טנא - טבע נוף אקולוגיה , הבזים האדומים

Population fragmentation leads to isolation by distance but not genetic impoverishment in the philopatric Lesser Kestrel: a comparison with the widespread and sympatric Eurasian Kestrel

MIGUEL ALCAIDE, DAVID SERRANO, JUAN J. NEGRO, JOSÉ L. TELLA, TONI LAAKSONEN*, CLAUDIA MÜLLER**, A. GAL*** and ERKKI KORPIMÄKI*

Departamento de Ecología Evolutiva. Estación Biológica de Doñana (CSIC). 9 Avda. Mª Luisa s/n. 41013, Sevilla (Spain)

*Section of Ecology, Department of Biology. University of Turku. FIN-20014, Turku (Finland)

*** Department of Evolution, Systematics and Ecology. The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

Population fragmentation is a widespread phenomenon usually associated with human activity. As a result of habitat transformations, the philopatric and steppe-specialist Lesser Kestrel Falco naumanni underwent a severe population decline during the last century which increased population fragmentation throughout its breeding range. In contrast, the ubiquitous Eurasian Kestrel Falco tinnunculus did not suffer such adverse effects, its breeding range still remaining rather continuous. Using microsatellites, we tested the effects of population fragmentation on large-scale spatial patterns of genetic differentiation and diversity by comparing these two sympatric and phylogenetically related species. Our results suggest that habitat fragmentation has increased genetic differentiation between Lesser Kestrel populations, following an isolation-by-distance pattern, whilst the covered population of Eurasian Kestrels is panmictic. Contrarily to expectations, we did not detect significant evidence of reduced genetic variation or increased inbreeding in Lesser Kestrels. Two island subspecies of the Eurasian Kestrel, Falco t. canariensis and Falco t. dacotiae, however, did exhibit significant signs of inbreeding and lower microsatellite diversity. These findings suggest that gene flow as well as large enough effective population sizes may have mitigated genetic depauperation in the Lesser Kestrel. Relevant to conservation genetics and evolutionary biology, this study reports genetic differentiation due to habitat alteration in a species that has potential for long-distance dispersal but philopatry-limited gene flow. Nonetheless, genetic diversity in Lesser Kestrels only seems to become seriously reduced after severe population bottlenecks following extreme habitat fragmentation.

Human activities transform the natural habitats of many species. Population fragmentation often leads to overall reductions in population sizes and diminishes connectivity among habitat patches. While population fragmentation increases extinction risks because of deterministic and stochastic factors acting on demographic parameters, restricted gene flow may jeopardize long-term persistence of populations due to inbreeding depression and loss of genetic diversity. Both demographic and genetic impacts of population fragmentation are believed to depend on the number, size and spatial distribution of populations as well as on time since fragmentation. In this regard, dispersal and associated gene flow become one of the most critical factors influencing the genetic structure and demography of fragmented populations (e.g. Young & Clarke 2000, Frankham et al. 2002). However, restricted gene flow and the subsequent emergence of genetic structuring is not only the result of physical or anatomical barriers to achieve long-distance displacements. Natal and breeding philopatry (i.e. the tendency of individuals to breed close to their birthplace or their previous breeding territory) are relevant life-history traits expected to enhance the effects of habitat fragmentation as well (e.g. Greenwood 1980). Genetic differentiation among fragments is hence expected to be inversely correlated with the dispersal ability of the species.

In spite of all the factors mentioned above, there is not necessarily a direct association between the spatial distribution of populations and the spatial distribution of genetic diversity (e.g. Dannewitz et al. 2005, Koopman et al. 2007, Jones et al. 2007). Independent demographic and genetic approaches are therefore being encouraged to rigorously evaluate the consequences of population fragmentation (e.g. Koenig & Dickinson 2004). In this respect, elucidating the demographic and ecological factors that determine the distribution of genetic variation in populations of the same or different species and subspecies at different scales has become a crucial issue in conservation and evolutionary biology. Polymorphic molecular markers and powerful statistical methods have allowed the investigation of the spatial distribution of genetic variation in fragmented populations, also providing a measure of population connectivity. Such approaches, combined with life-history and demographic information, have consistently provided relevant clues later considered for appropriate conservation and management initiatives aimed at preserving genetic diversity of endangered species. (e.g. Caizergues et al. 2003, Martínez-Cruz et al. 2004, Hansson & Richardson 2005, Koopman et al. 2007).

Studies on genetic structure and diversity in birds of prey are accumulating due to an emerging concern about the threats derived from population fragmentation and habitat alteration in this charismatic avian group (e.g. Martínez-Cruz et al. 2004, Godoy et al. 2004; Helbig et al. 2005; Nittinger et al. 2007; Hailer et al. 2007, Brown et al. 2007, Cadahía et al. 2007). Birds of prey typically have small populations with extended distributional ranges, but usually long-distance dispersal capabilities. Although raptor populations tend to be poorly structured (see references above), habitat fragmentation potentially increases genetic divergence and provokes a loss of genetic variation. In this study, we employed polymorphic microsatellites to assess the influence of population fragmentation on genetic diversity and large-scale (continental) spatial patterns of genetic differentiation in two phylogenetically related and sympatric birds of prey, the Lesser Kestrel Falco naumanni and the Eurasian Kestrel Falco tinnunculus. Both species breed in Eurasia, a continental mass with a broad tradition of human-induced landscape transformations which have generated serious threats for the conservation of many species (Goriup & Batten 1990, McNeely 1994). While the Lesser Kestrel is a specialist falcon inhabiting steppe and pseudosteppe ecosystems (Cramp & Simmons 1980), the Eurasian Kestrel is considered a truly cosmopolitan falcon that can live in most open-country environments (Village 1990). Open habitats in Europe have increased due to agriculture and clear-cutting of forests, a fact that may explain why the breeding range of the Eurasian Kestrel has not decisively been affected by human activities. In contrast, Lesser Kestrels have experienced a well-documented population decline during the 20th century that is mostly explained by human perturbations, such as the substitution of traditional agricultural practices by intensive agriculture and irrigated crops that reduce foraging habitats (Tella et al. 1998, Ursúa et al. 2005). Such dramatic population regression led to the extirpation or disappearance of the Lesser Kestrel from several European countries (Biber 1990). This is to a great extent responsible for a patchier distributional breeding range as compared to its generalist counterpart (Fig.1). In addition, long-term and extensive ringing studies of Lesser Kestrels in Spain have documented high natal and breeding philopatry as well as a negative association between effective dispersal and geographical distance (Negro et al. 1997, Serrano et al. 2001, Serrano et al. 2003, Serrano et al. 2008). On the contrary, Eurasian Kestrels have shown low philopatry and frequent effective long-distance dispersal in populations from Northern and Western Europe (Korpimäki 1988, Village 1990, Korpimäki et al. 2006, Vasko 2007), although preliminary data from a Spanish population suggest higher philopatry rates in Southern Europe (J.A. Fargallo, pers. comm.).

Hence, the main question that this article will address is whether habitat alteration has resulted in population differentiation and loss of genetic diversity in the highly philopatric Lesser kestrel compared with the widely distributed and highly dispersive Eurasian kestrel. The suitability of the genetic methods we used here was tested by means of additional analyses of two insular subspecies of the Eurasian Kestrel inhabiting the Canary Islands. We expected the populations of these subspecies to hold comparably lower levels of genetic variation because of the well documented effects of insularity on demography and genetic diversity (e.g. Bollmer et al. 2005).

The Lesser Kestrel is a small trans-Saharian migratory falcon whose breeding range covers mid-latitude and low elevations of Eurasia (Cramp & Simmons 1980). This colonial falcon originally occupied small cliffs surrounded by natural steppes (Tella et al. 2004), but most pairs breed nowadays in human structures surrounded by traditional agricultural land. The Eurasian Kestrel is a sedentary or partially migratory falcon of slightly larger size that is widespread in Eurasia, normally showing a territorial breeding behaviour (Cramp & Simmons 1980). In Europe, the estimated population size of Lesser Kestrels is about 25,000-42,000 breeding pairs, whilst that of Eurasian Kestrels is about 300,000-500,000 breeding pairs. We analysed breeding populations of the Lesser Kestrel in south-western Spain, central-western Spain, north-eastern Spain, France, Italy, Greece and Israel (see Fig. 1, Panel A). The continental subspecies of the Eurasian Kestrel (Falco tinnunculus tinnunculus) was sampled in south-western Spain, central-western Spain, north-eastern Spain, Switzerland, Finland and Israel (see Fig.1, Panel B). Two insular subspecies of the Eurasian Kestrel inhabiting the Canary Islands, Falco tinnunculus canariensis and Falco tinnunculus dacotiae, (see Fig. 1, Panel B) were also investigated to provide comparative data. Estimated population sizes are about 400-500 breeding pairs for F.t. dacotiae and less than 4,000 breeding pairs for F.t. canariensis (Madroño et al. 2004)

The majority of sampled individuals (>90%) were nestlings, and we only analysed one individual per brood to minimize problems associated with close relatedness. Extra-pair paternity in Lesser and Eurasian Kestrels has shown to be rare (below 7.5% of nestlings, see Alcaide et al. 2005 and Korpimäki et al. 1996 for details), and thus, the probability for adult males to raise their own offspring is high. Estimated population sizes of the geographically distinct populations of Lesser Kestrels investigated in this study are shown in Table 1. The number of Lesser and Eurasian Kestrels sampled at each location is shown in Tables 3 and 4, respectively.

About 100 μl of blood preserved in 96% ethanol or growing feathers that were pulled from the birds' dorsal plumage were digested by incubation with proteinase K for at least 3 hours. DNA purification was carried out by using 5M LiCl organic extraction method with chloroformisoamylic alcohol (24:1) and further DNA precipitation using absolute ethanol. Pellets obtained were dried and washed twice with 70% ethanol, and later stored at –20º C in 0.1ml of TE buffer. We amplified seven microsatellites that were isolated originally in the peregrine falcon Falco peregrinus by Nesje and co-workers (2000) (Fp5, Fp13, Fp31, Fp46-1, Fp79-4, Fp89, Fp107). In addition, we designed two set of primers flanking two microsatellite sequences also isolated in the peregrine falcon that were available in GenBank (AF448412 and AF448411, respectively). Locus Cl347 was amplified using primers Cl347Fw: tgtgtgtgtaaggttgccaaa and Cl347Rv: cgttctcaacatgccagttt. Locus Cl58 was amplified using primers Cl58Fw: tgtgtctcagtggggaaaaa and Cl58Rv: tgctttggtgctgaagaaac. For each locus, the polymerase chain reaction (PCR) was carried out in a PTC-100 Programmable Thermal Controller (MJ Research Inc.) using the following PCR profile: 35 cycles of 40s at 94ºC, 40s at 55ºC, 40s at 72º C and finally, 4 min at 72ºC. Each 11 µl reaction contained 0.2 units of Taq polymerase (Bioline), 1x PCR manufacturer supplied buffer, 1.5 mM MgCl2 , 0.02% gelatine (Amersham Life Sciences), 0.12 mM of each dNTP, 5 pmol of each primer and, approximately, 10 ng of genomic DNA. Forward primers were 5'-end labelled with HEX, NED or 6-FAM. Amplified fragments were resolved on an ABI Prism 3100 Genetic Analyser (Applied Biosystems).

Polymorphism statistics at each microsatellite marker (i.e. number of alleles and range size of the amplified fragment) were calculated using the programme Genetix 4.04 (Belkhir et al. 1996-2004). Conformity to Hardy-Weinberg equilibrium was analysed through GENEPOP (Raymond & Rousset 1995), using a single locus and a global multi-locus test for heterozygosity deficit or excess by the Markov Chain Method (Raymond & Rousset 1995).

We employed the software STRUCTURE 2.2 (Pritchard et al. 2000) to test for the presence of genetically distinct clusters within our study system. We did not use any prior information about the geographic origin of the individuals, and we assumed correlated allele frequencies and the admixture model. Ten simulations were performed for each of the K values ranging from 1 to 6 (i.e. number of putatively different genetic clusters), and probability values of the data, i.e. lnPr(X/K), were plotted. Values of K=1 indicate a genetically uniform population, whilst values of K=2 and so on indicate the existence of genetically different arrays of individuals. Analyses were carried out with 100,000 iterations, following a burn-in period of 10,000 iterations. Nonetheless, testing for differences in allele frequencies between geographically distinct populations may be more useful than clustering analyses performed in STRUCTURE when genetic differentiation is weak (e.g. Latch et al. 2006) or affected by isolation-by-distance (see software documentation in http://pritch.bsd.uchicago.edu/software/structure22/readme.pdf). Thus, we employed the programme GENETIX 4.04 to calculate FST values between groups of individuals sampled from different locations of the Lesser Kestrel breeding distribution. Although the distribution range of the Eurasian Kestrel is relatively continuous, we also calculated FST values between distant sampled locations in order to contrast FST pair-wise values with STRUCTURE results. The significance of FST pair-wise comparisons was given by a P-value calculated using 10,000 random permutations tests that was further adjusted according to sequential Bonferroni corrections for multiple tests (Rice 1989). Isolation by distance was investigated through Mantel tests based on the traditional F_ST / 1-F_ST approach. We introduced in the programme GENETIX a matrix containing values of genetic differentiation between each pair of sampled populations (i.e. F_ST / 1-F_ST values represented in the Y axis) plus a matrix containing the geographical distance in kilometres between each pair of sampled locations (represented in the X axis). Geographic distances were calculated according to a straight line connecting the geometrical centre of each pair of sampled populations. The significance of the correlation between genetic differentiation and geographical distance was tested in GENETIX 4.04 through a P-value calculated using 10,000 permutations.

Allelic richness, average observed heterozygosities and the inbreeding coefficient FIS among groups of samples encompassing individuals from different species or subspecies were compared using the permutation test (N = 10,000) implemented in FSTAT (Goudet 2001). The allelic richness estimate, which is calculated from random permutations of a minimum shared number of individuals between groups, is especially useful in this study since highly polymorphic loci such as Fp79-4 may decisively bias estimates of genetic diversity in relation to sample size. The non-parametric Wilcoxon-test was also employed to detect significant differences between sampled locations in polymorphism statistics obtained at each locus (i.e. allelic richness and average observed heterozygosities). Finally, microsatellite diversity at each pair of locations, measured as the mean number of alleles per individual, was compared using Student-t-tests.

Overall, 103 alleles were found in 320 Lesser Kestrels, 75 alleles in 128 mainland Eurasian Kestrels and 46 alleles in 28 island Eurasian Kestrels (see Table 2). Locus Fp107 departed significantly from Hardy-Weinberg expectations, showing heterozygosity deficits in most populations that are probably related to the presence of null alleles (see also Alcaide et al. 2005). Since null alleles may violate several assumptions of the genetic methods we intended to apply, locus Fp107 was removed from further analysis. Mainland populations from both kestrel species fitted to Hardy-Weinberg expectations after excluding this locus. We found, in contrast, statistically significant heterozygosity deficits, even after Bonferroni corrections for multiple tests, in the smallest insular population corresponding to Falco t. dacotiae.

In Lesser Kestrels, the Bayesian analysis of population structure excluding any a priori information about the origin of individuals indicated panmixia (i.e. K=1, see Fig. 2) as the most likely scenario. Nevertheless, traditional estimates of population differentiation relying on differences in allele frequencies revealed weak (FST<0.055) but significant patterns of genetic differentiation, even after Bonferroni corrections for multiple tests, when we compared geographically distinct populations (Table 3). In fact, genetic divergence across the study area adjusted significantly to an isolation-by-distance pattern (Fig. 3).

On the other hand, the clustering analysis implemented in STRUCTURE only detected two genetically distinct clusters within Eurasian Kestrels (i.e. K=2) that distinguished the mainland subspecies against the two insular subspecies. This finding agrees with the comparably high and statistically significant pairwise F_ST values reported between Eurasia and the Canary Islands (F_ST>0.075, all Bonferroni-corrected P-values<0.05; Table 4). Conversely, there was no evidence for genetic subdivision within Eurasia, as none of the pairwise F_ST values were significantly different from zero (F_ST<0.015, all non-Bonferroni corrected P-values>0.05), or within the Canarian Archipelago (F_ST=-0.018, P=0.87) (see Table 5). Contrary to Lesser Kestrels, our set of genetic markers did not reveal significant evidence of isolation-by-distance in the mainland subspecies of the Eurasian Kestrel (Fig. 3). To compare data from both species, we performed a generalized linear model with F_STas the response variable and species identity and Euclidean distance between populations as independent variables. After conservatively adjusting the denominator degrees of freedom to avoid non-independence between sampling locations (see Bailey et al. 2007), the interaction term remained significant (F_1,9= 9.11, P = 0.015).

The permutation test performed in FSTAT did not reveal statistically significant differences in genetic diversity (allelic richness and average observed heterozygosity) or increased inbreeding (FIS) when comparing the Lesser Kestrel and the mainland subspecies of the Eurasian kestrel (all two-sided P-Values > 0.05, Table 5). In contrast, average observed heterozygosity was significantly lower in island than in the continental subspecies of the Eurasian kestrel (0.46 vs 0.66, two-sided P-value = 0.009; Table 5), and allelic richness was marginally significant in the same direction (4.24 vs 5.28, two sided P-value = 0.08; Table 5). Furthermore, we found statistically significant evidence of increased inbreeding (FIS) in the kestrel genotypes from the Canary Islands (0.265 vs 0.084, two sided P-value = 0.02; Table 5).

Finally, pairwise analyses comparing locus by locus failed to detect statistically significant decreased genetic diversity between any of the geographically distinct populations of Lesser Kestrels investigated (Non-parametric Wilcoxon-test, all P-values > 0.05; see Table 6). Average microsatellite diversity per individual was not statistically different among populations either (t-tests, all P-Values > 0.05), except for a couple of comparisons involving the smallest and geographically isolated population from Southern France. Such comparisons involved the less genetically diverse population (France) and two of the most genetically diverse (Italy and Israel, see Table 6).

We studied the genetic implications of habitat fragmentation by comparing the generalist, continuously distributed mainland subspecies of the Eurasian Kestrel and the steppe-specialist, patchily distributed Lesser Kestrel. Our findings indicate similar levels of genetic variation in both species, but lower levels of genetic diversity in two island subspecies of Eurasian Kestrels. With respect to population differentiation, the Bayesian clustering method separated the mainland population of Eurasian Kestrels from their island counterparts. Coherently, FST analyses showed significant genetic differentiation between but not within both sampled clusters. In Lesser Kestrels, STRUCTURE assigned all individuals to a unique putative population. Nonetheless, estimates of population differentiation relying on the distribution of allele frequencies revealed low but significant levels of genetic differentiation following an isolation-by-distance model.

It is currently assumed that species thriving within a range of environmental conditions are more sensible to habitat transformations, their distributional ranges becoming patchier and the risk for genetic drift within fragments increasing (e.g. Ferrer & Negro 2004). Our empirical approach exemplifies a situation whereby genetic differentiation reflects the spatial distribution of populations, which, in turn, is delimited by habitat requirements. Thus, genetic differentiation between Lesser Kestrel populations increases with geographical distance (see also Alcaide et al. 2008 for data on MHC genes). Even though the Lesser Kestrel is a long-distance migratory species, gene flow is restricted over short distances due to high natal and breeding philopatry (Negro et al. 1997, Serrano et al. 2001, Serrano & Tella 2003). Elsewhere, we found, however, a lack of fine-scale patterns of genetic differentiation in a spatially structured population of Lesser Kestrels located in north-eastern Spain (Alcaide et al. in third revision, Journal of Animal Ecology). This finding was attributed to the fact that population subdivision at the geographical scale studied (about 10,000 km²) could have not been sufficiently important with respect to the dispersal capabilities commonly displayed by the species, and enough gene flow rates had homogenised allele frequencies. Nonetheless, long-distance effective dispersal in Lesser Kestrels (> 100 km) have been rarely documented by direct observations (Serrano et al. 2003, Prugnolle et al. 2003, P. Pilard and F. Martín, pers. comm., D.Serrano, E. Ursúa and J.L. Tella unpublish. data, M. Alberdi, pers. comm.), a fact that would be in agreement with the emergence of genetic structuring at large geographical scales. In contrast, it has been shown in several European populations of Eurasian Kestrels that natal dispersal regularly occurs over large distances (e.g. Snow 1968). Such amplitude of dispersal movements (see also Korpimäki 1988, Village 1990, Korpimäki et al. 2006, Vasko 2007) as well as a low incidence of habitat fragmentation in the Eurasian Kestrel would therefore explain a genetically uniform population.

Population genetics theory predicts that reductions in population size as well as limited migration decrease genetic variation, triggering negative genetic processes such as inbreeding depression and loss of adaptive potential (Frankham et al. 2002). Following these predictions, recent studies in the Lesser Kestrel have repeatedly looked at positive correlations between fitness component-traits and individual genetic diversity at 11 polymorphic microsatellite markers (Ortego et al. 2007a, 2007b). However, our genetic analyses, relying on at least six microsatellites previously amplified by Ortego and co-workers (Fp5, Fp13, Fp31, Fp46-1, Fp79-4 and Fp89), have not revealed comparably low levels of microsatellite diversity or increased inbreeding in Lesser Kestrels in relation to the putatively outbred subspecies of the Eurasian Kestrel. Genetic variation at functionally and evolutionary relevant MHC loci have also been shown extraordinary levels of polymorphism (> 100 alleles at a single locus) and heterozygosities above 95% in Lesser Kestrels (Alcaide et al. 2008). Although even normally outbred populations are expected to show inter-individual differences in the levels of inbreeding, this fact may explain the extremely weak (e.g. Ortego et al. 2007a) or even the lack of significant relationships (Ortego et al. 2007b) found by Ortego and co-workers. In addition, a short array of supposedly neutral markers is currently considered a poor predictor of fitness in open populations (reviewed by Coltman and Slate 2003) with the exception of those cases in which a strong linkage between certain neutral markers and some polymorphic fitness-related loci is demonstrated (e.g. Hansson et al. 2004).

We believe that additional analyses of the pre-bottlenecked population are however needed to evaluate the degree of genetic depauperation in the Lesser Kestrel. In any case, this study recommends caution when assuming that the population decline experienced by this species has likely translated into contemporary reduced levels of genetic variation and increased inbreeding. For instance, Brown and co-workers (2007) have recently failed to detect signatures of a genetic bottleneck in peregrine falcons after a devastating decline in the mid-20^th century due to organochlorine contaminants. In a similar way to this peregrine falcon study, some Lesser Kestrel populations have been known to experience demographic growth, either through a natural way (e.g. Tella et al. 1998, Ortego et al. 2007c) or by means of reintroduction or supplementation programs (e.g. Pomarol 1993). Yet even in the bottlenecked and geographically isolated population from Southern France, from where we report the lowest levels of microsatellite polymorphism (Table 7), there is no documented evidence of a relationship between inbreeding depression and fitness. Conversely, local first-year survival in Southern France was similar or even higher than in Spain (Hiraldo et al. 1996, Prugnolle et al. 2003, D. Serrano unpublished data), which suggests that ecological constraints may play nowadays a more prominent role in individual fitness than genetic diversity.

Our genetic analyses also indicate that genetic drift has provoked weak but significant fluctuations in allele frequencies (FST < 0.05) in Lesser Kestrels, but enough migration rates may have mitigated allele fixation (see for instance Mills & Allendorf 1996). In fact, it has been theoretically concluded that the rule of one migrant per generation is sometimes sufficient to maintain genetic diversity while allowing some divergence between fragmented populations (reviewed by Keyghobadi 2007). Moreover, interpopulation differentiation is though to proceed faster than loss of genetic variation after habitat fragmentation (e.g. Keyghobadi 2005). Although anecdotal, long distance dispersal events connecting adjacent populations of Lesser Kestrels have been recorded. For instance, several birds ringed as nestlings in the Iberian Peninsula have been resighted as breeding birds in Southern France, covering dispersal distances of up to 1,000 km (Prugnolle et al. 2003, P. Pilard, pers. comm.). Such effective dispersal displacements provide opportunities for genetic rescue (e.g. Vilá et al. 2003), probably explaining why lesser kestrels do not show reduced genetic diversity when compared to the continental subspecies of the Eurasian kestrel. The comparison between continental and insular subspecies of the Eurasian kestrel, using the same genetic methods, provides a valuable supporting reference in this respect. Speciation processes in islands may require the lack of gene flow after colonization (see for instance Coyne & Orr 2004). Restricted gene flow is therefore expected to accelerate genetic divergence (Table 4), loss of genetic variation and increased inbreeding. These predictions are in accordance with our estimates of genetic diversity (Table 5) and also with other comparisons between mainland and insular populations of kestrels (e.g. Nichols et al. 2001).

In conclusion, this study illuminates about the genetic consequences of habitat fragmentation in open populations of birds of prey. Even though habitat loss, population decline and restricted gene flow over short distances may increase genetic divergence, low rates of long-distance effective dispersal may provide enough opportunities to counteract the loss of genetic variation through genetic drift.

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We are indebted to all the people who kindly helped to collect kestrel samples. Therefore, we are thankful to E. Ursúa, A. Gajón, J. Blas, G. López, C. Rodríguez, J. Bustamante, R. Alcázar (LPN), JD Morenilla, P. Prieto, I. Sánchez, A. García, P. Antolín, M. Pomarol, G. González, R. Bonal, J.M. Aparicio, A. de Frutos, P. Olea, E. Banda, J.A. Fargallo, C. Gutiérrez, P. Pilard and L. Brun (LPO), M. Visceglia, and R. Blachos. This study was supported by the MCyT (project REN2001-2310 and CGL2004-04120) and the CSIC, which also provided a research grant to M. Alcaide.

Table 1. Estimated population sizes of Lesser Kestrels sampled for this study. Data were taken from BirdLife International (2008) and Liven-Schulman et al. (2004). See Fig. 1 for geographic locations

Table 2. Number of alleles across 9 microsatellite markers in the Lesser Kestrel (Falco naumanni), the European subspecies of the Eurasian kestrel (Falco tinnunculus tinnunculus) and the two subspecies of the Eurasian kestrel inhabiting the Canary Islands (Falco tinnunculus canariensis and Falco tinnunculus dacotiae). The number of individuals analysed for each species or subspecies is shown in brackets.

Locus

Range Size (bp)

Falco naumanni

(n=320)

Falco t. tinnunculus

(n=128)

Falco t. canariensis

(n=12)

Falco t. dacotiae

(n=16)

Fp5

99-111

101-115

101-113

Fp13

86-106

92-98

92-94

92-98

Fp31

124-142

128-142

134-138

Fp46-1

115-139

117-127

119-125

115-125

Fp79-4

125-192

129-154

137-149

137-152

Fp89

116-122

116-124

118-120

116-122

Fp107

185-231

195-233

193-221

Cl347

Cl58

96-116

118-123

100-116

n.a.

100-112

n.a.

100-112

n.a.

Table 3. Pairwise F_ST values (above diagonal) and corresponding P-values (below diagonal) between Lesser Kestrel populations from the Western Paleartic (see Fig.1 for geographical locations). Sample sizes at each location are indicated between brackets. Significant values after Bonferroni corrections for multiple tests are outlined in bold. Non-Bonferroni corrected P-values are given below the diagonal.

	NES	CWS	SWS	FRA	ITA	GRE	ISR
NES (68)		0.008	0.008	0.014	0	0.009	0.035
CWS (76)	<0.001		0.001	0.019	0.016	0.014	0.041
SWS (69)	0.0012	0.19		0.023	0.013	0.013	0.038
FRA (26)	0.0021	<0.001	<0.001		0.009	0.041	0.034
ITA (26)	0.56	<0.001	0.0048	0.0664		0.017	0.021
GRE (21)	0.002	0.0026	0.002	0.001	0.005		0.054
ISR (34)	<0.001	<0.001	<0.001	0.001	0.006	<0.001

Table 4. Pairwise F_ST values (above diagonal) and corresponding P-values (below diagonal) between Eurasian kestrel populations from the Western Paleartic and the Canary Islands (see Fig.1 for geographical locations). Sample sizes at each location are indicated between brackets. Significant values after Bonferroni corrections for multiple tests are outlined in bold. Non-Bonferroni corrected P-values are given below the diagonal.

	NES	CWS	SWS	SWI	FIN	ISR	TF	FV
NES (18)		0.009	0.002	0.009	0.006	0.008	0.066	0.083
CWS (18)	0.34		0.010	0	0.004	0	0.103	0.121
SWS (19)	0.14	0.35		0.014	0	0.006	0.078	0.107
SWI (26)	0.19	0.53	0.09		0	0.003	0.077	0.099
FIN (23)	0.23	0.29	0.49	0.60		0.001	0.078	0.105
ISR (24)	0.18	0.42	0.22	0.31	0.39		0.077	0.105
TF (12) FV (16)	<0.001 <0.001	<0.001 <0.001	<0.001 <0.001	<0.001 <0.001	<0.001 <0.001	<0.001 <0.001	0.87	-0.018

Table 5. Comparison of average genetic estimates among groups of kestrel populations that was performed using the permutation test (N = 10,000) implemented in the programme FSTAT. Allelic richness was calculated over a minimum number of 12 individuals.

Table 6. Genetic diversity across eight microsatellite markers in six geographically distinct populations of Lesser Kestrels. Allelic richness estimates were adjusted to a minimum sample size of 21 individuals. See Fig. 1 for geographical locations.

	Allelic Richness	Average Observed Heterozygosity	Inbreeding Coefficient (F_IS)
NES	6,6	0.63	0.07
CWS+SWS	7,06	0.65	0.05
FRA	6,02	0.60	0.04
ITA	6,89	0.67	-0.06
GRE	6,88	0.64	0.01
ISR	7,42	0.66	0.03

FIG 1. Breeding distributional ranges (grey areas) of Lesser (panel A) and Eurasian (panel B) Kestrels across the Western Paleartic. Populations analysed in this study are indicated by black dots. Lesser Kestrels were sampled from south-western Spain (SWS), central-western Spain (CWS), north-eastern Spain (NES), France (FRA), Italy (ITA), Israel (ISR) and Kazakhstan (KAZ). The continental subspecies of the Eurasian Kestrel was sampled from south-western Spain (SWS), central-western Spain (CWS), north-eastern Spain (NES), Switzerland (SWI), Finland (FIN) and Israel (ISR). In addition, two subspecies of the Eurasian Kestrel inhabiting the Canary Islands (indicated by asterisks) were sampled (FV for Falco t. dacotiae and TF for Falco t. canariensis).

FIG 2. Bayesian clustering analysis of 320 Lesser Kestrels sampled in different regions of the Western Palearctic. For each value of K (i.e. number of putatively different genetic clusters tested), ten simulations were carried out to obtain the probability of the data (y-axis)

FIG 3. Relationships between the extent of genetic differentiation and geographical distance in Lesser Kestrel (open dots, r = 0.50, P = 0.04) and Eurasian Kestrel (black dots, r = -0.44, P = 0.84) populations sampled across the Western Paleartic.