Journal of Animal Ecology 82:222-234

Home , Adaptive value

Journal of Animal Ecology 2013, 82, 222–234 doi: 10.1111/j.1365-2656.2012.02039.x The adaptive value of morphological, behavioural and life-history traits in reproductive female wolves

Daniel R. Stahler1*, Daniel R. MacNulty2, Robert K. Wayne3, Bridgett vonHoldt3 and Douglas W. Smith1

1Yellowstone Wolf Project, Yellowstone Center for Resources, Yellowstone National Park, WY, 82190, USA; 2Department of Wildland Resources, Utah State University, Logan, UT, 84322, USA; and 3Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095, USA

Summary 1. Reproduction in social organisms is shaped by numerous morphological, behavioural and life-history traits such as body size, cooperative breeding and age of reproduction, respectively. Little is known, however, about the relative influence of these different types of traits on reproduction, particularly in the context of environmental conditions that determine their adaptive value. 2. Here, we use 14 years of data from a long-term study of wolves (Canis lupus) in Yellow- stone National Park, USA, to evaluate the relative effects of different traits and ecological factors on the reproductive performance (litter size and survival) of breeding females. 3. At the individual level, litter size and survival improved with body mass and declined with age (c. 4–5 years). Grey-coloured females had more surviving pups than black females, which likely contributed to the maintenance of coat colour polymorphism in this system. 4. The effect of pack size on reproductive performance was nonlinear as litter size peaked at eight wolves and then declined, and litter survival increased rapidly up to three wolves, beyond which it increased more gradually. 5. At the population level, litter size and survival decreased with increasing wolf population size and canine distemper outbreaks. 6. The relative influence of these different-level factors on wolf reproductive success followed individual > group > population. Body mass was the primary determinant of litter size, followed by pack size and population size. Body mass was also the main driver of litter survival, followed by pack size and disease. Reproductive gains because of larger body size and cooperative breeding may mitigate reproductive losses because of negative density dependence and disease. 7. These findings highlight the adaptive value of large body size and sociality in promoting individual fitness in stochastic and competitive environments. Key-words: body mass, canine distemper virus, coat colour, cooperative breeding, density dependence, disease, group size, large carnivores, senescence, sociality

tions (e.g. competition and disease). Indeed, the extent to Introduction which a trait mitigates the impact of environmental stress Knowledge about the adaptive value of traits is funda- on fitness is perhaps the most robust gauge of its adaptive mental to understanding the biology of natural systems value. Studies of reproductive success highlight several and anticipating species response to environmental potentially adaptive traits including body size (Clutton- change. A key challenge lies in understanding a trait’s Brock 1988; Hamel et al. 2008), genetic heterozygosity contribution to fitness relative to environmental condi- (Slate et al. 2000; Zedrosser et al. 2007), cooperative breeding (Cockburn 1998; Clutton-Brock et al. 2001; Silk 2007) and age-specific performance (Clutton-Brock 1988; *Corresponding author. E-mail: [email protected] Rebke et al. 2010). Little is known, however, about the

© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society Reproductive performance in female wolves 223 relative importance of these traits for reproductive suc- dominance (Russell et al. 2003) with reproductive advan- cess, particularly in the context of environmental condi- tages; (iii) a positive correlation between multilocus het- tions that determine whether a trait is favoured or erozygosity estimates and reproductive success given penalized by natural selection. enhanced success demonstrated in outbred individuals of Environmental conditions that impact reproduction some species (Amos et al. 2001); (iv) differential reproduc- include disease prevalence, resource availability and popu- tive performance between black and grey-coloured females lation density. Disease is a top-down influence that reduces (determined by the K locus, CBD103,ab-defensin gene reproduction directly via offspring mortality (Kissui & that has two alleles) because recent studies have suggested Packer 2004; Almberg et al. 2009) and/or indirectly fitness differences among coat colours in North American through complex gene–environment interactions that gen- wolves (Musiani et al. 2007; Anderson et al. 2009; erate fitness trade-offs between reproduction and survival Coulson et al. 2011); and (v) a positive correlation (Graham et al. 2010). Resource abundance and population between a female’s pack size and her reproductive success density impact reproduction through bottom-up, density- because of the role of auxiliary adults as helpers. With dependent processes (e.g. intraguild competition; Creel, respect to ecological conditions, we expected reproductive Spong & Creel 2001; Kissui & Packer 2004; Watts & success to decline (i) with increasing population size Holekamp 2008, 2009). For cooperatively breeding species, because of density-dependent resource competition and group-size-related increases in reproduction conceivably (ii) during disease outbreaks because of spikes in offspring offset population-size-related decreases in vital rates, espe- mortality (Almberg et al. 2009). cially in group-territorial species where larger groups dom- We used a multilevel analysis that statistically controls inate smaller groups in the battle for limited resources for the effects of multiple factors, along with a sensitivity (Mosser & Packer 2009). However, the relationship analysis, to measure the relative strength of factors driv- between density dependence across multiple levels of bio- ing wolf reproduction across biological levels. Because logical organization remains largely unexplored. ecologically important phenotypic traits (e.g. morphology, Here, we use 14 years of morphological, life history, life history, behaviour) are thought to represent adaptive demographic and ecological data from wolves (Canis responses to selection pressures from competitive and lupus) in Yellowstone National Park (YNP) to assess the stochastic environments, we expected reproductive gains relative influence of different traits on the reproductive from these traits to compensate for losses because of success of females under varying levels of environmental environmental pressures. Specifically, we predicted group stress. Wolves are social carnivores that live in territorial, size to be most influential given the central role of social- kin-structured packs in which they cooperate to raise ity in wolf behavioural ecology (Mech & Boitani 2003). young, defend resources from competitors and hunt Consequently, we discuss our results in terms of the adap- (Mech 1970). They have a fast life history relative to other tive importance of multiple traits to fitness in this large large carnivores including a short generation time (c. 4–5 carnivore. years), early first reproduction (2 years old), high fecun- dity (5–6 pups per litter), rapid development (80% of adult body size acquired by the end of their first year) Materials and methods and brief life span (c. 5 years) (Peterson et al. 1998; Fuller, Mech & Cochrane 2003; MacNulty et al. 2009a). study site and population Although wolves are among the most-studied mammals in We analysed data from the initial 14 years (1996–2009) of a long- the world (Mech & Boitani 2003; Musiani, Boitani & term study of wild wolves in YNP. This 8991-km2 protected area is Paquet 2010), surprisingly, little is known about which located mainly in north-western Wyoming, USA. A full description traits drive reproduction in this charismatic top predator. of the study area is given elsewhere (e.g. Smith et al. 2004). Wolves We used multivariate mixed effects models to assess the in this study were either members or descendants of a population simultaneous influence of multiple traits and ecological of 41 radio-marked wolves reintroduced to YNP in 1995–1996 conditions on the annual reproductive performance (litter (Bangs & Fritts 1996). Each winter (January–February) after the size and litter survival) of 55 individually known female reintroduction, we captured and radio-marked 20–30 wolves, wolves and tested various predictions. With respect to including 30–50% of pups born in the previous year (Smith et al. female traits, we expected (i) that because of weakening 2004). Each wolf was aged, weighed, identified as having a black or selection for reproductive performance later in life grey coat and genetically sampled by drawing whole blood. Our (Hamilton 1966; Charlesworth 1980), the age-specific capture and handling protocols were approved by the National Park Service and are in accordance with recommendations from reproductive profile should follow a concave-down pat- the American Society of Mammalogists (Sikes, Gannon & The tern with a peak (i.e. onset of reproductive senescence) Animal Care Use Committee of the American Society of Mammal- near age 5 (median life span of YNP wolves; MacNulty ogists 2011). Including both radio-marked (N = 316) and et al. 2009b); (ii) a positive correlation between female unmarked wolves, we monitored over 1000 individuals from 38 body mass and reproductive success given that larger packs during our study. Each year, an average of 40% of the total body size in mammals can indicate higher quality individ- population census size (21–174 wolves; Smith et al. 2010) was uals (Hamel et al. 2008) or be a pre-requisite for social radio-marked, including the female breeder(s) of each pack.

Breeders were identified by observing a female’s breeding behav- performance because it was not feasible to annually weigh each iour, physical evidence of pregnancy (extended abdomen) and/or female. We derived these estimates from an updated version of denning behaviour (localization at or inside dens), followed by the wolf growth model described in MacNulty et al. (2009a; see observations of nursing pups and/or genetically verified maternity Table S1, Supporting Information). Estimates correspond to a (see below). A female breeder produced only one litter per year, female’s mass on the average parturition date in YNP (April 15). and reproduction was typically monopolized by a single female The growth model was fit to body mass data from 172 females that was behaviourally dominant to same-sex pack members. Sub- that were measured during annual capture. Twenty-six per cent ordinate females sometimes produced litters, but the majority of of these wolves were caught in multiple years to replace damaged litters in our data set (81%) came from socially dominant females radio tags and so were weighed more than once. Body mass was (i.e. female parents or siblings to other potential breeders). A total recorded using a 0–100 kg Pesola spring scale (Rebmattli, Baar, of 55 female breeders were individually identifiable by combina- Switzerland). Wolves were placed in a weighing tarp attached to tion of radio frequency, pelage colour, body shape and/or size. the scale and hoisted aloft until clear of the ground. We did not estimate and subtract stomach-content mass from body mass, so our measurements are likely maximum estimates. data collection

The reproductive performance of each female breeder was measured annually for 1–7 years, and 31 females were measured in Maternity analysis multiple years. Measurements came from year-round monitor- We analysed litter size and survival for only litters of known ing of all YNP packs (2–15 packs per year). Field personnel maternity. We used field observations to assign maternity of lit- observed female breeders and their pack mates daily in early ters to females, based on the obvious behaviour and appearance (mid-November to mid-December) and late winter (March) and of breeding females (see above), and confirmed these putative about weekly throughout the remainder of the year. Observations mother–offspring relationships with genetic data where available were recorded from the ground and fixed-wing aircraft (see Smith (75% of all litters). Genetic analysis included cases where mater- et al. 2004 for details). nity of litters was uncertain from field observations or in packs, We measured two components of reproductive performance for where both dominant and subordinate breeders existed (see each female breeder: litter size and litter survival. Litter size was Appendix S2, Supporting information). In these cases, we the maximum number of pups observed in a litter in the weeks assigned maternity according to a population pedigree con- – following den emergence (10 14 days following parturition). This structed for the YNP wolves where individual genotypes was a minimum estimate given that some pups may have died (N = 337) were based on 26 domestic dog microsatellite loci and – prior to den emergence. Pups are generally weaned at 5 9 weeks PCR amplification as described in vonHoldt et al. (2008). of age then fed by various pack members via meat regurgitation Because we restricted analyses to litters of known maternity, only (Mech 1970). Litter survival was the number of pups that sur- a subset (52%) of total observed litters from packs with both vived until 31 December of each year (8 months old). At this dominant and subordinate breeders could be analysed. Conse- age, wolves are approaching functional independence with respect quently, the sample of litters from subordinate breeders was too to their ability to hunt, disperse and breed (Medjo & Mech 1976; small (N = 25 litters) to determine how social status affected Mech & Boitani 2003). Eight-month-old pups were identifiable by reproduction. virtue of their size and behaviour relative to older age classes. Litter size and survival were scored as 0 (N = 4 for litter size; N = 30 for litter survival) if a female was first identified as a data analysis breeder and subsequently had total reproductive failure (see Appendix S1, Supporting information). To understand the adaptive value of different morphological, behavioural and life-history traits, we examined their relative effects on female reproductive performance under varying levels Age determination of environmental stress. This involved a separate analysis of the annual number of pups born and survived per litter. Analyses We calculated the age of female breeders as the number of years were conducted with generalized linear mixed models (GLMMs) < after their birth year. Females 1 year old were classified as age with a Poisson error distribution after verifying that the data zero. The birth year of most females (85%) was determined by were not over-dispersed. Such models can account for correlation marking them as pups, which provided an exact measure of age. between the observations taken on the same female in multiple Tooth wear and cementum annuli were used to estimate the birth years and on multiple females in the same year. We fitted individ- year of some live and dead adults, respectively (Gipson et al. ual identity and year as crossed random intercepts, such that the 2000). Wolves not captured as pups were sometimes caught as random intercept for individual i is shared across all years for a adults and considered known-aged if individually recognized from given individual i, whereas the random intercept for year j is birth via distinct morphological features (e.g. pelage markings, shared by all individuals in a given year j. Note that the random colour, body shape and size). We assigned a birth year to non- effect for year accounts for unmeasured year-related effects on captured wolves only if first observed as pups and individually reproduction, including prey abundance and climate. All models identifiable as adults. included a compound symmetric correlation structure, which assumed that all observations within individuals and years were, Body mass on average, equally correlated (Weiss 2005). Models were estimated with Laplacian approximation, with parameters estimated We used estimates of individual, age-specific body mass (kg) from maximum likelihood, and significance of effects determined to assess the effects of female body size on reproductive by an approximate z-test.

Fixed effects Model selection

We fitted fixed effects corresponding to different female traits, We performed a series of model selection procedures to identify including age, body mass, coat colour, internal relatedness (IR) the most parsimonious GLMMs of litter size and survival. First, and pack size. Because age-related reproductive patterns are we used information-theoretic statistics (Burnham & Anderson potentially confounded by the selective (dis)appearance of differ- 2002) to determine the best functional form of age- and pack- ent quality individuals, we also fitted individual age at first and size-specific effects on reproduction. For each effect, we sepa- last reproduction as fixed effects (van de Pol & Verhulst 2006; rately evaluated a set of saturated GLMMs of litter size and sur- Nussey et al. 2008). IR reflects a quantity measured between vival that contained all the other fixed effects along with different parental alleles that weights allele sharing by the frequencies of linear and nonlinear terms for age or pack size. Nonlinear terms the alleles involved. This estimate of heterozygosity gives more were spline variables with a single knot at 3–6 years old (age) or weight to homozygotes involving rare alleles and reflects parental 3–10 wolves (pack size). We selected knots a priori in accordance similarity more effectively than commonly used heterozygosity with guidelines for the efficient use of knots (Eubanks 1984; indices (Amos et al. 2001; Zedrosser et al. 2007). We calculated Seber & Wild 2003). By definition, knots selected a priori are IR for 47 genotyped females following Amos et al. (2001). With fixed (i.e. not random variables) and are therefore not estimated respect to coat colour, all genotyped grey-coloured female breed- as parameters in models. The best age and pack size models were ers were homozygous at the K locus, while all but one black the ones with the lowest Akaike Information Criterion (adjusted female were heterozygous at the K locus (Anderson et al. 2009). for small sample, AICc) and smallest ΔAICc. ΔAICc equals the

Homozygous black females are rare in the YNP population AICc for the model of interest minus the smallest AICc for the

(Coulson et al. 2011). set of models being considered. The best model has a ΔAICc of

Pack size is an index of sociality, and we measured it zero, and models with ΔAICc < 2 are plausibly the best. differently for each analysis. In the analysis of litter size, pack Next, we added our best-fit terms for age and pack size to the size was the mode total group size recorded over 3 months prior saturated GLMMs of litter size and survival and reduced these to parturition (January–March). We used this measure because it models with a backward stepwise procedure. We dropped non- encompasses the potential influence of pack members on breeder significant terms (P > 0Á10) one at a time until a likelihood ratio condition during breeding season and offspring development test indicated that the fit of the reduced model was significantly in utero. In the analysis of litter survival, pack size was the mode worse than that of the full model containing the dropped term. adult ( 1 year old) group size recorded from June through After the initial stepwise search, we refit the reduced model using December, as this measures how pack members may affect pup the selected terms and reconsidered inclusion of the omitted provisioning, development and protection. Breeding females were terms by adding them to the model one at a time and testing for included in all pack size counts. significance. To assess how environmental stress shapes the relationship We then verified the functional form of the age- and pack-size- between female traits and reproductive performance, we fitted specific effects remaining in the reduced models. For each effect,

fixed effects for disease and wolf population size. Canine dis- we used AICc to separately evaluate a set of reduced GLMMs of temper virus (CDV) has been linked to poor pup survival in litter size and survival that included different linear and nonlinear YNP wolves (Almberg et al. 2009), and individuals in our study terms for age and pack size as described above. We tested for experienced three CDV outbreaks (1999, 2005, and 2008). Our pairwise interactions between terms in the best-fit, reduced fixed effect for disease was therefore a dummy variable for the GLMMs by adding interaction terms to the models one at a time occurrence of a CDV outbreak in a given year. We used annual and testing for significance. counts of the YNP wolf population (Smith et al. 2010) to track We calculated population-averaged fitted values from the final changes in the intensity of the competitive environment given models by deriving marginal expectations of the responses aver- that territorial aggression between wolf packs increases with aged over the random effects but conditional on the observed population size (Yellowstone Wolf Project, unpublished data). covariates. We separately refitted certain fixed effects as categori- Counts of population size at April 1 and December 31 were cal factors and plotted the associated fitted values to illustrate the used in the analyses of litter size and survival, respectively. We distribution of the underlying data after controlling for individual used unadjusted population counts because resighting rates were and annual heterogeneity and the fixed effects of other variables. high (0Á96) and constant across years (Coulson et al. 2011). The We interpreted Poisson regression coefficients in terms of inci- probability of a CDV outbreak tended to increase with wolf dence-rate ratios (IRRs), which we obtained by exponentiating population size (logistic regression: b = 0Á03 ± 0Á02, P = 0Á15, the coefficients (Rabe-Hesketh & Skrondal 2008). IRR minus 1 N = 15 years), but this association was not strong (pseudo- equals the percentage change (+/À) in the dependent variable r2 = 0Á20). In general, our fixed effects were not highly collinear (e.g. litter size) for each one unit increase in a continuous vari- (r < 0Á30). able (e.g. body size) or when comparing one group to another in We used piecewise linear splines to test for nonlinear effects a categorical variable (e.g. disease vs. non-disease years) while of age and pack size (see Appendix S3, Supporting informa- holding all other variables in the model constant. IRRn rescales tion). Specifically, we tested for whether reproductive perfor- the unit change to n units. Throughout, means are reported with mance declined at advanced ages and in large packs because of standard errors. physiological senescence and intrapack competition, respectively. We created variables containing a linear spline for age and pack size with the MKSPLINE command in STATA 11.0. Sensitivity analysis The variables were constructed so that the estimated coeffi- To evaluate the relative strength of different effects in the final cients measure the slopes for the segments before and after a models of litter size and survival, we performed a sensitivity segment break.

© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society, Journal of Animal Ecology, 82, 222–234 226 D. R. Stahler et al. analysis that allowed comparison of effects across a common 60 scale. First, we calculated the predicted number of pups born (or survived) with continuous variables set to observed means and 50 categorical variables for coat colour and disease set to ‘black coat’ and ‘CDV outbreak’, respectively. Next, we separately per- 40 turbed each model parameter by 10%, recalculated the prediction and computed the difference between the initial and perturbed 30 prediction. A large difference corresponds to a high sensitivity, 20

and parameters with the highest sensitivity had the greatest effect Body mass (kg) on reproductive performance. We report absolute sensitivities and 10 sum those for spline parameters to show the overall inﬂuence of a nonlinear effect and to facilitate comparison between linear and 0 nonlinear effects. 02468 Age (years)

Results Fig. 1. Growth profile of female wolves (N = 172) in Yellow- stone National Park, 1995–2010. Points are observed age-specific We recorded 140 observations of annual female reproduc- weights (N = 238), and the solid line represents the population- tion from 55 female breeders (30 grey, 25 black) in 32 dif- averaged fitted growth curve from the best-fit mixed effects ferent packs across YNP, 1996–2009. An observation growth model (Table S1, Supporting information). Model selec- included information on whether a female breeder had tion results are in Table S2 (Supporting information). produced a litter, the size of the litter and the number of pups surviving to the end the year. Most observations involved litters (N = 125), and most of these included variables that were identified in initial model selection information on litter size and survival (N = 119). Obser- (Table S3–S4, Supporting information) and confirmed in vations that included litter survival but not litter size follow-up analyses (Table S5–S6, Supporting information). (N = 3) or vice versa (N = 3) occurred because litter size There were no significant pairwise interactions between at den emergence or subsequent pup survival, respectively, terms in the final GLMM model (results not shown). was undocumented. Thus, the total sample differed The spline variable for age indicates that litter size chan- somewhat between the analyses of litter size (N = 126 ged little from 2–4 years old (P = 0Á323), whereas it observations, 51 females) and litter survival (N = 136 decreased by 7% (incidence-rate ratio [IRR] = 0Á93 ± 0Á04, observations, 54 females). P = 0Á041) for each year beyond 4 (Fig. 2a). Note the Most litter observations were from packs with a single strength of this effect is uncertain given that a similar breeding female (77% of 125). Some were from packs model with a simple linear term for age (b = À0Á03 ± 0Á02, with > 1 female breeder, and these litters were produced P = 0Á180) fit the data nearly as well (DAICc = 0Á06; Table by socially dominant (13%) and subordinate (10%) S5, Supporting information). But fitting age as a categori- females. Female breeders were 2–9 years old with mean cal factor corroborated the apparent age-related decline (±SE) age of primiparity at 2Á7(±0Á1) years. Female because 7- and 9-year-old females produced 33% and 53% breeders lived 5Á4(±0Á4) years on average, and 50% died fewer pups, respectively, than did 4-year-old females by age 5 (median life span). We estimated age-specific (P < 0Á040). This age-related decline was not an artefact of body mass of female breeders from a model of female the selective (dis)appearance of different quality individu- growth (Table S1, Supporting information). According to als as age at both first and last measurement was not this best-fit model (DAICc = 0Á00), females exhibited three retained in the final model. growth phases: rapid growth to 0Á75 years old, moderate The main effect for female body mass suggests that big- growth from 0Á75–2Á75 years old and no growth beyond ger females produced bigger litters (Fig. 2b). Specifically, 2Á75 years old (Fig. 1). Other top-scoring models litter size tended to increase by 15% for each 10-kg

(DAICc < 2Á00; Table S2, Supporting information) suggest increase in female body mass, although this was statisti- that growth levelled-off from 1Á75–3Á75 years old. The cally insignificant (IRR = 1Á15 ± 0Á09, P = 0Á104). predicted body mass of female breeders from the best-fit The spline variable for pack size (total pack size prior to growth model was 26–53 kg. parturition; range = 2–15 wolves; mean 5Á19 ± 0Á24 wolves) indicates a threshold at which the effect of pack litter size size on litter size suddenly changed (Fig. 2c). Below 8 wolves, each additional wolf increased litter size by 10% Variation in litter size at den emergence (range = 0–11 (IRR = 1Á10 ± 0Á03, P < 0Á001). But for each wolf beyond pups; mean 4Á74 ± 0Á21 pups) was attributable to indi- 8, litter size decreased by 9% (IRR = 0Á91 ± 0Á05, vidual-, group- and population-level factors. The final P = 0Á036). Note the confidence set of models (DAICc GLMM of litter size includes terms for female age and < 2Á00; Table S6, Supporting information) indicates the body mass, adult pack size, population size and disease threshold adult group size may have occurred at seven or (Table 1). The terms for age and pack size are spline nine wolves.

Table 1. Best-ﬁt GLMM model for the effects of individual-, group- and population-level factors on the number of pups in a female’s litter at den emergence (litter size). Female’s age-1 and age-2 are the effects of a female’s age before and after she reaches 4 years old, respectively. Pack size-1 and pack size-2 are the effects of pack size when a female’s pack includes less than or greater than eight wolves (including breeding females), respectively. Disease year refers to years with canine distemper outbreaks. Incident rate ratios (IRR) are the exponentiated Poisson regression coefﬁcients. Model selection results are in Tables S3–S4 (Supporting information)

95% conﬁdence Parameter IRR b SE zPinterval for b

Intercept 0Á723 0Á404 1Á79 0Á073 À0Á068 1Á515 Female age-1 1Á072 0Á070 0Á071 0Á99 0Á323 À0Á069 0Á208 Female age-2 0Á926 À0Á076 0Á037 À2Á04 0Á041 À0Á149 À0Á003 Female body mass (kg) 1Á014 0Á014 0Á009 1Á62 0Á104 À0Á003 0Á032 Pack size-1 1Á094 0Á091 0Á025 3Á68 <0Á001 0Á042 0Á139 Pack size-2 0Á909 À0Á095 0Á045 À2Á10 0Á036 À0Á184 À0Á006 Population size 0Á997 À0Á003 0Á001 À2Á51 0Á012 À0Á006 À0Á001 Disease year 0Á772 À0Á258 0Á116 À2Á22 0Á027 À0Á486 À0Á030

(a) (b) 111134710 8 10 5878611433 7 16 29 22 20 19 11 5 4 8 10 11 13 6 5 6 4 4 3 Pups born Pups born 2 2 1 0 0 0246810 24 29 34 39 44 49 54 Age (years) Body mass (kg)

0 0 0 4 8 12 16 20 40 60 80 100 120 140 160 Total pack size Population size

Fig. 2. Effects of (a) age, (b) body mass, (c) total pack size and (d) population size on the number of pups in a female’s litter at den emergence (pups born) in Yellowstone National Park, 1996–2009. The number of wolves and individual litters included in this analysis were 51 and 126, respectively. Solid lines are population-averaged fitted values from the best-fit GLMM model (Table 1) with dotted lines indicating pointwise 95% confidence intervals. Points are predicted means with standard errors obtained by separately refitting covariates (a–d) as categorical factors in the best-fit model, with sample size indicated above each point.

Population size and disease were important extrinsic litter survival constraints on litter size. Wolf population size in YNP at As with litter size, variation in litter survival (range = 0–9 female parturition time (April) was 33–165 wolves pups; mean 3Á07 ± 0Á20 pups) was attributable to individ- (mean = 95 ± 10 wolves), and litter size decreased with ual-, group- and population-level factors. The final increasing population size (Fig. 2d). For every 10 addi- GLMM of litter survival includes female age, body mass, tional wolves in the population, litter size decreased by coat colour, pack size, population size and disease 3% (IRR = 0Á97 ± 0Á01, P = 0Á012). There were 23% (Table 2). Terms for age and pack size are spline variables fewer pups in a litter at den emergence in years with that were identified in initial model selection (Table S7– canine distemper virus outbreaks than in years without S8, Supporting information) and confirmed in follow-up CDV (IRR = 0Á77 ± 0Á09, P = 0Á027).

Table 2. Best-ﬁt GLMM model for the effects of individual-, group- and population-level factors on the number of pups in a female’s litter surviving until 8 months old (litter survival). Female’s age-1 and age-2 are the effects of a female’s age before and after she reaches 5 years old, respectively. The reference coat colour is black. Pack size-1 and pack size-2 are the effects of adult ( 1 year old) pack size when a female’s pack includes less than or greater than three adults (including breeding females), respectively. Disease year refers to years with canine distemper outbreaks. Incident rate ratios (IRR) are the exponentiated Poisson regression coefﬁcients. Model selection results are in Tables S5–S6 (Supporting information)

95% conﬁdence Parameter IRR b SE zPinterval for b

Intercept À1Á022 0Á705 À1Á45 0Á148 À2Á404 0Á361 Female age-1 1Á029 0Á029 0Á062 0Á47 0Á637 À0Á092 0Á150 Female age-2 0Á843 À0Á171 0Á071 À2Á41 0Á016 À0Á309 À0Á032 Female body mass (kg) 1Á033 0Á033 0Á012 2Á82 0Á005 0Á010 0Á056 Female coat colour 0Á751 À0Á287 0Á145 À1Á98 0Á047 À0Á571 À0Á003 Pack size-1 1Á452 0Á373 0Á163 2Á29 0Á022 0Á054 0Á693 Pack size-2 1Á047 0Á046 0Á013 3Á40 0Á001 0Á019 0Á072 Population size 0Á995 À0Á005 0Á003 À1Á82 0Á069 À0Á010 0Á000 Disease year 0Á471 À0Á754 0Á180 À4Á20 <0Á001 À1Á106 À0Á402

analyses (Table S9–S10, , Supporting information). There (IRR = 1Á45 ± 0Á16, P = 0Á022), but for each additional were no significant pairwise interactions between terms in adult beyond 3, litter survival increased by only 5% the final GLMM model (results not shown). Overall, litter (IRR = 1Á05 ± 0Á01, P = 0Á001). Note the confidence set survival was positively related to litter size at den emer- of models (DAICc < 2Á00; Table S10, Supporting informa- gence (Pearson correlation r = 0Á65, P < 0Á001, N = 119 tion) indicates the threshold adult group size may have litters). occurred at four or five wolves. Pack size of 0 (N = 3) The spline variable for age indicates that litter survival were cases where all adult pack members (including changed little from 2–5 years old (P = 0Á637), whereas it breeding female) died or disappeared during late pup rear- decreased by 16% (IRR = 0Á84 ± 0Á07, P = 0Á016) for each ing season, resulting in zero pup survival to independence year beyond 5 (Fig. 3a). Although a similar model with a in each case. simple linear term for age (b = À0Á06 ± 0Á03, P = 0Á06) Constraints on litter survival were driven by both popu- scored well (DAICc = 0Á79), the apparent age-related lation size and disease. YNP wolf population size (exclud- decline is corroborated by fitting age as a categorical fac- ing pups) at the time pups approached independence tor: 7- and 9-year-old females produced 39% fewer (December) was 28–115 wolves (mean = 84 ± 2Á2 wolves), (P = 0Á040) and 59% fewer (P = 0Á065) surviving pups, and litter survival decreased with increasing population respectively, than did 5-year-old females. As indicated by size (Fig. 3d). Each 10 additional wolves in the popula- the confidence set of models (DAICc < 2Á00; Table S9, tion decreased litter survival by 5%, but this effect was Supporting information), the threshold for reproductive statistically weak (IRR = 0Á95, P = 0Á069). Finally, pup decline conceivably occurred at age 4 or 6. This age-related survival was greatly reduced in CDV outbreak years, with decline was not an artefact of the selective (dis)appearance 53% fewer surviving pups in a litter than in non-disease of different quality individuals as age at both first and last years (IRR = 0Á47 ± 0Á18, P < 0Á001). measurement was not retained in the final model. The effect for female body mass indicates that pups relative influence of main effects on born to bigger females have higher survival to indepen- reproduction dence (Fig. 3b). Specifically, litter survival increased by 39% for each 10-kg increase in female body mass Our sensitivity analysis revealed the relative importance of (IRR = 1Á39 ± 0Á12, P = 0Á005). Moreover, the effect of a female’s morphological, behavioural and life-history coat colour indicates that the K locus is linked to repro- traits under the conditions of population density and dis- ductive performance. Specifically, black-coloured females ease outbreaks observed during the study. The sensitivity (all heterozygous at K locus, but one) had 25% fewer analysis indicates that individual-level traits were most surviving pups annually than grey-coloured females influential on female reproductive success, followed by (IRR = 0Á75 ± 0Á15, P = 0Á047). group effects, then population-level factors. Using total Pack size (adult pack size during pup rearing to inde- sensitivity scores (below in parentheses) to rank in the pendence; range = 0–26 wolves; mean 6Á76 ± 0Á36 wolves) order of largest effect, litter size was most influenced by positively influenced litter survival throughout its range, female body mass (0Á27), pack size (0Á20), population size but the spline variable indicates a threshold at which this (0Á14), female age (0Á12) and disease (0Á11), respectively effect diminishes (Fig. 3c). Below three wolves, each (Fig. 4). For litter survival, female performance was most additional adult increased litter survival by 55% influenced by female body mass (0Á21), followed by pack

4 5 4 7 11 7 10 12 12 13 6 96 9 6 3 4 8 (a) 4 18 31 24 21 19 13 7 3 (b)

6 3

4 2 Pups survived Pups survived 2 1

0 0 02468103035404550 Age (years) Body mass (kg)

6 4

4 Pups survived

Pups survived 2 2

0 0 0 4 8 12 16 20 24 28 20 40 60 80 100 120 Adult pack size Population size

Fig. 3. Effects of (a) age, (b) body mass, (c) adult pack size and (d) population size on the number of pups in a female’s litter surviving until 8 months old (pups survived) in Yellowstone National Park, 1996–2009. The number of wolves and individual litters included in this analysis were 54 and 136, respectively. Solid lines are population-averaged fitted values from the best-fit GLMM model (Table 2) with dotted lines indicating pointwise 95% confidence intervals. Points are predicted means with standard errors obtained by separately refitting covariates (a)-(d) as categorical factors in the best-fit model, with sample size indicated above each point.

0·3 significantly influenced by several individual-, group- and Litter size population-level factors (summarized in Table S11, Sup- 0·25 Litter survival porting information). Importantly, we demonstrate that 0·2 the strength and direction of effects on litter size and litter survival were not uniform and sometimes contrasting as 0·15 reproductive losses at one level were offset by gains at Sensitivity 0·1 another. By simultaneously evaluating the effects and 0·05 comparing their relative influence, our analysis indicates that individual traits (body size) and behaviour (sociality) 0 Age Body mass Color Pack size Population Disease had the greatest effect on reproduction and helped coun- Size ter the impact of competition and disease. Below, we Fig. 4. Relative influence of individual-, group- and population- discuss each effect and its importance to reproductive level effects on a female’s litter size at den emergence (black bars) performance in Yellowstone wolves. and litter survival until 8 months old (white bars) in Yellowstone National Park, 1996–2009. Each bar represents a sensitivity value generated by taking the difference between initial and perturbed individual-level factors influencing (10%) predicted values for each parameter identified in Tables 1 reproduction and 2. The greater the sensitivity value, the more influential that parameter is on reproductive performance. Sensitivities for age Improved reproductive performance with increased female and pack size are sums of the sensitivity of each variable’s spline body mass is common in mammals (e.g. ungulates – parameters. Albon, Guinness & Clutton-Brock 1983; sciurids – King, Festa-Bianchet & Hatfield 1991; pinnipeds – Iverson et al. size (0Á19), disease (0Á10), population size (0Á06), coat 1993), but hitherto undocumented in wild wolves. The colour (0Á04) and age (0Á02), respectively (Fig. 4). reproductive benefit of larger size can be manifested in many ways including improved conception (Boyd 1984), foraging ability (MacNulty et al. 2009a), lactation (Bowen Discussion et al. 2001) and offspring mass (Iverson et al. 1993). Our Our comprehensive analysis of wolf reproduction demon- analysis of YNP wolves revealed that the effect of body strates that heterogeneity in female performance was mass on female reproduction exceeded that of other

© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society, Journal of Animal Ecology, 82, 222–234 230 D. R. Stahler et al. factors including pack size. Although the effect body mass influence of coat colour overall. While proximate mecha- on litter size was not statistically significant, it was qualita- nisms mediating covariation between coat colour and tively similar (Fig. 2b) to its highly significant effect on lit- reproduction remain unclear, our findings may represent ter survival (Fig. 3b). The stronger effect on litter survival trade-offs between reproduction and other fitness mea- may reflect greater maternal investment in pup survival sures (e.g. survival). This is possibly due to antagonistic (e.g. lactation, offspring development) vs. litter size (e.g. pleiotropy associated with the K locus (a b-defensin gene) gestation). The reproductive importance of body mass is responsible for melanism in wolves (Anderson et al. 2009) further highlighted by close correspondence between the and associated with innate and adaptive immunity (Yang ages of primiparity (2Á7 years) and maximum body mass et al. 1999). Given that melanin-based coloration is often (2Á75 years). By contrast, female ungulates and ursids associated with regulatory effects on energy balance, stress start reproducing long before reaching maximum size and immunity in wild vertebrates (Ducrest, Keller & (Zedrosser et al. 2009; Martin & Festa-Bianchet 2011), Roulin 2008; Gasparini et al. 2009), there may be a perhaps because they exhibit a comparatively slower life positive association between melanism and immunocom- history and less competitive social environment. In wolves, petency that grants a survival advantage to black wolves. the reproductive benefits of large size combined with early Indeed, preliminary investigations of YNP wolf survival age at first reproduction are likely strong selective pres- rates show black females experience greater survival than sures for rapid neonatal growth as illustrated in our grey females (Yellowstone Wolf Project, unpublished growth model (Fig. 1). This growth pattern suggests that data). However, the costs of immunity may contribute to early life experiences may strongly influence lifetime fit- reproductive costs, a pattern demonstrated in other mam- ness, as has been shown in other cooperative breeders mals (Graham et al. 2010). Additionally, a recent study (meerkats Suricata suricatta, Russell et al. 2003; red wolf, found higher fitness for black heterozygous wolves in Canis rufus, Sparkman et al. 2011). YNP, suggesting balancing selection (Coulson et al. Reproduction’s sensitivity to body mass, combined with 2011). Together, these patterns indicate fitness differences rapid neonatal growth, effectively constant adult body associated with the K locus that may help explain the mass with increasing age and short life span, likely explains maintenance of colour polymorphism in some North the moderate effects of age on female reproduction. Age- American wolf populations. specific reproductive performance is typically attributed to Although estimates of heterozygosity (internal related- either increased experience or investment in resources ness, IR) have been correlated with the variation in repro- (Curio 1983; Clutton-Brock 1988) or senescence (Nussey ductive performance in some species (e.g. Amos et al. et al. 2008), or alternatively, can be masked by the selective 2001; Zedrosser et al. 2007), we found no significant effect (dis)appearance of individuals of varying quality (Reid of this trait on reproduction. This is likely due to high et al. 2003; de Pol & Verhulst 2006). With respect to the genetic variation and inbreeding avoidance in YNP latter, we found no effect of age at first or last reproduc- wolves (vonHoldt et al. 2008), along with an insufficient tion, indicating that age-related performance is not being range of IR values to evaluate whether relatively outbred masked by differential onset of reproduction or mortality individuals have enhanced success compared to relatively associated with individual quality. Although reproductive inbred ones (Amos et al. 2001). success did not improve with age, it did decline beyond 4– 5 years old. To our knowledge, this is the first demonstra- group-level factors influencing tion of reproductive senescence in wild wolves. This result reproduction complements recent findings that YNP wolves exhibit senescence in hunting ability (MacNulty et al. 2009b) and The evolution of sociality in large carnivores is influenced supports the hypothesis that natural selection is too weak by many factors, including territorial defence (Mech & to support genetic health late in life (Hamilton 1966; Boitani 2003; Mosser & Packer 2009), group hunting Charlesworth 1980). Whereas social effects may moderate (MacNulty et al. 2012), food defence (Creel, Spong & ageing (Lee 2003; Bourke 2007), we found no significant Creel 2001; Vucetich, Peterson & Waite 2004), kin selec- interaction between age and group size, suggesting auxilia- tion (Schmidt & Mech 1997) and cooperative breeding ries did not influence the rate or onset of reproductive (e.g. Mech 1970; Clutton-Brock 2002). Our results high- senescence, similar to findings in other cooperative breed- light the adaptive value of sociality by showing pack size ers (Sharp & Clutton-Brock 2010). Although senescence as the second most important driver of reproductive suc- has been widely detected among mammals (Nussey et al. cess. Similar effects have been found in other canid sys- 2008), its importance to fitness in wild populations remains tems (e.g. Harrington, Mech & Fritts 1983; Moehlman controversial, especially in short-lived species (Turbill & 1986; McNutt & Silk 2008; Sparkman et al. 2011) and are Ruf 2010). Given wolves’ relatively short life spans, it is typically attributed to auxiliaries caring for pups. Yet, not surprising that age was relatively unimportant to some canid studies have shown no correlation (e.g. Peter- reproduction compared to body mass. son, Woolington & Bailey 1984; Pletscher et al. 1997) or That grey females were reproductively more successful a negative effect of auxiliaries on reproduction, particu- than black females is intriguing, despite the moderate larly when unfavourable socio-ecological conditions

© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society, Journal of Animal Ecology, 82, 222–234 Reproductive performance in female wolves 231 prevail (e.g. high intraguild competition, low prey density; this system (Almberg et al. 2009), with pup mortality Harrington, Mech & Fritts 1983; Gusset & Macdonald occurring after weaning and sometimes culminating in 2010; Sparkman et al. 2011). complete loss of litters. Our results add to this knowledge Our results showing nonlinear, contrasting effects of by showing that CDV outbreaks also lead to reduced lit- pack size on reproduction are significant because they ter size at den emergence. CDV has been documented to demonstrate that group effects are conditional on the bree- cross placental barriers in domestic dogs (Canis lupus der’s life cycle stage and not uniform across group sizes. familiaris), causing abortion, weak offspring and neuro- Few studies have demonstrated significant nonlinear logical diseases (Pandher et al. 2006). Depending on CDV effects of group size in cooperatively breeding mammals exposure and infection patterns in mothers, maternal con- (e.g. marmots, Armitage & Schwartz 2000). The negative dition and/or disease transmission to neonate pups may correlation between early litter size and larger pack sizes explain reduced early litter sizes during outbreak years. (> 8 wolves) draws attention to apparent costs of sociality Our findings suggest that disease may be a strong selective at this stage of reproduction. Mechanisms underlying such force in canid systems, especially if linked to individual costs may include intrapack competition for food traits that offset its negative effects. For example, selec- (Harrington, Mech & Fritts 1983; Schmidt & Mech 1997) tion for traits that may be linked to maternal condition or socially induced stress from competitors during the and immunocompetency (e.g. body size, coat colour) may breeding season (Creel 2001; McNutt & Silk 2008), both strengthen via associations with variable environmental of which can impact maternal condition important to early stresses such as disease. components of reproduction in cooperative breeders Our finding of negative density-dependent effects on (Russell et al. 2003; Sharp & Clutton-Brock 2010). In con- reproduction is consistent with many vertebrate popula- trast, we found positive effects of auxiliaries on litter sur- tions, where changes in vital rates occur through behavio- vival throughout all pack sizes, demonstrating that pup urally meditated competition over resources (Fowler 1981). survival was enhanced in larger packs. In addition to hav- This effect in YNP is likely due to increased competition ing more helpers to provision young, larger groups have with conspecifics under high wolf densities during our numerical advantages during intergroup (Mech & Boitani study (Yellowstone Wolf Project, unpublished data). How- 2003) and intraguild (Wilmers et al. 2003; Vucetich, Peter- ever, our sensitivity results showing that group-level posi- son & Waite 2004) competition for resources (e.g. food, tive density dependence was more influential than territory), which may contribute to offspring survival, as population-level negative density dependence highlights a shown in lions (Panthera leo; Mosser & Packer 2009). benefit of wolf sociality. Specifically, group augmentation Importantly, the positive influence of auxiliaries was can serve as a buffer against the negative effects of inter- strongest for small packs, indicating that there is a thresh- group competition. These results demonstrate a more old below which helpers are particularly critical to breeder nuanced relationship between ecological conditions and success. Although wolves are not considered obligate sociality, as favourable conditions (i.e. high resource abun- cooperative breeders, our results are consistent with an dance) are thought to relax the need for cooperative behav- Allee effect (i.e. inverse density dependence) at the pack iour, making significant group effects on offspring fitness level where recruitment critical to group persistence less apparent (Gusset & Macdonald 2010). Here, we pro- depends on a minimum group size (Courchamp, Clutton- pose that under the socio-ecological conditions of high Brock & Grenfell 1999; Gusset & Macdonald 2010). prey abundance during our study, which in turn resulted in We recognize that our analysis did not examine the role high wolf densities, competition over territories and/or of food availability as a mechanism underlying covaria- breeding opportunities strengthened the relationship tion between pup production and pack size. Additionally, between sociality and fitness. Our findings differ from other this study did not address whether group effects on repro- wolf studies (Harrington, Mech & Fritts 1983; Sparkman duction were influenced by kin-directed altruism and et al. 2011) where helpers were found to have either nega- inclusive fitness benefits, which may occur in wolves tive or no effect on pup survival under high densities. (Harrington, Mech & Fritts 1983; Schmidt & Mech 1997). While these findings downplay the extent to which individ- Future work aims to test these ideas by evaluating effects uals benefit from group-living (Silk 2007), our results high- of pack hunting success (e.g. prey and biomass acquisition light how the fitness consequences of sociality are rates), pack composition (e.g. relatedness, age structure, conditional upon prevailing socio-ecological conditions. sex ratio) and social dominance on fitness measures. Conclusions population-level factors influencing reproduction Measures of reproductive success from longitudinal studies are essential for linking individual traits to ecological and Although CDV was less influential overall than individual evolutionary dynamics in wild populations, especially in traits or group effects, it did have a pronounced, stochas- response to environmental change (e.g. Coulson et al. tic impact on female reproduction. CDV-related decreases 2006, 2011). Our study identifies trait- and environmental- in litter survival are concordant with earlier findings for specific patterns of wolf reproduction that could improve

© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society, Journal of Animal Ecology, 82, 222–234 232 D. R. Stahler et al. models linking age structure, social structure, density and Burnham, K.P. & Anderson, D.R. (2002) Model Selection and Multimodal disease patterns with ecological and evolutionary dynamics Inference: A Practical Information-Theoretic Approach, 2nd edn. Springer, New York, New York. in large carnivores. Additionally, our study clarifies how Charlesworth, B. (1980) Evolution in Age-Structured Populations. life history, sociality and ecological conditions interact in Cambridge University Press, Cambridge. cooperative breeders and ranks the adaptive value of traits Clutton-Brock, T.H. (1988) Reproductive Success. University of Chicago Press, Chicago, Illinois, USA. in promoting individual fitness in competitive and stochas- Clutton-Brock, T.H. (2002) Behavioral ecology—breeding together: kin tic environments. Consistent with findings from a diverse selection and mutualism in cooperative vertebrates. Science, 296,69–72. array of mammalian studies, we demonstrate similar pat- Clutton-Brock, T.H., Russell, A.F., Sharpe, L.L., Brotherton, P.N.M., McIlrath, G.M., White, S. & Cameron, E.Z. (2001) Effects of helpers terns in trait- and environmental-specific influences on on juvenile development and survival in meerkats. Science, 293, 2446– reproduction, while uniquely evaluating the relative 2449. strengths of such factors. In wolves, it appears that indi- Cockburn, A. (1998) Evolution of helping behavior in cooperatively breeding birds. Annual Review in Ecology, Evolution, and Systematics, 29, vidual performance is influenced more by phenotypes than 141–177. environmental conditions, and it would be valuable to Coulson, T., Benton, T.G., Lundberg, P., Dall, S.R.X., Kendall, B.E. & know if this were true in other taxa. Knowledge of traits Gaillard, J.M. (2006) Estimating individual contributions to population growth: evolutionary fitness in ecological time. Proceedings of the Royal that promote fitness in the context of environmental stress Society of London Series B: Biological Sciences, 273, 547–555. is a key to understanding how wild populations respond Coulson, T., MacNulty, D.R., Stahler, D.R., vonHoldt, B., Wayne, R.K. to global climate change, disease outbreaks, habitat alter- & Smith, D.W. (2011) Modeling effects of environmental change on wolf population dynamics, trait evolution and life history. Science, 334, ation and human exploitation, particularly with respect to 1275–1278. apex species, which can have a disproportionate effect on Courchamp, F., Clutton-Brock, T.H. & Grenfell, B.T. (1999) Inverse den- natural systems via trophic cascades (Estes et al. 2011). sity dependence and the Allee effect. Trends in Ecology and Evolution, 14, 405–410. Creel, S. (2001) Social dominance and stress hormones. Trends in Ecology & Evolution, 16, 491–497. Acknowledgements Creel, S., Spong, G. & Creel, N. (2001). Interspecific competition and the population biology of extinction-prone carnivores. Carnivore Conserva- We thank Erin Stahler, Debra Guernsey, Rick McIntyre, and numerous tion. (eds J.L. Gittleman, S.M. Funk, D.D. Macdonald & R.K. Wayne), field technicians with data collection and management assistance. We also pp. 35–60. Cambridge University Press, Cambridge. thank Roger Stradley from Gallatin Flying Service and Bob Hawkins Curio, E. (1983) Why do young birds reproduce less well? Ibis, 125, 400– from Hawkins and Powers, Inc. and Sky Aviation, Inc. for safe piloting. 404. This work was supported in part by the National Science Foundation Ducrest, A.L., Keller, L. & Roulin, A. (2008) Pleiotropy in the melanocor- grants DEB-0613730 and DEB-1021397, University of California, Los tin system, coloration and behavioural syndromes. 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Table S1. Best-fit GLMM model of age-specific change in body form of the relationship between female age (years) and litter mass (kg) for female wolves (N = 172) in Yellowstone National survival to independence (N = 54 breeding females, 136 litters). Park, 1995–2010. Age_1 is the slope before 0Á75 years-old, age_2 is the slope between 0.75 and 2.75 years-old, and age_3 is the slope Table S8. A priori candidate GLMM models for identifying the beyond 2Á75 years-old. form of the relationship between adult pack size and litter survival to independence (N = 54 breeding females, 136 litters). Table S2. A priori candidate GLMM models for the effects of age (years) on female wolf body mass (kg) (N = 172 female wolves, 238 Table S9. A priori candidate GLMM models for confirming the observations). Variables age_1, age_2, and age_3 contain a linear form of the relationship between female age (years) and litter spline for age at the indicated breakpoint(s). survival to independence (N = 54 breeding females, 136 litters).

Table S3. A priori candidate GLMM models for identifying the Table S10. A priori candidate GLMM models for confirming the form of the relationship between female age (years) and litter size form of the relationship between adult pack size and litter survival following den emergence (N = 51 breeding females, 126 litters). to independence (N = 54 breeding females, 136 litters).

Table S4. A priori candidate GLMM models for identifying the Table S11. Summary of predictions and results regarding the effects form of the relationship between adult pack size and litter size of individual-, group-, and population-level factors on annual following den emergence (N = 51 breeding females, 126 litters). reproductive success (litter size at den emergence, pup survival to independence) in female gray wolves of Yellowstone National Table S5. A priori candidate GLMM models for confirming the Park, 1996–2009. form of the relationship between female age (years) and litter size following den emergence (N = 51 breeding females, 126 litters). As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials Table S6. A priori candidate GLMM models for confirming the may be re-organized for online delivery, but are not copy-edited form of the relationship between adult pack size and litter size or typeset. Technical support issues arising from supporting following den emergence (N = 51 breeding females, 126 litters). information (other than missing ﬁles) should be addressed to the authors. Table S7. A priori candidate GLMM models for identifying the