Animal Conservation. Print ISSN 1367-9430
Is lack of evidence of inbreeding depression in a threatened
New Zealand robin indicative of reduced genetic load?
R. J. Laws & I. G. Jamieson
Department of Zoology, University of Otago, Dunedin, New Zealand
Keywords
bottleneck; inbreeding depression; juvenile
survival; lethal equivalents; Petroica australis;
purging.
Correspondence
Ian G. Jamieson, Department of Zoology
University of Otago, 340 P.O. Box 56,
Dunedin, 9054, New Zealand. Tel: +64 3
4797 608; Fax: +64 3 4797 584
Email: [email protected]
Received 20 May 2010; accepted 21 July
2010
doi:10.1111/j.1469-1795.2010.00388.x
Abstract
Continuous inbreeding exposes deleterious recessive alleles to selection and can
thereby lead to partial purging of the genetic load and reduced inbreeding depression.
Purging has been well documented in experimental laboratory populations, but
evidence of reduced inbreeding depression due to purging in wild populations is
largely lacking. This study examines the inbreeding load associated with juvenile
survival at a protected island site of a bottlenecked population of the Stewart Island
robin Petroica australis rakiura. Based on a complete pedigree of the island
population, we found little evidence that inbreeding coefficients explained any
additional variation in juvenile survival, once demographic factors such as the effects
of density, timing of fledging and age of mother were taken into account. Lethal
equivalents, a standardized measure of the strength of inbreeding depression, were
close to zero (B= 0.24, 95% CI=!1.92–1.04, n= 326) and lower than that
documented for an island population of a widespread congener (B= 6.71, 95%
CI=!0.66–14.08, n= 238) and for several other species for which significant
inbreeding depression was detected (B= 1.30–7.47). There are several reasons as to
why studies can fail to detect pedigree-based inbreeding depression in wild populations, but evidence presented here of low lethal equivalents and relatively high
survival of both inbred and non-inbred juveniles are consistent with a population
that has undergone partial purging of its genetic load during historical population
bottlenecks. Although our study does not imply a complete absence of inbreeding
depression, it is one of the first studies of a wild population where weak inbreeding
depression for juvenile survival appears to be associated with a prolonged bottleneck.
Introduction
Inbreeding depression is one of the factors that can increase
the risk of extinction of small populations (Frankham,
Ballou & Briscoe, 2002). Recent studies of inbreeding in
wild populations have found significant differences across
species in the magnitude of inbreeding depression (Keller &
Waller, 2002). Inbreeding depression can be environmentally sensitive in wild populations (Crnokrak & Roff, 1999;
Armbruster & Reed, 2005), but all else being equal, its
overall magnitude is primarily determined by the genetic
load of the population (Kruuk, Sheldon & Merila, 2002).
The genetic history and structure of a population, in
particular its historical size, can impact significantly on the
genetic load (Hedrick, 1994; Crnokrak & Barrett, 2002). A
population’s genetic load can be reduced through the
process known as purging, which occurs when increased
homozygosity resulting from inbreeding exposes recessive
deleterious alleles to natural selection. Therefore, further
inbreeding would result in minimal reduction in fitness
(Kimura, Maruyama & Crow, 1963).
The process of purging itself is not controversial, but
empirical evidence indicating how effective it is in reducing
genetic load in populations is much more contradictory
(Leberg & Firmin, 2008). Ballou (1997) found evidence of
purging in only one of 25 captive mammal populations,
although it was later shown that the analysis lacked statistical power to detect purging when inbreeding depression is
caused by mildly deleterious alleles (Boakes & Wang, 2005).
More recently, Boakes, Wang & Amos (2007) found significant purging in 14 out of 119 zoo populations, but the
overall change in inbreeding depression due to purging
averaged across all populations was o1%. Crnokrak &
Barrett (2002) found more evidence of purging in 28 experimental studies involving mainly selfing plants and sib–sib
matings in mammals. The one feature that many of these
laboratory and captive studies share is that the rate of
inbreeding is often intense. Purging, on the other hand, is
thought to be more effective when the rate of inbreeding is
slow and applied over a prolonged period (Bijlsma, Bundgaard & Boerema, 2000; Day, Bryant & Meffert, 2003;
Swindell & Bouzat, 2006a; Demontis et al., 2009), as might
occur in a wild population subjected to a prolonged bottleneck. Few studies of animals in the wild, where pedigrees are
difficult to maintain, have examined the link between the
magnitude of inbreeding depression and a population’s
c 2010 The Authors. Animal Conservation "
c 2010 The Zoological Society of London
Animal Conservation 14 (2011) 47–55 "
47
Inbreeding depression in a bottlenecked population
R. J. Laws and I. G. Jamieson
historical size, genetic structure and ultimately its genetic
load.
Critical to resolving this debate about the significance of
purging in wild populations is the ability to measure
differences in the magnitude of inbreeding depression
among populations. Given that the log of overall fitness (or
a major component such as survival) is expected to decline
linearly with increases in the inbreeding coefficient f, the
slope of this relationship (!B) serves as an estimate of the
population’s inbreeding load or lethal equivalents, defined
as the number of deleterious genes per haploid genome
whose cumulative effect is equivalent of one lethal gene
(Keller & Waller, 2002). Therefore, lethal equivalents can be
used as a standardized measure of inbreeding depression,
and were first calculated by Morton, Crow & Muller (1956)
using a linear regression approach, (equation 1), where Sf is
the probability of survival at f = 0.25 and S0 is the probability of survival at f = 0, with 2B equal to the number of
lethal equivalents per diploid organism.
B ¼ ! lnðSf =S0 Þ=f
ð1Þ
This method was improved upon by Kalinowski &
Hedrick (1998) who described a non-linear maximum likelihood estimation for modelling relationships between survivorship and inbreeding. More recently, Armstrong &
Cassey (2007) pointed out several advantages of using
generalized linear mixed models (GLMM) to estimate B.
The aim of the present study is twofold. First, to use
pedigree data to calculate inbreeding coefficients and lethal
equivalents to determine the inbreeding load on a key lifehistory trait (juvenile survival) in a reintroduced island
population of Stewart Island robins Petroica australis rakiura, a New Zealand forest passerine with a highly reduced
range and a prolonged population bottleneck of o500
individuals. Second, to compare this estimate with that from
a previously published study of a reintroduced island
population of the closely related North Island robin Petroica longipes, which has a much larger range and a population
estimated at 10 000 birds (Jamieson et al., 2007). We also
compare lethal equivalents for New Zealand robins to those
published for several other wild populations of birds. By
doing so, we examine possible links between a historical
bottleneck, reduced genetic load and reduced inbreeding
depression in Stewart island robins.
Methods
Study population
Robins on the North, South and Stewart Islands of New
Zealand were considered to belong to the same species P.
australis (Higgins & Peter, 2002), but the North and South
Island subspecies have now been given a separate species
status (Holdaway, Worthy & Tennyson, 2001; Miller &
Lambert, 2006). Stewart Island robins have been isolated
from South Island robins at least since the last glaciation
over 10 000 years ago (Suggate, Stevens & Te Punga, 1978).
The range and population size of Stewart Island robins
48
declined drastically with the arrival of Pacific rats Rattus
exulans around 400 years ago and continued to decline with
the serial introduction from 1800s onwards of two more
species of rats, feral cats and brushtail possum Trichosurus
vulpecula (Harper, 2009). There are only three sub-populations of robins remaining on Stewart Island, all confined to
Leptospermum swamp scrubland. Although not the preferred habitat of robins, the wetter Leptospermum scrub has
a lower density of mammalian predators compared to other
forest types, but it only accounts for c. 1% the historical
available habitat (Harper, 2009). There are approximately
200–300 breeding-age individuals in total (K. Ludwig, pers.
comm.), and the population shows signs of a genetic bottleneck with low overall microsatellite diversity (observed
heterozygosity = 0.48) (Jamieson, 2009).
Because of the decline in the Stewart Island robin population, the Department of Conservation reintroduced 25
robins in 2000–2001 to Ulva Island (257 ha), where ship rats
(Rattus rattus) had previously been eradicated in 1996. Ulva
Island is located in Paterson Inlet and over 20 km from the
nearest mainland robin population. Survival and reproductive success of robins on Ulva Island have been closely
monitored since their release and a complete pedigree of all
individuals is available. This reintroduced island population
where the confounding effects of exotic predators are absent
thereby provides an ideal opportunity to examine fitness
effects of recent inbreeding in a population that has a history
of a prolonged bottleneck.
Measuring inbreeding and juvenile survival
Robins are naturally inquisitive toward humans and we take
advantage of this trait by training fledglings to approach the
sound of a researcher clapping hands to receive a mealworm. In addition, when fed a mealworm the male calls his
mate off the nest during the incubation stage to feed her. By
following the female back to the nest, we are able to find the
nests of all breeding pairs. Robins on Ulva Island have a
modal clutch size of two (1% of nests with one egg, 92%
with two eggs, 7% with three eggs; n = 82) (Laws, 2009).
Offspring are banded either in the nest (if reachable)
3–4 days before fledging or caught with baited traps as
recent fledglings still being fed by their parents.
Their natural inquisitiveness and mealworm training also
mean robins have a high resight probability (Armstrong &
Ewen, 2002). A marked grid system of 100 & 100 m squares
was used to systematically search the island one week before
the beginning of each breeding season, where a researcher
hand-clapped over a 15-min interval to attract any birds in
the vicinity. The entire island was also extensively surveyed
over the following five months during nest monitoring. The
nearest point to the mainland is 800 m, but dispersing
juvenile robins are reluctant to fly across open spaces of
more than 100 m (Richard & Armstrong, 2010), and no
banded robins have ever been sighted on the adjacent mainland where monitoring has been conducted (B. Beaven, pers.
comm.). For the purposes of estimating survival, any
individuals that were not resighted during the study were
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Animal Conservation 14 (2011) 47–55 "
R. J. Laws and I. G. Jamieson
considered to have died. Juvenile survival is calculated from
the fledging (October–January) to the beginning of the
subsequent breeding season (mid-September). Robins breed
in their first year at which time sex can be determined based
on plumage and behaviour.
Breeding pairs on Ulva Island and elsewhere are genetically monogamous, with extra-pair fertilizations extremely
rare (Taylor, Bossenkool & Jamieson, 2008); therefore, the
attending adults at the nest were presumed to be the genetic
parents. Six of the 12 genetic founders on Ulva Island were
offspring from marked birds in the source population, and
included three pairs of nest mates (Jamieson, 2010); all of
this information was integrated into the pedigree database.
Pedigrees and inbreeding coefficients were constructed using
the program PEDSYS (South-west Foundation for Biomedical
Research, San Antonio, TX, http://www.sfbr.org). Individuals at the top of the pedigree with no known parents were
assigned inbreeding coefficients (f) of 0; hence, all f values
are relative to the base population. To avoid underestimating the true level of inbreeding, only juveniles for whom
both sets of grandparents were known or were known to
have closely related parents (i.e. greater than first cousins,
f40.0625) were included in the analysis.
Construction of GLMMs
The effect of inbreeding on probability of juvenile survival
was modelled using generalized linear mixed modelling
(GLMM) (Bolker et al., 2008), within an Akaike information criteria and model averaging framework (AIC-IT)
(Burnham & Anderson, 2002). We followed Freckleton
(2010), however, by undertaking preliminary data exploration to identify the possible collinearity among a number of
demographic variables. Collinearity among predictor variables can be a problem in model selection and lead to
unreliable parameter estimates (Freckleton, 2010). Removing one of two positively correlated predictors (e.g. fledging
period and clutch number; density and year; age and breeding experience) yielded a sub-set of variables that could
potentially impact on survival of juveniles. The final set of
variables included fledging period (early or late based on the
median fledging date for that year), density (number of
breeding pairs during birth year of juvenile) and maternal
age (age of the mother of the juvenile). These factors were
included along with the inbreeding coefficient of the juvenile
(f), as well as the juvenile’s parents (i.e. maternal f and
paternal f), to take into account any additional inbreeding
effects of the parents. Although these three inbreeding
factors are likely to show multicollinearity, AIC-IT methods
are generally robust to collinearity, especially when sample
sizes are reasonable (Freckleton, 2010). Our sample size was
large enough to incorporate multiple inbreeding variables in
our models without causing unreasonable inflations of
standard errors (SE) of model parameters (see ‘Results’).
Finally, because many juveniles shared the same parents,
parental ID was added as a random variable to account for
non-independence of the data. We also included interactions
among all demographic variables and inbreeding in the
Inbreeding depression in a bottlenecked population
global model, although none were important in the final
model set.
Juvenile survival was the response variable, and so the
GLMMs were fitted with a binomial error structure. Global
models were fitted using the package lme4 (Bates & Maechler, 2009) in the program R (R Development Core Team,
2009). Predictors were standardized to a mean of 0 and a
standard deviation of 0.5 as recommended (Gelman, 2008),
using the function available in the R package arm (Gelman
et al., 2009). The global model was then used to generate a
model set of all possible sub-models, using functions available in the R package MuMIn (Bartoñ, 2009). The submodels were ranked by AICc and model averaging using
MuMIn was performed on all models within four AICc of
the best model. We report model-averaged parameter estimates, their unconditional SE (which take into account
model selection uncertainty) and the relative importance of
each parameter to the other parameters in the final model.
To quantify the effect of inbreeding on juvenile survival,
we used model-averaged values to generate conditional
survival estimates at the population mean for all other
parameters. To solve the model, standardized predictors
for other input variables were substituted along with 0
mean, and ðxi ! x!Þ=ð2 & sx Þ for different levels of inbreeding (xi). Standardized fitted probabilities were back-transformed using the equation:
P ¼ 1=ð1 þ 1=ex Þ
ð2Þ
where x is the probability of survival on the logit scale
[‘invlogit’ function is available in the R package arm (Gelman et al., 2009)], to evaluate actual survival probabilities
across a range of f, and to calculate lethal equivalents using
Equation 1.
Results
Juvenile survival
The number of fledglings produced each year on the island
(which was strongly correlated with the number of breeding
pairs, r40.90) increased between 2000 and 2005, followed
by a slight decrease in 2006. Juvenile survival, on the other
hand, decreased steadily from 2001 onwards (Fig. 1). Resighting probability of juveniles that survived their first
winter was very high (99.7%), with only one case of an
individual not encountered during the first breeding season
being resighted the following season. Of the individuals that
survived to their first breeding season, there was no significant difference between the number of males and females
(t=!0.30, d.f. = 6, P= 0.77; Fig. 1).
Pedigree and inbreeding
The pedigree for the population consisted of 12 genetic
founders (seven males and five females) plus eight cohorts
of descendents, with the longest lineage of seven generations. The distribution of inbreeding coefficients of fledglings increased over time (Fig. 2), as the number of breeding
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Animal Conservation 14 (2011) 47–55 "
49
Inbreeding depression in a bottlenecked population
Figure 1 The relationship between juvenile survival (y-axis on left and
bars: open, females; shaded, males; black, unknown sex) and the
number of juveniles produced each season (y-axis on right and line) for
Stewart Island robins on Ulva Island. Note that only two pairs of robins
bred in the first breeding season after the release.
Figure 2 The change in distribution of inbreeding coefficients (f) of
juvenile Stewart Island robins on Ulva Island over the study period.
Size of circles is indicative of the number of individuals for each value
of f and ranges from 1 for the smallest circle to 30 for the largest circle
(total n = 326).
pairs in the population increased and became more related.
A total of 326 juveniles were used to estimate survival to one
year of age, of which 55.8% were inbred, yielding an overall
mean level of inbreeding of f = 0.039 ( 0.054 SD. Most
inbred juveniles fell within the low (04fo0.0625; n = 91)
to moderate (0.0625Zfo0.125; n = 65) category of inbreeding, with fewer juveniles with high (0.125Zfo0.25; n = 15)
or very high (fZ0.25; n = 11) inbreeding coefficients.
Modelling the effects of inbreeding on
juvenile survival
The data dredging function of R produced 64 possible
models from the global model, of which 13 composed the
top model set, that is models within four AICc of the best
model (Table 1). All explanatory variables considered in the
global model were included in at least one model of the top
model set. Density (number of breeding pairs) and fledging
period were common to all models, while f was included in
only five of the 13 top models (Table 1). Model averaging
50
R. J. Laws and I. G. Jamieson
indicated that both density and fledging period were having
the strongest effect on juvenile survival, although density
had a much greater effect size and was more robust (coefficient/SE42) than fledging period (Table 2). By contrast, the
effect size of f on juvenile survival was small, highly variable
(coefficient/SE ) 2) and was the least important relative to
the other variables (Table 2). Whether the mothers of the
juveniles were inbred (Maternal f) was of moderate importance, but the effect size was still small and variable
(coefficient/SE ) 2). After the effects of each of the other
variables are taken into account by model averaging, the
slope of the predicted relationship between inbreeding and
juvenile survival was close to zero (Fig. 3). However,
confidence intervals around the survival estimates for more
inbred birds (e.g. f = 0.25) were wide due to smaller sample
sizes; thus, we could not exclude the possibility that the slope
was slightly negative.
For comparative purposes, we derived lethal equivalent
(LE) values (B, equation 1) for Ulva Island robins based on
GLMM estimates (using model averaging). LE was low with
confidence intervals close to zero (LEGLMM =0.24 95% CI:
!1.92–1.04). We also calculated LE using GLM, an approach similar to that used in previous inbreeding studies;
the value was still close to zero (LEGLM = 0.34 95% CI:
!1.86–1.08) By contrast, reintroduced North Island robins
on Tiritiri Matangi Island experienced moderate inbreeding
depression for juvenile survival, with an effect size nearly 30
times greater than that of Stewart Island robins, although
the estimates are much less certain in North Island robins
with the lower confidence intervals including zero (Table 3).
Lethal equivalents for Stewart Island robins are also low
relative to those reported for other studies of wild bird
populations where significant inbreeding depression has
been detected (LE range from 1.30 to 7.47; Table 3).
Discussion
Our modelling analysis indicated that the effect of f on
juvenile survival was weak and was the least important
relative to the other demographic variables. The estimated
lethal equivalents, a measure of the inbreeding load in the
population, were close to zero. Overall, there was no strong
evidence that recent inbreeding was substantially reducing
juvenile survival for Stewart Island robins reintroduced to
Ulva Island. There are several possible reasons as to why the
effects of inbreeding on juvenile survival appear to be
relatively weak in the Stewart Island robin population.
First, the dataset may have lacked the statistical power to
detect inbreeding depression (Kalinowski & Hedrick, 1999;
Keller, Marr & Reid, 2006). The sample sizes for juveniles
that were the result of close inbreeding (fZ0.125) or very
close inbreeding (f= 0.25) were 26 and 11, respectively, and
are comparable to other avian studies that have estimated
lethal equivalents (Table 3). Further, similarly small sample
sizes did not prevent moderate inbreeding depression in
juvenile survival being detected in the closely related North
Island robin (Jamieson et al., 2007), although confidence
intervals around the estimate of lethal equivalents were
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Animal Conservation 14 (2011) 47–55 "
R. J. Laws and I. G. Jamieson
Inbreeding depression in a bottlenecked population
Table 1 The 13 top-ranked candidate models sorted by corrected Akaike information criteria (AICc) value, with model deviance, AICc, difference
in AICc from the best model (DAICc) and weight (AICw) values of models also indicateda
Model
Deviance
AICc
DAICc
AICw
Fledging period+density+maternal age+maternal f
Fledging period+density+maternal f
Fledging period+density+maternal f+paternal f
Fledging period+density+maternal age+maternal f+paternal f
Fledging period+density+maternal age+maternal f+f
Fledging period+density+maternal age
Fledging period+density+maternal f+f
Fledging period+density+maternal age+paternal f
Fledging period+density
Fledging period+density+paternal f
Fledging period+density+maternal age+maternal f+f+paternal f
Fledging period+density+maternal f+f+paternal f
Fledging period+density+maternal age+f
376
378
377
375
375
380
378
378
383
381
375
377
379
388
388
389
390
390
390
390
391
391
391
391
391
392
0
0.14
1.59
1.83
1.86
2.05
2.22
2.93
3.01
3.53
3.59
3.64
3.92
0.20
0.19
0.09
0.08
0.08
0.07
0.07
0.05
0.04
0.03
0.03
0.03
0.02
a
Models within four AICc of top model were considered the top candidate models.
Table 2 Standardized coefficients of model predictors for juvenile
survival of Stewart Island robins on Ulva Island from 2000 to 2006,
after model averaging of 13 top candidate models (see Table 1)
Standardized
coefficient
Unconditional
Predictor
SE
Relative
importance
Intercept
Density
Date fledged
Maternal f
Maternal age
Paternal f
f
0.843
!0.950
!0.074
!0.195
0.446
!0.163
0.090
0.130
0.277
0.265
0.251
0.297
0.245
0.285
1
1
0.77
0.54
0.32
0.24
Unconditional standard errors and relative importance of each parameter to the other parameters in the final model are also indicated.
larger for North Island robins (Table 3). Using an information theoretic approach, which is sensitive to small sample
sizes (Burnham & Anderson, 2002), there was little evidence
that inbreeding explained any additional variation in juvenile survival, once demographic factors were taken into
account. All studies of wild bird populations that report
lethal equivalents show wide confidence intervals around
these estimates (Table 3), even studies that report severe
inbreeding depression (e.g. Kruuk et al., 2002). By contrast,
confidence intervals around lethal equivalent estimates for
Stewart Island robins were relatively narrow and close to
zero, presumably because inbreeding was not an important
factor in the main model for explaining variation in juvenile
survival.
Second, some studies have shown that mild environmental conditions can reduce the impact inbreeding depression
has on survival (Crnokrak & Roff, 1999; Armbruster &
Reed, 2005). Extreme wet and cold weather events are
common on Stewart Island. Intensive monitoring of robin
nests every 2–4 days over two breeding seasons indicated
that prolonged periods of wet and cold weather can impact
negatively on nest survival, but an analysis failed to detect
any interactions between low temperatures and high rainfall
and f (Laws et al., in press). Juveniles from the same cohort
would have all experienced similar weather conditions on
the island as a whole during their first winter. If mild
weather conditions strongly influenced survival in some
years, then including year as a variable in our initial models
should have detected such an effect.
Third, fitness of life-history traits other than juvenile
recruitment might have suffered from inbreeding depression. A related study where nests were visited regularly over
two breeding seasons to estimate hatching and fledgling
success found no evidence of f negatively affecting these
earlier life-history stages, although there was evidence for an
effect of maternal f (Laws, 2009), indicating that the effects
of inbreeding may be delayed until inbred mothers attempt
to breed. Nevertheless, variation in juvenile survival is an
important life-history component in terms of population
fitness, and inbreeding can significantly reduce juvenile
recruitment rates and thus slow population growth (Mills
& Smouse, 1994). Therefore, a lack of an effect of inbreeding
on juvenile survival, especially when such an effect is more
apparent in the closely related North Island species (Jamieson et al., 2007) demands further explanation.
Fourth, fixation of deleterious alleles due to drift in
populations with historically small size may result in a
population-wide reduction in fitness but little observed
differences between inbred and non-inbred individuals
based on pedigree data (Keller & Waller, 2002; Leberg &
Firmin, 2008). This type of population-level inbreeding
depression referred to as ‘drift load’ (as distinct from
inbreeding depression caused by matings between relatives
or ‘inbreeding load’) can be detected by experimentally
introducing individuals from other populations and examining offspring of mixed parentage for signs of heterosis
(Keller & Waller, 2002; Marr, Keller & Arcese, 2002). Such
an approach is not possible with this sub-species reduced to
a single remnant population. Therefore, we cannot rule out
the fact that fixation of deleterious alleles reduced population-wide fitness in our study population, although the
c 2010 The Authors. Animal Conservation "
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Animal Conservation 14 (2011) 47–55 "
51
Inbreeding depression in a bottlenecked population
R. J. Laws and I. G. Jamieson
survival rate of non-inbred juveniles was high (0.78, 95%
CI: 0.70–0.84; Fig. 3) relative to that of North Island robins
(0.30, 95% CI: 0.23–0.38) (Jamieson et al., 2007). This
suggests that if there is population-wide inbreeding depression in the Stewart Island population, it does not appear to
Figure 3 Juvenile survival as a function of the inbreeding coefficient (f)
for Stewart Island robins on Ulva Island from 2000 to 2006. Points
represent the observed survival rate at each inbreeding level, with
error bars indicating 95% CI from the binomial distribution (sample
sizes above bars); the solid line indicates the predicted survival rate
derived from the final model (after averaging) at the population mean
of all other parameters in the model; dashed lines show 95% CI
calculated using the 95% CI values for the parameter estimate for f
(see ‘Methods’).
be severe or have reduced juvenile survival to the same level
as North Island robins.
Finally, failing to detect inbreeding depression in juvenile
survival of Stewart Island robins may be due to partial
purging of the inbreeding load, via historical inbreeding and
selection (Keller & Waller, 2002; Swindell & Bouzat, 2006b;
Boakes et al., 2007; Bouzat, 2010). We lack direct evidence
of genetic purging, but a history of small population size can
be a strong indicator that purging is likely to have reduced
the genetic load (Bataillon & Kirkpatrick, 2000). Unlike
Stewart Island robins, the central North Island robins (from
where the Tiritiri Matangi Island birds were sourced) consist
of a large (*10 000 birds) and contiguous population (Jamieson et al., 2007). This difference in historic population
size correlates with an apparent difference in inbreeding
depression between the two robins populations (Table 3),
although confidence intervals for lethal equivalents for
North Island robins include zero. Other than the differences
in historical size of the source populations, the two reintroduced island populations are very similar. For example,
fitness and inbreeding data from both were collected over a
period time when the two reintroduced populations were
establishing and growing, although both also showed signs
of density dependence (Armstrong & Ewen, 2002; this
study). Although we lack comparative data on microsatellite
variation, the relatively low estimates of heterozygosity in
the bottlenecked Stewart Island population (Jamieson,
2009) is presumably the result of inbreeding and drift over
time, and therefore provided an opportunity for purging
and reduction of genetic load. This possible explanation of
Table 3 Comparison of lethal equivalents (B, or the slope of the relationship between inbreeding coefficients and log survival), across several
pedigree studies of wild bird populations
Species
Collared flycatchers
Ficedula albicollis
North Island robin
Petroica longipes
Large ground finch
Geospiza magnirostris
Cactus finch
Geospiza scandens
Song sparrow
Melospiza melodia
Great tit Parus major
Stewart Island robin
Parus australis rakiura
Medium ground finch
Geospiza fortis
Lethal equivalents (B)
(95% CI)a
Sample size
f= 0.25
Life-history stage
examined
Method of calculating
lethal equivalents
Study
7.47 (2.60–15.52)
15
Egg to recruitb
Maximum likelihood
Kruuk et al. (2002)
6.71 (!0.66–14.08)c
23
Banding to recruit
GLMM
4.47 (0.8–9.1)
NAd
Banding to recruit
Maximum likelihood
Armstrong & Cassey
(2007)
Keller et al. (2002)
4.27e
4
Banding to recruit
Maximum likelihood
Keller et al. (2002)
1.32e
NAd
Fledgling to recruit
Linear regression
Keller (1998)
1.3
0.24 (!1.92–1.04)
45
11
Banding to recruit
Banding to recruit
GLM
GLMM (model average)
Szulkin et al. (2007)
This study
3
Banding to recruit
Maximum likelihood
Keller et al. (2002)
0e
a
95% confidence intervals for lethal equivalents are provided only in cases where they were reported in the original paper or were calculated from
standard errors.
b
Juvenile survival stage (banding to recruitment) accounted for most of the inbreeding depression (Kruuk et al., 2002).
c
An earlier analysis of the same dataset with a GLM produced lethal equivalents of 4.14 (!0.36–8.65).
d
Value not presented in original article.
e
These are median values calculated over several years.
GLMM, generalized linear mixed model; NA, not applicable.
52
c 2010 The Authors. Animal Conservation "
c 2010 The Zoological Society of London
Animal Conservation 14 (2011) 47–55 "
R. J. Laws and I. G. Jamieson
weak inbreeding depression in Stewart Island robins is
essentially the same as that given by Kruuk et al. (2002) to
explain the opposite pattern of severe inbreeding depression
in a large and outbred population of collared flycatcher
Ficedula albicollis. In this case, the confidence intervals
around estimated lethal equivalents do not overlap between
the two species (see Table 3), suggesting that inbreeding
depression is indeed weak in the Stewart Island robins.
Although theoretically sound, purging has been controversial in conservation biology in the past because of its
association with intentional inbreeding as a potential management tool in captive populations (Templeton & Read,
1983; Kalinowski, Hedrick & Miller, 2000), and its assumed
but unproven association with reduced inbreeding depression in some natural populations (Jamieson, Wallis &
Briskie, 2006). Complete purging of non-lethal recessive
alleles of weak effect in wild populations is considered
unlikely for several reasons (see Keller & Waller, 2002), but
our results do not imply an absence of inbreeding depression, only that it is weak and its expression possibly delayed
to later life-history stages. Overall, the evidence supporting
purging varies widely and there are as yet no clear patterns
as to why some populations experience purging and others
do not (Boakes et al., 2007; Leberg & Firmin, 2008; but see
Bouzat, 2010). Purging should be most effective in populations consisting of several hundred individuals (Glémin,
2003), and when the rate of inbreeding is slow and occurs
over long periods of time (Bijlsma et al., 2000; Day et al.,
2003; Swindell & Bouzat, 2006b; Demontis et al., 2009), a
scenario consistent with some threatened populations (Jamieson et al., 2006; Bouzat, 2010), including Stewart Island
robins.
Conclusion
There are a great many unknowns regarding the stochastic
effects of bottlenecks, and variation in the efficiency of
purging in different environments, to recommend using
intentional inbreeding to purge genetic load in captive
populations (Kalinowski et al., 2000; Leberg & Firmin,
2008; Bouzat, 2010). Similarly, there are several reasons
why studies can fail to detect significant inbreeding depression in wild populations even when complete pedigrees are
available. In the case of Stewart Island robins, we argue that
evidence of weak inbreeding depression is consistent with a
population with low genetic load as a result of a historical
population bottleneck, but we cannot rule out the fact that
the bottleneck resulted in fixation of deleterious alleles
leading to both inbred and non-inbred individuals having
similarly reduced fitness. The limited number of studies
examining the effects of inbreeding depression in wild
populations and the large margins of error associated with
estimating inbreeding effects (when sample sizes are small)
mean that conclusive evidence for genetic purging in wild
populations is difficult to obtain. Because of these issues, the
link between historical rates of inbreeding and the impact of
inbreeding depression on the viability of threatened populations of endangered species remains an important area of
Inbreeding depression in a bottlenecked population
study in conservation biology. Given the current debate
over the effectiveness of purging in wild populations, further
studies of the sort described here are required to advance
our understanding of the underlying processes involved.
Acknowledgements
We thank C. Grueber and S. Nakagawa for statistical
assistance and B. Beaven and P. Dobbins of the Department
of Conservation for logistical support. Funding was provided to I.G.J by the New Zealand Department of Conservation (contract no. 3576) and Landcare Research
(contract no. C09X0503), University of Otago, and the Ulva
Island Trust.
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