Molecular Ecology (2008) 17, 545–556
doi: 10.1111/j.1365-294X.2007.03591.x
No evidence for loss of genetic variation following
sequential translocations in extant populations of
a genetically depauperate species
Blackwell Publishing Ltd
S A B R I N A S . TAY L O R † and I A N G . J A M I E S O N
Department of Zoology, University of Otago, PO Box 56, Dunedin, New Zealand
Abstract
Repeated population bottlenecks can lead to loss of genetic variation and normally should
be avoided in threatened species to preserve evolutionary potential. We examined the effect
of repeated bottlenecks, in the form of sequential translocations, on loss of genetic
variation in a threatened passerine, the saddleback (Philesturnus carunculatus carunculatus), a species that has recovered from a remnant population with historically low levels of
genetic variation. Although a slight but nonsignificant loss of alleles may have occurred
between the first-order translocation and the extirpated source population, first-, second-,
and third-order translocated populations had very similar levels of genetic variation to each
other. The most obvious difference among the seven island populations appeared to lie in
allele frequencies with little or no loss of alleles among extant populations. Although
sequential translocations are known to cause loss of variation in genetically diverse species,
our study indicates that genetically depauperate species may be less sensitive to loss of
genetic variation through founder events presumably because the few remaining alleles
are well represented in founding individuals. These results show that ancient bottlenecks
may have a long-term effect on genetic variation, to the extent that contemporary population bottlenecks may leave no appreciable genetic signature. Our results suggest that
subjecting genetically depauperate endangered species to sequential translocations could
be used to rapidly establish new populations without further eroding genetic variation.
Keywords: bottlenecks, drift, genetic variation, Philesturnus carunculatus, saddleback, translocations
Received 20 May 2007; revision received 20 August 2007; accepted 17 September 2007
Introduction
Threatened and extirpated species are frequently translocated to islands and former areas of their range to restore
populations and prevent extinctions (Griffith et al. 1989;
Wolf et al. 1996). However, translocations are often conducted with a small number of founders and populations
may be slow to grow, potentially causing a loss of genetic
variation (Nei et al. 1975; Allendorf 1986; Fuerst & Maruyama
1986). Indeed, translocated populations show lower genetic
variation than their source populations for neutral and
Correspondence: Ian G. Jamieson, Fax: 64 3 479 7584; E-mail:
[email protected]
†Present address: Centre for Applied Conservation Research,
Department of Forest Sciences, University of British Columbia,
2424 Main Mall, Vancouver, BC, CanadaV6T 1Z4.
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
major histocompatibility (Mhc) loci (Miller & Lambert 2004)
and sequential translocations decrease diversity even further
(Stockwell et al. 1996; Broders et al. 1999; Gautschi et al. 2002a;
Lambert et al. 2005). Similarly, species that have naturally
colonized new habitat or go through sequential founding
events show losses in genetic variation relative to source
populations (Clegg et al. 2002; Pruett & Winker 2005),
observations that are substantiated by theoretical models
(Le Corre & Kremer 1998).
Following multiple sequential translocations, a New
Zealand passerine, the threatened South Island saddleback
(Philesturnus carunculatus carunculatus), has made a remarkable recovery to over 1200 birds from just 36 individuals
originating from a single remnant population with historically low levels of genetic variation (Hooson & Jamieson
2003; Taylor et al. 2007). The practice of undertaking secondand even third-order translocations of South Island
546 S . S . TAY L O R and I . G . J A M I E S O N
Historical background
Fig. 1 Locations of South Island saddleback study populations.
saddlebacks from island to island, and its potential to
diminish genetic diversity, has been questioned because it
may reduce the viability of populations over the long-term
(J. Briskie, personal communication). We used the translocation history of South Island saddlebacks to examine some
fundamental evolutionary and conservation biology principles related to loss of genetic variation due to founder
events. Specifically, we examine potential loss of genetic
variation over the course of first, second and third order
sequential translocations from a source population that had
considerably less genetic variation as compared to historical
mainland populations. Unlike previous studies involving
more genetically diverse species, the results revealed little
or no detectable loss of genetic diversity in this genetically
depauperate species. More importantly, modelling scenarios
suggest that future loss of genetic variation was only
likely to occur via drift on small islands with low carrying
capacity.
Saddlebacks belong to the ancient endemic family of New
Zealand wattlebirds (Callaeidae); they are insectivorous
forest passerines that are socially (Heather & Robertson
1996) and genetically monogamous (S. Taylor, S. Boessenkool,
and I. Jamieson, unpublished data). With the introduction
of mammalian predators in the 1800s, South Island saddlebacks were extirpated from the South Island and Stewart
Island by early 1900 (Heather & Robertson 1996) and only
persisted on predator-free Big South Cape Island, off the
southwestern coast of Stewart Island (Fig. 1). This enormous
contraction in range caused substantial loss of genetic
variation in saddlebacks as a species: historic mainland
populations had 143 alleles at 22 loci (n = 24 birds)
compared to 35 alleles at 22 loci (n = 20 birds) in the Big
South Cape Island population (Taylor et al. 2007).
In 1962, ship rats (Rattus rattus) invaded Big South Cape
and the saddleback population rapidly declined (Merton
1975). To prevent their extinction, the New Zealand Wildlife
Service moved 36 saddlebacks to Big (n = 21) and Kaimohu
(n = 15) Islands in 1964 where, in the absence of rats, they
successfully established populations (Merton 1975).
Saddlebacks therefore experienced a second bottleneck in
1964 (but this time a bottleneck that affected the single
remaining population) when just 21 and 15 birds were
moved from Big South Cape, an island that probably had a
population of at least 1000 birds (Hooson & Jamieson 2004).
Since the transfers to Big and Kaimohu Islands, South
Island saddlebacks have been translocated to 18 additional
islands and currently have a combined population of over
1200 individuals (Hooson & Jamieson 2003). A complete,
though complex, history for these island translocations
exists (Lovegrove 1996; Hooson & Jamieson 2003), including
the islands that are part of this study (Fig. 2).
Materials and methods
Sampling
Saddleback populations off the coast of Stewart Island are
located on islands where local Maori undertake customary
harvest of titi or sooty shearwater (Puffinus griseus). Access
to the islands is restricted during the 2-month harvest
period but otherwise prohibited. We gained permission to
collect saddleback blood samples from three islands under
Maori control (Big, Kaimohu, and Putauhinu Islands) and
three islands administered by the New Zealand Department of Conservation (Ulva, Breaksea and Motuara Islands;
Figs 1 and 2). Saddlebacks no longer exist on Big South
Cape Island, so museum toepad samples from 1931 to 1965
obtained for a larger study on historical diversity in saddlebacks (Taylor et al. 2007) were used to assess genetic
variation.
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
G E N E T I C VA R I AT I O N & S E Q U E N T I A L T R A N S L O C AT I O N S 547
Fig. 2 Translocation history for South Island saddleback study populations with source population(s), island area, founding date and size,
and current population size given. Populations for which we had DNA data are in bold.
DNA extraction and microsatellite analysis
DNA was extracted from contemporary blood samples
using proteinase K (10 mg/mL) in a Chelex resin solution
(50 mg/mL; Walsh et al. 1991). DNA was extracted from
museum toepad samples using the QIAGEN DNeasy kit
according to the manufacturer’s instructions. DNA was
amplified using 10 μL polymerase chain reactions (PCRs),
which consisted of 1 μL DNA, 0.5 μm of each primer,
0.8 μm dNTP, 1 μL buffer, 0.5 U Taq DNA polymerase (AB
Gene), an optimized concentration of MgCl2, and for
primers that produced shadow bands, 2.2 μL betaine (5 M)
and 0.2 μL DMSO. The PCR profile was denaturation at
92 °C for 3 min, followed by 35 cycles at annealing
temperature for 30 s, 72 °C for 1 min, and 92 °C for 1 min
followed by one final annealing step for 30 s and extension
at 72 °C for 4 min. DNA fragments were examined on 6–10%
vertical nondenaturing or 6% denaturing polyacrylamide
gels. For denaturing gels, 10 pmols of reverse primer was
radioactively end-labelled in 10 μL reaction volumes
containing 5 μCi of [γ33P-ATP], 2.5 U T4 polynucleotide
kinase (Bioline), and 1× kinase buffer (Bioline). Individuals
expressing all known alleles were run on every gel as size
standards and on nondenaturing gels, molecular rulers (10
bp or 20 bp ladders) were used as additional size standards.
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
To identify polymorphic loci, we screened primer pairs
in two to six populations (including the mainland historic sample) from microsatellite libraries developed for
saddlebacks (two libraries), the closely related kokako
(one library), and avian primers already available in our
laboratory. Additional primer pairs were obtained from published papers and DAD’s birdmarker database (www.
shef.ac.uk/misc/groups/molecol/deborah-dawson-birdmarkers.html) if the loci were polymorphic across many
species or were from related groups (e.g. corvids). Out of 97
loci screened, we identified seven loci polymorphic in
contemporary saddlebacks (Hru6, Pgm1, Pca08, Pca15, K13/
14, Ase18, and CK5A4B; Appendix I) and 22 loci polymorphic in historic samples from the mainland (Taylor et al.
2007). The alleles at one locus were large (K13/14; 278 bp)
and did not amplify for many of the Big South Cape museum
specimens. Consequently, this locus was excluded from all
analyses including Big South Cape Island specimens;
results obtained using seven loci in the contemporary
populations did not alter conclusions reported here (Taylor
2006) and all seven loci were used for analyses that did not
include museum samples (bottlesim models, see below).
Further details on DNA extraction from blood and museum
skins, and microsatellite analysis are described in detail in
Taylor et al. (2007).
548 S . S . TAY L O R and I . G . J A M I E S O N
Data analysis
Deviations from Hardy–Weinberg expectations (HWE;
Fisher’s exact test) and linkage disequilibrium (LD; Fisher’s
exact test) were assessed with genepop version 3.4 (Raymond & Rousset 1995). F-statistics and genetic diversity
measures including the number of polymorphic loci, alleles
per locus, allelic richness (which corrects for differences in
sample size among populations; El Mousadik & Petit 1996),
and expected heterozygosity were calculated in fstat
(Goudet 1995) and genetix version 4.03 (Belkhir et al.
1999). Differences in genetic diversity (number of alleles,
allelic richness, and HE) between each population (n = 21
comparisons per measure of genetic diversity) were calculated using two-tailed Wilcoxon signed-rank tests to allow
for tests paired for loci (Whitehouse & Harley 2001; Hansson
& Richardson 2005; Martinez-Cruz et al. 2007). Differences
in FST values among populations were calculated using the
θ estimator (Weir & Cockerham 1994) in genetix using
1000 iterations. Genic differentiation for each population
pair was calculated in genepop using Fisher’s exact test.
geneloss (England & Osler 2001) was used to estimate the
number of breeding pairs that should be translocated to
maintain the genetic variation found on each of the seven
populations.
Although our primary aim was to examine immediate
loss of genetic variation associated with founder events, we
also modelled loss of genetic variation over 100 years for
each of the six contemporary populations (extirpated population on Big South Cape Island excluded). Simulations
performed in bottlesim version 2.6 (Kuo & Janzen 2003)
used 1000 iterations with a random starting age for all
individuals, random mating with equal sex ratios, and an
estimated expected longevity of 8 and 12 years. Little information on expected longevity exists for saddlebacks;
however, resightings of banded birds and a study begun
in 2000 on Ulva Island with marked individuals indicates
that at least 8 years may be usual and 17 years maximal
(Nillson 1978; I. Jamieson, unpublished data). At low
densities following translocations, saddlebacks can
breed at 1 year of age; however, we used reproductive
maturation at 2 years because it is more common in
established populations (Craig 1994; Armstrong et al. 2005;
I. Jamieson, unpublished data), and more conservative for
this model.
bottlesim uses the population size before the bottleneck
and the population size during the bottleneck to model
loss of genetic variation. We defined the population size
before the bottleneck as the estimated population size of
the source population (Appendix II). The population size
during the bottleneck was given as 75% of the translocated
birds to account for an estimated 25% mortality rate in
the year following translocations (Hooson & Jamieson
2003).
Saddleback populations show density-dependent growth
following introductions (Armstrong et al. 2005; Taylor et al.
2005); therefore, we used the variable population parameter
in bottlesim. The population size in a given year was calculated using a logistic growth equation:
P(t) = K/(1 + Ae–tr), where
A = (K – P0)/P0
P(t) = the population size at time t
P0 = initial population size
K = carrying capacity
r = relative growth rate
A summary of the parameter values used to calculate
annual population size is given in Appendix II. We used a
growth rate (r) of 0.5 per annum, based on census data (I.
Jamieson, unpublished data) and other published studies
(Armstrong et al. 2005), and we included two other growth
rates on either side of this estimate (0.25 and 1.0) to provide
a margin of error and obtain an indication of the sensitivity
of the parameter. In addition to the six populations where
DNA was sampled and allele frequencies estimated, we
implemented simulations for saddleback populations on
three islands with much smaller carrying capacities [Betsy
(6 ha), North (8 ha), and Women’s (8 ha)], using allele frequencies from their source populations, Big and/or Kaimohu
Islands.
Results
HWE and LD
All populations appeared to be in Hardy–Weinberg
equilibrium (P > 0.05). Three locus pairs showed linkage
disequilibrium in two to four populations: Ase 18 and Pgm
1 for Big, Ulva, Motuara, and Putauhinu Islands; Pgm 1 and
6E4 for Big South Cape and Ulva Islands; and Hrμ6 and
Pgm 1 for Ulva and Motuara Islands. Pgm 1 and Ase 18 (but
not 6E4 and Hrμ6) are mapped on the predicted microsatellite map of the passerine genome and are both located
on Chromosome 3, the third largest chromosome (approximately 120 Mb) where they lie at nearly opposite ends (Ase
18 at 23.9 Mb; Pgm 1 at 80.5 Mb; Dawson et al. 2006). Although
well-separated markers on the same chromosome are likely
to segregate randomly and have been proposed for primer
selection (Keller et al. 2001; Dawson et al. 2006), we removed
Pgm 1 from the analyses (a locus involved in all three instances
of linkage disequilibrium) to test whether the analyses were
affected. Removal of Pgm 1 did not affect the results.
© 2007 The Authors
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G E N E T I C VA R I AT I O N & S E Q U E N T I A L T R A N S L O C AT I O N S 549
Table 1 Allelic diversity and heterozygosity (HE, expected) in seven saddleback populations. No significant differences among populations
were detected (Wilcoxon signed-rank tests, P > 0.10)
Population
n
Source Island
Big South Cape
20
First-order translocations
Big
35
Kaimohu
16
Second-order translocations
Putauhinu
15
Ulva
190
Third-order translocations
Breaksea
114
Motuara
135
Polymorphic
loci
No. of
alleles
Mean alleles
per locus
Mean allelic
richness
HE
6
19
3.17
3.03
0.516
6
5
16
15
2.67
2.50
2.63
2.44
0.475
0.379
6
6
15
16
2.50
2.67
2.49
2.58
0.498
0.489
6
6
17
17
2.83
2.83
2.61
2.78
0.461
0.428
Fig. 3 Frequency of alleles at each of six loci (Hru6, Pgm 1, PCA15, Pca08, Ase 18, CK5A4B). Allele frequencies are different in each
populations but few populations have fixed or private alleles.
Genetic variation
Contemporary populations of saddlebacks appear to have
low levels of genetic variation. Of 97 loci screened, 55 were
monomorphic, 35 were unscoreable, and two of the six
polymorphic loci were di-allelic. Genetic variation was
very low across all seven saddleback populations (Table 1)
and is low relative to other threatened species (Frankham
et al. 2002; Jamieson et al. 2006). Sequential translocations
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
did not appear to reduce genetic diversity; there was no
significant difference among populations for numbers of
alleles, allelic richness, and heterozygosity irrespective of
their classification as source, first, second, or third order
translocations (Wilcoxon’s signed-rank tests: all P values
> 0.10; Table 1, Fig. 3). Sample size tended to increase with
translocation order; however, there were no significant
differences in allelic richness or HE, which are robust to
changes in sample size (El Mousadik & Petit 1996). Although
550 S . S . TAY L O R and I . G . J A M I E S O N
Big
Kaimohu
Putauhinu
Ulva
Breaksea
Motuara
Kaimohu
Putauhinu
Ulva
Breaksea
Motuara
0.137*
0.092*
0.220*
0.003
0.124*
0.074*
0.019*
0.115*
0.076*
0.025*
0.055*
0.205*
0.140*
0.076*
0.100*
Big South
Cape
Table 2 Pairwise FST values among six South
Island saddleback populations
0.032*
0.132*
0.029*
0.025*
0.006
0.110*
* Significant at P < 0.05.
Breeding pairs required to maintain genetic variation
during translocations
Fig. 4 geneloss simulations showing the number of alleles
remaining vs. the number of breeding pairs translocated from each
of seven source populations.
geneloss showed that translocations from populations with
low frequency alleles (Big South Cape, Kaimohu, Putauhinu,
and Breaksea) required a larger number of individuals to
maintain genetic variation than translocations from populations with common alleles (Big, Ulva, and Motuara; Fig. 4).
Translocation of 15 breeding pairs appeared to maintain
the genetic variation present in all populations except Big
South Cape, and for Big, Ulva, and Motuara, 10 breeding
pairs appeared to be sufficient (Fig. 4). Populations established with individuals from Big South Cape showed a loss
of alleles even with translocation of 30 breeding pairs, a
result that agrees well with the loss of alleles between Big
South Cape and the six contemporary populations noted
above.
Loss of genetic variation modelled in BOTTLESIM
differences in the number of alleles among populations
were not significant, the source island, Big South Cape, had
five alleles not present in contemporary populations and
similarly, contemporary populations had three alleles not
present in Big South Cape. This suggests that 17 alleles
remain in contemporary birds out of a possible total of 22,
indicating some loss of alleles between the source and
contemporary populations. Importantly, the number of
alleles present in contemporary populations (i.e. the populations available for management) was virtually identical
among first, second, and third order translocations.
Population differentiation
All seven saddleback populations showed different allele
frequencies (Fig. 3) and all pairwise population comparisons
showed significant genic differentiation (P < 0.0001) except
for Ulva and Big Islands (P = 0.21). Similarly, all FST
comparisons between each population pair were significant
except those between Ulva and Big, and Big South Cape and
Breaksea Islands, which had very small FST values (Table 2).
Simulations in bottlesim showed considerable future loss
of genetic diversity in two first order translocated populations on small islands (Big and Kaimohu Islands; 18.7–53.9%
loss of variation for observed number of alleles, effective
number of alleles and HE; Fig. 5, Appendix III) but little loss
in second and third order translocated populations on
larger islands (4–16.9%; Fig. 5, Appendix III). Inclusion of
three small saddleback islands (Betsy, North, Women’s; all
second order translocations) also showed substantial future
loss of genetic variation (32.5–67.9%; Fig. 5, Appendix III),
indicating that carrying capacity (which is related to island
area) predicts loss of genetic variation and allele fixation in
extant populations of saddlebacks but founder size in the
range considered here and translocation order do not (Fig. 5,
Appendix III).
Discussion
Translocations of threatened species to unoccupied habitat
can serve a useful conservation purpose (Griffith et al. 1989)
but their effect on genetic variation may be negative (e.g.
© 2007 The Authors
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G E N E T I C VA R I AT I O N & S E Q U E N T I A L T R A N S L O C AT I O N S 551
Fig. 5 Simulated loss of observed alleles over 100 years for nine saddleback populations. Solid lines, longevity = 12 years, dotted lines,
longevity = 8 years. Growth rates (r = 0.25, 0.50, 1.00) increase from bottom to top within each estimated longevity parameter.
Stockwell et al. 1996; Gautschi et al. 2002a). Theory predicts
that bottlenecks should initially decrease allelic diversity
through random sampling of individuals from the source
population and subsequently through genetic drift (Nei
et al. 1975; Allendorf 1986). Rare alleles are most likely to be
lost after bottlenecks, and genetic drift will most affect
populations that are kept small for long periods (Nei et al.
1975; Allendorf 1986). Most studies investigating sequential
bottlenecks support these theoretical predictions, finding
that translocated populations have lower diversity than
source populations and successive bottlenecks decrease
genetic variation (Stockwell et al. 1996; Broders et al. 1999;
Gautschi et al. 2002a).
South Island saddlebacks showed little evidence for loss
of genetic variation (measured as number of alleles, allelic
richness, and expected heterozygosity) following sequential translocations. Allele frequencies did change but there
were no significant differences in genetic variation among
any of the seven populations. Despite the lack of significant
differences among populations, a few alleles (n = 5) were
probably lost between the original source population (now
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
extinct) and the six extant populations. Although this loss
was not statistically significant, low genetic variation reduces
power to detect such differences and a loss of five alleles
may be biologically relevant. Notably, the number of alleles
present among contemporary populations was virtually
identical on each of the six islands, thus even if differences
among islands had been significant, the effect size was so
small (1–2 alleles) we would still conclude that translocations have not caused a biologically important loss of genetic
diversity in the populations left to be managed. Contrary
to our results, Lambert et al. (2005) reported that significant
genetic changes occurred with sequential translocations in
the North Island subspecies of the saddleback (Philesturnus
carunculatus rufusater). However, closer inspection of their
data indicates that significant changes occurred for allele
frequencies, not loss of alleles for six polymorphic microsatellite loci, a result that agrees well with our data.
A concurrent study of historical South Island saddleback
populations found a 75% reduction in the number of alleles
between museum samples from New Zealand’s South Island
mainland and Big South Cape Island, suggesting that a
552 S . S . TAY L O R and I . G . J A M I E S O N
historic bottleneck, founding event and/or significant drift
on Big South Cape Island produced the low genetic variation observed in contemporary populations of South Island
saddlebacks (Taylor et al. 2007). Current saddleback populations subjected to new bottlenecks through sequential
translocations may show little sensitivity to loss of genetic
variation through founder events because mostly common
alleles remain, and presumably, the average number of
saddlebacks transferred in this study (29 ± 15.44 SD) has
been adequate to conserve these few alleles, as indicated by
simulations in geneloss (see Fig. 4).
Although the six extant populations in our study had
similar levels of genetic variation, most populations showed
significant differences in genic differentiation and FST
values. These differences were primarily caused by differences in allele frequency distributions, a common outcome
of translocations (Fuerst & Maruyama 1986; Williams et al.
2000; Williams et al. 2002), rather than the presence of
unique alleles in individual populations. Population differentiation solely caused by differences in allele frequencies
may not be an important management consideration in
translocated species such as saddlebacks for the following
reasons. First, differences in allele frequencies would be
recent (40 years or five generations at most in saddlebacks)
and probably created by random sampling of individuals
during translocations, not local adaptation to the new habitat. Second, in saddlebacks, the little allelic diversity that
remains appears to have been largely maintained within
each of the six contemporary populations suggesting that
no population has superior potential to adapt to environmental change. Clearly, differences in allele frequencies
among populations can be an important management
consideration for other species. For instance, shad (Alosa
sapidissima) and salmon (Oncorhynchus tshawytscha) show
differences in allele frequencies among populations, a
probable consequence of strong philopatry to natal streams
that may reflect local adaptation worth conserving (Waples
& Teel 1990; Waters et al. 2000). However, transferring
saddlebacks among islands to ensure the presence of all
alleles and identical allele frequencies is probably unnecessary, particularly given the expense and increased risk of
transferring disease.
Translocations may have had little effect on current
levels of genetic variation, but what about losses in the
future? Of the six populations we sampled, Big and Kaimohu appear to be most at risk of losing substantial genetic
variation over the next 100 years. By including three of the
smallest saddleback islands in our modelling, we showed
that carrying capacity (determined by island area) appears
to have the greatest impact on predicted loss of genetic variation. Small islands have limited carrying capacity, which
curtails population size, prolongs bottleneck duration indefinitely, and increases the risk of allelic fixation via drift
(Nei et al. 1975; Allendorf 1986). Additional South Island
saddleback populations that risk future loss of genetic
variation due to drift include Jacky Lee (30 ha), Kundy
(19 ha), and Pohowaitai Islands (27 vegetated ha; D. Scott
personal communication). Future saddleback translocations should be made to large islands, and existing populations on small islands may occasionally require new
migrants (via translocations) to prevent long-term loss of
genetic variation. In this study, we used neutral microsatellite loci because they are relatively easy to develop and
presumably indicate diversity across the genome, but in
future studies it may be useful to examine loss of genetic
variation at specific functional genes such as Mhc loci
(Hansson & Richardson 2005; Westerdahl et al. 2000).
Our research shows that historical bottlenecks may have
a long-term effect on genetic variation, to the extent that
contemporary population-size bottlenecks leave no appreciable genetic signature. To our knowledge, this is the first
study to illustrate that genetically depauperate threatened
species may be less sensitive to further losses of genetic
variation during translocation/bottleneck events than
more genetically diverse species. Clearly, sequential translocations are not ideal for genetically variable species
susceptible to loss of genetic variation through founder
effects. However, in saddlebacks and other genetically
depauperate species, our data suggest that subjecting
endangered species with low genetic variation to sequential translocations and reintroductions to rapidly establish
new populations should minimize risk of extinction due
to stochastic demographic events without further eroding
genetic variation.
Acknowledgements
We thank the Department of Conservation for providing invaluable
logistical and field support, with special thanks to H. Edmonds,
K.-A. Edge, M. Willans, and P. McClelland. C. Bragg helped
arrange trips to the Titi Islands, and we thank the families on Big,
Kaimohu, and Putauhinu Islands for their generous hospitality
and field assistance. Essential fieldwork was undertaken by K.
Hale, K. Beavan, R. Johnston, and L. Tracy who collected samples
on Motuara and Ulva Islands. In the lab, G. Wallis, T. King, J.
Waters, C. Tepolt, and N. Margraf provided helpful assistance. We
are grateful to R. Stoffels for assistance with the logistic growth
models, R. Nilsson for information on the numbers of birds transferred to various islands, H. Spencer for his comments on an earlier
draft, and T. King for compiling the data for Appendix I. Four
anonymous reviewers provided very helpful comments that
improved the paper. Canterbury, Te Papa, and the Australian
Museum generously provided museum saddleback samples from
Big South Cape Island. This research was conducted under University of Otago Animal Ethics permits 74/02 and 87/05 and
funded by the Department of Conservation (contract no. 3576),
Landcare Research (contract no. C09X0503), and University of
Otago. S.S.T. was awarded scholarships from NSERC, University of Otago, and the International Federation of University
Women.
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Journal compilation © 2007 Blackwell Publishing Ltd
G E N E T I C VA R I AT I O N & S E Q U E N T I A L T R A N S L O C AT I O N S 553
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© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
Ninety-seven microsatellite loci screened for genetic variation in saddlebacks. Amplification results refer to contemporary samples. Codes: C, contemporary; H, historic; P, polymorphic;
M, monomorphic; U, unscorable/no product. Where multiple loci are listed, the number of individuals screened is given as the mean per locus
Locus
No. screened Amplification Species of origin
Reference
ApCo02, ApCo22, ApCo29, ApCo30, ApCo37
Ase18
Ase 64
BBR13
Budex2
CK5A4B
CK1B5D, CK1B6G, CK4A3G, CK5A4D, CK5A5F
Crex1, 2, 4, 6, 7, 8, 9, 11, 12
Dpu16
Escu2, 6
Fhu2
GgaMu128
Hru6
Hru2, 3, 5, 7
Indigo28
K13/14
K1/2, K3/4*, K5/6, K7/8, K9/10*, K11/12, K15/6*
Mcyu4
MJG1, 3, 4, 7
Mme12
Pca5, 7, 9
Pca08, Pca15
Pca01*, Pca02*, Pca03, Pca04, Pca05*,
Pca06, Pca07*, Pca09, Pca10, Pca11, Pca12*,
Pca13*, Pca14*, 1C3, 1F9, 2F9*, 3D5, 4D7, 4F9
Pcc1, 2*, 3, 4*, 5, 6, 7, 8, 9
Pdo5
Pgm1
Pgm2–7
Pocc1*, 6*, 8*
Ppi1, 2
Tm27, 31B, 101, 105
18 C, 16 H
505 C, 44 H
9C
27 C, 11 H
9C
505 C, 44 H
17 C, 10 H
12 C, 8 H
8 C, 11 H
46 C, 10 H
9 C, 11 H
9 C, 34 H
505 C, 44 H
15 C, 2 H
12 C, 19 H
505 C, 44 H
52 C, 20 H
62 C, 44 H
16 C, 11 H
50 C, 44 H
13 C, 22 H
505 C, 44 H
45 C, 13 H
4 M, 1 U
P
U
U
M
P
3 M, 2 U
1 M, 8 U
U
1 M, 1 U
M
M
P
3 M, 1 U
M
P
7M
U
3 M, 1 U
U
2 M, 1 U
P
14 M, 5 U
Scrub jay, Aphelocoma coerulescens
Seychelles warbler, Acrocephalus sechellensis
Seychelles warbler, A. sechellensis
Buff-banded rail, Gallirallus philippensis
Budgerigar, Melopsittacus undulatus
Mariana crow, Corvus kubaryi
Mariana crow, C. kubaryi
Corncrake, Crex crex
Yellow warbler, Dendroica petechia
Reed bunting, Emberiza schoeniclus
Pied flycatcher, Ficedula hypoleuca
Chicken, Gallus gallus
Swallow, Hirundo rustica
Swallow, H. rustica
Village indigo bunting, Vidua chalybeata
Kokako, Callaeas cinerea
Kokako, C. cinerea
Superb fairy-wren, Malurus cyaneus
Mexican jay, Aphelocoma ultramarina
Song sparrow, Melospiza melodia
Blue tit, Parus caeruleus
Saddleback, Philesturnus carunculatus
Saddleback, P. carunculatus
Stenzler & Fitzpatrick (2002)
Richardson et al. (2000)
Richardson et al. (2000)
Manson (2003)
Edwards et al. (1999)
Tarr & Fleischer (1998)
Tarr & Fleischer (1998)
Gautschi et al. (2002b)
Dawson et al. (1997)
Hanotte et al. (1994)
Primmer et al. (1996)
Crooijmans et al. (1997)
Primmer et al. (1995), (1996)
Primmer et al. (1995), (1996)
Sefc et al. (2001)
Hudson (1999)
Hudson (1999)
Double et al. (1997)
Li et al. (1997)
Jeffery et al. (2001)
Dawson et al. (2000)
Lambert et al. (2005)
Lambert et al. (2005), Taylor et al. (2007),
T. King personal communication
27 C, 26 H
12 C, 7 H
505 C, 44 H
52 C, 15 H
70 C, 44 H
15 C
16 C, 6 H
5 M, 2 U
M
P
4 M, 2 U
2 M, 1 U
2U
1 M, 3 U
Saddleback, P. carunculatus
House sparrow, Passer domesticus
Red-capped robin, Petroica goodenovii
Red-capped robin, P. goodenovii
Large-crowned leaf warbler, Phylloscopus occipitalis
Magpie, Pica pica
Tasmanian native hen, Gallinula mortierii
Taylor et al. (2007), T. King personal communication
Griffith et al. (1999)
Dowling et al. (2003)
Dowling et al. (2003)
Bensch et al. (1997)
Martinez et al. (1999)
Bucchan (1999)
*Loci polymorphic in historical mainland specimens. Where several loci are listed, the genotyped individuals (n = 44) at historical polymorphic loci were excluded when calculating the
mean number of individuals screened per locus.
G E N E T I C VA R I AT I O N & S E Q U E N T I A L T R A N S L O C AT I O N S 555
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd
Appendix I
556 S . S . TAY L O R and I . G . J A M I E S O N
Appendix II
Parameter values used in bottlesim simulations for six saddleback populations sampled for allele frequencies and three unsampled
populations with estimated allele frequencies (K = carrying capacity)
Population (island area)
Sampled
Big (23 ha)
Kaimohu (11 ha)
Putauhinu (126 ha)
Ulva (270 ha)
Breaksea (170 ha)
Motuara (59 ha)
Unsampled
Betsy (6 ha)
North (8 ha)
Women's (8 ha)
Population size
of source island*†
No. of birds
translocated
(founder size)
No. of
survivors
assuming 25%
mortality (P0)
K
Basis for K
1000
1000
80
80
140
60
21
15
65
30
59
26
16
11
49
22
44
20
80
30
350
750
472
164
Census
Census
Vegetated area × 0.36 ha/bird
Total area × 0.36 ha/bird
Total area × 0.36 ha/bird
Total area × 0.36 ha/bird
80
67
71
16
19
20
12
14
15
17
22
22
Total area × 0.36 ha/bird
Total area × 0.36 ha/bird
Total area × 0.36 ha/bird
*Data from Hooson & Jamieson (2003).
†Where there were two source islands, we added the proportions of each source island population that was equivalent to the proportion of
birds translocated from that island. For example, Motuara Island was founded with 26 birds. One bird (1/26) came from Jacky Lee Island
(population = 65) and 25 birds (25/26) came from North Island (population = 60). We estimated Motuara population size prior to the
bottleneck as approximately 60 birds (65 × 1/26 + 60 × 25/26).
Appendix III
Loss of genetic variation over 100 years for nine saddleback populations on islands varying in area. The most conservative model showing
the greatest loss of genetic variation is presented where saddleback average longevity was set to 8 years and growth rate was set to 0.25
Big
(23 ha)
Observed number of alleles
t=0
2.57
t = 100 years
2.09
% variation retained
81.3
Effective number of alleles
t=0
2.00
t = 100 years
1.62
% variation retained
81.4
He
t=0
0.45
t = 100 years
0.32
% variation retained
71.8
Fixation probability
Hru6
0.01
Pgm1
0.02
6E4
0.06
3B6
0.29
K13/14
0.25
Ase18
0.25
Ck5A4B
0.21
Kaimohu
(11 ha)
Putauhinu
(126 ha)
Ulva
(270 ha)
Breaksea
(170 ha)
Motuara
(59 ha)
Betsy
(6 ha)
North
(8 ha)
Women's
(8 ha)
2.43
1.55
63.6
2.43
2.28
93.7
2.65
2.48
93.4
2.67
2.50
93.6
2.71
2.37
87.1
2.50
1.40
56.1
2.52
1.52
60.3
2.52
1.53
60.6
1.78
1.31
73.8
1.88
1.79
95.0
1.96
1.86
94.8
1.89
1.82
96.0
2.04
1.73
85.0
1.93
1.24
64.1
1.94
1.31
67.3
1.94
1.31
67.5
0.39
0.18
46.1
0.43
0.40
93.4
0.44
0.41
92.8
0.44
0.41
93.0
0.40
0.33
83.1
0.43
0.14
32.1
0.43
0.17
40.0
0.43
0.17
40.5
0.50
0.22
0.56
0.33
0.33
N/A
0.51
0.00
0.00
0.00
0.00
0.21
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.08
0.06
0.21
0.51
0.17
0.45
0.43
0.56
0.72
0.72
0.71
0.69
0.32
0.34
0.43
0.65
0.64
0.62
0.61
0.31
0.32
0.46
0.64
0.62
0.63
0.60
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd