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Feb 5, 2012 - Claire Raisin • Alain C. Frantz • Samit Kundu •. Andrew G. Greenwood • Carl G. Jones •. Nicolas Zuel • Jim J. Groombridge. Received: 15 April ...
Conserv Genet (2012) 13:707–715 DOI 10.1007/s10592-012-0319-0

RESEARCH ARTICLE

Genetic consequences of intensive conservation management for the Mauritius parakeet Claire Raisin • Alain C. Frantz • Samit Kundu Andrew G. Greenwood • Carl G. Jones • Nicolas Zuel • Jim J. Groombridge



Received: 15 April 2011 / Accepted: 12 January 2012 / Published online: 5 February 2012 Ó Springer Science+Business Media B.V. 2012

Abstract For conservation managers tasked with recovering threatened species, genetic structure can exacerbate the rate of loss of genetic diversity because alleles unique to a sub-population are more likely to be lost by the effects of random genetic drift than if a population is panmictic. Given that intensive management techniques commonly used to recover threatened species frequently involve movement of individuals within and between populations, managers need to be aware not only of pre-existing levels of genetic structure but also of the potential effects that intensive management might have on these patterns. The Mauritius parakeet (Psittacula echo) has been the subject of an intensive conservation programme, involving translocation and reintroduction that has recovered the population from less than 20 individuals in 1987 to approximately 500 in 2010. Analysis of genotype data derived from 18 microsatellite markers developed for this species reveals a clear signal of structure in the population before intensive

Electronic supplementary material The online version of this article (doi:10.1007/s10592-012-0319-0) contains supplementary material, which is available to authorized users. C. Raisin (&)  J. J. Groombridge Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent, Canterbury, Kent CT2 7NR, UK e-mail: [email protected] C. Raisin  A. C. Frantz NERC Biomolecular Analysis Facility, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield S10 2TN, UK C. Raisin  C. G. Jones  N. Zuel Mauritian Wildlife Foundation, Grannum Road, Vacoas, Mauritius

management began, but which subsequently disappears following management intervention. This study illustrates the impacts that conservation management can have on the genetic structure of an island endemic population and demonstrates how translocations or reintroductions can benefit populations of endangered species by reducing the risk of loss of genetic diversity. Keywords Conservation management  Endemic island species  Mauritius parakeet  Population structure

Introduction The need to maintain population genetic diversity is a widely accepted priority for conservation biologists tasked with securing the long-term viability of populations of endangered species (Frankel and Soule 1981; Frankham et al. 2010). Habitat loss, degradation and fragmentation are responsible for the structured spatial distribution of many endangered species, which leads to an uneven S. Kundu Division of Infection and Immunity, Faculty of Medical Sciences, University College London, Gower Street, London WC1E 6BT, UK A. G. Greenwood International Zoo Veterinary Group, Station House, Parkwood Street, Keighley, West Yorkshire BD21 4NQ, UK C. G. Jones Durrell Wildlife Conservation Trust, Les Augres Manor, Trinity, Jersey JE3 5BP, UK

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distribution of genetic diversity (Owens and Bennett 2000; Fahrig 2001). Population fragments unconnected by gene flow can become genetically differentiated through the random effects of genetic drift. Continued prevention of migration and gene flow exacerbates these effects leading to further isolation over time as the genetic make-up within each fragment changes and levels of inbreeding accumulate (Frankham et al. 2010). Crucially for threatened species, genetic structure can exacerbate the rate of loss of genetic diversity because alleles unique to a sub-population are more likely to be lost by the effects of random genetic drift than if a population is panmictic (Hartl and Clark 1997). Therefore, conservation managers need to be aware not only of existing levels of genetic structure, but also of the potential effects that intensive management might have on these patterns. Two conservation approaches are generally available to minimise the detrimental genetic effects of population fragmentation. Habitat corridors can be created to physically link the fragments, allowing individuals to move freely between sub-populations (Beier and Noss 1998; Debinski and Holt 2000). Alternatively, management strategies can aim to translocate individuals between existing population fragments (Beier and Noss 1998; Armstrong and Ewen 2002). Whilst restoring suitable habitat to allow natural movement of individuals is the ideal long-term solution, for many habitats, such as slowgrowth forest, such corridors can take many years to establish. Given that time is frequently at a premium when recovering endangered species, short-term intensive management is often the preferred choice. Translocation of individuals between population fragments has the potential for a more immediate impact on slowing the rate of loss of genetic diversity and as such these methods are now in widespread use for restoring endangered species (Jones and Duffy 1993; Seddon et al. 2007). Given that the use of such techniques is likely to increase in the future, there is a need to evaluate their impact on the distribution of genetic diversity in managed populations of endangered species. In this study we investigate the effect that intensive management has had on the genetic structure of a postbottleneck endangered island endemic species, the Mauritius parakeet (Psittacula echo). This species declined to less than 20 known birds during the mid to late 1980s (Fig. 1) (Duffy 1993; Lovegrove et al. 1995) before being restored to a current population size of approximately 500 individuals (Richards et al. 2010). The decline of the species was primarily driven by human mediated habitat alteration and destruction. At present the entire population is restricted to upland areas of the Black River Gorges National Park in the south west of Mauritius (Fig. 2) and the majority of birds nest in managed nest sites. This recovery is the result of a 30-year management programme

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Fig. 1 Census population size of the Mauritius parakeet from 1973 to 2009 (curve) and number of birds released since monitoring began (shaded bars). Different phases of the management programme indicated below

coordinated by the Government of Mauritius National Parks and Conservation Service (NPCS) and the Mauritian Wildlife Foundation (MWF), together with International Conservation Organisations. Due to the severely endangered status of this species at the inception of the recovery programme, the priority was to increase population size as rapidly as possible. Therefore the main focus of the programme was initially to maximise breeding output and recruitment in each breeding season (Jones 1987). Consequently, the retention of genetic diversity or equalising genetic contributions across the population was not considered a priority during this period.

Population management of the Mauritius parakeet The intensity of management of the Mauritius parakeet has varied considerably throughout the conservation programme and a number of management techniques to increase productivity have been employed. See Supplementary Material for an outline of the programme history, and Jones and Duffy (1993) and Jones et al. (1998) provide a detailed account of the methods employed to maximise productivity of breeding pairs. Here we summarise the history of the species’ conservation management programme and in doing so set out important background information which subsequently allows us to evaluate the genetic impacts of that management. Monitoring of the Mauritius parakeet population began in 1973 and the management programme was intensified in 1987. From 1990 to 1997 the population was intensively surveyed and monitored and in 1997 the first trial release of captive birds took place; by 1999, 22 birds had been released into the Camp area of the Black River Gorges

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Fig. 2 Map of Black River Gorges National Park on Mauritius showing the seven sub-populations containing Mauritius parakeet nest sites (filled circle). These subpopulations include the four northerly populations in the Black River Gorges and the two more southerly populations in Bel Ombre. The seventh subpopulation is the isolated captive population at GDEWS. Inset shows location of the national park within Mauritius

(Fig. 2). Each season additional wild nest sites were discovered and in 2001 seven birds were released at Camp and a trial release of four birds was performed in Combo, an area of native forest with no wild Mauritius parakeet population. From this point until 2005 can be considered the most intensive period of population management with numerous birds being transferred between sites and released from captivity. The number of wild birds translocated between 2000 and 2005 and the direction of their translocation are summarised in Table 1 (these figures do not include captive birds released into the wild during the release program). The priority of the conservation programme at this time was to increase productivity of wild breeding pairs as rapidly as possible and to boost population size. Consequently, the

Table 1 Matrix indicating number of eggs and chicks transferred between sites during the intensive management period

Italicized value indicate birds that were moved to a different site but that remained within the same region. NB These numbers only include wild chicks and eggs, i.e. not birds that were part of the release programme

distribution of genetic diversity across the population was not considered a priority when implementing these management measures and even captive breeding decisions were primarily based on likelihood of successful breeding rather than genetic representation. Due to an outbreak of the highly infectious psittacine beak and feather disease (PBFD) in 2005, management practices had to be rapidly re-assessed and modified in an attempt to prevent further spread of the infection. All interventions that involved moving birds or eggs between sites or taking them into captivity were ceased and the level of ‘hands-on’ intervention at wild nests was reduced. PBFD is a highly contagious viral disease spread between individuals (Ritchie et al. 1989) and its outbreak in the population was considered to pose a serious threat to the

Receiving region BOL

BOU

Camp

GDEWS

Gorges

Macabe

South scarp

Source region BOL

1

BOU

1

Camp

1

GDEWS

1

2

South Scarp

3

24

2

Gorges Macabe

1

1 2

2 1

2

1

1 12

2 2

5

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710

continued recovery of the species. Consequently, since 2005 the management of the population has taken a less intensive approach, but the population continued to be monitored closely for productivity, survival and disease. As such, the chronology of the management history for the Mauritius parakeet can be split into three distinct phases: (i) Pre-intensive management; (ii) Intensive management (defined here as approximately occurring between 2000 and 2005), and (iii) Post-intensive management (Fig. 1). This sequence of events enables an assessment of genetic structure before and after the intensive management period to reveal how management might have affected spatial patterns of genetic diversity. Whilst genetic diversity is expected to have been redistributed in the restored population, what is less clear is whether the artificial movement of individuals between sites has disrupted any pre-existing patterns of genetic structure or even created new structure by chance redistribution of alleles. In this study, we use microsatellite DNA markers to examine patterns of genetic structure in the endangered Mauritius parakeet before and after a period of intensive management. We examine whether the Mauritius parakeet population was panmictic or genetically structured prior to management intervention, and assess the effect of that intervention on the genetic structure of the current restored population.

Methods Samples A total of 504 Mauritius parakeets from across the species’ range were blood-sampled between 1995 and 2008. All samples were taken from banded birds, or if the bird had not previously been caught it was banded at the time of sampling, to prevent accidental re-sampling and to allow individuals to be individually monitored for breeding success as part of the continuing long-term monitoring programme. The majority of samples were collected from wild birds of approximately 45-days-old at managed nest sites. Adult birds were caught opportunistically throughout the range either in nest and roost sites or in specially constructed field aviaries that are used to provide supplemental food. Samples from adults were taken from individuals that had been caught either in mist nets erected in their range, in field aviaries at supplemental feeding stations or whilst roosting in their nest sites during the non-breeding season. Individuals from the captive population at GDEWS were also sampled. Blood was obtained by puncturing the brachial vein with a 25 G needle and collected in a

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1.2 mm 9 75 mm capillary tube. Blood was stored in 70–90% ethanol at 4°C.

Laboratory methods DNA extraction and amplification Genomic DNA was extracted using an ammonium acetate precipitation method (Nicholls et al. 2000) and visualised on 0.8% agarose gels stained with ethidium bromide (Fisher Scientific, LE, UK). The DNA concentration was estimated using a Nanodrop 8000 (Thermo Scientific, Denver, USA.) and normalised with a Biomek 2000 Laboratory Automation Workstation (Beckman Coulter, CA, USA). Mauritius parakeet samples were genotyped using 20 fluorescently labelled autosomal microsatellite DNA markers developed for the species (Peq01, Peq02, Peq03, Peq04, Peq05, Peq06, Peq07, Peq09, Peq10, Peq11, Peq12, Peq13, Peq14, Peq15, Peq16, Peq17, Peq18, Peq19, Peq20 and Peq21; Raisin et al. 2009) in five multiplex PCRs each containing different combinations of loci (Table 2).

Table 2 Details of multiplex combinations, allele size ranges Locus

Multiplex

Allele size range (bp)

A

Ho

He

Null allele frequency

Peq01

5

187–209

9

0.454

0.509

0.05

Peq02

2

131–153

4

0.517

0.522

0.00

Peq03

2

274–300

7

0.731

0.753

0.01

Peq04

1

282–306

6

0.543

0.617

0.06

Peq05

1

122–131

5

0.551

0.618

0.06

Peq06

3

213–244

9

0.783

0.794

0.00

Peq07

2

114–130

6

0.237

0.254

0.03

Peq09

1

207–242

8

0.406

0.556

0.19

Peq10

3

109–129

6

0.796

0.795

0.00

Peq11

1

253–281

8

0.720

0.783

0.04

Peq12

2

271–297

8

0.780

0.816

0.02

Peq13

1

114–125

5

0.518

0.569

0.04

Peq14

3

209–229

7

0.286

0.325

0.06

Peq15

4

202–225

11

0.747

0.814

0.04

Peq16 Peq17

4 5

128–149 197–224

5 6

0.203 0.695

0.492 0.738

N/A 0.03

Peq18

1

154–183

8

0.680

0.764

0.06

Peq19

1

219–235

5

0.619

0.663

0.03

Peq20

4

223–235

5

0.644

0.666

0.01

Peq21

3

160–188

8

0.346

0.710

N/A

Number of alleles per locus (A), mean observed (Ho) and expected (He) heterozygosity and null allele frequencies in the Mauritius parakeet

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Fragments were amplified using Qiagen Multiplex PCR kits (Qiagen Inc., West Sussex, UK). Each 2 ll PCR reaction contained 19 Qiagen multiplex PCR master mix (final magnesium concentration of 3 mM), 0.2 lM of each primer and approximately 10 ng of template DNA (following Kenta et al. 2008). PCR amplification was performed under mineral oil using the following cycling conditions: 95°C for 15 min; then 35 cycles of 94°C for 30 s, 56°c for 90 s, 72°C for 90 s, followed by a final step of 10 min at 72°C. A fraction of this product was loaded onto an ABI 3730 DNA Analyser with GeneScan ROX500 size standard and allele sizes were scored using GeneMapper software (Applied Biosystems, CA, USA).

Data analysis We tested for differences in the average number of alleles and private alleles per locus using Wilcoxon signed-rank tests in Minitab 15.1 (Minitab Ltd., CV, UK). A genotypic equilibrium test for linkage disequilibrium, and exact probability test to detect deviations from Hardy–Weinberg equilibrium, were assessed in Genepop (Raymond and Rousset 1995) and corrected for multiple comparisons using a sequential Bonferroni correction (Rice 1989). Null allele frequencies were estimated using Cervus (Marshall et al. 1998). Population structure Mauritius parakeet nest sites were sub-divided into six potential sub-populations; Camp (n = 199), Macabe (n = 54), Gorges (n = 64), South Scarp (n = 44), Bel Ombre Uppers (n = 36) and Bel Ombre Lowers (n = 55) according to their geographical location and management history (Fig. 2). The remaining samples (n = 116) were either collected from birds housed at GDEWS or from unknown sites that could not be confidently assigned to a sub-population. The Camp, Macabe, Gorges and South Scarp sub-populations are all located within the northern Black River Gorges region of the national park. The remaining two populations, Upper and Lower Bel Ombre are located in the more southerly Bel Ombre forest, but are still within the boundaries of the national park. The captive population at GDEWS was considered as a separate subpopulation. Global Fst values were calculated using Fstat v2.9.3.2 (Goudet 1995) and two non-spatial Bayesian clustering methods were used to examine population structure: STRUCTURE (Pritchard et al. 2000) and BAPS v5 (Corander et al. 2003, 2008). Any bird hatched before 2000 (i.e. before the most intensive period of management) and which had no history of translocation amongst its ancestors

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was included in the pre-intensive management sample set (n = 95), therefore reflecting the natural distribution of the remnant Mauritius parakeet population. Included in this sample set were those birds that were held at GDEWS, but not those that had been released from GDEWS into the wild population. The post-intensive management sample set (n = 179) comprised those individuals known to have hatched since 2005 when the intensive management ceased and therefore represent the population distribution from 2005 to 2008. Fstat v.2.9.3 was used to test for differences in Fst values between pre- and post-management time periods. After first calculating the average for the chosen statistics for each of these two time periods, individuals were permutated between groups, keeping the number of samples in each group constant, in order to assess whether the averages differed significantly between the groups. Two non-spatial Bayesian clustering methods were used to examine population structure: STRUCTURE (Pritchard et al. 2000) and BAPS v5 (Corander et al. 2003, 2008). Genotypes from all individuals were pooled into a single dataset and analysed for signals of genetic structure, before the data were split into pre- and post-intensive management sample sets and analysed separately. The programme STRUCTURE (Pritchard et al. 2000) implements a Bayesian approach to estimate the most likely number of population clusters (K). By choosing the admixture model and assuming gene flow among population clusters, a proportion of the genome of each individual is assigned to each inferred population according to allele frequency by minimising Hardy–Weinberg deviations. The method allows the input of predefined population to allow the comparison of ecologically inferred population structure with the structure suggested from allele frequencies. For this study, populations were delineated using a combination of the natural boundaries shown by the behaviour of the monitored populations and the natural topography and relief of the island, resulting in seven sub-populations for the Mauritius parakeet (six wild and one captive; see Fig. 2). The Monte-Carlo Markov chain parameters in STRUCTURE were ten independent simulations of 1,500,000 iterations, each with a burn-in of 50,000 for a range of values of K, from K = 1–20, and a separate alpha was inferred for each population. The assignment values, log likelihood scores and DK (Evanno et al. 2005) were examined in order to determine the optimal number of clusters. BAPS v5 (Corander et al. 2003, 2008) was also used to assess population structure. Its computational approach is somewhat different to STRUCTURE and is considered to better able to identify distinct clusters when Fst estimates between subpopulations are small (Latch et al. 2006). However, this method does tend to create more populations

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when cluster analysis is based on individuals (Frantz et al. 2009). A mixture analysis was first implemented to identify the number of clusters in the data (a cluster was defined as having five or more individuals) considering a maximum K = 1–15, with five repetitions. The results of these mixture analyses were then used to conduct the admixture analysis (Corander and Marttinen 2006). Tests for patterns of isolation by distance were performed using the ISOLDE programme within the GenePop software (Rousset 1997, 2000). This programme regresses estimates of Fst/(1-Fst) to the natural log of the geographic distance between populations and performs a simple Mantel test on these (Rousset 1997). Geographic distances between each pair of areas were calculated as linear distance between mean latitude and longitude of sample locations from each area. The captive population of Mauritius parakeets was excluded from this analysis.

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Fig. 3 STRUCTURE bar plot output for a pre-management individuals, and b post-management individuals, drawn from the seven putative populations sampled. BO_L Lower Bel Ombre, BO_U Upper Bel Ombre, Camp, G Gorges, MacS Macabe South, and SS South Scarp

Results All microsatellite loci were polymorphic and average gene diversity in the Mauritius parakeet was 0.64. Two pairs of loci (Peq03–Peq05 and Peq09–Peq12) were in linkage disequilibrium (Raisin et al. 2009); consequently Peq05 and Peq09 were excluded from the analyses. Loci that were sex linked (linked to the Z-chromosome; Peq16 and Peq21) were also excluded for the purposes of this study, thus a total of 16 loci were used in this analysis. 20% of the samples were re-amplified and no evidence for allelic dropout was found in these repeats. Global Fst for the entire Mauritius parakeet dataset was low (Fst = 0.0366). Global Fst of the pre-intensive management birds (Fst = 0.072) was higher than that of the post-intensive management birds (Fst = 0.021) although this difference was not significant (p = 0.110). STRUCTURE analysis of the entire Mauritius parakeet dataset did not reveal a clear signal of population structure. The log likelihood values reached an asymptote at K = 6 and the highest value for DK was achieved at K = 2, followed by K = 4 and bar plots of these assignments showed no clear pattern between geographic location and STRUCTURE inferred cluster (see supplementary material). Analysis of the pre-intensive management data alone suggested K = 4 and the bar plot shows strong clustering of the southern Bel Ombre birds but relatively mixed ancestry of birds from the other regions (Fig. 3a). In comparison, analysis of the post-management dataset suggested an optimal clustering of K = 3, but these were homogenised between the populations and there was no visible distinction between individuals from any area (Fig. 3b). See supplementary material for log likelihood plots and calculation of DK.

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Fig. 4 BAPS bar plot output for a pre-management individuals, and b post-management individuals, drawn from the seven putative populations sampled. BO_L Lower Bel Ombre, BO_U Upper Bel Ombre, Camp, G Gorges, MacS Macabe South, and SS South Scarp

Analysis of the entire dataset using BAPS suggested the optimal number of groups was K = 2 with a probability of 1. When the pre-management data were considered separately, the optimal number of clusters remained at K = 2 with a probability of 1. However, when the post-management data were considered separately, the optimal outcome was a single cluster, K = 1, with a probability of 1 (see Fig. 4). When the genotype data were analysed separately for pre- and post-intensive management periods of the Mauritius parakeet, there was no significant difference in the average heterozygosity (0.662 and 0.642, respectively; W = 38.0, p = 0.127). There was also no significant difference detected in the number of alleles per locus between the two periods (W = 6.5, p = 0.066). Given that the two southern populations at Bel Ombre are geographically the most isolated from all other populations, individuals from

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Table 3 Results of Isolation by Distance analysis for the entire Mauritius parakeet dataset; the pre-intensive management dataset, and the pre-intensive management dataset with data for Bel Ombre (BO) birds removed Scenario

r2

r

P

DF

All Mauritius parakeets

0.0203

0.142478

0.251

13

Pre-management Mauritius parakeets*

0.4532

0.673201

0.047

13

Pre-management Mauritius parakeets (BO excluded)

0.2827

0.531695

0.093

13

* Significant at 95%

that population are most likely to show genetic differences when compared to the rest of the population. Therefore average numbers of alleles per locus and private alleles per population were compared between these two regions across the pre- and post-intensive management periods. Prior to intensive management, the average number of alleles per locus detected in the southern sub-populations was significantly lower than in the northern sub-populations combined (southern = 3.44, northern = 5.81; W = 0.0, p \ 0.001), and following intensive management this difference was still significant (post-intensive management; southern = 4.56, northern = 5.19; W = 0.0, p = 0.006). Prior to intensive management, a total of three private alleles were detected in the southern sub-populations and ten amongst the northern sub-populations, whereas following intensive management there were significantly fewer private alleles (none in the southern sub-populations and a single private allele in the northern sub-populations (W = 41.5, p = 0.028) (see supplementary material). Tests for isolation by distance revealed a significant relationship between degree of genetic differentiation and geographical distance in the Mauritius parakeet population prior to management. However, the significant relationship between geographic distance and estimates of Fst did not hold when data for the southern Bel Ombre regions were removed from the analysis, and no significant correlation was detected in the entire Mauritius parakeet dataset (Table 3).

Discussion Our study has demonstrated how intensive conservation management can have a considerable genetic effect on a restored population. Prior to intensive management, the Mauritius parakeet population showed a higher level of population structure compared to the post-intensive management population. Pre-intensive management individuals showed a pattern of clustering that reflected their

geographical location, with both genetic clustering analyses identifying those birds from the southern region of Bel Ombre as being genetically differentiated from the rest of the population. The pattern of isolation by distance observed in the pre-management population was the result of this population genetic structure. In contrast, the clusters detected in the post-management period were dispersed across the geographical range of the population and individual assignments were very low, suggesting that ancestral lineages which were previously isolated in the pre-intensive management period may not have been fully masked by management activities. This can be attributed to the movement of birds between sites in the intensive management period and to the release programme, in particular birds that were moved from the southern to the northern populations (and vice versa). In addition to this, the majority of transfers were of wild birds to the captive population at GDEWS, the majority of which were later released as part of the on-going release programme. For example, in the 2002–03 season 19 birds were released in the southern Bel Ombre forest of which only six were captive reared and the remainder had been rescued from wild sites. Furthermore, significantly more private alleles were detected in both regions before intensive management began than in the post-intensive management period. Although the northern population still showed a significantly higher average number of alleles per locus in both management periods, this result is likely to be a consequence of its larger population size. Despite the loss of genetic structure, we found little evidence of an overall loss of genetic diversity. When the population was considered as a whole, there was no overall difference in heterozygosity or number of alleles per locus (irrespective of sample location) before and after intensive management. The signal of genetic structure observed in the Mauritius parakeet population before intensive management began is intriguing given this species’ recent population crash. Two contrasting explanations could account for the initial structure. Firstly, fragmentation of the dwindling endemic population as a consequence of recent habitat loss could have exacerbated the random effects of genetic drift on the small population, thus increasing levels of genetic differentiation between fragments (Caizergues et al. 2003; Segelbacher et al. 2003). Alternatively, the initial structure may be representative of structure that naturally occurred in the ancestral population. Mauritius parakeets do show high levels of philopatry despite their movements in the non-breeding season when individuals are seen to roam further and aggregate together in communal feeding areas (Jones 1987). Such site fidelity would imply that ancestral structure may have been possible and could be a consequence of the natural behaviour of this species.

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However, retention of ancestral genetic structure would be surprising for a severely bottlenecked population. It is perhaps more likely that the signal of structure detected prior to intensive management is more recent and a direct consequence of genetic drift driven by the fragmentation of the parakeet habitat which has taken place over the last 300 years (Cheke and Hume 2008). Detailed records of the spread of agriculture across Mauritius since human colonisation in the Seventeenth century documents systematic habitat fragmentation, supporting the idea that genetic drift contributed to the pattern of structure observed prior to intensive management. These records show not only how the south west corner of Mauritius was among the last of the areas to be cleared, but also how the Bel Ombre forest fragment (which supports the southern population of Mauritius parakeets) became isolated from the more northerly core area of forest that subsequently remained in the Black River Gorges (Cheke and Hume 2008). The effect that habitat fragmentation can have on genetic diversity has been documented for many continental bird species, such as red-cockaded woodpeckers (Picoides borealis) (Haig et al. 1996) and greater rhea (Rhea americana albescens) (Bouzat 2001), as well as more recent examples: the white-starred robin (Pogonocichla stellata) (Galbusera et al. 2004) and the golden-cheeked warbler (Dendroica chrysoparia) (Lindsay et al. 2008). Our study has demonstrated how genetic structure has been homogenised by a conservation management programme. This finding suggests that genetic monitoring of populations undergoing reintroductions and translocations should be carried out not just prior to intervention, but also afterwards as part of long-term monitoring to assess the genetic impacts of population management. Webley et al. (2007) detected two genetically distinct clusters in an introduced population of European fallow deer (Dama dama dama) in Tasmania; as such, the authors recommended that migration between the two clusters be encouraged to promote gene flow. Importantly, although our study has shown how gene flow has been promoted in the Mauritius parakeet as a consequence of management, these actions were motivated by a need to increase productivity rather than to promote genetic mixing. We recommend caution when considering similar actions in cases where observed structure is thought to be indicative of local adaptation because homogenisation of genetic variation could have potentially negative impacts. However, in the case of small populations of endangered species, these potential negative impacts will likely be outweighed by the more immediate benefits of minimising short-term, drift-induced losses of genetic diversity, particularly in cases where intensive intervention might hold the greatest promise for population recovery. Our finding that structure does appear to have been affected by intensive conservation management, is likely to

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be important for conservation programmes considering translocations and reintroductions. Population viability analysis has been used to assess reintroduced populations and model the potential impact of follow-up translocations on the demography of the new population (Armstrong and Ewen 2001), but our study suggests that follow up translocations may also help to limit the effects of genetic drift. In conclusion, the genetic homogenisation revealed for the Mauritius parakeet population can be interpreted as a beneficial consequence of the intensive management as the re-distribution of genetic material has reduced the likelihood of private alleles being lost from the recovering population through genetic drift. Given that this species is currently exposed to PBFD, the recovering population is likely to fare better against this threat if it is as genetically diverse as possible (Acevedo-Whitehouse et al. 2003). Therefore, we suggest that conservation programmes should actively promote re-distribution of genetic diversity when implementing intensive management, especially if fragmented sub-populations face additional exposure to genetic drift. Given the evidence from this study, genetic monitoring of restored or reintroduced populations should be encouraged to ensure persistence of recently restored populations of endangered species. Acknowledgments This work was funded by a NERC PhD studentship award to JG with CASE partner Wildlife Vets International. The laboratory work was performed at the NERC Biomolecular Analysis Facility at the University of Sheffield and we would particularly like to thank Deborah Dawson and Andy Krupa for their assistance. We also thank all the staff of the National Parks and Conservation Service of the Government of Mauritius and the Mauritian Wildlife Foundation for support with fieldwork.

References Acevedo-Whitehouse K, Gulland F, Greig D, Amos W (2003) Disease susceptibility in California sea lions. Nature 422:35–36 Armstrong DP, Ewen JG (2001) Assessing the value of follow-up translocations: a case study using New Zealand robins. Biol Conserv 101:239–247 Armstrong DP, Ewen JG (2002) Dynamics and viability of a New Zealand robin population reintroduced to regenerating fragmented habitat. Conserv Biol 16:1074–1085 Beier P, Noss RF (1998) Do habitat corridors provide connectivity? Conserv Biol 12:1241–1252 Bouzat JL (2001) The population genetic structure of the Greater Rhea (Rhea americana) in an agricultural landscape. Biol Conserv 99:277–284 Caizergues A, Ra¨tti O, Helle P, Rotelli L, Ellison L, Rasplus J-Y (2003) Population genetic structure of male black grouse (Tetrao tetrix L.) in fragmented vs. continuous landscapes. Mol Ecol 12:2297–2305 Cheke AS, Hume J (2008) Lost land of the Dodo. An ecological history of Mauritius, Reunion & Rodrigues. T & AD Poyser, London

Conserv Genet (2012) 13:707–715 Corander J, Marttinen P (2006) Bayesian identification of admixture events using multilocus molecular markers. Mol Ecol 15: 2833–2843 Corander J, Waldmann P, Sillanpaa MJ (2003) Bayesian analysis of genetic differentiation between populations. Genetics 163:367–374 Corander J, Marttinen P, Siren J, Tang J (2008) Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinformatics 9:539 Debinski DM, Holt RD (2000) A survey and overview of habitat fragmentation experiments. Conserv Biol 14:342–355 Duffy K (1993) Echo parakeet project-Progress report August 1992– April 1993. Mauritian Wildlife Foundation, Vacoas Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620 Fahrig L (2001) How much habitat is enough? Biol Conserv 100:65–74 Frankel OH, Soule ME (1981) Conservation and evolution. Cambridge University Press, Cambridge Frankham R, Ballou JD, Briscoe DA (2010) Introduction to conservation genetics, 2nd edn. Cambridge University Press, Cambridge Frantz AC, Cellina S, Krier A, Schley L, Burke T (2009) Using spatial Bayesian methods to determine the genetic structure of a continuously distributed population: clusters or isolation by distance? J Appl Ecol 46:493–505 Galbusera P, Githiru M, Lens L, Matthysen E (2004) Genetic equilibrium despite habitat fragmentation in an Afrotropical bird. Mol Ecol 13:1409–1421 Goudet J (1995) FSTAT (Version 1.2): a computer programme to calculate F-Statistics. J Hered 86:485–486 Haig SM, Bowman R, Mullins TD (1996) Population structure of redcockaded woodpeckers in south Florida: RAPDs revisited. Mol Ecol 5:725–734 Hartl DL, Clark AG (1997) Principles of Population Genetics. Sinauer Associates, Sunderland Jones CG (1987) The larger land-birds of Mauritius. In: Diamond AW (ed) Studies of Mascarene Island birds. British Ornithologists Union and Cambridge University Press, Cambridge, pp 208–301 Jones CG, Duffy K (1993) Conservation management of the echo parakeet. Dodo 29:126–148 Jones CG, Swinnerton KJ, Thorsen M, Greenwood A (1998) The biology and conservation of the echo parakeet Psittacula eques of Mauritius. In: Proceedings of IV International Parrot Convention, Tenerife, pp 110–123 Kenta T, Gratten J, Haigh NS, Hinten GN, Slate J, Butlin RK, Burke T (2008) Multiplex SNP-SCALE: a cost-effective mediumthroughput single nucleotide polymorphism genotyping method. Mol Ecol Resour 8:1230–1238 Latch E, Dharmarajan G, Glaubitz J, Rhodes O (2006) Relative performance of Bayesian clustering software for inferring

715 population substructure and individual assignment at low levels of population differentiation. Conserv Genet 7:295–302 Lindsay DL, Barr KR, Lance RF, Tweddale SA, Hayden TJ, Leberg PL (2008) Habitat fragmentation and genetic diversity of an endangered, migratory songbird, the golden-cheeked warbler (Dendroica chrysoparia). Mol Ecol 17:2122–2133 Lovegrove TG, Nieuwland AB, Green S (1995) Interim report on the echo parakeet conservation project, February 1995. Mauritian Wildlife Foundation, Vacoas Marshall TC, Slate J, Kruuk LEB, Pemberton JM (1998) Statistical confidence for likelihood-based paternity inference in natural populations. Mol Ecol 7:639–655 Nicholls JA, Double MC, Rowell DM, Magrath RD (2000) The evolution of cooperative and pair breeding in thornbills Acanthiza (Pardalotidae). J Avian Biol 31:165–176 Owens IPF, Bennett PM (2000) Ecological basis of extinction risk in birds: Habitat loss versus human persecution and introduced predators. Proc Natl Acad Sci USA 97:12144–12148 Pritchard J, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959 Raisin C, Dawson DA, Greenwood AG, Jones CG, Groombridge JJ (2009) Characterization of Mauritius parakeet (Psittacula eques) microsatellite loci and their cross-utility in other parrots (Psittacidae, Aves). Mol Ecol Resour 9:1231–1235 Raymond M, Rousset F (1995) GENEPOP (Version 1.2): population genetics software for exact tests and ecumenicism. J Hered 86:248–249 Rice WR (1989) Analysing tables of statistical tests. Evolution 43:223–225 Richards H, Chowrimootoo A, Garrett M, Bednarczuk E, Smith D, Tollington S, Skinner A (2010) Management of the echo parakeet in the wild 2009/10. Mauritian Wildlife Foundation, Vacoas Ritchie BW, Niagro FD, Lukert PD, Latimer KS, Steffens WL, Pritchard N (1989) A review of psittacine beak and feather disease: characteristics of the PBFD virus. J Assoc Avian Vet 3:143–149 Rousset F (1997) Genetic differentiation and estimation of gene flow from F-Statistics under isolation by distance. Genetics 145: 1219–1228 Rousset F (2000) Genetic differentiation between individuals. J Evol Biol 13:58–62 Seddon PJ, Armstrong DP, Maloney RF (2007) Developing the science of reintroduction biology. Conserv Biol 21:303–312 Segelbacher G, Ho¨glund J, Storch I (2003) From connectivity to isolation: genetic consequences of population fragmentation in capercaillie across Europe. Mol Ecol 12:1773–1780 Webley LS, Zenger KR, Hall GP, Cooper DW (2007) Genetic structure of introduced European fallow deer (Dama dama dama) in Tasmania, Australia. Eur J Wildl Res 53:40–46

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