• animal model;
  • body mass index;
  • breeding value;
  • condition;
  • dominance variance;
  • fitness;
  • heritability;
  • natural selection


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Although there is substantial evidence that skeletal measures of body size are heritable in wild animal populations, it is frequently assumed that the nonskeletal component of body weight (or ‘condition’) is determined primarily by environmental factors, in particular nutritional state. We tested this assumption by quantifying the genetic and environmental components of variance in fledgling body condition index (=relative body weight) in a natural population of collared flycatchers (Ficedula albicollis), and compared the strength of natural selection on individual breeding values with that on phenotypic values. A mixed model analysis of the components of variance, based on an ‘animal model’ and using 18 years of data on 17 717 nestlings, revealed a significant additive genetic component of variance in body condition, which corresponded to a narrow sense heritability (h2) of 0.30 (SE=0.03). Nongenetic contributions to variation in body condition were large, but there was no evidence of dominance variance nor of contributions from early maternal or common environment effects (pre-manipulation environment) in condition at fledging. Comparison of pre- and post-selection samples revealed virtually identical h2 of body condition index, despite the fact that there was a significant decrease (35%) in the levels of additive genetic variance from fledging to breeding. The similar h2 in the two samples occurred because the environmental component of variance was also reduced by selection, suggesting that natural selection was acting on both genotypic and environmental variation. The effects of selection on genetic variance were confirmed by calculation of the selection differentials for both phenotypic values and best linear unbiased predictor (BLUP) estimates of breeding values: there was positive directional selection on condition index both at the phenotypic and the genotypic level. The significant h2 of body condition index is consistent with data from human and rodent populations showing significant additive genetic variance in relative body mass and adiposity, but contrasts with the common assumption in ecology that body condition reflects an individual’s nongenetic nutritional state. Furthermore, the substantial reduction in the additive genetic component of variance in body condition index suggests that selection on environmental deviations cannot alone explain the maintenance of additive genetic variation in heritable traits, but that other mechanisms are needed to explain the moderate to high heritabilities of traits under consistent and strong directional selection.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Traits under strong and consistent directional selection are expected to show low heritabilities because of the erosion of genetic variability by selection (Falconer & Mackay, 1996). In accordance with this expectation, traits closely associated with fitness typically have lower heritabilities than traits less closely associated with fitness (Mousseau & Roff, 1987; Roff & Mousseau, 1987; Merilä & Sheldon, 1999, 2000; Kruuk et al., 2000; but see Hoffmann, 2000). However, whether the lower heritabilities are indeed the result of reduced levels of additive genetic variance, rather than the capture of larger amounts of environmental or nonadditive genetic variance by fitness traits, remains contentious (Price & Schluter, 1991; Houle, 1992; Merilä & Sheldon, 1999). Furthermore, we are not aware of any study of a wild animal population which has explicitly demonstrated that natural selection reduces the additive genetic variance of a trait. In contrast, van Noordwijk (1986) and van Noordwijk et al. (1988) demonstrated that the heritability of body size in Great tits (Parus major) was increased by selection, and that this increase was attributable to a reduction of environmental variance, whereas the additive genetic variance remained largely unchanged. In the same vein, several authors (e.g. Price & Liou, 1989; Alatalo et al., 1990; Thessing & Ekman, 1994; Larsson et al., 1998) have suggested that selection observed acting on heritable traits is acting primarily on the environmental component of individual phenotypes, rather than on genotypes – or on traits with phenotypic, but not genetic, correlations with the trait in question. Apart from the studies by van Noordwijk (1986) and van Noordwijk et al. (1988), there have been no attempts to assess directly the effects of selection on a trait on different causal components of variation (but see van Tienderen & de Jong, 1994), and none of the studies listed above has explicitly compared the action of selection on phenotypes and breeding values. Consequently, there is a major gap in our understanding of the effects of selection on the genetic architecture of phenotypic traits in wild populations, and in particular of whether selection on environmental deviations could help to explain the maintenance of additive genetic variance in traits related to fitness.

In this paper, we use long-term data from a natural bird population to quantify the effects of selection on the genetic and environmental components of variance in body condition. Condition is a trait known to be subject to strong selection, but one for which there are conflicting opinions as to the degree of genetic determination. It is usually defined as either the residual from the regression of body weight on a structural size measure (e.g. Lindén et al., 1992; Brown, 1996; Merilä, 1996), as body weight divided by the square of some structural size measure (e.g. Maes et al., 1997), or as some objective discrete score (e.g. Calavas et al., 1998). Either way, body condition is an important component of both parental and offspring fitness in a number of vertebrate species (fish: Henderson & Wong, 1996; Adams, 1999; birds: Alatalo et al., 1990; Hochachka & Smith, 1991; Lindén et al., 1992; Merilä & Svensson, 1995; Bensch et al., 1996; mammals: Frisch, 1988; Dobson & Michener, 1995; White et al., 1997; Festa-Bianchet, 1998; Guinet et al., 1998). In passerine birds, offspring condition has been shown to be under directional selection several times (references above), and recent work suggests moderate to high heritability of this trait (Merilä, 1996; Sheldon et al., 1997; Meriläet al., 1999; Sheldon, 1999). Similar conclusions have been reached from analysis of data on humans (Barsh et al., 2000 and references therein) and laboratory populations of rodents (e.g. Chagnon & Bouchard, 1996; Brockmann et al., 1998). The significant heritability is puzzling in light of the fact that condition has previously been considered to reflect an individual’s nutritional, and hence nongenetic, state (e.g. Alatalo et al., 1990; Pietiäinen & Kolunen, 1993; Schluter & Gustafsson, 1993). Furthermore, it is not entirely clear how heritable variation is maintained in the face of strong selection. In addition to arguments invoking some form of balancing selection (e.g. Roff, 1997), two more simple and plausible explanations for the maintenance of genetic variation in condition are apparent. First, moderate to high heritability estimates could be a methodological artefact, with heritability estimates being inflated by early maternal or environmental effects or by nonadditive genetic variance. Secondly, as suggested in previous studies of other strongly selected, heritable traits (cf. van Noordwijk et al., 1988; Price et al., 1988; Price & Liou, 1989; Alatalo et al., 1990; Thessing & Ekman, 1994; Larsson et al., 1998), selection may be acting primarily on the environmental component of variation in condition, with little or no selection acting on breeding values.

The main goal of this paper was to set out to determine the genetic basis of offspring body condition in the collared flycatcher (Ficedula albicollis) and to test the suggestion that selection on this trait is acting mainly on the environmental component of the phenotype rather than on individual genotypes or breeding values. To this end we analysed 20 years of data involving 20 074 (including parents) individuals from a closely monitored population of collared flycatchers breeding on the island of Gotland, Sweden. To determine the relative importance of additive genetic, nonadditive genetic, and maternal/early environmental contributions to offspring condition, we first subjected the data to a series of variance component estimation procedures based on an ‘animal model.’ These techniques make maximum use of information in multigenerational pedigrees and produce less assumption-burdened estimates of genetic variability than traditional parent-offspring or full-sib analyses (e.g. Knott et al., 1995; Lynch & Walsh, 1998). In contrast to earlier studies of the inheritance of offspring condition in birds, the animal model approach allowed us, for the first time, to separate genetic (both additive and nonadditive) effects from early environmental (pre cross-fostering) effects. Furthermore, by repeating the analyses for the data before (fledglings) and after (adults recruiting to the breeding population) selection, we were able to assess the effect of natural selection on the different causal components of variance (viz. additive genetic and environmental variance) and heritability. We also assess the suggestion (Alatalo et al., 1990) that selection acts mainly on the environmental, rather than on the genetic, components of variation in this trait by comparing the magnitude of selection differentials on phenotypic and breeding values.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The study species

The collared flycatcher is a small, socially monogamous, insectivorous hole-nesting passerine bird, which inhabits deciduous woods of central Europe and the Baltic islands of Gotland and Öland. Adults overwinter in central Africa, and arrive at breeding grounds in late April–early May, where they establish territories and lay a single clutch of, on average, six eggs. Eggs hatch after about 12 days of incubation, and nestlings are fed (mainly with caterpillar larvae) by both parents until fledging, which usually occurs 2 weeks after hatching. By the time of fledging, the nestling tarsus has attained its final size (Alatalo et al., 1990; Merilä, 1997), and the fledglings have gained large fat reserves and weigh more than the adults (Merilä, 1996). After reaching independence, fledglings undergo a partial moult in the breeding grounds, and start migration to winter areas. Surviving birds return to breed to their natal area, and the first breeding usually takes place in the year after birth. More information on the life history of the species is given in Gustafsson (1989).

The data

Data were collected between 1980 and 1999 as part of the long-term study of the nest-box breeding population on the Swedish island of Gotland in the Baltic Sea. In each year, breeding was monitored in 6–18 different woodlands (the number has increased with time) from early in the breeding season until the last young had fledged. When 11–12 days old, the nestlings were measured for tarsus length with digital callipers (to nearest 0.1 mm) and weighed with a Pesola spring balance to nearest 0.1 g. A condition index was estimated as the residual from a linear regression (see Pärt, 1990 for analysis of linearity) of body mass on tarsus length, so that one unit of relative mass corresponds to a deviation of 1 g from the allometrically expected mass. We note that this procedure may not remove all ‘body size’ dependent variation in ‘condition’ as tarsus length (or any other measure of body size for that matter) is not likely to capture all aspects of body size variation, and hence, part of the measured variation may still reflect individual size differences. At the time of measurement, or a few days earlier, the parents of all offspring were captured and identified (from individually numbered aluminium rings), and all nestlings were provided with individually numbered aluminium rings to enable identification if they were recaptured. See Kruuk et al. (2001) for a full analysis of the genetics of, and selection on, the skeletal component of body size, tarsus length.

Pedigrees were determined by assuming that the parents attending a given nest were the true parents of all offspring in the nest. This assumption is almost certainly correct in the case of the females as no egg dumping is known to occur (Sheldon & Ellegren, 1999), but some error is involved in the determination of paternal pedigrees because of the occurrence of extra-pair paternity. About 15% of nestlings in this population are known to result from extra-pair copulations (Sheldon & Ellegren, 1999), and consequently the paternal pedigrees are likely to be wrong in a corresponding proportion of cases. In the animal model approach adopted in this study (see below), these erroneous paternities could lead to a deflated estimate of additive genetic variance (e.g. Geldermann et al., 1986). However, previous studies of this population have shown that the effect of extra-pair paternity on estimates of heritability are minimal (cf. Meriläet al., 1998). Another potential problem with our analyses involves the pooling of data from both sexes in the same analyses; this was necessary as fledglings cannot be sexed from appearance, and data on sex determined by molecular methods are only available for a small proportion of the population. However, there is no evidence to suggest that males and females differ in fledgling condition in the collared flycatcher (Sheldon et al., 1998), or that selection acts differently on male and female condition (Meriläet al., 1997). Hence, combining data from both sexes for the analyses should not affect the results.

Some of the nestlings in the data were subject to brood size manipulations and cross-fostering experiments (see: Gustafsson & Sutherland, 1988; Merilä, 1997, for details). As brood size manipulations are known to affect fledgling growth and condition (Merilä, 1996, 1997), the average effects of the experiments were accounted for by including brood size manipulation as a fixed effect in the models (see below). For our main analyses, we restricted the data to nonfostered offspring. However, as explained below, offspring from broods involved in cross-fostering experiments were used in part of the analyses to evaluate the importance of pre-manipulation common environment, post-manipulation common environment, and dominance effects on offspring condition. The total number of breeding attempts monitored over the study period was 7575 (28 759 nestlings), but for the reasons detailed below, only 3836 breeding attempts (17 717 nestlings), were included in the analyses of nonfostered offspring. First, some of the nestlings were not measured for tarsus length (for example, all individuals ringed in 1982), and hence were excluded from the analyses as their body condition was not estimable. Secondly, some of the nests were subject to partial clutch size manipulations, in which eggs rather than nestlings were transferred between nests, with the result that it was not possible to distinguish between native and fostered fledglings in a nest. Thirdly, some nestlings were the result of pairings between collared and pied flycatchers F. hypoleuca: these breeding attempts, and any involving known first generation hybrid parents, were excluded from the data.

Genetical analyses

We used a mixed-model analysis of variance based on an ‘animal model’ and restricted maximum likelihood (REML) estimation procedure to quantify the different causal components of variance for nestling condition (Groeneveld & Kovac, 1990; Groeneveld, 1995; Knott et al., 1995; Lynch & Walsh, 1998). Although mixed models have been widely used in animal breeding science, they have rarely, and only very recently, been implemented in the analysis of data from natural populations (but see Réale et al., 1999; Kruuk et al., 2000, 2001; Milner et al., 2000). The animal model expresses the phenotype of each individual i as a sum of fixed and random effects, with the latter comprising a component of additive genetic value and other random effects such as a maternal effect value:

inline image

where yi is the individual’s phenotype, μ is the population mean, bi,j are fixed effects, ai is the individual’s additive genetic value, uij are other random effects and ei is a random residual value. In matrix form, for measurements on many individuals, this gives:

inline image

where y is the vector of phenotypic values, β and u are column vectors of fixed and random effects, respectively, X and Z are the corresponding incidence matrices and e is a vector of residual values (Knott et al., 1995; Lynch & Walsh, 1998). These methods are more flexible and make less assumptions about the data than the conventional models used in estimating quantitative genetic parameters (Shaw, 1987; Lynch & Walsh, 1998). In particular, they have the advantages of allowing for highly unbalanced data sets and the inclusion of fixed effects; also, by exploiting all relationships between individuals in a pedigree, they are considerably more powerful than the conventional models used in estimating quantitative genetic parameters (Sorenson & Kennedy, 1986; Knott et al., 1995; Lynch & Walsh, 1998). The animal model provides estimates of components of variance in a base population that are unbiased by any effects of finite population size, selection or inbreeding in subsequent generations (Thompson, 1973; Sorenson & Kennedy, 1984; van der Werf & Boer, 1990). Because information in any pedigree rarely dates back to a true base population, an assumption concerning the base population is usually made, namely that the first generation of animals with data form the base population; the subsequent analysis will then estimate the components of variance in this generation. If the first generation does consist of selected individuals, the resulting estimates will still apply to that generation, but not to an unselected (‘true’) base population (van der Werf & Boer, 1990). Here, we estimated components of variance, including the additive genetic variance and hence the heritability, using REML-VCE (version 3.2, Groeneveld, 1995), and single trait animal model best linear unbiased predictor (BLUP) estimates of breeding values were obtained using the software package PEST (Groeneveld & Kovac, 1990; Groeneveld et al., 1992).

In our basic model, the total phenotypic variance (VP) in offspring condition was partitioned into its causal components: VP=VA + VEy + VEa + VEn + VR, where VA is the additive genetic variance, VEy, VEa and VEn are the environmental components of variance attributable to year, area and box of rearing (common nest environment) effects, respectively, and VR is the residual variance. Narrow sense heritabilities were calculated from (h2=VA/VP) (Falconer & Mackay, 1996), and the environmental effect variance quantified as the summed effects of different environmental sources of variance and residual variance to total phenotypic variance (E=VEy + VEa + VEn + VR). Year, area and common nest environment were included as random effects in the model because these sources of variation are relevant for estimating heritability in the population: for example, as parents and offspring are necessarily measured in different years, large year-to-year variation would reduce the similarity between parents and offspring and hence the heritability and potential response to selection. However, inclusion of year and area effects as fixed terms did not lead to any significant increases in heritability (h2) estimates. The VCE program returns standard errors for the estimates of variance components and heritability, from which significance was assessed by t-tests. Significance levels for variance components were assessed from z-scores, calculated as the ratio of the estimate to its standard error, and tested against an asymptotic (large sample) standard normal distribution.

Note that a component of variance due to box of rearing will include variance due to both common environment and maternal (or paternal) effects. As most of the parents in our data occur only once, or a few times, and almost never together in more than 1 year, the separation of maternal and common environment effects is difficult. However, we attempted to evaluate the relative importance of maternal vs. common environment effects by splitting the box of rearing term into components because of paternal and maternal identity. In the presence of strong maternal effects, we expected the random effect of maternal identity to capture more of the box of origin variance than the random effect of paternal identity. As a further test of this, we ran a model that included both the box of rearing, as well as maternal and paternal identities as random effects: if maternal or paternal effects were present, part of the variance in nestling condition should be accounted for by maternal and/or paternal identities beyond the effect accounted for by the random effect of box of rearing.

As our data included a large number of full-sib families, we also evaluated the potential significance of dominance variance in condition. Dominance variance will increase the variance between full-sib groups (Falconer & Mackay, 1996), but it is usually not possible to separate this effect from nongenetic effects such as those caused by a common environment. Here, we make use of data from several cross-fostering experiments performed on the population in different years (Gustafsson & Sutherland, 1988; Gustafsson et al., 1995; Merilä, 1996) to test whether the variance between groups of full-sibs is greater than expected after accounting for that due to additive genetic and common nest environment effects. Cross-fostering experiments in this population involved the splitting and reciprocal transfer of broods so that full-sibs were reared apart in two different nest-boxes: one group in the nest-box with their true parents, the other in a foster parent nest-box (see, for example, Merilä, 1996; Merilä & Fry, 1998; Sheldon et al., 1998, for details). Each nest box therefore included nestlings from two full sibships. The animal model for these analyses included – in addition to the random effects of additive genetic, year and area effects, and a fixed effect of brood size manipulation – a random effect for box of rearing and a random effect identifying full-sibships (i.e. box of origin). The existence of any dominance variance for condition should be reflected in this final term, which estimates the variance between groups of full sibs after accounting for additive genetic and common environment variance. However, note that any early common environment effects acting prior to experimental manipulation (up to 2 days of age) will also contribute to this term. A priori, we expect early common environment effects to be minimal, for two reasons: in the pied flycatcher, there is no association between the size of eggs produced by a mother and the subsequent condition at fledging of the offspring (Potti, 1999), and in the current species there is no correlation between condition at 2 days of age and condition at 13 days (Merilä, 1996). Nevertheless, the estimate of the variance component due to nest of origin can only provide an upper limit on the potential contribution of dominance variance.

Selection analyses

Viability selection on survival from fledging to adulthood was assessed from recapture data. During the study period, including 1982 when no tarsus length measurements were made, virtually all collared flycatchers breeding in study plots were captured and checked for aluminium rings. Individuals marked and measured as nestlings, and recaptured as breeding adults were classified as survivors (11.8% of nestlings in the data, with 35.6% of nests containing at least one survivor). All other individuals were assumed to be dead. Although some individuals assumed to be dead may have emigrated outside the study area, the natal dispersal distance has been previously shown to be uncorrelated with body condition index in this population (Pärt, 1990). Hence, the use of local recruitment rate as a criterion for survival is justified.

We quantified the effect of viability selection on variance components by repeating the quantitative genetic analyses on two different sets of data: (i) pre-selection, using data on all (nonfostered) nestlings in the database (with the restrictions detailed above), which estimates the different causal components of variance before most of the selection has taken place; (ii) post-selection, using a restricted data set consisting of only phenotypic measurements on those individuals that returned as adults to the breeding site; this approach is directly analogous to any animal model analysis of a trait expressed only in adults (e.g. Réale et al., 1999; Kruuk et al., 2000; Milner et al., 2000). As the animal model estimates the components of variance in a base population (Sorenson & Kennedy, 1984; Lynch & Walsh, 1998), any difference in the estimates from the two approaches will reflect the difference between the constitution of the total population and that of the subset that then survived to become breeding adults. It therefore provides an estimate of the effects of selection on the additive genetic variance similar to that adopted in standard selection experiments (e.g. Meyer & Hill, 1991), but allowing for the fact that, as a result of continuous immigration into the study area, different generations are distributed at different times throughout the pedigree. We also tested the prediction that, under truncation selection, selection should reduce the additive genetic variance of a trait by a factor of:

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where VA′ is the additive genetic variance after selection, h2 is the narrow sense heritability and k is the factor by which the phenotypic variance is reduced (Falconer & Mackay, 1996, p. 202). Standardized selection differentials for body condition index were estimated using least squares regression of survival on standardized (zero mean, unit variance) trait values (Arnold & Wade, 1984a,b). Before analyses, the individual survival values (0=nonsurvivor, 1=survivor) were divided by the population mean rate of survivorship to give a measure of relative fitness (Arnold & Wade, 1984a,b). The use of standardized trait values and relative fitness in the analyses facilitates the comparison of results with those from other studies, and allows prediction of the selection response from standard quantitative genetic theory. Directional (S) and nonlinear (c) selection differentials were estimated using linear and second order polynomial regressions, respectively. Nonlinear selection differentials reveal the presence or absence of stabilizing (negative sign) or disruptive (positive sign) selection, and were estimated as detailed in Meriläet al. (1997). Although the selection differentials were estimated with least squares methods, their statistical significance was tested with logistic regression analyses (Mitchell-Olds & Shaw, 1987; Meriläet al., 1997). Analyses were performed for each of the study years separately, as well as for the data pooled over years. In each of the analyses, relative fitness was calculated over the entire data set used in the given analysis, but the condition index was standardized within the years. Selection analyses were performed with PROC GLM and PROC GENMOD available in SAS statistical package (SAS Institute Inc., 1996).


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Genetical analyses

Additive and maternal effects variance

A basic model using only nonfostered offspring revealed a significant additive genetic component of variance in offspring condition, corresponding to a heritability of 0.299 (SE=0.026; Table 1a). The significant component of variance due to year in mean offspring condition indicated that the mean offspring condition differed between study years, but this source of variation was small (ca. 7% of the total variance) relative to the variance accounted for by the common environment, or nest-box of rearing, effect (ca. 49% of variation; Table 1a). The variance attributable to differences between areas was negligible (Table 1a). To evaluate whether the effect of common nest environment could be partitioned into maternal and paternal effects, we ran a model in which the term due to nest of rearing was replaced with maternal and paternal identity terms. Both maternal (0.285 ± 0.011) and paternal (0.237 ± 0.009) identities accounted for significant proportions of the variance in offspring condition, although the maternal contribution was significantly larger than the latter (t35 432=3.37, P < 0.001). The summed maternal and paternal effects accounted for approximately similar proportions of the variance in nestling condition as the nest of origin effect did (0.52 and 0.49, respectively). Because of the structure of our data, it is generally not possible to distinguish between parental and nest of origin effects: for parents which bred in only 1 year these quantities are identical. When both the box of rearing, as well as parental identities, were included in the same model, only the first term explained any variance in offspring condition. Hence, we conclude that there was a significant additive genetic contribution and an even more substantial common environment contribution (part of which may reflect parental effects) to fledgling condition. Finally, we note that the results were not sensitive to treatment of year and area effects as random factors: their inclusion in the model as fixed effects resulted in a heritability estimate (h2=0.325 ± 0.025) that was not significantly different from that presented in Table 1a (t35 432=0.71, P=0.48).

Table 1.   Absolute magnitude (var) and relative (var%) contributions of different causal components of variance in condition index in the collared flycatcher. (a) Before selection: all fledglings; (b) after selection: only survivors. Nest-box=identity of common nest environment. Analyses restricted to nonfostered individuals. Thumbnail image of
Dominance variance

As the condition index was subject to directional selection (see below), we tested the suggestion (Crnokrak & Roff, 1995) that the trait should be subject to significant dominance variance contribution. Considering only the data from broods involved in cross-fostering experiments, there was no indication of any significant variance between groups of full-sibs, after accounting for the variance due to additive genetic or nest-box of rearing effects (Table 2). This suggests a negligible contribution (< 4.8%) of dominance effects to the variance in fledgling condition. Variance between nest-box of origin may also have been generated by early common environment, so the lack of significance confirms the expectation that most of the common environment effects in nestling condition were caused by conditions experienced during the late nestling period. The relative contributions of other effects to offspring condition were of similar magnitude to those in the analyses presented in Table 1a, although the heritability estimate from this analysis was somewhat lower (0.219 ± 0.029, Table 2).

Table 2.   Mixed model analyses of variation of condition index using cross-fostering data. Test for presence of dominance variance, which will be reflected in the term ‘box of origin’, identifying groups of full-sibs. See Methods and text for further details. Var=absolute magnitude of variance, var%=variance as a proportion of total phenotypic variance (VP). Thumbnail image of

Effects of selection on additive genetic and environmental components of variance

To test the hypothesis that selection acting on nestling condition affected solely the environmental component of variance, with no effect on the additive genetic component of variance (Alatalo et al., 1990), we compared the results of the analysis presented in Table 1a to those from a similar analysis of a subset of the data, consisting of those individuals that survived to reproduce. This comparison showed that the absolute magnitude of additive genetic variance was significantly lower in the post-selection sample (VA=0.363 ± 0.054), as compared with the pre-selection sample (VA=0.559 ± 0.044; t-test: t19 090=2.84, P=0.005; Fig. 1a). The different environmental components of variance, and, hence, the total phenotypic variance, were also reduced by selection (Table 1b; Fig. 1a), showing that selection was weeding out both genetic and environmental variation in condition. The combined result of these reductions in the variance components was that the heritability – the proportion of the total phenotypic variance attributable to additive genetic variance – did not differ between the pre- and post-selection samples (t-test: t19 090=0.12, P=0.907; Fig. 1b; Table 1b). However, using eqn 1, we found that the actual reduction in VA (to 65.0% of its original value) was much larger than that predicted by theory (to 80.0% of the original value).


Figure 1.  Effects of natural selection on causal components of variance and heritability in condition index: (a) total phenotypic (VP), environmental (VE) and additive genetic (VA) components of variance before and after selection, and (b) heritability of condition index before and after selection. See Table 1 for details of sample sizes and statistical tests.

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Selection on offspring condition

The survival rate varied between 5.6 and 16.5% across years, with an average over the entire study period of 11.3% (Table 3). In most years (11/17), as well as in the entire sample, offspring condition was under significant directional selection, with relatively weaker stabilizing selection on this trait (Table 3). The standardized directional selection differential for the entire sample was 0.234 (SE=0.021), which corresponds well with the previously published estimates of selection on condition in this species based on smaller datasets (Lindén et al., 1992; Meriläet al., 1997). However, these analyses give us little information as to the relative magnitude of selection acting on environmental and genetic components of variation in condition index. Estimates of selection differentials for individual breeding values revealed significant overall selection on breeding values− although the strength of selection on breeding values was consistently less than that observed on the phenotypic values (Table 3; Fig. 2; paired t-tests: linear selection differentials: t16=2.692, P=0.016; nonlinear selection differentials: t16=3.510, P=0.003). In accordance with the results of the variance component analyses, this suggests that the selection is acting both on breeding values and environmental deviations. Finally, it is worth noticing that the intensity of selection acting on phenotypic values varied significantly among the years (directional selection: F17,19 020=9.66, P < 0.001; stabilizing selection: F16,19 056=3.64, P < 0.001), whereas no heterogeneity was detected in this respect in the case of the breeding values (directional selection: F17,19 019= 1.47, P=0.09; stabilizing selection: F16, 19 018=1.38, P=0.13).

Table 3.   Standardized directional (S) and nonlinear (c2) selection differentials on (a) phenotypic and (b) breeding values of offspring condition in a population of collared flycatchers 1980–99 on the island of Gotland. Values in bold are significant after sequential Bonferroni correction (Rice, 1989). Thumbnail image of

Figure 2.  Frequency distributions of phenotypic and breeding values of condition index before and after selection in 1980–98: (a) distribution of phenotypic values before selection together with mean survivorship (circles) for each class of values; (b) distribution of phenotypic values after selection; (c) distribution of breeding values before selection together with mean survivorship (circles) for each class of values, and (d) distribution of breeding values after selection.

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  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

In this paper we have demonstrated the existence of: (i) significant additive genetic variance in fledgling body condition; (ii) significant directional selection on both phenotypic and breeding (genotypic) values for condition; and (iii) a significant reduction in both the genetic and environmental components of variance in the trait as a result of this selection. Although the action of natural selection at a phenotypic level has been demonstrated in numerous studies (e.g. Endler, 1986), this is, to our knowledge, the first study of a wild animal population to show explicitly that natural selection is acting on the genetic component of variation in trait, and that the effect of this selection is to deplete the additive genetic variance in the trait. van Noordwijk (1986) and van Noordwijk et al. (1988) demonstrated that the effect of directional natural selection on body weight in Great tits was to reduce the total phenotypic variance in body weight, and that the heritability of body weight was thus increased in the post-selection sample as compared with the sample before selection. These changes were attributed to a reduced environmental component of variance, suggesting that natural selection was presumably removing the individuals with the largest negative environmental deviations from their breeding values – with no effect on genetic variation. Similar arguments have since been raised in several other studies (e.g. Alatalo et al., 1990; Thessing & Ekman, 1994; Larsson et al., 1998), but the inference has been highly circumstantial: none of these studies have presented data on changes in additive genetic or environmental components of variance, nor have they compared selection on phenotypic and breeding values, respectively. Working with a reduced subset of the data used in this study, Alatalo et al. (1990) argued that the existence of positive directional selection on total body weight (rather than condition) was evidence for selection on environmental deviations. Their reasoning was based on the assumption that variation in body condition does not have any genetic component – an assumption refuted by this and earlier studies (see below). In addition, our results demonstrate explicitly that the selection is not acting only on the environmental component of variance in body condition, but also on actual breeding values.

The results of this study confirm earlier findings of a significant additive genetic component to phenotypic variation in offspring condition in both this (Merilä, 1996; Sheldon et al., 1997; Sheldon, 1999) and ecologically related bird species (Meriläet al., 1999). However, in contrast to these earlier studies, the significant component of additive genetic variance cannot be attributed to pre-manipulation (either pre-hatching, or prior to 2 days of age) common environment or maternal effects as the analyses explicitly accounted for these sources of variation. In fact, our analyses suggest that early maternal and common environment effects on offspring condition are negligible, and that most of the environmental variation in this trait is attributable to conditions experienced during the late nestling period (2–12 days of age). In contrast, there are significant early maternal effects on tarsus length in this species (Kruuk et al., 2001) – possibly reflecting a positive correlation between egg size and tarsus length, as demonstrated in pied flycatchers (Potti & Merino, 1994). Furthermore, the results seem to refute the possibility that significant heritabilities from earlier maternal half-sib analyses (Sheldon et al., 1997; see also Meriläet al., 1999 for discussion of this issue) could have been inflated by dominance variance. The effect of sib-ship identity explained hardly any variation in offspring condition beyond that accounted for by nest of rearing and additive genetic effects, suggesting that dominance contributions to this trait must have been negligible.

It is also worth repeating the point that the moderate to large heritability of offspring condition index seriously undermines its use as an indicator of an individual’s nongenetic nutritional state (e.g. Alatalo et al., 1990; Schluter & Gustafsson, 1993; Potti, 1999). For example, the evidence for a positive maternal effect on clutch size in the collared flycatcher (Schluter & Gustafsson, 1993) is based on the assumption that the covariance between daughter and mother condition is entirely of environmental origin. If condition has a large additive genetic component, the positive maternal effect (M=0.43) detected by Schluter & Gustafsson (1993) could be largely, or even entirely, explained by mothers in good condition producing daughters in good condition due to genetic, and not because of environmental reasons. This considerably weakens the evidence for maternal effects mediated by female condition – and hence for maternal effects on clutch size – in the collared flycatcher. In the same vein, the positive correlation between nestling condition and egg volume reported by Potti (1999) could be because of an additive genetic correlation between egg volume and nestling condition. Hence, the point we wish to stress here is that it is not safe to assume that correlations between a condition index and other traits are driven by environmental factors – body condition index is a heritable trait and a large part of the phenotypic variation in this trait is genetically determined. This is also the conclusion drawn by studies of laboratory populations of rodents, as well as studies of human body mass index (see Introduction).

Our analyses revealed a substantial reduction (ca. 35%) in average levels of additive genetic variance as a result of viability selection in the first year of life, and therefore suggest that 35% of the additive genetic variance for this trait will be removed in each generation. This was more than predicted by theory, although the prediction makes assumptions (e.g. that selection is truncating) that are not fulfilled by the data. Nevertheless, the large reduction in additive genetic variance constitutes a paradox: how are substantial levels of additive genetic variance maintained in the face of such drastic effects of selection? We have little evidence that selection on breeding values varies sufficiently in time or space to counteract the overall tendency to reduce additive genetic variance, or that negative genetic correlations with adult fitness components may act in opposition (Meriläet al., 2001). In the absence of detailed information about mutational variance and the number of loci influencing the trait, we can only repeat the obvious point that strong mutational pressure could explain the maintenance of genetic variability in traits under strong selection. For example, it is currently thought that traits under strong directional selection may capture mutational variance over many more loci than traits subject to weaker selection (e.g. Houle et al., 1996). Rowe & Houle (1996) suggested that the high additive genetic variance in strongly selected secondary sexual traits, which often show condition dependent expression (Andersson, 1994), could be explained by their capture of genetic variability from the presumably many loci determining an individual’s general condition. In accordance with results from studies of life-history traits in Drosophila (Charlesworth & Hughes, 1999), we suggest that the additive genetic variance in condition index could be accounted for by a mutation-selection balance, with the loss of genetic variation in each generation being counteracted by the introduction of new variance due to mutations. In addition, migration from other populations, and the introduction of new genetic material as a result of hybridization with the closely related pied flycatcher may also act as sources replenishing lost additive genetic variance (1.8% of pairings in the population involve backcrosses of fertile F1 hybrid male flycatchers with female collared flycatchers; Veen et al., 2001).

Finally, our data provide interesting insights into the extent of temporal variability in the strength of natural selection in wild. The selection on offspring condition varied in strength from year to year, reinforcing the view that detection of positive natural selection may require long-term data: very different conclusions might have been drawn from single year studies conducted, for example, in 1986 as compared with 1996 (Table 3).

In conclusion, our analysis confirms the results of recent studies which have suggested that offspring body condition is a heritable trait, and not merely an indicator of environmental conditions experienced during the nestling period. However, the moderate heritability is puzzling in light of our demonstration that the directional selection to which condition is subject reduces not only the environmental but also the additive genetic component of variance in this trait. This suggests that the mutational input to variance in condition index must be large, and/or that there must be mechanism(s) that act to protect or counteract the erosion of additive genetic variance in this trait. To this end, further studies area required to understand the details of maintenance of genetic variation in condition index, and other traits similarly subject to directional selection in the wild. In more general terms, our results illustrate how quantitative genetic tools, in particular those developed in animal breeding science, can be used to tackle interesting questions about inheritance and selection in wild animal populations. Finally, we note that the results of our analyses challenge several assumptions of earlier studies of selection and inheritance in wild animal populations, and suggest that selection on the additive genetic component of phenotypic variation may be more widespread than the current literature tends to suggest.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

We thank all the people that have helped in collecting the data during the past 19 years. Sue Brotherstone and Peter Visscher provided advice with the statistical analyses. Our research was financed by the Swedish Natural Science Research Council, Academy of Finland, and the Royal Society, London. LEBK and BCS are Royal Society University Research Fellows.

  1. *present address: Juha Merilä, Division of Population Biology, Department of Ecology and Systematics, PO BOX 17, University of Helsinki, FIN-00014 Helsinki, Finland. Tel.: +358-40-837 41 65; fax: +358-9-191 28701; e-mail:


  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  • 1
    Adams, S.M. 1999. Ecological role of lipids in the health and success of fish populations. In: Lipids in Freshwater Ecosystems (M. T. Arts & B. C. Wainman, eds), pp. 132–160. Springer-Verlag, New York.
  • 2
    Alatalo, R.V., Gustafsson, L., Lundberg, A. 1990. Phenotypic selection on heritable size traits. Environmental variance and genetic response. Am. Nat. 135: 464471.
  • 3
    Andersson, M. 1994. Sexual Selection. Princeton University Press, Princeton, NJ.
  • 4
    Arnold, S.J. & Wade, M.J. 1984a. On the measurement of natural and sexual selection. Evolution 38: 709719.
  • 5
    Arnold, S.J. & Wade, M.J. 1984b. On the measurement of natural and sexual selection: applications. Evolution 38: 720734.
  • 6
    Barsh, G.S., Farooqi, I.S., O'Rahilly, S. 2000. Genetics of body-weight regulation. Nature 404: 644651.
  • 7
    Bensch, S., Källander, H., Lager, R. 1996. Mass and wing length of young black-headed Gulls Larus ridibundus as predictors of age and survival. Ornis Svecica 6: 5766.
  • 8
    Brockmann, G.A., Haley, C.S., Renne, U., Knot, S.A., Schwerin, M. 1998. Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth. Genetics 150: 369381.
  • 9
    Brown, M.E. 1996. Assessing body condition in birds. Current Ornithol. 13: 67135.
  • 10
    Calavas, D., Sulpice, P., Lepetitcolin, E., Bugnard, F. 1998. Assessing the accuracy of a body condition scoring in ewes under field conditions. Vet. Res. 29: 129138.
  • 11
    Chagnon, Y.C. & Bouchard, C. 1996. Genetics of obesity: advances from rodent studies. Trends Genet. 12: 441444.
  • 12
    Charlesworth, B. & Hughes, K.A. 1999. The maintenance of genetic variation in life-history traits. In: Evolutionary Genetics: From Molecules to Morphology (R. S. Singh & C. B. Krimbas, eds), pp. 369–390. Cambridge University Press, Cambridge.
  • 13
    Crnokrak, P. & Roff, D.A. 1995. Dominance variance: association with selection and fitness. Heredity 75: 530540.
  • 14
    Dobson, F.S. & Michener, G.R. 1995. Maternal traits and reproduction in Richardson’s ground squirrels. Ecology 76: 851862.
  • 15
    Endler, J. 1986. Natural Selection in Wild. Princeton University Press, Princeton, NJ.
  • 16
    Falconer, D.S. & Mackay, T. 1996. Introduction to Quantitative Genetics. Longman, New York.
  • 17
    Festa-Bianchet, M. 1998. Condition-dependent reproductive success in bighorn ewes. Ecol. Lett. 1: 9194.
  • 18
    Frisch, R.E. 1988. Fatness and fertility. Sci. Am. 258: 8895.
  • 19
    Geldermann, H., Pieper, U., Weber, W.E. 1986. Effect of misidentification on the estimation of breeding values and heritability in cattle. J. Anim. Sci. 63: 17591768.
  • 20
    Groeneveld, E. 1995. REML VCE, a Multivariate Multi-Model Restricted Maximum Likelihood (Co) Variance Component Estimation. Package, Version 3.2 User’s Guide. Institute of Animal Husbandry and Animal Behaviour, Federal Research Center of Agriculture (FAL), Mariensee, Germany.
  • 21
    Groeneveld, E. & Kovac, M. 1990. A generalized computing procedure for setting up and solving mixed linear-models. J. Dairy Sci. 73: 513531.
  • 22
    Groeneveld, E., Kovac, M., Wang, T.L., Fernando, R.L. 1992. Computing algorithms in a general purpose BLUP package for multivariate prediction and estimation. Arch. Anim. Breed. – Arch. Fur Tierzucht 35: 399412.
  • 23
    Guinet, C., Roux, J.P., Bonnet, M., Mison, V. 1998. Effect of body size, body mass, and body condition on reproduction of female South African fur seals (Arctocephalus pusillus) in Namibia. Can. J. Zool. 76: 14181424.
  • 24
    Gustafsson, L. 1989. Collared flycatcher. In: Life Time Reproduction in Birds (I. Newton, ed.), pp. 75–88. Academic Press, London.
  • 25
    Gustafsson, L. & Sutherland, W.J. 1988. The costs of reproduction in the collared flycatcher. Nature 335: 813815.
  • 26
    Gustafsson, L., Qvarnström, A., Sheldon, B.C. 1995. Trade-offs between life-history traits and a secondary sexual character in male collared flycatchers. Nature 375: 311313.
  • 27
    Henderson B.A. & Wong, J.L. 1996. Control of lake trout reproduction: the role of lipids. J. Fish. Biol. 52: 10781082.DOI: 10.1006/jfbi.1997.0631
  • 28
    Hochachka, W.M. & Smith, J.N.M. 1991. Determinants and consequences of nestling condition in song sparrows. J. Anim. Ecol. 60: 9951008.
  • 29
    Hoffmann, A.A. 2000. Laboratory and field heritabilities: some lessons from Drosophila. In: Adaptive Genetic Variation in Wild (T. A. Mousseau, B. Sinervo & J. Endler, eds), pp. 200–219. Oxford University Press, Oxford.
  • 30
    Houle, D. 1992. Comparing evolvability of quantitative traits. Genetics 130: 195204.
  • 31
    Houle, D., Morikawa, B., Lynch, M. 1996. Comparing mutational variabilities. Genetics 143: 14671483.
  • 32
    Knott, S.A., Sibly, R.M., Smith, R., Møller, H. 1995. Maximum likelihood estimation of genetic parameters in life-history studies using the ‘Animal Model’. Funct. Ecol. 9: 122126.
  • 33
    Kruuk, L.E.B., Clutton-Brock, T.H., Slate, J., Pemberton, J.M., Brotherstone, S., Guinness, F.E. 2000. Heritability of fitness in a wild mammal population. Proc. Natl. Acad. Sci. USA 97: 698703.
  • 34
    Kruuk, L.E.B., Merilä, J., Sheldon, B.C. 2001. Phenotypic selection on heritable size traits revisited. Am. Nat. (in press).
  • 35
    Larsson, K., Van Der Jeugd, H.P., Van Der Veen, I.T., Forslund, P. 1998. Body size declines despite of positive directional selection on heritable size traits in a barnacle goose population. Evolution 52: 11691184.
  • 36
    Lindén, M., Gustafsson, L., Pärt, T. 1992. Selection of fledging mass in the collared flycatcher and the great tit. Ecology 73: 336343.
  • 37
    Lynch, M. & Walsh, B. 1998. Genetics and Analysis of Quantitative Traits. Sinauer, Sunderland, MA.
  • 38
    Maes, H.H., Neale, M.C., Eaves, L.J. 1997. Genetic and environmental factors in relative body weight and human adiposity. Behav. Genet. 27: 325351.
  • 39
    Merilä, J. 1996. Genetic variation in offspring condition – an experiment. Funct. Ecol. 10: 465474.
  • 40
    Merilä, J. 1997. Expression of genetic variation in body size of the collared flycatcher under different environmental conditions. Evolution 51: 526536.
  • 41
    Merilä, J. & Fry, J.D. 1998. Genetic variation and causes of genotype–environment interaction in blue tit body size. Genetics 148: 12331244.
  • 42
    Merila, J., Kruuk, L.E.B., Sheldon, B.C. 2001. Cryptic evolution in a wild bind population. Nature 412: 7679.
  • 43
    Merilä, J. & Sheldon, B.C. 1999. Genetic architecture of fitness and non-fitness traits – empirical patterns and development of ideas. Heredity 83: 103109.
  • 44
    Merilä, J. & Sheldon, B.C. 2000. Lifetime reproductive success and heritability in nature. Am. Nat. 155: 301310.
  • 45
    Merilä, J. & Svensson, E. 1995. Fat reserves and health state in migrant goldcrests Regulus regulus. Funct. Ecol. 9: 842848.
  • 46
    Merilä, J., Sheldon, B.C., Ellegren, H. 1997. Antagonistic natural selection revealed by molecular sex identification of nestling collared flycatchers. Mol. Ecol. 6: 11671175.
  • 47
    Merilä, J., Sheldon, B.C., Ellegren, H. 1998. Quantitative genetics of sexual size dimorphism in the collared flycatcher. Evolution 52: 870876.
  • 48
    Merilä, J., Przybylo, R., Sheldon, B.C. 1999. Genetic variation and natural selection on blue tit body condition in different environments. Genet. Res. 73: 165176.
  • 49
    Meyer, K. & Hill, W.G. 1991. Mixed model analysis of a selection experiment for food-intake in mice. Genet. Res. 57: 7181.
  • 50
    Milner, J.M., Brotherstone, S., Pemberton, J.M., Albon, S.D. 2000. Variance components and heritabilities of morphometric traits in a wild ungulate population. J. Evol. Biol. 13: 804813.DOI: 10.1046/j.1420-9101.2000.00222.x
  • 51
    Mitchell-Olds, T. & Shaw, R.G. 1987. Regression analysis of natural selection: statistical inference and biological interpretation. Evolution 41: 11491161.
  • 52
    Mousseau, T.A. & Roff, D.A. 1987. Natural selection and heritability of fitness components. Heredity 59: 181197.
  • 53
    Van Noordwijk, A.J. 1986. Two stage selection in which the first stage only reduces the environmental variation in body size in the Great tit. In: Acta XIX Congress International Ornithology (Quellet, H., ed.), Vol. II, pp. 1409–1415. University of Ottawa Press, Ottawa.
  • 54
    Van Noordwijk, A.J., Van Balen, J.H., Scharloo, W. 1988. Heritability of body size in a natural population of the great tit (Parus major) and its relation to age and environmental condition during growth. Genet. Res. 51: 149162.
  • 55
    Pärt, T. 1990. Natal dispersal in the collared flycatcher: possible causes and reproductive consequences. Orn. Scand. 21: 8388.
  • 56
    Pietiäinen, H. & Kolunen, H. 1993. Female body condition and breeding of the Ural Owl Strix uralensis. Funct. Ecol. 7: 726735.
  • 57
    Potti, J. 1999. Maternal effects and the pervasive influence on nestling history of egg size in a passerine bird. Evolution 53: 279285.
  • 58
    Potti, J. & Merino, S. 1994. Heritability estimates and maternal effects on tarsus length in pied flycatchers, Ficedula hypoleuca. Oecologia 100: 331338.
  • 59
    Price, T.D. & Liou, L. 1989. Selection on clutch size in birds. Am. Nat. 134: 950959.
  • 60
    Price, T.D. & Schluter, D. 1991. On the low heritability of life history traits. Evolution 45: 853861.
  • 61
    Price, T.D., Kirkpatrick, M., Arnold, S.J. 1988. Directional selection and the evolution of breeding date in birds. Science 240: 798799.
  • 62
    Réale, D., Festa-Bianchet, M., Jorgenson, J.T. 1999. Heritability of body mass varies with age and season in wild bighorn sheep. Heredity 83: 526532.
  • 63
    Rice, W.R. 1989. Analysing tables of statistical tests. Evolution 43: 223225.
  • 64
    Roff, D.A. 1997. Evolutionary Quantitative Genetics. Chapman & Hall, New York.
  • 65
    Roff, D.A. & Mousseau, T.A. 1987. Quantitative genetics and fitness: lessons from Drosophila. Heredity 59: 103118.
  • 66
    Rowe, L. & Houle, D. 1996. The lek paradox and the capture of genetic variance by condition dependent traits. Proc. R. Soc. Lond. B 263: 14151421.
  • 67
    SAS Institute, Inc. 1996. SAS/STAT User’s Guide, Version 6. SAS Institute Inc., Cary, NC.
  • 68
    Schluter, D. & Gustafsson, L. 1993. Maternal inheritance of condition and clutch size in the collared flycatcher. Evolution 47: 658667.
  • 69
    Shaw, R.G. 1987. Maximum-likelihood approaches applied to quantitative genetics of natural populations. Evolution 41: 812826.
  • 70
    Sheldon, B.C. 1999. Revealing quantitative genetic relationships in sexual selection using molecular markers. In: Proceedings of the 22 International Ornithology Congress Durban (N. J. Adams & R. H. Slotow, eds), pp. 1099–1114. BirdLife South Africa, Johannesburg.
  • 71
    Sheldon, B.C. & Ellegren, H. 1999. Sexual selection resulting from extra-pair paternity in collared flycatchers. Anim. Behav. 57: 285298.DOI: 10.1006/anbe.1998.0968
  • 72
    Sheldon, B.C., Merilä, J., Qvarnström, A., Gustafsson, L., Ellegren, H. 1997. Paternal genetic contribution to offspring condition predicted by male secondary sexual character. Proc. R. Soc. Lond. B. 264: 297302.
  • 73
    Sheldon, B.C., Merilä, J., Lindgren, G., Ellegren, H. 1998. Gender and environmental sensitivity in nestling collared flycatchers. Ecology 79: 19391948.
  • 74
    Sorenson, D.A. & Kennedy, B.W. 1984. Estimation of genetic variances from unselected and selected populations. J. Anim. Sci. 58: 10971106.
  • 75
    Sorenson, D.A. & Kennedy, B.W. 1986. Analysis of selection experiments using mixed model methodology. J. Anim. Sci. 63: 245258.
  • 76
    Thessing, A. & Ekman, J. 1994. Selection on the genetical and environmental components of tarsus length in juvenile willow tits (Parus montanus). J. Evol. Biol. 7: 713726.
  • 77
    Thompson, R. 1973. The estimation of variance and covariance components with an application when records are subject to culling. Biometrics 29: 527550.
  • 78
    Van Tienderen, P.H. & De Jong, G. 1994. A general model of the relation between phenotypic selection and genetic response. J. Evol. Biol. 7: 112.
  • 79
    Van Der Werf, J.H.J. & De Boer, I.J.M. 1990. Estimation of additive genetic variance when base populations are selected. J. Anim. Sci. 68: 31243132.
  • 80
    Veen, T., Berge, T., Griffith, S.C., Saetre, E.-P., Bures, S., Gustatssen, L., Sheldon, B.C. 2001. Hybridization and adaptive mate chance in flycatchers. Nature 411: 4550.
  • 81
    White, R.G., Rowell, J.E., Hauer, W.E. 1997. The role of nutrition, body condition and lactation on calving success in muskoxen. J. Zool. 243: 1320.