Conserv Genet (2008) 9:581–591
DOI 10.1007/s10592-007-9373-4
RESEARCH ARTICLE
Significant genetic admixture after reintroduction of peregrine
falcon (Falco peregrinus) in Southern Scandinavia
Frode Jacobsen Æ Marit Nesje Æ Lutz Bachmann Æ
Jan T. Lifjeld
Received: 15 February 2007 / Accepted: 21 June 2007 / Published online: 27 July 2007
Springer Science+Business Media B.V. 2007
Abstract The peregrine falcon (Falco peregrinus) population in southern Scandinavia was almost extinct in the
1970’s. A successful reintroduction project was launched
in 1974, using captive breeding birds of northern and
southern Scandinavian, Finnish and Scottish origin. We
examined the genetic structure in the pre-bottleneck population using eleven microsatellite markers and compared
the data with the previously genotyped captive breeding
population and contemporary wild population. Museum
specimens between 53 and 130 years old were analyzed.
Despite an apparent loss of historical genetic diversity, the
contemporary population shows a relatively high level of
genetic variation. Considerable gene introgression from
captive breeding stock used to repopulate the former range
of southern Scandinavian peregrines may have altered the
genetic composition of this population. Both the historical
and contemporary northern and southern Scandinavian
populations are genetically differentiated. The reintroduction project implemented in the region and the use of nonnative genetic stock likely prevented the southern Scandinavian population from extinction and thus helped maintain the level of genetic diversity and prevent inbreeding
depression. The population is rapidly increasing in
F. Jacobsen L. Bachmann J. T. Lifjeld
Natural History Museum, University of Oslo, P.O. Box 1172,
Blindern 0318 Oslo, Norway
F. Jacobsen (&)
Department of Biological Sciences, University of Maryland
Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250,
USA
e-mail: frode1@umbc.edu
M. Nesje
The Norwegian School of Veterinary Science, Oslo, Norway
numbers and range and shows no indication of reduced
fitness or adaptive capabilities in the wake of the severe
bottleneck and the reintroduction.
Keywords Admixture Falco peregrinus Microsatellites Museum specimens Population
bottleneck Reintroductions
Introduction
Populations that experience large reductions in effective
size (bottlenecks) can be subjected to increased demographic stochasticity, increased rate of inbreeding, loss of
genetic variation, and fixation of deleterious alleles (Nei
et al. 1975). Such detrimental effects reduce the adaptive
potential of a population and may increase the probability
of extinction (Leberg 1990; Mills and Smouse 1994;
Frankham 1995; Saccheri et al. 1998). Conservation of
genetic diversity is therefore of utmost importance to
species reintroductions (Frankel and Soulé 1981; Soulé
1987) and many strategies have been designed to restore
population sizes and levels of genetic diversity in order to
minimize the negative effects of population bottlenecks. If
the remaining breeding population is very small, supplementary breeding using stock from other sub-populations
may be useful to reduce inbreeding depression.
The peregrine falcon (Falco peregrinus) not only represents a species that experienced a bottleneck, but also one
of the most successful population restoration efforts. Populations across the Northern Hemisphere experienced
severe bottlenecks in the 1960’s and 70’s due to persecution and extensive agricultural use of insecticides such as
organo-chlorines (e.g., DDT, dieldrin, and PCB) and mercury. Bioaccumulation of these chemicals had devastating
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effects on the hatching success of peregrine falcons and
other raptors and resulted in a steep decline in population
sizes (Newton 1979; Ratcliffe 1993). The severity of the
peregrine population decline and the detrimental effects of
the pesticides led to legal protection from persecution,
banning of harmful pesticides, and several reintroductions
and captive breeding programs in Europe and North
America. As a result, peregrine falcon populations are today almost fully recovered in most of their historic range
(Cade and Burnham 2003; Rizolli et al. 2005; Steen 2007).
The peregrine falcon populations in Scandinavia benefited strongly from the above-mentioned restoration efforts.
The historically common raptor (Lindberg 1977; Wille
1977; Steen 1996a) decreased to as few as 17 known pairs
in 1976 (Lindberg et al. 1988; Steen 1996a, b), with 15
remaining in northern Scandinavia and two remaining in
southern Scandinavia. The two southern pairs did not
produce any offspring due to hatching failure, most likely
caused by the detrimental effects of the organo-chlorines.
The initiation of reintroduction projects and the banning of
harmful chemicals such as DDT were instrumental in
helping increase the number of wild peregrine populations
across Fennoscandia, beginning in the early 1980’s. Today,
an estimated 550–600 pairs breed throughout Fennoscandia
(Lindberg et al. 1988; Steen 1996b; Steen 2003), of which
150–200 pairs comprise the contemporary southern Scandinavian population. Accordingly, the peregrine falcon is
no longer considered a threatened species and has been
reclassified as Near Threatened in the Norwegian Red List
(Gjershaug et al. 2006).
A major contributor to the recovery of the southern
Scandinavian peregrine falcon population was the reintroduction project launched in 1974 (Lindberg 1983, 1985;
Lindberg et al. 1988), in which birds from all over Fennoscandia and Scotland were used to initiate a captive
breeding program to prevent extinction and further purging
of genetic variability (Lindberg 1977). During the most
productive phase of the captive breeding project in the late
1980’s (Cade et al. 1988; Järås 1991), the captive population comprised 20 birds from SE Norway (2), SW Sweden (5), N Sweden/Finland (9), and Scotland (4). This
captive population produced 140 young that were released
in southern Scandinavian. The development of polymorphic microsatellite markers by Nesje et al. (2000b) laid the
groundwork for population genetic and phylogeographic
studies on the peregrine falcon and related species and
facilitated a large-scale study on genetic diversity and
population differentiation across peregrine populations
worldwide (Nesje et al. 2000a). A more fine-scaled analysis of the Fennoscandic populations revealed a significant
genetic differentiation between contemporary populations
in northern Fennoscandia (N Sweden and Finland) and
southern Scandinavia (SE Norway and SW Sweden). These
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neighbouring populations may have become isolated during the demographic bottleneck and levels of genetic differentiation may have increased due to genetic drift
(Johnson et al. 2004).
Here we present the analysis of population admixture in
peregrine falcons breeding in southern Scandinavia following the population crash during the second half of the
20th century through typing of DNA microsatellites of
museum specimens. Based on the population demographic
data, we define the historical population prior to 1950 as
the pre-bottleneck population. By comparing novel genotypic data on this pre-bottleneck population (representing
the ancestral indigenous population) with data on the
captive and the wild contemporary populations that have
been published earlier (Nesje et al. 2000a), we address two
major questions. First, what was the level of genetic
diversity in the pre-bottleneck population in southern
Scandinavia and second, to what extent has the use of
exogenous captive breeding birds in the reintroduction
project had an impact on the genetic composition of the
contemporary wild-nesting population in southern Scandinavia? Finally, we discuss the implications of our results on
the conservation of the Scandinavian peregrine falcon and
reintroduction programs for other species.
Material and methods
Sampling and DNA-extraction
We used genotype data presented in Nesje et al. (2000a)
for the captive and contemporary population in southern
Scandinavia and northern Fennoscandia. Blood samples
from all reproducing captive birds (n = 20) had previously
been obtained at the reintroduction project’s facilities near
Gothenburg, Sweden. Similarly, blood samples from the
contemporary wild populations had previously been collected from wild-raised broods in SE Norway and SW
Sweden (southern Scandinavia, n = 44) during 1978–1996
and from wild-raised broods in N Sweden and Finland
(northern Fennoscandia, n = 31) during 1977–1998 (Nesje
et al. 2000a). In the previous study by Nesje at al. (2000a),
individual captive breeding birds were assigned to their
population of origin prior to data analysis. The genotypic
data on the captive and contemporary wild populations thus
needed to be re-organized for the purpose of this study.
For the genotyping of the pre-bottleneck population we
extracted DNA from 38 museum skin specimens (see
Appendix) collected in southern Scandinavia (Norway and
Denmark) between 1877 and 1951. In order to secure
adequate amounts of template DNA without distorting the
integrity of the specimens, we extracted DNA from both
skin tissue (toe pad) and feather tissue (s6) from all
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specimens. The DNA extractions of both tissue types were
performed using a QIAamp DNA Mini Kit (Qiagen), following the manufacturers protocol for tissue DNA extraction. Negative control samples were processed in order to
control for cross-contamination. Contemporary peregrine
falcon DNA had not been processed in the DNA laboratory
of the Natural History Museum, Oslo, for several years
prior to the extraction of the historical samples.
both alleles at a given locus were misread as one repeat
unit shorter or longer without altering the inter-allelic size
difference. For the second method, we followed Hoffman
and Amos (2005) and calculated error rates as the number
of errors per allele and the number of errors per reaction
summarized across loci.
Microsatellite markers and amplification procedures
Deviations from Hardy-Weinberg equilibrium (HWE) and
linkage equilibrium (LE) were assessed using GENEPOP
3.3 (Raymond and Rousset 1995), which uses a Markov
chain method following the algorithm of Guo and
Thompson (1992). Mean number of alleles (AO), allelic
richness (R: a measure of allele number independent of
sample size; see Petit et al. (1998), and mean observed
(HO) and expected heterozygosity (HE) were calculated for
all populations using the computer program FSTAT 2.9.3
(Goudet 1995, 2001). Changes in allelic richness, mean
number of alleles per locus, and mean heterozygosity were
tested using a two-tailed Wilcoxon matched pair test,
which pairs the data by locus. Amount of non-random
mating within populations (FIS) and differentiation among
populations (FST) were estimated using FSTAT and GenAlEx 5.1 (Peakall and Smouse 2001). Unless noted, all
significance tests were performed using the statistical
software package Statistica 6.1 (Statsoft Inc., Tulsa, USA).
Eleven polymorphic dinucleotide microsatellite loci
developed for peregrine falcons were analysed; NVH fp5,
NVH fp13, NVH fp31, NVH fp46-1, NVH fp54, NVH
fp79-4, NVH fp82-2, NVH fp86-2, NVH fp89, NVH fp921, NVH fp107 (Nesje et al. 2000b). The same loci were
also used in the previous study by Nesje et al. (2000a),
allowing direct comparisons of genetic diversity and
changes in population structure. PCR on the historic samples was performed using a PTC-100 thermal cycler (MJ
Research, Inc.), following the protocols described by Nesje
et al. (2000a) with the only exception of lowering the
annealing temperature to 50 C for all markers but locus
NVH fp13 (61 C). PCR products amplified with fluorescently labelled F-primers were run on an ABI 310 automated sequencer (Applied Biosystems, Inc.). Data on
fragment size were collected and analysed using Genescan
2.0 and Genotyper 2.0 software (Applied Biosystems, Inc.).
The low quality and quantity of the source DNA (Hofreiter et al. 2001) may render amplification and scoring of
museum specimens and noninvasive samples such as e.g.,
shed hairs, feathers, or faeces prone to genotyping errors
(Creel et al. 2003; Broquet and Petit 2004; Hoffman and
Amos 2005). In order to ensure the quality and repeatability of our data, two additional replicates of all historic
samples were run applying the same protocols and instruments. These replicates facilitate estimation of genotyping
error rates. Two to three replicates have been proven sufficient to accurately score the genotype in 99% of sampleand locus-combinations as long as the museum or noninvasive samples contain reasonable amounts of suitable
source DNA (Sefc et al. 2003). The genotyping error rates
presented below are based on all three replicates, and
estimated using two different methods. For the first method, we followed Broquet and Petit (2004) and calculated
the rates of allelic dropouts and false alleles. Both sources
of errors may occur during amplification of low quality/
quantity source DNA and cannot be easily monitored
(Broquet and Petit 2004). False alleles (i.e., alleles resulting from replication slippage during amplification
(Schlötterer and Tautz 1992) were first identified after
correcting for shifts in allele size calling occurring between
runs on the ABI instrument, by which the fragment size of
Genetic diversity analysis
Population admixture analysis
We performed a population admixture analysis to assess
the genetic implications of the population restoration efforts and the captive breeding program in particular. In
addition to the peregrine falcons from southern Scandinavia, the use of falcons from northern Fennoscandia and
Scotland in the captive breeding population has likely
influenced the genetic composition of the population.
Based on three decades of nest-site monitoring, dispersal
and recruitment data on the southern Scandinavian population (Steen 2004), we consider the relict indigenous
population (represented by historical pre-bottleneck samples) and the captive breeding population as the major
contributors to the contemporary gene pool.
Admixture methods allow us to estimate admixture
proportions (i.e., the relative genetic contribution from each
source populations) and assign the sampled portion of the
contemporary population to either one of these two known
source populations. Chikhi et al. (2001) recently introduced
a Markov chain Monte Carlo (MCMC) method, implemented in the computer program LEA (likelihood-based
estimation of admixture), which provides estimates of
admixture proportions taking both sampling variance and
genetic drift into account. This MCMC method has been
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shown to perform better than other commonly used methods
in estimation of marginal admixture proportions, especially
with low effective population sizes and low differentiation
of parental populations as is the case here (see below)
(Choisy et al. 2004). We ran the chain for 100,000 steps and
chose the median as the point estimate and 5% and 95%
quantiles as limits of the confidence interval of the posterior
distribution of admixture proportions.
We also used a maximum likelihood method introduced
by Wang (2002), based on a simple admixture model where
two or more parental populations, descendants from a
common ancestral population, evolve independently for a
number of generations until they come into secondary
contact (e.g., in a captive breeding program) and form a
hybrid or admixed population. After the admixture event,
both the parental and hybrid populations evolve independently for a number of generations until the sampling event
takes place. The genetic structure is assumed to be shaped
mainly by admixture and drift. As implemented in the
program LEADMIX 1.0 (likelihood estimator of admixture
proportions) (Wang 2003a, b), this method estimates
admixture proportions p1 and p2 = 1 –– p1 from parental
(source) populations 1 and 2, respectively. Separate estimations were run assuming complete or incomplete sampling of contributing parental populations. Each run was
performed using a full admixture model where the differentiation between sampled parental populations is taken
into consideration. The minimum amount of drift allowed
in the estimation was set to 0.00001.
We used the Bayesian clustering method implemented
in STRUCTURE 2.1 (Pritchard et al. 2000) to test the
validity of our hypothesis that the relict indigenous population and the captive breeding population are the two only
significant contributors to the admixed contemporary
population. Assuming that all populations are in Hardy–
Weinberg equilibrium (HWE) and linkage equilibrium
(LE), this method assigns individuals with a certain probability to one of the pre-specified numbers of genetic
clusters, K, using multilocus genotype data and Markov
chain Monte Carlo (MCMC) sampling. We ran separate
clustering simulations with and without inferring any prior
structure knowledge, and calculated the probabilities for a
range of pre-specified numbers of clusters (1–4). Test runs
showed consistent convergence of values after a burn-in
period of 5 · 104 and all runs were performed using a
chain length of 105 iterations. Simulations were run
assuming an ancestry model that incorporates admixture
and correlated allele frequencies across loci. Simulations
were repeated five times and the results presented as the
mean probabilities for each specified K. After flagging
historical and captive birds as individuals of known
ancestry and all contemporary samples as individuals of
unknown ancestry, we let the program calculate the
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probability of each contemporary sample descending from
the historical indigenous population or the captive breeding
population.
We also employed STRUCTURE to investigate the level of differentiation between the historical and contemporary southern and northern Scandinavian populations. As
before, we ran separate simulations with and without
inferring any prior structure knowledge. Each run was
performed using a burn-in period of 5 · 104 and a chain
length of 105 iterations under an ancestry model with
admixture.
Results
Assessment of genotyping quality of historical DNA
samples
We achieved a 98.8% amplification success of historical
peregrine falcon samples and yielded 35 complete multilocus genotypes representing the ancestral indigenous
southern Scandinavian population. This outcome actually
exceeded that of the previous analysis of high-quality DNA
samples of captive and contemporary peregrine falcons
(97.8% amplification success yielding 16 and 37 complete
multi-locus genotypes from the captive and contemporary
wild population, respectively) (Nesje et al. 2000a).
The combined allelic dropout and false allele rates of all
three replicates of the historical samples were 3.1% and
3.7%, respectively. Based on the method by Hoffman and
Amos (2005), we calculated a genotyping error rate of
6.9% per reaction and 3.8% per allele across all loci. Since
each sample was amplified and genotyped three times, we
feel confident that genotyping errors were minimal in this
study. Overall, these findings highlight the importance of
running multiple replicates in order to obtain accurate
genotypes. In addition to blank negative controls, unique
genotypes across all loci for each individual confirmed that
cross-contamination during lab procedures was negligible.
Genetic variation before and after the demographic
bottleneck
A total of 33 tests for deviations from Hardy-Weinberg
equilibrium (HWE) were performed. As expected when
pooling data from multiple differentiated sub-populations
(see below), the global multi-locus Hardy–Weinberg exact
test for heterozygote deficiency was highly significant
(P < 0.0001). Single locus Hardy–Weinberg tests by population yielded eight significant cases of heterozygote
deficiency, of which only three remained significant after
sequential Bonferroni corrections (Rice 1989) (Table 1).
4.33
2.00
2.45
10.78
38 6
36 5
NVH fp31
NVH fp46-1 38 2
38 3
NVH fp13
NVH fp54
NVH fp79-4 36 12
3.42
NVH fp107
0.65 (0.54)
0.76 (0.79)
0.47 (0.60)
0.55 (0.62)
0.24 (0.24)
0.64 (0.89)
0.29 (0.47)
0.42 (0.43)
0.78 (0.67)
0.87 (0.76)
0.16 (0.19)
HO (HE)
AO
2.94
7.55
5.66
2.99
1.99
10.0
3.83
3.0
4.90
5.85
2.85
R
0.44 (0.44)
0.80 (0.79)
0.60 (0.55)
0.55 (0.54)
0.15 (0.14)
0.65 (0.85)
0.25 (0.37)
0.45 (0.59)
0.79 (0.74)
0.75 (0.75)
0.20 (0.18)
HO (HE )
4.82 ± 0.75 4.69 ± 0.73 0.51 ± 0.07 (0.54 ± 0.07)
18 3
20 8
20 6
20 3
20 2
17 10
20 4
20 3
19 5
20 6
20 3
n
Captive population
AO
2.63
7.55
4.60
2.39
2.00
8.34
3.16
1.97
4.75
4.41
2.89
R
0.64 (0.51)
0.86 (0.85)
0.25 (0.40)
0.48 (0.51)
0.15 (0.31)
0.75 (0.82)
0.39 (0.46)
0.10 (0.14)
0.61 (0.73)
0.55 (0.59)
0.25 (0.25)
HO (HE )
4.64 ± 0.82 4.06 ± 0.65 0.46 ± 0.08 (0.50 ± 0.07)
44 3
43 8
44 5
44 3
41 2
44 11
44 4
40 2
44 5
44 5
44 3
n
Contemporary population
N = number of scored individuals, AO = observed number of alleles, R = allelic richness, HO = observed heterozygosity, and HE = expected heterozygosity. Bolded values indicate significant
heterozygote deficiency (P < 0.05) and underlined values indicate significant heterozygote deficiency following Bonferroni corrections (n = 33 comparisons, critical P = 0.0015)
5.27 ± 0.84 4.69 ± 0.77 0.53 ± 0.07 (0.56 ± 0.07)
37 4
6.35
5.96
NVH fp89
38 7
NVH fp92-1 38 7
Mean ± SE
3.57
3.95
NVH fp82-2 38 5
NVH fp86-2 38 4
5.87
2.44
38 3
NVH fp5
R
n
Locus
AO
Historical population
Table 1 Analysis of genetic variability in the historical (prior to 1950) indigenous, captive breeding, and contemporary (1978–1996) Southern Scandinavian populations of peregrine falcons
(Falco peregrinus)
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The three significant outcomes related to two loci (NVH
fp79-4 (2) and NVH fp92-1 (1)) are most likely a Wahlund
effect resulting when pooling data from different subpopulations, as is likely for the heterogeneous captive
population and the admixed contemporary wild populations. Nevertheless, we cannot entirely rule out the presence of null alleles at these loci. Previous tests performed
on the contemporary wild Scandinavian populations by
Nesje et al. (2000a; 2000b) also detected deviations from
Hardy-Weinberg expectations and resulted in significant
heterozygote deficiency at the five loci NVH fp46-1, NVH
fp79-1, NVH fp79-4, NVH fp82-2, and NVH fp92-1.
However, none of these was significant after Bonferroni
corrections (n = 60, critical P = 0.00085). We found no
evidence for linkage disequilibrium between loci as only
one case remained significant in each population following
sequential Bonferroni corrections (Rice 1989) (n = 55,
critical P = 0.0009).
We detected a total of 69 microsatellite alleles across all
populations and loci (Table 1). Twenty-one alleles were
unique to a particular population (historical (10), captive
(1) and contemporary wild (10)). All but two private alleles
were rare with a frequency below 0.15 and may possibly
have gone undetected in the other populations due to random sampling effects. Several alleles private to the historical population may have been lost due to drift or may
have not been sampled. Conversely, eight alleles shared by
the contemporary population and the captive population
were most likely introduced by exogenous breeding birds
brought in from northern Fennoscandia and Scotland. The
mean number of alleles (AO) (Table 1) was not significantly higher in the historical (AO = 5.27 ± 0.84) than in
the contemporary population (AO = 4.64 ± 0.82; Z = 1.54,
P = 0.11). Allelic richness (R) did not differ significantly
between the historical (R = 4.67 ± 0.77) and the contemporary population (R = 4.06 ± 0.65; Z = 1.60, P = 0.11)
when using the minimum sample size of 16 individuals in
comparison across all three populations. However, when
only comparing the historical and contemporary southern
Scandinavian populations, and thus increasing the minimum sample size to 36 individuals, the data suggest a
reduction in allelic richness (R = 5.25 ± 0.83 and
4.54 ± 0.79 respectively; Z = 1.88, P = 0.06). Neither observed (HO) nor expected heterozygosity (HE) (Table 1)
differed significantly between the historical and the contemporary southern Scandinavian population (Z = 0.98,
P = 0.33; Z = 1.24, P = 0.21, respectively).
Population structure and admixture proportions
The amount of non-random mating was low within all three
populations, although slightly higher in the contemporary
wild population (FIS = 0.14 vs. 0.08 and 0.07 in the historic and captive populations respectively, P > 0.37 for all
pair wise comparisons). The pairwise genetic distances
(FST) were low but significant between all pairs of populations (Table 2). As previously found by Nesje et al.
(2000a), the genetic distance was greatest between the
contemporary southern Scandinavian and northern Fennoscandic populations (FST = 0.075, P < 0.001) and least
between the captive and northern Fennoscandic populations (FST = 0.03, P < 0.001) (Table 2). An analysis of
molecular variance (AMOVA) showed that differences
between the four populations explained only 5% of the
total genetic variation (AMOVA, overall FST = 0.05,
P = 0.001).
Ten alleles present in the contemporary wild population (Nesje et al. 2000a) but not in the historical
population had a mean frequency of 0.072. Eight of
these ten novel alleles (NVH fp5 allele 109; NVH fp13
allele 108; NVH fp31 allele 156; NVH fp54 alleles 110
and 114; NVH fp79-4 alleles 158 and 171; NVH fp89
allele 121) were also present in the captive breeding
population used in the reintroduction project, suggesting
that the captive breeding program introduced new genetic variation to the local gene pool. The relatively
high frequency (paverage = 0.17) by which three of the
above mentioned alleles (NVH fp13 allele 108; NVH
fp79-4 alleles 158 and 171) occur in the captive population may indeed explain how they were introduced
into the contemporary gene pool.
Table 2 Genetic distances between the historical indigenous, captive breeding, contemporary Southern Scandinavian, and the contemporary
Northern Fennoscandic peregrine falcon (Falco peregrinus) populations
Historical
Historical
Captive
0.001
Captive
0.025
S-Scandinavian
0.061
0.046
N-Fennoscandic
0.033
0.018
S-Scandinavian
N-Fennoscandic
0.001
0.001
0.001
0.012
0.001
0.075
All pairwise population FST values (below diagonal) and their respective p values (above diagonal) remained significant after sequential
Bonferroni corrections (n = 6 comparisons, critical P = 0.0083)
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The admixture analysis produced estimates of admixture
proportions suggesting the contemporary gene pool to be
almost entirely a product of the captive breeding population used to reintroduce the peregrine falcon in southern
Scandinavia. Assuming incomplete sampling of contributing parental populations provided similar estimates as
when assuming all contribution parental populations to be
sampled. The genetic contribution (p1) from the indigenous
historical population (P1) was estimated to be as little as
0.6 (95% CI: 0.1–19.6) and 9.1 (95% CI: 0.8–29.3) percent
after the ML and MCMC method, respectively. The
remainder was contributed by the captive population.
The cluster analysis and assignment test provided in
STRUCTURE 2.1 complement the two aforementioned
methods, by allowing ascertainment of the genetic contribution from both of the known source populations as well
as estimating the probabilities of individual representatives
of the contemporary wild population descending from any
of the inferred source populations. The cluster analysis
strongly supports the previous findings and suggests that
the contemporary wild population is almost entirely a
product of the captive breeding program. We obtained
highest likelihood (i.e., closest to zero with very little
variance between runs) of having two genetically distinct
clusters (K = 2) present in our data set when comparing the
likelihoods obtained when inferring a number of genetic
clusters ranging from one to five (Fig. 1A). This result
remained the same regardless of including population
information in the analysis. We therefore only present the
result from simulations done without prior population
information (Fig. 1 A, B). In the assignment test, we designated historical and captive individuals as birds of known
ancestry. The entire historical population and a portion of
the captive population were assigned to one cluster and the
remainder of the captive population and almost the entire
contemporary admixed wild population were assigned to a
second cluster (data not shown). All but three contemporary samples could be assigned to one of the two known
source populations with high probabilities, and only two
contemporary individuals had highest probability of
descending from the historical indigenous population
(P = 0.76 and 0.81, respectively). Three contemporary
individuals sampled in SE Norway showed ambiguous
ancestry, with a roughly equal probability of descending
from either of the two source populations (0.42 < P < 0.54
for descending from the remnant indigenous population).
When including the contemporary northern Fennoscandic samples in the cluster analysis, we obtained highest
probability for three clusters when comparing the likelihoods obtained when simulating a range of genetic clusters
(K = 1–5) (Fig. 2A). This result indicates that the contemporary northern Fennoscandic population constitutes a
third genetic cluster, distinct from both the historical and
587
contemporary southern Scandinavian population (Fig. 2B).
Furthermore, it suggests that the evident genetic differentiation between the historical southern Scandinavian population and the contemporary northern Fennoscandic
population (Table 2) pre-dates both the demographic bottleneck and the subsequent reintroduction. However, recent
drift may account for much of this differentiation as both
the northern and southern Scandinavian peregrine populations were severely reduced in size in the 1970’s.
Discussion
The southern Scandinavian population of peregrine falcons
experienced a series of population bottlenecks in the last
centuries. The initial cause of these demographic bottlenecks was heavy persecution (Newton 1979; Steen 1996a)
from 1850 into the early 1900’s and again during World
War II. However, the greatest population decline followed
World War II with widespread use of bio-accumulating
insecticides such as DDT, which had detrimental effects on
the reproductive success and dwindling population sizes
across Europe and North America (Newton 1979; Ratcliffe
1993). The southern Scandinavian population size remained low but stable for the first half of the 20th-century,
followed by a dramatic reduction to near extirpation (90%
reduction in less than two decades). However, due to legal
protection from persecution, banning of harmful compounds and restoration efforts, the current population size
is even higher than prior to 1950.
This study adds to an increasing number of studies (e.g.,
Wyner et al. 1999; Hansen 2002; DeYoung et al. 2003;
Vernesi et al. 2003) that document the genetic effects of
restocking a heavily bottlenecked population from both
indigenous and exogenous source populations. Still, by
gathering genotypic data on the ancestral indigenous population, this study is one of few able to directly assess
temporal changes in population structure and genetic variability on a historical scale. The population admixture
analysis provides strong evidence for a considerable gene
introgression from the captive breeding population into the
southern Scandinavian population, which consequently
altered the genetic composition of this peregrine population. However, this pattern may be misleading as some
alleles may have gone undetected in the historical population due to random sampling effects. Despite evidence for
significant admixture and its effect on the genetic structure
of the southern Scandinavian peregrine population, the
cluster analysis suggests that factors other than genetic drift
and introgression from the captive population may also be
responsible for the differentiation observed between
southern Scandinavian and northern Fennoscandic peregrine populations today.
123
588
Conserv Genet (2008) 9:581–591
Fig. 1 Structure analysis of
Southern Scandinavian
peregrine falcon (Falco
peregrinus) populations. (A)
Scatter plot showing the
estimated log-likelihood of each
number of inferred genetic
clusters. The optimal number of
clusters, K = 2, was determined
by highest log-likelihood value
and lowest amount of variance
for five independent iterations
per K. (B) Bayesian assignment
of individuals to K = 2 clusters
without using prior population
information. Each bar represents
the estimated posterior
probability of each individual
bird belonging to each of the
inferred clusters. The solid
black vertical lines define the
boundaries between the three
sampled populations
A)
Clusters (K)
-2440
0
1
2
3
4
5
6
-2460
Estimated likelihood
lnP (X/K)
-2480
-2500
-2520
-2540
-2560
-2580
-2600
B)
Clusters (K)
A)
-3050
0
1
2
3
4
5
6
Estimated likelihood
lnP (X/K)
-3100
-3150
-3200
-3250
-3300
-3350
B)
Fig. 2 Structure analysis of Southern Scandinavian and Northern
Fennoscandic peregrine falcon (Falco peregrinus) populations. (A)
Scatter plot showing the estimated log-likelihood of each number of
inferred genetic clusters. The optimal number of clusters, K = 3, was
determined by highest log-likelihood value and lowest amount of
variance for five independent iterations per K. (B) Bayesian
123
assignment of individuals to three genetic clusters of Southern
Scandinavian and Northern Fennoscandic peregrine falcon populations, without using prior population information. The bars represent
the estimated posterior probabilities of each individual bird belonging
to each of the three inferred clusters. The solid white vertical lines
define the four sampled populations
Conserv Genet (2008) 9:581–591
The rapid population recovery, supported by the release
of large numbers of young produced by the captive
breeding population and an increased survivorship of both
chicks and adults in the wild, may explain why the level of
genetic diversity remains higher than that expected from
the demographic trajectory. The high degree of bandsharing between wild-raised broods of peregrines found by
Lifjeld et al. (2002) raised concerns that the post-bottleneck population may be suffering from high levels of nonrandom mating (i.e., inbreeding). However, the recent
population growth and increased reproductive success
(Järås 1991; Steen 1999) suggests that the contemporary
wild peregrine population in southern Scandinavia neither
suffers from inbreeding depressions nor maladapted gene
combinations. Nevertheless, this study demonstrates the
importance of detailed knowledge about the genetic relationship between the source and target populations and
careful planning before implementing a reintroduction
scheme. It is important to keep in mind that no knowledge
existed about the genetic relationship between peregrine
falcon populations considered as stock material at the time
when the Scandinavian reintroduction project was launched. Although the adaptive role of the alleles apparently
lost during the bottleneck is unknown, more ancestral
alleles might have been preserved if a greater proportion of
indigenous birds had been used in the genetic stock. On the
other hand, if not for the early initiation of the breeding
program, using the captive breeding material available at
the time, the stochastic effects of genetic drift might have
been more pronounced and the loss of genetic diversity
more severe.
Similar reintroduction projects in North America used
a highly mixed captive breeding stock of seven subspecies
from around the world to repopulate the species in the
former range of the subspecies F. p. anatum (Tordoff and
Redig 2001). Following a combined release of approximately 7,000 birds in the United States and Canada
(White et al. 2002), the species is today successfully reestablished and increasing in numbers (Cade and Burnham 2003). Albeit, very little is known about the genetic
implications of the admixture of different gene pools and
the future adaptive potential for the species. In a comprehensive appraisal of the genetic bottleneck effects on
Canadian peregrine falcon populations, Brown et al.
(2007) recently found that the genetic structure and levels
of differentiation between two of the three North American subspecies had changed significantly due to the
bottleneck. Similar to the data presented in this study, the
levels of allelic diversity and heterozygosity remained
unchanged (but low) despite the apparent changes in
population structure (Brown et al. 2007). A direct comparison of these two studies, facilitated by the use of the
same microsatellite markers, indicates striking similarities
589
in all indices of DNA diversity between the Canadian and
Scandinavian populations, a notion that warrants future
investigations. The significant changes in population
structure in the North American peregrine populations
(Brown et al. 2007) may have resulted from gene introgression from the captive populations in Canada and
USA. A more extensive sampling of both the historic and
contemporary range of the Scandinavian, European, and
North American populations would allow for a more
complete appraisal of the peregrine bottleneck, which in
turn would enable us to fully quantify the genetic effects
of the species reintroductions. Only then will we be able
to fully evaluate the success of the restoration efforts and
develop new guidelines for future restoration projects on
other endangered species and populations. Although
our data suggest that the southern and northern peregrine
populations differentiated prior to the demographic
bottleneck, more extensive sampling of the historic range
of the Fennoscandic populations is needed to estimate
historical and current levels of gene flow between the
northern and southern Fennoscandic populations. Until
then, it is difficult to determine the degree to which the
use of exogenous captive breeding stock has affected the
level of differentiation between Fennoscandic peregrine
populations.
As other studies on endangered and bottlenecked species
(e.g., Groombridge et al. 2000; Rosenbaum et al. 2000;
Pertoldi et al. 2001; Brown et al. 2007), our data prove the
importance of museum specimens as a source of genetic
information to address questions related to changes in genetic diversity and population structure. Whenever historical samples of endangered populations are available, they
provide unique genetic information that cannot be inferred
from contemporary samples with the same confidence and
reliability. Acquiring genotypic data on the historical
southern Scandinavian peregrine population not only enabled comparison of temporal levels of genetic diversity
before and after the demographic bottleneck, but also
unravelled the genetic implications of the reintroduction
project in the region.
Acknowledgements We thank M. A. Torres and R. Vallender for
invaluable analytical support, J. Wang for technical advice, and the
Lifjeld Research Group for valuable comments on earlier drafts of
this manuscript. The project was supported by the National Centre for
Biosystematics (project no. 146515/420), co-funded by the NRC and
the NHM, University of Oslo, Norway.
Appendix
Voucher data for historical museum specimens of peregrine falcon (Falco peregrinus) deposited at the Natural
History Museum, University of Oslo, Norway
123
590
Conserv Genet (2008) 9:581–591
Voucher
#
Sampling
year
Sampling location (Location, county,
country)
L2850
1887
Lista, Vest-Agder, Norway
L2856
1891
Nærland, Rogaland, Norway
L2851
L2867
1887
1935
Lista, Vest-Agder, Norway
Stokke, Vestfold, Norway
L2859
1894
Thune, Østfold, Norway
L2846
1877
Farsund, Vest-Agder, Norway
L2858
1893
Lista, Vest-Agder, Norway
L4425
1951
Langøya, Vestfold, Norway
L2855
1890
Lista, Vest-Agder, Norway
L2864
1935
Enebakk, Akershus, Norway
L2852
1889
Vigsnes, Rogaland, Norway
L2873
1949
Ulefoss, Telemark, Norway
L2847
1879
Østre Aker, Akershus, Norway
L2872
1943
Staubo, Aust-Agder, Norway
L2853
1889
Lista, Vest-Agder, Norway
L2857
1893
Lista, Vest-Agder, Norway
L2849
1887
Lista, Vest-Agder, Norway
L2854
1889
Lista, Vest-Agder, Norway
L2861
L2863
1896
1904
Nærland, Rogaland, Norway
Lista, Vest-Agder, Norway
L3279
1892
Elverum, Hedmark, Norway
L3354
1902
Lørenskog, Akershus, Norway
L3138
1886
Farsund, Vest-Agder, Norway
L3137
1880
Lørenskog, Akershus, Norway
L3142
1887
Ullensaker, Akershus, Norway
L3136
1879
Farsund, Vest-Agder, Norway
L3143
1887
Lista, Vest-Agder, Norway
L3516
1935
Østfold, Norway
26505
1920
Haslev, Vestsjælland, Denmark
26511
1919
Nødebo, Fredriksborg, Denmark
26510
1920
Saltholm, København, Denmark
26503
1923
Stabberud, Storstrøm, Denmark
26509
1924
Gundsømagle, Roskilde, Denmark
26507
26512
1932
1929
Rønnebækholen, Storstrøm, Denmark
Randers, Århus, Denmark
26508
1919
Haslev, Vestsjælland, Denmark
26504
1923
Fure Sø, København, Denmark
26506
1927
Lellinge, Roskilde, Denmark
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