (King et al. 2011).
  • Social groups range size 2 9 individuals include 1 2 breeding females (Pochron and Wright 2003a; Morelli et al. 2009).
  • Reproduction highly most births occurred

  • May July (with the exception of 1 in 54 births, occurred September; Wright P, unpublished data).
  • Dispersal by both sexes September, individuals disperse times their lifetime (Morelli et al. 2009).
  • Pochron et al. (2004) history research habituation study groups, aspects demography published (Wright 1995; Pochron Wright 2003a; Pochron et al. 2004).
  • Male and female growth rates and durations not differ (King et al. 2011), age categories both sexes defined follows infants <1 year, juveniles 1--3.5 years, adults >3.5 years (Morelli et al. 2009).

  • Data this study represent 80 group-years observations (24 years Group I Group , 19 years Group III, 13 years Group IV).
  • Study animals (n = 41 females, 34 males) presence humans; group followed minimum 5 days month, time follows continued dawn dusk.
  • All births, deaths, immigrations, emigrations recorded ad libitum average 1 week ( Pochron et al. 2004 details).
  • Individuals by collar-tag combinations ( Wright 1995 capture marking procedures this population).

  • date of birth most individuals start this study known 2 weeks (n = 30 females, 22 males), ages some individuals that entered study groups groups some before 1986 estimated on the basis tooth wear during captures (n = 8 females, 8 males; King et al. 2005; Wright et al. 2008).
  • ages remaining individuals (dates of birth not molds not taken) estimated (n = 3 females, 46 males) by author Patricia Wright, facilitated by breeding differences body mass 1-, 2-, 3-, 4-year-old individuals.
  • ages 2 older individuals (female, 7 years and male, 6 years) estimated during captures on the basis body mass, tooth tartar, tooth sharpness.

  • All work approved by Stony Brook University Institutional Animal Care Use Committee.
  • All procedures conformed American Society Primatologists Principles Treatment Non-Human Primates laws Republic Madagascar.

Data and analyses

  • analyzed sex ratios by calculating proportion females population as course study (1986--2009) age, .
  • survival analyses, examined pattern age-specific exits from social groups evaluated the effect of sex on cumulative probability exiting.
  • Survival analyses framework determining time takes event occur; events exits from social group, defined 1) confirmed death or 2) confirmed dispersal ( out of the study population).
  • Dispersals defined any transition group and not dispersal animal group.
  • best efforts, 10 events could not classified either dispersal out of the study area death, exit from the study area.
  • Instead of removing observations individuals, bias, exclusion not events ( Garrott 1990), provide 2 analyses dispersals and survival 1) assuming unknowns are all deaths

  • 2) assuming unknowns are all dispersals.
  • Either assumption , expect cumulative distribution between 2.
  • restrict interpretation results effect of sex only analyses .
  • Survival data included 26 observations males and 38 observations females study area.
  • Individuals that dispersed study area not followed until death.
  • assumed dispersing , , into the study area processes rather than , observed dispersals random variable, greater population.
  • males disperse 19 times and females disperse 15 times, total .
  • Cox proportional hazards regression model (Cox 1972) implemented in the R package eha ( 2012) estimate cumulative distributions exits.
  • comparing 2 models, (no covariates) sex (included sex effect on survival cumulative distribution), estimating 1) time until group dispersal and 2) time until death.
  • considered t, time until event, random variable our model event defined ( model including sex covariate)

  • sex = 0 β 1 sex .
  • cox model allows baseline hazard function (h 0 ) , model incorporate covariate effects on survival distribution; , model .
  • Depending individual, observations individual life, left individuals transfer into the study population, animals transfer out of the study population.
  • Parameter estimation maximum likelihood more data (Broström 2002), model parsimony evaluated Akaike information criterion (AIC c ) second-order bias correction sample size (Burnham Anderson 2002).
  • compared models evaluate the effect of sex on dispersals and survival by calculating model probabilities, Pr(model j data), known Akaike weight (Burnham al. 2011).
  • proportional hazards assumption our model tested analysis residuals (Grambsch Therneau 1994) implemented in the R package survival ( 2012); α = 0.05 determine significance.

results

Sex ratios

  • Age-specific population sex ratios female biased birth 2--2.9 years, point became equal (Appendix S1 Figure 1a).
  • After 2.9 years of age, sex ratios became male biased remained until age 17.
  • At age 17--17.9, number females equal greater than number males.
  • majority age categories, sex ratio of this population male biased, more females than males.
  • mean sex ratio of this population flux from year to year not male or female biased (Appendix S2 Figure 1b).

Survival

  • Neither survival analysis rejected proportional hazards assumption (P > 0.05; Table 1).
  • unknowns assumed , AIC c values 2 models 319.10 ( ) 317.66 (sex).
  • Akaike weight 0.67 (sex) 0.32 ( ), such that the model with the effect of sex 2.06 times the more parsimonious model, given our data.
  • Under the sex model,

  • assumption regarding unknowns; more males survive ages 2--18.
  • between ages 9 18, male survival probability declines quickly, decline females is more .
  • After age 18, probability of female not male mortality approaches zero.
  • oldest male this study 19 years  ; there is no evidence our study area males living age.
  • contrast, females reach 19 years of age live 30s.

  • regardless of the assumption unknowns, there is moderate support for a difference in cumulative probabilities of age-specific survival males and females; effect of sex was in the same direction (Table 1).
  • Both sexes experience high mortality during the first 2 years life (Figure 2).
  • After 2 years, male and female survival probabilities ,

  • found proportional hazards assumption not rejected either dispersal analyses (P > 0.05).
  • When assuming the unknowns had all , AIC c values dispersal analyses 371.52 ( ) 368.68 (sex).
  • Akaike weight was 0.81 (sex) 0.19 ( ), such that the model with the effect of sex 4.15 times the more parsimonious model, given the data.
  • Given the sex model, median predicted ages dispersal of males and females 7.12 (95% CI, 5.01--8.00) 4.58 (95% CI, 4.25--6.00), .
  • When assuming the unknowns had all dispersed, AICc values 531.47 ( ) 528.82 (sex).
  • Akaike weight 0.79 (sex) 0.21 ( ); thus the model with the effect of sex 3.77 times the more parsimonious model, given the data.
  • Given the sex model, median predicted ages dispersal of males and females 7.81 (95% CI, 6.62--8.91) 4.81 (95% CI, 4.62--7.11), .

  • There was moderate support for a difference in cumulative probabilities of age-specific dispersal both males and females, regardless of the assumptions unknowns, effect of sex was in the same direction (Table 1).
  • Neither males nor females disperse before 3--4 years of age (Figure 3).
  • Males have higher probability of dispersing, between ages 6 10.
  • highest probability of female dispersal occurs between ages 4 6 declines  ; by age 10, females have less than 0.1 probability of dispersing.
  • unknown female exit from the population 27 years

  • median predicted life span of males and females 1.1 (95% CI, 0.50--3.25) 2.8 (95% CI, 0.50--12.2), .
  • When assuming the unknowns all dispersals, AICc values 297.39 ( ) 294.53 (sex).
  • Akaike weight was 0.81 (sex) 0.19 ( ); thus the model with the effect of sex 4.16 times the more parsimonious model, given our data.
  • Under the sex model, median predicted life spans of males and females 2.17 (95% CI, 1.10--4.21) 3.1 (95% CI, 1.85--4.67), .

  • higher in males) (Tecot al., preparation), higher female mortality may related to female dominance this species (Pochron and Wright 2003b).
  • predicted by ``risky male hypothesis, 13--18 years of age, male survival probability declined quickly.
  • After age 18, male mortality exceeded females, as a consequence dispersal by males at older ages.
  • Our data reveal that variability timing and causes of sex-specific mortality lead complex patterns asymmetries survivorship at different life stages.

Sex ratios

  • Sexual selection theory predicts competition males reproductive opportunities results in higher mortality rates in males course their lifetime (Trivers 1972).
  • polygynous species mammals, including primates, support accelerated mortality in males (Clutton-Brock and Isvaran 2007; Bronikowski et al. 2011).
  • predicted, ``fragile male and ``live slow, die old hypotheses, males and females experienced similar probabilities infant survival.
  • After age 2 (during juvenility), males, not females, more survive 18.
  • growth rates and durations not differ this species (Morelli et al. 2009; King et al. 2011), reject development and maturation significant factors influencing longevity this species.
  • Males live faster lives by virtue younger.
  • pattern differs male

  • we expected that male and female survivorship equal during adulthood, males had higher survival than females during adulthood.
  • both sexes , testosterone levels do not differ among males and females (

  • Our data show birth sex ratios females, contrast other primate species where birth sex ratios are typically nearly equal (see Fedigan and Zohar 1997), or male biased, as in the closely related Verreaux's sifaka (P. ) (Richard et al. 1991, 2002).
  • infant mortality high both sexes, lemurs (Wright 1999; Richard et al. 2002), sex ratios became male biased dispersal, juvenile mortality was greater for females than males.
  • Given greater probability of female mortality during the juvenile period of development, our data ``fragile male hypothesis supported other species (Clutton-Brock et al. 1982; van Schaik and de Visser 1990; Owen-Smith 1993; Fedigan and Zohar 1997; Loison al. 1999; Alberts and Altmann 2003; Setchell et al. 2005; van Schaik and de Visser 1990 review).
  • birth

  • age, females stop dispersing age 21 (last confirmed dispersal) continue probability of dispersing .

dIscussIon

  • sex ratios differ P. P. , patterns sex-based infant and juvenile mortality suggest that males neither spe-cies .
  • contrary, females sex infancy.
  • females have greater mortality rate infancy development and maturation, greater female longevity

Patterns of dispersal

  • research on this species reported that male and female average dispersal frequency or distance not differ (Morelli et al. 2009), predicted similar patterns rate and timing of dispersal.
  • Instead, our data reveal that differences in the timing rates dispersal between males and females.
  • males continued to disperse until their deaths, whereas females stopped dispersing after 11 years of age.
  • Only 1 female after 11, at age 21 ( 1 unknown disappearance at age 27).
  • cause dispersal remains unknown.
  • dispersal by males their lifetime mortality ``high risk, high gain hypothesis, predicting higher mortality rates in males during adolescence and adulthood due to risky behavior (Trivers 1985; Rajpurohit and Sommer 1991; Fedigan and Zohar 1997).
  • mortality risk greater dispersers relative conspecifics (e.g., Isbell et al. 1993; Alberts and Altmann 1995), males continue risk later in life compared with females.
  • suggest that dispersal between groups affects male longevity by removing individuals from the population not emigrants, by reducing survival individuals risks during dispersal.

  • Research on blackbirds (Greenwood Harvey 1976) differences in life span can exist between dispersing individuals.
  • sources risk emigrants include increased predation risk (Isbell et al. 1990; Hass Valenzuela 2002), decreased knowledge resources (Waser Jones 1983), costs associated with loss group-mates (Isbell van Vuren 1996).
  • Our study suggests that dispersal carries risk individuals.
  • P. edwardsi groups remain home ranges, emigration consists movement area, by individual (Wright 1995; Wright P, unpublished data).
  • Male survival curves incorporating types exits (mortality and dispersal; data not shown) were age , exits occurring near rate life, dispersal patterns observed.
  • contrast, female survival curves were age , showing declining rate exiting the population ( mortality and dispersal) age, result observed dispersal behavior.
  • results suggest that dispersal higher mortality, longer female life span this species lack females transferring groups at older ages.

  • this species, males continue to disperse later in life
  • lacking characteristics polygynous species, P. , intrasexual competition explain differences in male and female dispersal behavior.
  • mating system, rank-related reproductive success, resulting in significant (e.g., Setchell et al. 2005).
  • effects intense intrasexual competition limit

  • male breeding success.
  • males weaker selection live lives relative to females (Clutton-Brock and Isvaran 2007; Bronikowski et al. 2011).
  • P. edwardsi, competition among males dispersal and mating seasons (Wright P, unpublished data).
  • Similar male ring-tailed lemurs (Lemur catta), disperse mating season (Parga Lessnau 2008), dispersal by both male and female P. edwardsi function (Morelli et al. 2009).
  • 4 months dispersal season, frequency marking increases (Pochron, Morelli, Scirbona, al. 2005; Pochron, Morelli, Terranova, al. 2005), androgens peak (Tecot al. 2010; Tecot S, preparation), testes increase size, reaching maximum during the mating season (Pochron and Wright 2002; Pochron et al. 2002; Morelli 2008).

  • Male-directed aggression by both males and females during the mating dispersal seasons , leading lacerations, castration, death (Wright 1995, 1999; Wright P, unpublished data), similar during the mating season other species (e.g., P. 1966; Lawler al. 2005).
  • fights occur between residents immigrants (Morelli 2008), groups seldom contain more than 1 adult male periods of time (Morelli et al. 2009).
  • note both males and females disperse, competition occurs females males (Morelli et al. 2009), both sexes benefit by dispersal behavior.
  • instance, events group takeovers by dispersing individual result in increased reproductive opportunities invader, whether male or female (Morelli et al. 2009).

  • information behavior this species, things remain .
  • instance, not know whether males or females more wounds participate bouts.
  • addition, not know individuals more than individuals bouts.
  • data help determine death as a result dispersal-related aggression sex-biased mortality patterns .
  • Fedigan and Zohar (1997) determined mortality in male macaques (Macaca fuscata) higher birth/emigration season than mating season.
  • emigration P. edwardsi , analysis help test hypothesis that dispersal higher rates of male mortality.
  • that dispersal impose challenges sifaka.
  • chances engaging intense intrasexual competition costs associated with competition may cause damage males (Clutton-Brock and Isvaran 2007), suggesting immigration riskier more occurs.
  • research on soil ( berlesei) model system found greater capita mortality adults younger adults during dispersal (Bowler Benton 2009), suggesting dispersing at older ages carries greater costs.
  • As individuals age, ability perform activities (e.g., reduced acuity locomotion), increasing difficulty detecting escaping predators, locating resources, groups.
  • evidence suggest locomotion P. edwardsi compromised as individuals age old females more time feeding less time than females, terrain (Achilles E, Godfrey L, King SJ, Tecot SR, Wright PC, preparation), bone volume head decrease females (Chan A, Chan NM, Wright PC, Boyer D, Gosselin-Ildari

  • Tecot SR, unpublished data).
  • If males undergo similar age-related declines females, costs dispersal may exacerbated older males continue disperse.
  • If males, like females, costs, continue dispersing
  • answer sex ratios.
  • Sex ratios and availability mates group known influence individual disperses (Morelli et al. 2009).
  • Aggression directed most sex group, sex individuals driven out of the group (Wright 1995; Wright P, unpublished data).
  • males females ages 2.9 17, males may driven out of the group more than females lives.

Kin, dispersal, and mortality

  • This study broader implications understanding dynamics.
  • predicted relatives show kin bias, participating more behavior one (Hamilton 1963), resulting in direct fitness benefits (Alouatta seniculus Pope 1990, 2000; M. fuscata Pavelka al. 2002; Cercopithecus sabaeus Fairbanks 1988).
  • lack sex-biased dispersal, bias dispersal distance one sex more relatives non-natal groups than other (Waser al. 1994; Kappeler 2008).
  • instance, Coquerel dwarf lemur (Mirza coquereli), females have shorter dispersal distances than males, resulting in population structure (Kappeler al. 2002), creating opportunity sex-specific kin bias.
  • lack dispersal bias this species (Morelli et al. 2009), same-sex pairs living together biased, female pairs living together longer than male pairs (Morelli et al. 2009; Wright P, unpublished data).
  • sample sizes , sex differences group tenure nota-ble female adult relatives lived 5--10 years, male adults (relatives nonrelatives) lived 1--2 years average ( males group; Wright P, unpublished data).
  • slower rate of female dispersal after 5--8 years of age report this study females are more live other females longer periods of time suggests opportunities long-term relationships are greater for females than males ( noted low fertility and high infant and juvenile mortality reduce opportunities kin groups in the species whole; Pochron et al. 2004).
  • As a consequence, males may experience stress more than females.
  • primates and humans, individuals integrated social relationships greater likelihood surviving than social relationships (Holt-Lunstad al. 2010; Silk al. 2010), demonstrating influence relationships mortality and life span.

conclusIons

  • population, female-biased sex ratios high mortality resulted in male-biased sex ratios maturity 18 years of age, pattern other lemur species (Kappeler 2000; Ostner Kappeler 2004), including P. verreauxi.
  • male and female mortality rates more similar other by age 5 years, our data reveal that females dispersed earlier than males.
  • higher female infant mortality, resulted in higher rate of females leaving population, either dispersal death.
  • Exit

  • rates between males and females converged at age 10, males and females exit the population, either death or dispersal until age 14.
  • After 14 years of age, males continued to disperse from the population , whereas females remained until their deaths.
  • continued dispersal by males explanation female-biased sex ratios at older ages , , longer female life spans.

  • results this study address importance different life-history strategies influence longevity.
  • found support ``risky male hypothesis, risky behavior occurs at older ages males than in females, resulting in shorter male life spans.
  • results shifts mortality and dispersal rates produced sex-ratio patterns observed any given point time and elucidate causes female-biased life span in other lemur-oidea (P. Richard et al. 2002; L. catta Gould al. 2003; M. murinus: Kraus et al. 2008).
  • studies needed investigate cause death help determine why females higher mortality, males continue to disperse later in life, factor(s) interacting contribute patterns observed this population.

suppleMentary MaterIal


FundIng

  • This work supported by donors National Science Foundation USA (BCS 721233, BCS 0333078), Earthwatch Institute, Stony Brook University Study Program, Wenner-Gren Foundation, J. William Fulbright Program, University Helsinki Center Excellence.

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