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Genetic assessment of the San Clemente Island loggerhead shrike reveals evidence of historical gene flow with Santa Catalina Island
Global Ecology and Conservation 11 (2017) 42–52
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Original research article
Genetic assessment of the San Clemente Island loggerhead shrike reveals evidence of historical gene flow with Santa Catalina Island L.Y. Rutledge a, *, A. Coxon b , B.N. White a a b
Trent University, Biology Department, 2140 East Bank Drive, Peterborough, Ontario, K9L 1Z8, Canada Trent University, Environmental & Life Sciences Graduate Program, 1600 West Bank Drive Peterborough, Ontario, K9J 7B8, Canada
article
info
Article history: Received 5 December 2016 Received in revised form 11 April 2017 Accepted 11 April 2017
Keywords: Conservation Endangered species Gene flow Loggerhead shrike Microsatellites Mitochondrial DNA Population genetics
a b s t r a c t The San Clemente loggerhead shrike (Lanius ludovicianus mearnsi) is an endangered species endemic to San Clemente Island in California. Previous genetic analyses of the California shrike populations have had mixed results due to small sample sizes and/or few genetic markers. Here we present a rigorous analysis of 381 historical and contemporary California shrike samples genotyped at 11 new polymorphic microsatellite loci and the mitochondrial DNA control region. Our results suggest generally high genetic diversity in all populations and that loggerhead shrikes on San Clemente Island are genetically differentiated from both the Mainland and other island populations. Bayesian clustering suggests primarily three genetically differentiated populations: (1) Mainland, (2) San Clemente Island, and (3) the islands of Santa Catalina, Santa Cruz and Santa Rosa. Historically, however, the San Clemente Island shrike cluster closely with the Santa Catalina Island population, suggesting historical gene flow between these populations. A Bayesian phylogeny of common mtDNA haplotypes across North America reveals two primary clades and a general division between western and eastern populations. Geographic patterns suggest maternal gene flow from mainland to the islands but not vice versa. These results indicate that the captive breeding program has been successful at maintaining genetic diversity in the San Clemente Island shrike population, but that allele frequencies have shifted significantly over the past 100 years. Overall, our results suggest the San Clemente shrike (L. l. mearnsi) is a validated subspecies that is morphologically and genetically distinct, and that ongoing conservation efforts are justified. © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction The loggerhead shrike (Lanius ludovicianus) is a passerine bird that was once found throughout North America. Habitat alteration has led to a shift in its range and numbers have declined in several core regions of its historical distribution (see Fig. 1 in Cade and Woods, 1997). In California, loggerhead shrikes have been categorized, either morphologically or genetically, into three main subspecies: L. l. gambeli on the mainland L. l. anthonyi on the northern Channel Islands; and L. l. mearnsi on San Clemente Island (see Eggert et al., 2004). At the beginning of the 20th century, sightings of the San Clemente Island shrike were common and the population was considered well-distributed, but by the mid-1980s their population had plummeted to fewer than 30 individuals (Stahl et al., 2014).
*
Corresponding author. E-mail addresses: [email protected] (L.Y. Rutledge), [email protected] (A. Coxon), [email protected] (B.N. White).
http://dx.doi.org/10.1016/j.gecco.2017.04.002 2351-9894/© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
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The San Clemente loggerhead shrike (L. l. mearnsi) was listed by the United States Fish and Wildlife Service (USFWS) as a federally endangered species in 1977 and is currently considered one of the rarest birds in North America. Non-endemic predators, such as cats (Felis catus) and rats (Rattus rattus), played a primary role in the decline (Shuford and Gardali, 2008) and subsequent degradation of nesting habitat by introduced livestock, namely sheep (Ovis aries) and goats (Capra hircus), impeded recovery efforts (Scott and Morrison, 1990). A monitoring program began on San Clemente Island in 1991 to ensure appropriate management of the population. Roemer and Wayne (2003), however, argued that the predator control program that is part of the shrike conservation on Clemente is endangering the endemic San Clemente Island Fox (Urocyon littoralis clementae). Previous genetic studies concluded that the San Clemente Island shrike had evolved sufficient genetic differentiation from mainland shrike subspecies (L.l. gambeli and L.l. grinelli) to justify its conservation as an evolutionarily significant unit (ESU). Although genetic analyses have suggested that San Clemente is distinct (Mundy et al., 1997a, 1997b; Eggert et al., 2004), Patten and Campbell (2000) suggested little differentiation between Clemente and the other islands due to genetic swamping by the other island subspecies (L. l. anthonyi). More recently, Caballero and Ashley (2011) analyzed 96 historical samples from the islands and mainland from 1897–2008 to clarify the evolutionary lineage and conservation status of L. l. anthonyi. Their interpretation was that historical L. l. mearnsi from San Clemente had mixed ancestry and that L. l. anthonyi from Santa Rosa and Santa Cruz Islands were genetically distinct. They found three genetic clusters (Mainland, San Clemente; Santa Catalina / Santa Rosa/ Santa Cruz), with post 1991 San Clemente being less admixed than the 1915 population. Additionally, they found the historical shrike population on San Clemente (up until 1915) was different than that population post 1991. Although various genetic analyses have provided insight into the population structure of California shrike populations, previous work has been limited by the small sample sizes and relatively few genetic markers. It has been suggested that further analysis with more samples and more genetic markers could help to clarify the relationships among the different populations (Caballero and Ashley, 2011). The purpose of this study was to use more genetic markers and more substantial sampling over a broad time period to clarify a number of conflicting conclusions regarding the San Clemente Island shrike population. We tested the hypotheses that: (a) the San Clemente shrike is, and has always been, genetically differentiated from other island/mainland populations; (b) Santa Catalina Island serves as a stepping stone for gene flow between the mainland and San Clemente Island, and (c) that species identified morphologically as L. l. mearnsii cluster accordingly with the San Clemente Island population. 2. Methods 2.1. Sample collection and DNA extraction A comprehensive collection of over 400 loggerhead shrike samples dated between 1897 and 2004 was assembled, representing L. l. mearnsi from San Clemente Island (n = 180), L.l. anthonyi from Santa Catalina, Santa Rosa, Santa Cruz and Anacapa Islands (n = 80), and L.l. gambeli and L.l. grinnelli from a large area of mainland California (n = 143) (Fig. 1). We focused on collecting contemporary samples from wild-nesting shrikes and from shrikes of unknown origin captured on San Clemente Island, nesting shrikes on Santa Catalina Island, and samples from shrikes captured from areas of mainland California. Samples from individuals representing 17 out of 18 existing genetic founder lines of L.l. mearnsi were contributed by the San Diego Zoo Center for Research of Endangered Species (CRES). We also obtained historical samples from the San Diego, Santa Barbara and Los Angeles Museums of Natural History, as well as the University of California at Los Angeles (UCLA). A toe pad was removed from the foot of each museum specimen, following the methods outlined in Mundy et al. (1997c). Captured shrikes were either sampled from the nest prior to fledging, in which case feathers were plucked from the flank region, or captured using a modified version of a Potter’s trap – in which case a blood sample was taken from the jugular vein according to methods described in Santolo and Yamamoto (1999). This work was conducted under Institutional Animal Care and Use Committee Protocol #178, California Department of Fish and Game Scientific Collectors Permit #002407 and associated Memorandum of Understanding, and Federal Bird Banding Permit #22717. R R Genomic DNA was extracted from blood samples stored on Whatman⃝ FTA⃝ collection cards, with a DNeasy Tissue Kit (Qiagen) according to the manufacturer’s instructions. DNA extraction from the feather and toe pad samples followed the protocol modifications outlined in Segelbacher (2002), whereas the DNA extraction from museum samples followed the modified protocol of Mundy et al. (1997c). Furthermore, the following precautions were taken to ensure accuracy of results from the historical museum samples: (1) all work was conducted in a lab where no other avian research was being conducted; (2) DNA extraction and PCR amplification on all museum samples was carried out at a separate time and at a separate bench space from the modern samples; (3) benchtops were decontaminated before each use with Decon (Decon Laboratories Limited, UK) and then covered with new benchcoat; (4) dedicated new pipettes (and dedicated consumables and reagents) were used for processing the historical specimens and all equipment was cleaned with Decon prior to each use; (5) DNAase-free filter tips were used throughout the project; (6) museum samples were split in half and extracted twice – the second extraction was done at a later date – so the results were duplicated at least two times; (7) negative extraction and PCR controls were used throughout and no positive results were obtained from the amplification of the negative controls. Although some additional extractions of some historical samples may have occurred after extraction of contemporary samples, the precautionary steps outlined above minimized the risk of contamination and false results.
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2.2. Mitochondrial DNA & phylogenetic analysis A total of 214 samples were sequenced at the mitochondrial DNA (mtDNA) control region. These samples represented shrikes banded on San Clemente Island from 1897 to 2004 (n = 88), shrikes banded on Santa Catalina, Santa Cruz, and Santa Rosa Islands from 1907 to 2004 (n = 77), and shrikes banded on the coastal mainland areas of California from 1923 to 2003 (n = 49). Amplification of 249bp of the mtDNA control region was performed using the primers DLL1 and DLH1 (Mundy et al., 1997b), in 25 µL volumes including 1.0 µL Taq polymerase (Invitrogen), 1X PCR buffer, 50 µM each dNTP, 0.4 uM each primer, 1.5 mM MgCl2 (increased to 2.5 mM for DNA extracted from skin and feather samples), and 25 µg bovine serum albumin (BSA). The thermal cycling conditions were as follows: 3 min at 94 ◦ C; 35 cycles of 94 ◦ C for 30 s, 56 ◦ C for 60 s, and 72 ◦ C for 90 s; followed by a final extension of 72 ◦ C for 10 min. Note that low template samples (feathers and museum) were cycled 55 times. Amplified products were visualized on a 1.2% agarose gel, cleaned with ExoSAP-IT (USB Corporation, Ohio) and analyzed on a MegaBace 1000 with a DYEnamic ET Dye Terminator Cycle Sequencing Kit (GE Healthcare Bio-Sciences, Quebec). For samples that had an unresolved base call at site 410 (with both C and T peaks), samples were re-extracted and re-sequenced. Museum samples amplified as a single fragment and they were sequenced at least twice in both forward and reverse directions to ensure accuracy. Sequences were compared to published sequences and assigned haplotypes from the literature (Table 1). New haplotypes were identified as LluNx. Sequences were aligned with ClustalW in Geneious 6.1.8 (Biomatters). The alignment was trimmed to 200bp, which captured all variable sites. The most common mtDNA haplotypes (where n ≥ 5) found in this study and in the literature were used to construct a Bayesian phylogenetic tree with the default HKY85 substitution model, which incorporates parameters for realistic rates of substitution, in the MrBayes 3.2.2 (Ronquist et al., 2011) plug-in of Geneious 6.1.8 with the following parameters: gamma rate variation with 4 categories, 110,000 chain length, 4 heated chains, subsampling frequency of 200 and a burn-in of 100,000. Sequence AI1 (Genbank Accession EU490661) from Aphelocoma insularis was used as an outgroup to root the tree. 2.3. Microsatellite analysis (genetic diversity, divergence and clustering analysis) Eleven new polymorphic microsatellite loci were developed for this study (see Coxon et al., 2012). LLU15, LLU39, LLU55, LLU82, LLU85, LLU90, LLU95, LLU102, LLU112, LLU157 and LLU176 were amplified in 3 multiplexed PCR reactions as outlined in Coxon et al. (2012). These loci have been shown to be appropriate for population structure and pedigree analysis; they are not sex-linked and all but two (Llu102; Llu15) have been shown to be in Hardy–Weinberg equilibrium after Bonferroni correction (Coxon et al., 2012). Each 10 µL multiplex reaction contained 5ng genomic DNA, 4 µL QIAGEN Multiplex PCR Master Mix and 1 µL of forward and reverse primers at 0.56 µM to 2.3 µM of each primer. The thermal cycling conditions were as follows: 15 min at 95 ◦ C; 35 cycles of 94 ◦ C for 30 s, 60 ◦ C for 90 s and 72 ◦ C for 90 s; followed by a final extension of 72 ◦ C for 10 min. A total of 404 samples were genotyped at 11 microsatellite loci. Samples with low DNA template concentration were amplified singly for each locus with 55 cycles, and then pooled prior to genotyping. PCR products were genotyped on a MegaBace 1000 (GE Healthcare) and alleles were scored with the CEQ8000 Genetic Analysis System (Beckman Coulter) and checked manually. Samples with more than 4 missing alleles were excluded from further analyses, such that 381 of 404 genotyped samples were subsequently analyzed. We assessed the dataset for scoring error in Micro-checker (Van Oosterhout et al., 2004). To estimate allele frequency changes over time, we divided each group of samples into three timescales: Historical (Hist: 1897–1949), Middle (Mid: 1950–1999), and Contemporary (Cont: 2000–2004). We calculated estimates of heterozygosity and Fst among populations (999 permutations) in GenAlEx 6.501 (Peakall and Smouse, 2012). We also calculated Jost Dest estimates of divergence with 1000 replicates in SMOGD (Crawford, 2010). For Bayesian clustering analysis in the program STRUCTURE v. 2.3.4 (Falush et al., 2003), we used the San Diego zoo studbook to filter for relatedness. Siblings were removed randomly, leaving one single offspring from a known captive breeding pair in the dataset. The remaining dataset included 303 individuals. To estimate the number of clusters (K ) in the dataset we implemented the I-model with possible number of clusters ranging from K = 1 to 10. Each K value was run 5 times with a burn-in of 250,000 followed by 500,000 iterations. These parameters are above the minimum requirements suggested in the Structure software manual, and they meet the requirement of convergence of summary statistics. Output was analyzed in Structure Harvester (Dent and vonHoldt, 2012) and both the maximum LnProbData and the second order rate of change (Evanno et al., 2005) were visualized to estimate the optimal number of clusters. Subsequently, K = 3 (Supplementary Fig. 1) was run 10 times with the same parameters that were used in the initial runs and Q values were averaged over the 10 runs. Standard errors were calculated to identify any significant deviation in individual runs. We also conducted a Principal Components Analysis (PCA) in the adegenet package (Jombart, 2008) of R 3.2. 3. Results 3.1. Mitochondrial DNA & Phylogeny We identified 10 new haplotypes identified as Lluxx (Table 1: Genbank numbers MF101793-MF101801). LluN6, LluN10, LluN11, LluN12, LluN13 were all found in single occurrences from the mainland population, with LluN6 and LluN13 found
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only in samples collected in 1935. Haplotype LluN8, identified as a heteroplasmic haplotype, was documented in a single occurrence of a captive bred San Clemente female (Sample SB833). The haplotype LluN5 is a heteroplasmic haplotype but the variation with a cytosine at position 335 was documented recently in Olsson et al. (2010) (AH744) from a L. l. ludovicianus mexicanus/gambeli specimen from the University of Greifswald collection. Several individuals appear to exhibit single-site heteroplasmy at site 410 (Supplementary Figure 2). Duplicate rounds of extraction and multiple independent sequencing runs had consistent results, suggesting this is not contamination or a sequencing artifact. Siblings of one of the individuals were also sequenced with similar results at this site. Heteroplasmic haplotype LluN4 is a combination of Haplotype A and Haplotype L2, which we tracked in pedigrees based on the San Diego Zoo Studbook (Supplementary Figure 3). We documented 13 different haplotypes in the Mainland population (C most common), 7 haplotypes in the San Clemente Island population (A most common and L2 being found almost exclusively within that population), 3 haplotypes in the Santa Catalina Island population, 3 haplotypes in the Santa Cruz Island population, and 4 in the Santa Rosa Island population (Table 2). Seven of the eight L2 haplotypes were found in the San Clemente captive breeding individuals with the only other L2 haplotype found in a Mainland individual sampled near Los Angeles in 1969 (Supplemental File). The phylogenetic analysis of the most common haplotypes found across North America revealed two primary clades (Fig. 2). Based on the criterion of at least 5 occurrences of the haplotype, Haplotype B appears largely confined to the Channel Islands and L2 to San Clemente Island. There also appears to be an east–west division with haplotype C3 and C4 found in eastern North America, whereas Haplotype C1 was distributed across central and western North America (Fig. 3). Although Haplotype A is found throughout North American loggerhead shrike populations, the Channel Islands haplotypes are only found on the islands. 3.2. Microsatellite & clustering analysis Micro-checker output indicated no scoring errors in the dataset. Homozygote excess was suggested at the following loci: Llu15, Llu82, Llu90, Llu157, Llu39, and Llu102, which Micro-checker interprets as potential null alleles. It is, however, more likely that the excess is due to the influence of siblings from the captive breeding program being included in the initial analysis because bottleneck populations are known to have significant false positives in null allele detection (Dabrowski et al., 2014). Heterozygosity was generally high but lower than expected in every population. The Mainland population had the highest heterozygosity and San Clemente Island had the lowest, with the highest number of private alleles occurring in the Mainland population; private alleles were also found in the San Clemente and Santa Catalina Islands dataset (Table 3). As expected, the Mainland population had the highest number of alleles, but the San Clemente Island population also had a high number of alleles. San Clemente shrikes were most differentiated from the northern Channel Islands and most similar to Santa Catalina (Table 4). The Mainland and San Clemente Island populations were most differentiated based on Jost Dest comparisons which measures allele sharing, whereas the Santa Catalina Island population was most similar to the Mainland population based on pairwise Fst (Table 4). This pattern is generally similar across time periods (Table 5), although in some cases the sample sizes are too small for reliable estimates of differentiation. 3.3. Bayesian clustering Results from I-model Bayesian clustering analysis in the program STRUCTURE had the highest support for K = 3 clusters with somewhat lower support for K = 2 and some support for K = 5 (Supplementary Figure 1). At K = 2, San Clemente Island is clearly differentiated with three samples collected from the Mainland in 1991–1992 (ID 47803, 47822, 48102) (and identified morphologically as L. l. mearnsi), clustering with Q = 1.0 to the San Clemente Island population (Fig. 4). Similarly, individual SB565D (born in the captive breeding center) was field assigned to the Santa Catalina population because it was sampled there in 2003 after being transferred from San Clemente Island; this individual clustered with Q = 1.0 to the San Clemente Contemporary population. At K3, the Mainland becomes differentiated from the island populations and at K5 the Mainland population becomes highly admixed and the historical San Clemente and Santa Catalina populations emerge as an independent single cluster. When the STRUCTURE output is ordered according to field identification of subspecies, the clustering shows a shift in the L. l. mearnsi subspecies and that those individuals historically identified as L. l. anthonyi in the Santa Catalina Island population were misclassified (Fig. 5). The Principal Components Analysis (PCA) was generally consistent with the STRUCTURE results and shows clear differentiation of San Clemente Island with overlap of Mainland and Santa Catalina, as well as some evidence of migration between San Clemente, Santa Catalina, and the Mainland (Fig. 6). 4. Discussion 4.1. Mitochondrial DNA & phylogeny Similar to the results reported in Caballero and Ashley (2011) we found both mtDNA haplotypes A and B on Santa Rosa and Santa Cruz Islands, although we did not find J in any of our samples and Haplotype B was found only in island birds.
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L.Y. Rutledge et al. / Global Ecology and Conservation 11 (2017) 42–52 Table 1 Variable sites of mtDNA control region haplotypes found in this study. Sequences with distinct equivalent heteroplasmy are indicated in BOLD. Haplotype names in parentheses are alternative names for the same sequence.
Table 2 mtDNA control region haplotypes by population. Haplotypes are based on the literature and new haplotypes documented in this study. Haplotype
Mainland (n = 49)
San Clemente Island (n = 88)
Santa Catalina Island (n = 39)
Santa Cruz Island (n = 21)
Santa Rosa Island (n = 17)
A B C D I7 L2 M/I1 LluN1 LluN3 LluN4 LluN5 LluN6 LluN8 LluN10 LluN11 LluN12 LluN13
7 0 31 1 1 1 1 0 1 0 1 1 0 1 1 1 1
59 6 8 0 0 7 0 1 0 6 0 0 1 0 0 0 0
16 12 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0
12 8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
5 10 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
Haplotype C was shared among the Mainland, San Clemente and Santa Catalina but was absent from Santa Cruz and Santa Rosa although this absence may be due to small sample sizes. Most of the new haplotypes were found in the Mainland population at low frequency, but one new non-heteroplasmic haplotype (LluN1) was found in a sample collected in 2004 from San Clemente Island. Also, haplotype L2 appeared primarily in samples from the captive breeding program (n = 7) with one L2 individual sampled in 1969 on the Mainland. This Mainland L2 sample clustered with Q = 0.999 to the Mainland population based on microsatellites, but the San Clemente captive breeding sample (SB758) clustered with Q = 0.997 to the Contemporary San Clemente cluster, suggesting historical introgression of this haplotype into the San Clemente population. Four of the other samples from the captive breeding population with the L2 haplotype were full siblings of SB758, one was unrelated (SB503), and one was the sister of the maternal grandmother (SB131). Of note is that the mother of SB131 is SB275 who was the descendant of a wild individual but is noted in the studbook as having haplotype A, which is only one base pair different from haplotype L2 with a T → C transition. The L2 haplotype has been identified as rare, but specific to the L. l. ludovicianus subspecies from southeastern
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Table 3 Genetic diversity estimates. Na = number of alleles, Ne = number of effective alleles. Location
N
Ho
He
Na
Ne
Private Alleles
Calculations based on complete dataset of 381 individuals before removal of siblings from the captive breeding program. Mainland San Clemente Island Santa Catalina Island Santa Cruz Island Santa Rosa Island Overall
131 174 38 21 17 381
0.703 0.552 0.583 0.618 0.616 0.614
0.820 0.628 0.726 0.675 0.681 0.706
12.8 10.9 7.2 5.7 5.8 8.5
6.7 3.1 4.2 3.8 3.8 4.3
23 6 1 0 0 n/a
Calculations based on dataset with siblings removed from the captive breeding program and data divided into Historical (1898–1949), Mid (1950–1999), and Contemporary (2000–2004) Mainland Historical Mainland Mid Mainland Contemporary San Clemente Historical San Clemente Mid San Clemente Contemporary (7 wild) Santa Catalina Historical Santa Catalina Mid Santa Catalina Contemporary Santa Cruz Historical Rosa Historical Rosa Mid Overall
46 57 30 22 11 61 24 10 4 21 12 5 303
0.658 0.713 0.726 0.621 0.533 0.618 0.603 0.541 0.545 0.618 0.597 0.655 0.619
0.794 0.815 0.810 0.650 0.501 0.649 0.703 0.685 0.634 0.675 0.652 0.642 0.684
10.7 11.0 10.2 6.3 4.0 9.5 6.4 5.0 4.0 5.7 5.1 4.4 6.8
6.0 6.1 6.1 3.6 2.2 3.3 3.7 3.6 3.4 3.8 3.4 3.6 4.1
5 4 4 3 1 2 1 0 0 0 0 0 n/a
Table 4 Genetic distance between populations. Fst is below diagonal and Jost Harmonic Mean of Dest across all loci is above diagonal. Calculations are based on complete dataset of 381 individuals before removal of siblings from the captive breeding program. Total individuals (N) = 381. All values are significantly different (p < 0.005) based on 999 permutations in the AMOVA function of GenAlEx 6.501. Location
N
Mainland
San Clemente Island
Santa Catalina Island
Santa Cruz Island
Santa Rosa Island
Mainland San Clemente Island Santa Catalina Island Santa Cruz Island Santa Rosa Island
131 174 38 21 17
– 0.137 0.060 0.087 0.105
0.403 – 0.109 0.159 0.169
0.217 0.214 – 0.071 0.070
0.205 0.350 0.193 – 0.019
0.265 0.370 0.157 0.028 –
Table 5 Genetic distance between subdivided populations. Fst is below diagonal and Jost Harmonic Mean of Dest across all loci is above diagonal. Calculations based on dataset with siblings removed from the captive breeding program and data divided into Historical (1898–1949), Mid (1950–1999), and Contemporary (2000–2004). Total individuals (N) = 303. * indicates not significant at p >0.05 based on 999 permutations in the AMOVA function of GenAlEx 6.501. Location/ Time Period
N
MainHist MainMid MainCont ClemHist ClemMid ClemCont CatIsHist CatIsMid CatIsCont CruzIsHist RosaIsHist RosaIsMid
MainHist MainMid MainCont ClemHist ClemMid ClemCont CatIsHist CatIsMid CatIsCont CruzIsHist RosaIsHist RosaIsMid
46 57 30 22 11 61 24 10 4 21 12 5
– 0.018 0.021 0.103 0.173 0.131 0.069 0.047 0.046 0.086 0.113 0.094
0.034 – 0.008 0.110 0.172 0.113 0.083 0.061 0.050 0.099 0.125 0.092
0.053 0.020 – 0.127 0.185 0.127 0.083 0.065 0.057 0.091 0.118 0.088
0.289 0.367 0.397 – 0.089 0.065 0.092 0.054 0.033 0.111 0.135 0.094
0.478 0.459 0.440 0.088 – 0.060 0.178 0.154 0.097 0.208 0.225 0.200
0.397 0.321 0.333 0.115 0.048 – 0.129 0.094 0.067 0.146 0.183 0.144
0.209 0.275 0.292 0.215 0.293 0.277 – 0.038 0.028* 0.100 0.112 0.072
0.155 0.200 0.237 0.126 0.225 0.162 0.074 – 0.019* 0.046 0.056 0.039
0.116 0.099 0.183 0.075 0.067 0.080 0.020 0.044 – 0.055 0.097 0.013*
0.192 0.265 0.238 0.302 0.402 0.338 0.240 0.117 0.117 – 0.028 0.015*
0.290 0.403 0.333 0.307 0.366 0.417 0.214 0.130 0.140 0.030 – 0.028*
0.171 0.174 0.143 0.168 0.245 0.279 0.126 0.044 0.001 0.039 0.027 –
United States (Vallianatos et al., 2001, 2002), so finding it within an historical Mainland California sample (which was not categorized to species morphologically) and especially within the captive breeding population of L. l. mearnsii with relatively high frequency is very unexpected. The data show several cases of heteroplasmy in the mtDNA control region. The state of mtDNA heteroplasmy, where more than one mitochondrial sequence occurs in a single individual, was once thought to be rare. Current thinking has changed, however, as mtDNA heteroplasmy is documented more frequently in both plant and animal taxa and arises due to recombination, small-scale mutation, or paternal leakage (Kmiec et al., 2006; McLeod and White, 2010). Although more common in plant mtDNA, recombination has been noted in humans (Kajander et al., 2000, 2001) but remains controversial. Paternal leakage of mtDNA has been noted in birds (Kvist et al., 2003), with heteroplasmy of tandem repeat patterns in the mtDNA control region documented in San Clemente Island shrike collected between 1991 and 1992 (Mundy et al., 1996).
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Fig. 1. Map of locations for samples used in this study.
The heteroplasmy observed in our data involves transitions from T → C (based on Haplotype A). Although DNA degradation can result in identification of false transitions, the most common sequencing error is due to deamination of cytosine residues such that C → T, with T → C transitions in contemporary samples being infrequent (Hofreiter et al., 2001). The rare occurrence of this transition combined with our multiple extractions and sequencing of heteroplasmic individuals, suggests the results are not due to sequencing error associated with DNA degradation. As well, the LluN4 heteroplasmic haplotype is a combination of Haplotype A and L2, both of which we tracked through the pedigrees based on the San Diego Zoo studbook. We hypothesize the heteroplasmy may be due to paternal leakage, although further sequencing of complete pedigrees would help resolve this more completely. Documenting multiple copies of mtDNA in individuals may be important for the captive breeding program since mtDNA heteroplasmy has been linked to phenotypic variation and disease in humans (Wallace and Chalkia, 2013). 4.2. Microsatellite & clustering analysis We identified relatively high genetic diversity in the San Clemente Island population, and both the historical and contemporary heterozygosity is higher than reported in Mundy et al. (1997a) and Eggert et al. (2004), but this is likely due to larger sample sizes and more markers used in our dataset. Although measures of genetic differentiation were low, the low level of allele sharing suggests limited gene flow between the Mainland and San Clemente Island, which is consistent with data reported in Mundy et al. (1996, 1997a). The lack of allele sharing, however, may be due in part to controlled breeding in the San Clemente population and the lack of dispersal from the islands to the mainland. Clustering analysis with Structure and PCA supports previous reports of three primary genetic types: Mainland (L. l. gambeli), Northern Channel Islands (L. l. anthonyi), and San Clemente Island (L. l. mearnsi) (Caballero and Ashley, 2011) but is in contrast to the suggestion by Eggert et al. (2004) that Santa Catalina is a separate cluster. Our dataset utilizes 11 new microsatellite loci and a larger sample size from all populations and may, therefore, provide more accurate genetic clustering estimates. Also, the genetic analysis confirms that the San Clemente subspecies can be identified morphologically, which is in contrast to that suggested by Patten and Campbell (2000). We do note that Santa Catalina shows little admixture at K = 3 with more admixture evident at K = 5 in the Mid and Contemporary sampling periods. Of particular importance is that
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Fig. 2. Bayesian phylogenetic analysis of North American Loggerhead Shrike (Lanius ludovicianus) common (n ≥ 5) mtDNA control region haplotypes. Data compiled from Vallianatos et al. (2002), Eggert et al. (2004), Mundy et al. (1997a, b, c), Caballero and Ashley, (2011), and this study. Values above lines are substitutions per site, node values below lines represent posterior probability scores >0.5. * indicates haplotype common only to San Clemente Island population.
Fig. 3. North American Loggerhead Shrike (L. ludovicianus) mtDNA haplotype distribution map showing common (n ≥ 5) mtDNA control region haplotype distribution. distribution of haplotype A; central/western/island distribution of haplotype C; Channel Islands distribution of haplotype B; and San Clemente Island distribution of haplotype L2. Data compiled from Vallianatos et al. (2002), Eggert et al. (2004), Mundy et al. (1997a, b, c), Caballero and Ashley (2011), and this study. Legend shows color codes for the different haplotypes.
historically the Santa Catalina population appears to have been the same as the San Clemente population, and only diverged after the San Clemente population dwindled, forcing the implementation of the captive breeding program. Additionally, the Santa Rosa and Santa Cruz populations appear distinct, which when combined with the recent decline in population size (Hicks and Walter, 2009) suggests that those populations of L. l. anthonyi warrant further conservation efforts.
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Fig. 4. Histogram of clustering assignments at K = 2, K = 3, and K = 5 from the I-model in STRUCUTRE. Populations are: 1 = Mainland Historical, 2 = Mainland Mid, 3 = Mainland Contemporary, 4 = San Clemente Island Historical, 5 = San Clemente Island Mid, 6 = San Clemente Island Contemporary, 7 = Catalina Island Historical, 8 = Santa Catalina Island Mid, 9 = Santa Catalina Island Contemporary, 10 = Santa Cruz Island Historical, 11 = Santa Rosa Island Historical, 12 = Santa Rosa Island Mid.
Fig. 5. Histogram of clustering assignments at K = 5 with samples ordered according to field subspecies identification. 1 = L.l.anthonyi, 2 = L.l.gambeli, 3 = L.l.grinelli, 4 = L.l.mearnsi, 5 = L.l.sonoriensis, 6 = unknown. Pink sections are historic Santa Catalina Island and Historic San Clemente Islands populations. Red in Group 1 is from Santa Cruz and Santa Rosa Islands. The blue in Group 4 is from San Clemente Island sampled after 1991.
5. Conclusions Our results, which are based on the largest sample size and highest number of genetic markers to date, support previous claims that the San Clemente Island loggerhead shrike is a separate subspecies that has been genetically differentiated from the mainland and other island populations for over 100 years. There has, however, been a shift in allele frequencies in the population due to a bottleneck associated with small population size at the start of the captive breeding program. Samples collected prior to 1992 are closely associated with the shrike population from Santa Catalina Island. Migration between the Mainland – Santa Catalina – San Clemente occurs, but is rare, and gene flow appears limited. Patterns of mtDNA haplotype distribution indicate that maternal gene flow is directional from mainland to the islands with an east–west continental division of haplotypes. Overall, these results suggest that Santa Catalina Island is an important geographic link and could be considered a potential secondary location for San Clemente shrike restoration efforts. Such an undertaking, however, could negatively impact the declining population of L. l. anthonyi currently located on Santa Catalina (Hicks and Walter, 2009). There is no evidence of a cline between Mainland – San Clemente through Santa Catalina and it seems more likely that birds from the Mainland are ending up on San Clemente Island without necessarily leaving their genes behind on Santa Catalina. Overall, the captive breeding program has been successful in maintaining genetic diversity in the San Clemente population, which will be important as conservation efforts continue. We recommend, however, a balanced ecosystem management approach that includes conservation of endangered predators on the island, namely the San Clemente Island fox
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Fig. 6. Principal Components Analysis (PCA) of all 381 samples with all siblings from the captive breeding program included.
(Urocyon litteralis clementae) (Roemer and Wayne, 2003) to ensure a naturally-regulated balance of predator–prey dynamics for long-term persistence of all endemic species. Acknowledgments Thank you to the United States Navy Region Southwest for funding the project and providing logistics and access to San Clemente Island. We also acknowledge the contributions of Point Reyes Bird Observatory, United States Fish and Wildlife, San Diego Zoo, the San Diego Zoo Center for the Reproduction of Endangered Species, San Diego Museum of Natural History, Los Angeles County Museum of Natural History, Santa Barbara Museum of Natural History, and the University of California at Los Angeles. Much gratitude to Gary Santolo for the collection of wild samples, and to the Santa Catalina Conservancy. Thank you to the technicians at the Natural Resources DNA Profiling and Forensic Center at Trent University, and to Kevin Middel for creating the sampling map figure. Data Accessibility All new sequence data is available on Genbank (Accession MF101793-MF101801). Microsatellite data is available upon request from the corresponding author. Author Contributions LYR consolidated data, conducted data analysis, created the figures, and drafted the manuscript. AC collected samples, conducted lab work, analyzed sequence data, generated microsatellite data, wrote lab methods and reviewed the manuscript. BNW supervised the research, guided lab work and study design, and reviewed the manuscript. Appendix. Supplementary data Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.gecco.2017.04.002. References Caballero, I.C., Ashley, M.V., 2011. Genetic analysis of the endemic island loggerhead shrike. Lanius Ludovicianus Anthonyi. Conserv. Genet. 12, 1485–1493. Cade, T.J., Woods, C.P., 1997. Changes in distribution and abundance of the loggerhead shrike. Conserv. Biol. 11, 21–31. Coxon, A., Chabot, A.A., Lougheed, S.C., Dávila, J.A., White, B.N., 2012. Characterization of 17 microsatellite loci for use in population genetic and mating system studies of the endangered North American passerine, loggerhead shrike (Lanius ludovicianus). Conserv. Genet. Res. 4, 503–506. Crawford, N.G., 2010. SMOGD: software for the measurement of genetic diversity. Mol. Ecol. Res. 10, 556–557. Dabrowski, M.J., Pilot, M., Kruczyk, M., Zmihorski, M., Umer, H.M., Gliwicz, J., 2014. Reliability assessment of null allele detection: inconsistencies between and within different methods. Mol. Ecol. Res. 14, 361–373. Dent, E.A., vonHoldt, B.M., 2012. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Res. 4, 359–361.
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Eggert, L.S., Mundy, N.I., Woodruff, D.S., 2004. Population structure of loggerhead shrikes in the California Channel Islands. Mol. Ecol. 13, 2121–2133. 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. Falush, D., Stephens, M., Pritchard, J.K., 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587. Hicks, J.J., Walter, H.S., 2009. Population decline of the island loggerhead shrike (Lanius ludovicianus anthonyi) in the California Channel Islands. Wilson J. Ornithol. 121, 184–187. Hofreiter, M., Jaenicke, V., Serre, D., von Haeseler, A., Pääbo, S., 2001. DNA sequences from multiple amplification reveal artifacts induced by cytosine deamination in ancient DNA. Nucleic Acids Res. 29, 4793–4899. Jombart, T., 2008. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405. Kajander, O.A., Karhunen, P.J., Holdt, I.J., Jacobs, H.T., 2001. Prominent mitochondrial DNA recombination intermediates in human heart muscle. EMBO Rep. 2, 1007–1012. Kajander, O.A., Rovio, A.T., Majamaa, K., Poulton, J., Spelbrink, J.N., Holt, I.J., Karhunen, P.J., 2000. Human mtDNA sublimons resemble rearranged mitochondrial genomes found in pathological states. Hum. Mol. Genet. 22, 2821–2835. Kmiec, B., Woloszynska, M., Janska, H., 2006. Heteroplasmy as a common state of mitochondrial genetic information in plants and animals. Current Genet. 50, 149–159. Kvist, L., Martens, J., Nazarenko, A.A., Orell, M., 2003. Paternal leakage of mitochondrial DNA in the great tit (Parus major). Mol. Biol. Evol. 20, 243–247. McLeod, B.A., White, B.N., 2010. Tracking mtDNA heteroplasmy through multiple generations in the North Atlantic right whale (Eubalaena glacialis). J. Hered. 101, 235–239. Mundy, N.I., Unitt, P., Woodruff, D.S., 1997c. Skin from feet of museum specimens as a non-destructive source of DNA for avian genotyping. The Auk 114 (1), 126–129. Mundy, M.I., Winchell, C.S., Burr, T., Woodruff, D.S., 1997a. Microsatellite variation and microevolution in the critically endangered San Clmente Island loggerhead shrike (Lanius ludovicianus mearnsi). Proc. R. Soc. B — Biol. Sci. 264, 869–875. Mundy, N.I., Winchell, C.S., Woodruff, D.S., 1997b. Genetic differences between the endangered San Clemente Island loggerhead shrike Lanius ludovicianus mearnsi and two neighbouring subspecies demonstrated by mtDNA control region and cytochrome b sequence variation. Mol. Ecol. 6, 29–37. Mundy, N.I., Winchell, C.S., Woodruff, D.S., 1996. Tandem repeats and heteroplasmy in the mitochondrial DNA control region of the loggerhead shrike (Lanius ludovicianus). J. Hered. 87, 21–26. Olsson, U., Alström, P., Svensson, L., Aliabadian, M., Sundberg, P., 2010. The Lanius excubitor (Aves, Passeriformes) conuncrum –taxonomic dilemma when molecular and non-molecular data tell different stories. Mol. Phylogenet. Evol. 55, 347–357. Patten, M.A., Campbell, K.F., 2000. Typological thinking and the conservation of subspecies: the case of the San Clemente island loggerhead shrike. Diver. Distrib. 6, 177–188. Peakall, R., Smouse, P.E., 2012. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28, 2537–2539. Roemer, G.W., Wayne, R.K., 2003. Conservation in conflict: the tale of two endangered species. Conserv. Biol. 17, 1251–1260. Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Höhna, S., Larget, B., Liu, L., Suchard, M.A., Huelsenback, J.P., 2011. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542. Santolo, G.M., Yamamoto, J.T., 1999. Selenium in blood of predatory birds from Kesterson Reservoir and other areas of California. J. Wildl. Manage. 63, 1273–1281. Scott, T.A., Morrison, M.L., 1990. Natural history and management of the San Clemente loggerhead shrike. Proc. Western Found. Vertebr. Zool. 4, 23–57. Segelbacher, G., 2002. Noninvasive genetic analysis in birds: testing reliability of feather samples. Mol. Ecol. Notes 2, 367–369. Shuford, W.D., Gardali, T. (Eds.), 2008. California Bird Species of Special Concern: A ranked assessment of species, subspecies, and distinct population of birds of immediate conservation concern in California. In: Studies of Western Birds. Western Field Ornithologists, Camarillo, California and California Department of Fish and Game, Sacramento. Stahl, J.T., Desnoyers, N.J., Bridges, A.S., Garcelon, D.K., 2014. San Clemente Loggerhead Shrike Monitoring and Release Project Final Annual Report — 2013. 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Global Ecology and Conservation journal homepage: www.elsevier.com/locate/gecco
Original research article
Genetic assessment of the San Clemente Island loggerhead shrike reveals evidence of historical gene flow with Santa Catalina Island L.Y. Rutledge a, *, A. Coxon b , B.N. White a a b
Trent University, Biology Department, 2140 East Bank Drive, Peterborough, Ontario, K9L 1Z8, Canada Trent University, Environmental & Life Sciences Graduate Program, 1600 West Bank Drive Peterborough, Ontario, K9J 7B8, Canada
article
info
Article history: Received 5 December 2016 Received in revised form 11 April 2017 Accepted 11 April 2017
Keywords: Conservation Endangered species Gene flow Loggerhead shrike Microsatellites Mitochondrial DNA Population genetics
a b s t r a c t The San Clemente loggerhead shrike (Lanius ludovicianus mearnsi) is an endangered species endemic to San Clemente Island in California. Previous genetic analyses of the California shrike populations have had mixed results due to small sample sizes and/or few genetic markers. Here we present a rigorous analysis of 381 historical and contemporary California shrike samples genotyped at 11 new polymorphic microsatellite loci and the mitochondrial DNA control region. Our results suggest generally high genetic diversity in all populations and that loggerhead shrikes on San Clemente Island are genetically differentiated from both the Mainland and other island populations. Bayesian clustering suggests primarily three genetically differentiated populations: (1) Mainland, (2) San Clemente Island, and (3) the islands of Santa Catalina, Santa Cruz and Santa Rosa. Historically, however, the San Clemente Island shrike cluster closely with the Santa Catalina Island population, suggesting historical gene flow between these populations. A Bayesian phylogeny of common mtDNA haplotypes across North America reveals two primary clades and a general division between western and eastern populations. Geographic patterns suggest maternal gene flow from mainland to the islands but not vice versa. These results indicate that the captive breeding program has been successful at maintaining genetic diversity in the San Clemente Island shrike population, but that allele frequencies have shifted significantly over the past 100 years. Overall, our results suggest the San Clemente shrike (L. l. mearnsi) is a validated subspecies that is morphologically and genetically distinct, and that ongoing conservation efforts are justified. © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction The loggerhead shrike (Lanius ludovicianus) is a passerine bird that was once found throughout North America. Habitat alteration has led to a shift in its range and numbers have declined in several core regions of its historical distribution (see Fig. 1 in Cade and Woods, 1997). In California, loggerhead shrikes have been categorized, either morphologically or genetically, into three main subspecies: L. l. gambeli on the mainland L. l. anthonyi on the northern Channel Islands; and L. l. mearnsi on San Clemente Island (see Eggert et al., 2004). At the beginning of the 20th century, sightings of the San Clemente Island shrike were common and the population was considered well-distributed, but by the mid-1980s their population had plummeted to fewer than 30 individuals (Stahl et al., 2014).
*
Corresponding author. E-mail addresses: [email protected] (L.Y. Rutledge), [email protected] (A. Coxon), [email protected] (B.N. White).
http://dx.doi.org/10.1016/j.gecco.2017.04.002 2351-9894/© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
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The San Clemente loggerhead shrike (L. l. mearnsi) was listed by the United States Fish and Wildlife Service (USFWS) as a federally endangered species in 1977 and is currently considered one of the rarest birds in North America. Non-endemic predators, such as cats (Felis catus) and rats (Rattus rattus), played a primary role in the decline (Shuford and Gardali, 2008) and subsequent degradation of nesting habitat by introduced livestock, namely sheep (Ovis aries) and goats (Capra hircus), impeded recovery efforts (Scott and Morrison, 1990). A monitoring program began on San Clemente Island in 1991 to ensure appropriate management of the population. Roemer and Wayne (2003), however, argued that the predator control program that is part of the shrike conservation on Clemente is endangering the endemic San Clemente Island Fox (Urocyon littoralis clementae). Previous genetic studies concluded that the San Clemente Island shrike had evolved sufficient genetic differentiation from mainland shrike subspecies (L.l. gambeli and L.l. grinelli) to justify its conservation as an evolutionarily significant unit (ESU). Although genetic analyses have suggested that San Clemente is distinct (Mundy et al., 1997a, 1997b; Eggert et al., 2004), Patten and Campbell (2000) suggested little differentiation between Clemente and the other islands due to genetic swamping by the other island subspecies (L. l. anthonyi). More recently, Caballero and Ashley (2011) analyzed 96 historical samples from the islands and mainland from 1897–2008 to clarify the evolutionary lineage and conservation status of L. l. anthonyi. Their interpretation was that historical L. l. mearnsi from San Clemente had mixed ancestry and that L. l. anthonyi from Santa Rosa and Santa Cruz Islands were genetically distinct. They found three genetic clusters (Mainland, San Clemente; Santa Catalina / Santa Rosa/ Santa Cruz), with post 1991 San Clemente being less admixed than the 1915 population. Additionally, they found the historical shrike population on San Clemente (up until 1915) was different than that population post 1991. Although various genetic analyses have provided insight into the population structure of California shrike populations, previous work has been limited by the small sample sizes and relatively few genetic markers. It has been suggested that further analysis with more samples and more genetic markers could help to clarify the relationships among the different populations (Caballero and Ashley, 2011). The purpose of this study was to use more genetic markers and more substantial sampling over a broad time period to clarify a number of conflicting conclusions regarding the San Clemente Island shrike population. We tested the hypotheses that: (a) the San Clemente shrike is, and has always been, genetically differentiated from other island/mainland populations; (b) Santa Catalina Island serves as a stepping stone for gene flow between the mainland and San Clemente Island, and (c) that species identified morphologically as L. l. mearnsii cluster accordingly with the San Clemente Island population. 2. Methods 2.1. Sample collection and DNA extraction A comprehensive collection of over 400 loggerhead shrike samples dated between 1897 and 2004 was assembled, representing L. l. mearnsi from San Clemente Island (n = 180), L.l. anthonyi from Santa Catalina, Santa Rosa, Santa Cruz and Anacapa Islands (n = 80), and L.l. gambeli and L.l. grinnelli from a large area of mainland California (n = 143) (Fig. 1). We focused on collecting contemporary samples from wild-nesting shrikes and from shrikes of unknown origin captured on San Clemente Island, nesting shrikes on Santa Catalina Island, and samples from shrikes captured from areas of mainland California. Samples from individuals representing 17 out of 18 existing genetic founder lines of L.l. mearnsi were contributed by the San Diego Zoo Center for Research of Endangered Species (CRES). We also obtained historical samples from the San Diego, Santa Barbara and Los Angeles Museums of Natural History, as well as the University of California at Los Angeles (UCLA). A toe pad was removed from the foot of each museum specimen, following the methods outlined in Mundy et al. (1997c). Captured shrikes were either sampled from the nest prior to fledging, in which case feathers were plucked from the flank region, or captured using a modified version of a Potter’s trap – in which case a blood sample was taken from the jugular vein according to methods described in Santolo and Yamamoto (1999). This work was conducted under Institutional Animal Care and Use Committee Protocol #178, California Department of Fish and Game Scientific Collectors Permit #002407 and associated Memorandum of Understanding, and Federal Bird Banding Permit #22717. R R Genomic DNA was extracted from blood samples stored on Whatman⃝ FTA⃝ collection cards, with a DNeasy Tissue Kit (Qiagen) according to the manufacturer’s instructions. DNA extraction from the feather and toe pad samples followed the protocol modifications outlined in Segelbacher (2002), whereas the DNA extraction from museum samples followed the modified protocol of Mundy et al. (1997c). Furthermore, the following precautions were taken to ensure accuracy of results from the historical museum samples: (1) all work was conducted in a lab where no other avian research was being conducted; (2) DNA extraction and PCR amplification on all museum samples was carried out at a separate time and at a separate bench space from the modern samples; (3) benchtops were decontaminated before each use with Decon (Decon Laboratories Limited, UK) and then covered with new benchcoat; (4) dedicated new pipettes (and dedicated consumables and reagents) were used for processing the historical specimens and all equipment was cleaned with Decon prior to each use; (5) DNAase-free filter tips were used throughout the project; (6) museum samples were split in half and extracted twice – the second extraction was done at a later date – so the results were duplicated at least two times; (7) negative extraction and PCR controls were used throughout and no positive results were obtained from the amplification of the negative controls. Although some additional extractions of some historical samples may have occurred after extraction of contemporary samples, the precautionary steps outlined above minimized the risk of contamination and false results.
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2.2. Mitochondrial DNA & phylogenetic analysis A total of 214 samples were sequenced at the mitochondrial DNA (mtDNA) control region. These samples represented shrikes banded on San Clemente Island from 1897 to 2004 (n = 88), shrikes banded on Santa Catalina, Santa Cruz, and Santa Rosa Islands from 1907 to 2004 (n = 77), and shrikes banded on the coastal mainland areas of California from 1923 to 2003 (n = 49). Amplification of 249bp of the mtDNA control region was performed using the primers DLL1 and DLH1 (Mundy et al., 1997b), in 25 µL volumes including 1.0 µL Taq polymerase (Invitrogen), 1X PCR buffer, 50 µM each dNTP, 0.4 uM each primer, 1.5 mM MgCl2 (increased to 2.5 mM for DNA extracted from skin and feather samples), and 25 µg bovine serum albumin (BSA). The thermal cycling conditions were as follows: 3 min at 94 ◦ C; 35 cycles of 94 ◦ C for 30 s, 56 ◦ C for 60 s, and 72 ◦ C for 90 s; followed by a final extension of 72 ◦ C for 10 min. Note that low template samples (feathers and museum) were cycled 55 times. Amplified products were visualized on a 1.2% agarose gel, cleaned with ExoSAP-IT (USB Corporation, Ohio) and analyzed on a MegaBace 1000 with a DYEnamic ET Dye Terminator Cycle Sequencing Kit (GE Healthcare Bio-Sciences, Quebec). For samples that had an unresolved base call at site 410 (with both C and T peaks), samples were re-extracted and re-sequenced. Museum samples amplified as a single fragment and they were sequenced at least twice in both forward and reverse directions to ensure accuracy. Sequences were compared to published sequences and assigned haplotypes from the literature (Table 1). New haplotypes were identified as LluNx. Sequences were aligned with ClustalW in Geneious 6.1.8 (Biomatters). The alignment was trimmed to 200bp, which captured all variable sites. The most common mtDNA haplotypes (where n ≥ 5) found in this study and in the literature were used to construct a Bayesian phylogenetic tree with the default HKY85 substitution model, which incorporates parameters for realistic rates of substitution, in the MrBayes 3.2.2 (Ronquist et al., 2011) plug-in of Geneious 6.1.8 with the following parameters: gamma rate variation with 4 categories, 110,000 chain length, 4 heated chains, subsampling frequency of 200 and a burn-in of 100,000. Sequence AI1 (Genbank Accession EU490661) from Aphelocoma insularis was used as an outgroup to root the tree. 2.3. Microsatellite analysis (genetic diversity, divergence and clustering analysis) Eleven new polymorphic microsatellite loci were developed for this study (see Coxon et al., 2012). LLU15, LLU39, LLU55, LLU82, LLU85, LLU90, LLU95, LLU102, LLU112, LLU157 and LLU176 were amplified in 3 multiplexed PCR reactions as outlined in Coxon et al. (2012). These loci have been shown to be appropriate for population structure and pedigree analysis; they are not sex-linked and all but two (Llu102; Llu15) have been shown to be in Hardy–Weinberg equilibrium after Bonferroni correction (Coxon et al., 2012). Each 10 µL multiplex reaction contained 5ng genomic DNA, 4 µL QIAGEN Multiplex PCR Master Mix and 1 µL of forward and reverse primers at 0.56 µM to 2.3 µM of each primer. The thermal cycling conditions were as follows: 15 min at 95 ◦ C; 35 cycles of 94 ◦ C for 30 s, 60 ◦ C for 90 s and 72 ◦ C for 90 s; followed by a final extension of 72 ◦ C for 10 min. A total of 404 samples were genotyped at 11 microsatellite loci. Samples with low DNA template concentration were amplified singly for each locus with 55 cycles, and then pooled prior to genotyping. PCR products were genotyped on a MegaBace 1000 (GE Healthcare) and alleles were scored with the CEQ8000 Genetic Analysis System (Beckman Coulter) and checked manually. Samples with more than 4 missing alleles were excluded from further analyses, such that 381 of 404 genotyped samples were subsequently analyzed. We assessed the dataset for scoring error in Micro-checker (Van Oosterhout et al., 2004). To estimate allele frequency changes over time, we divided each group of samples into three timescales: Historical (Hist: 1897–1949), Middle (Mid: 1950–1999), and Contemporary (Cont: 2000–2004). We calculated estimates of heterozygosity and Fst among populations (999 permutations) in GenAlEx 6.501 (Peakall and Smouse, 2012). We also calculated Jost Dest estimates of divergence with 1000 replicates in SMOGD (Crawford, 2010). For Bayesian clustering analysis in the program STRUCTURE v. 2.3.4 (Falush et al., 2003), we used the San Diego zoo studbook to filter for relatedness. Siblings were removed randomly, leaving one single offspring from a known captive breeding pair in the dataset. The remaining dataset included 303 individuals. To estimate the number of clusters (K ) in the dataset we implemented the I-model with possible number of clusters ranging from K = 1 to 10. Each K value was run 5 times with a burn-in of 250,000 followed by 500,000 iterations. These parameters are above the minimum requirements suggested in the Structure software manual, and they meet the requirement of convergence of summary statistics. Output was analyzed in Structure Harvester (Dent and vonHoldt, 2012) and both the maximum LnProbData and the second order rate of change (Evanno et al., 2005) were visualized to estimate the optimal number of clusters. Subsequently, K = 3 (Supplementary Fig. 1) was run 10 times with the same parameters that were used in the initial runs and Q values were averaged over the 10 runs. Standard errors were calculated to identify any significant deviation in individual runs. We also conducted a Principal Components Analysis (PCA) in the adegenet package (Jombart, 2008) of R 3.2. 3. Results 3.1. Mitochondrial DNA & Phylogeny We identified 10 new haplotypes identified as Lluxx (Table 1: Genbank numbers MF101793-MF101801). LluN6, LluN10, LluN11, LluN12, LluN13 were all found in single occurrences from the mainland population, with LluN6 and LluN13 found
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only in samples collected in 1935. Haplotype LluN8, identified as a heteroplasmic haplotype, was documented in a single occurrence of a captive bred San Clemente female (Sample SB833). The haplotype LluN5 is a heteroplasmic haplotype but the variation with a cytosine at position 335 was documented recently in Olsson et al. (2010) (AH744) from a L. l. ludovicianus mexicanus/gambeli specimen from the University of Greifswald collection. Several individuals appear to exhibit single-site heteroplasmy at site 410 (Supplementary Figure 2). Duplicate rounds of extraction and multiple independent sequencing runs had consistent results, suggesting this is not contamination or a sequencing artifact. Siblings of one of the individuals were also sequenced with similar results at this site. Heteroplasmic haplotype LluN4 is a combination of Haplotype A and Haplotype L2, which we tracked in pedigrees based on the San Diego Zoo Studbook (Supplementary Figure 3). We documented 13 different haplotypes in the Mainland population (C most common), 7 haplotypes in the San Clemente Island population (A most common and L2 being found almost exclusively within that population), 3 haplotypes in the Santa Catalina Island population, 3 haplotypes in the Santa Cruz Island population, and 4 in the Santa Rosa Island population (Table 2). Seven of the eight L2 haplotypes were found in the San Clemente captive breeding individuals with the only other L2 haplotype found in a Mainland individual sampled near Los Angeles in 1969 (Supplemental File). The phylogenetic analysis of the most common haplotypes found across North America revealed two primary clades (Fig. 2). Based on the criterion of at least 5 occurrences of the haplotype, Haplotype B appears largely confined to the Channel Islands and L2 to San Clemente Island. There also appears to be an east–west division with haplotype C3 and C4 found in eastern North America, whereas Haplotype C1 was distributed across central and western North America (Fig. 3). Although Haplotype A is found throughout North American loggerhead shrike populations, the Channel Islands haplotypes are only found on the islands. 3.2. Microsatellite & clustering analysis Micro-checker output indicated no scoring errors in the dataset. Homozygote excess was suggested at the following loci: Llu15, Llu82, Llu90, Llu157, Llu39, and Llu102, which Micro-checker interprets as potential null alleles. It is, however, more likely that the excess is due to the influence of siblings from the captive breeding program being included in the initial analysis because bottleneck populations are known to have significant false positives in null allele detection (Dabrowski et al., 2014). Heterozygosity was generally high but lower than expected in every population. The Mainland population had the highest heterozygosity and San Clemente Island had the lowest, with the highest number of private alleles occurring in the Mainland population; private alleles were also found in the San Clemente and Santa Catalina Islands dataset (Table 3). As expected, the Mainland population had the highest number of alleles, but the San Clemente Island population also had a high number of alleles. San Clemente shrikes were most differentiated from the northern Channel Islands and most similar to Santa Catalina (Table 4). The Mainland and San Clemente Island populations were most differentiated based on Jost Dest comparisons which measures allele sharing, whereas the Santa Catalina Island population was most similar to the Mainland population based on pairwise Fst (Table 4). This pattern is generally similar across time periods (Table 5), although in some cases the sample sizes are too small for reliable estimates of differentiation. 3.3. Bayesian clustering Results from I-model Bayesian clustering analysis in the program STRUCTURE had the highest support for K = 3 clusters with somewhat lower support for K = 2 and some support for K = 5 (Supplementary Figure 1). At K = 2, San Clemente Island is clearly differentiated with three samples collected from the Mainland in 1991–1992 (ID 47803, 47822, 48102) (and identified morphologically as L. l. mearnsi), clustering with Q = 1.0 to the San Clemente Island population (Fig. 4). Similarly, individual SB565D (born in the captive breeding center) was field assigned to the Santa Catalina population because it was sampled there in 2003 after being transferred from San Clemente Island; this individual clustered with Q = 1.0 to the San Clemente Contemporary population. At K3, the Mainland becomes differentiated from the island populations and at K5 the Mainland population becomes highly admixed and the historical San Clemente and Santa Catalina populations emerge as an independent single cluster. When the STRUCTURE output is ordered according to field identification of subspecies, the clustering shows a shift in the L. l. mearnsi subspecies and that those individuals historically identified as L. l. anthonyi in the Santa Catalina Island population were misclassified (Fig. 5). The Principal Components Analysis (PCA) was generally consistent with the STRUCTURE results and shows clear differentiation of San Clemente Island with overlap of Mainland and Santa Catalina, as well as some evidence of migration between San Clemente, Santa Catalina, and the Mainland (Fig. 6). 4. Discussion 4.1. Mitochondrial DNA & phylogeny Similar to the results reported in Caballero and Ashley (2011) we found both mtDNA haplotypes A and B on Santa Rosa and Santa Cruz Islands, although we did not find J in any of our samples and Haplotype B was found only in island birds.
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L.Y. Rutledge et al. / Global Ecology and Conservation 11 (2017) 42–52 Table 1 Variable sites of mtDNA control region haplotypes found in this study. Sequences with distinct equivalent heteroplasmy are indicated in BOLD. Haplotype names in parentheses are alternative names for the same sequence.
Table 2 mtDNA control region haplotypes by population. Haplotypes are based on the literature and new haplotypes documented in this study. Haplotype
Mainland (n = 49)
San Clemente Island (n = 88)
Santa Catalina Island (n = 39)
Santa Cruz Island (n = 21)
Santa Rosa Island (n = 17)
A B C D I7 L2 M/I1 LluN1 LluN3 LluN4 LluN5 LluN6 LluN8 LluN10 LluN11 LluN12 LluN13
7 0 31 1 1 1 1 0 1 0 1 1 0 1 1 1 1
59 6 8 0 0 7 0 1 0 6 0 0 1 0 0 0 0
16 12 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0
12 8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
5 10 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
Haplotype C was shared among the Mainland, San Clemente and Santa Catalina but was absent from Santa Cruz and Santa Rosa although this absence may be due to small sample sizes. Most of the new haplotypes were found in the Mainland population at low frequency, but one new non-heteroplasmic haplotype (LluN1) was found in a sample collected in 2004 from San Clemente Island. Also, haplotype L2 appeared primarily in samples from the captive breeding program (n = 7) with one L2 individual sampled in 1969 on the Mainland. This Mainland L2 sample clustered with Q = 0.999 to the Mainland population based on microsatellites, but the San Clemente captive breeding sample (SB758) clustered with Q = 0.997 to the Contemporary San Clemente cluster, suggesting historical introgression of this haplotype into the San Clemente population. Four of the other samples from the captive breeding population with the L2 haplotype were full siblings of SB758, one was unrelated (SB503), and one was the sister of the maternal grandmother (SB131). Of note is that the mother of SB131 is SB275 who was the descendant of a wild individual but is noted in the studbook as having haplotype A, which is only one base pair different from haplotype L2 with a T → C transition. The L2 haplotype has been identified as rare, but specific to the L. l. ludovicianus subspecies from southeastern
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Table 3 Genetic diversity estimates. Na = number of alleles, Ne = number of effective alleles. Location
N
Ho
He
Na
Ne
Private Alleles
Calculations based on complete dataset of 381 individuals before removal of siblings from the captive breeding program. Mainland San Clemente Island Santa Catalina Island Santa Cruz Island Santa Rosa Island Overall
131 174 38 21 17 381
0.703 0.552 0.583 0.618 0.616 0.614
0.820 0.628 0.726 0.675 0.681 0.706
12.8 10.9 7.2 5.7 5.8 8.5
6.7 3.1 4.2 3.8 3.8 4.3
23 6 1 0 0 n/a
Calculations based on dataset with siblings removed from the captive breeding program and data divided into Historical (1898–1949), Mid (1950–1999), and Contemporary (2000–2004) Mainland Historical Mainland Mid Mainland Contemporary San Clemente Historical San Clemente Mid San Clemente Contemporary (7 wild) Santa Catalina Historical Santa Catalina Mid Santa Catalina Contemporary Santa Cruz Historical Rosa Historical Rosa Mid Overall
46 57 30 22 11 61 24 10 4 21 12 5 303
0.658 0.713 0.726 0.621 0.533 0.618 0.603 0.541 0.545 0.618 0.597 0.655 0.619
0.794 0.815 0.810 0.650 0.501 0.649 0.703 0.685 0.634 0.675 0.652 0.642 0.684
10.7 11.0 10.2 6.3 4.0 9.5 6.4 5.0 4.0 5.7 5.1 4.4 6.8
6.0 6.1 6.1 3.6 2.2 3.3 3.7 3.6 3.4 3.8 3.4 3.6 4.1
5 4 4 3 1 2 1 0 0 0 0 0 n/a
Table 4 Genetic distance between populations. Fst is below diagonal and Jost Harmonic Mean of Dest across all loci is above diagonal. Calculations are based on complete dataset of 381 individuals before removal of siblings from the captive breeding program. Total individuals (N) = 381. All values are significantly different (p < 0.005) based on 999 permutations in the AMOVA function of GenAlEx 6.501. Location
N
Mainland
San Clemente Island
Santa Catalina Island
Santa Cruz Island
Santa Rosa Island
Mainland San Clemente Island Santa Catalina Island Santa Cruz Island Santa Rosa Island
131 174 38 21 17
– 0.137 0.060 0.087 0.105
0.403 – 0.109 0.159 0.169
0.217 0.214 – 0.071 0.070
0.205 0.350 0.193 – 0.019
0.265 0.370 0.157 0.028 –
Table 5 Genetic distance between subdivided populations. Fst is below diagonal and Jost Harmonic Mean of Dest across all loci is above diagonal. Calculations based on dataset with siblings removed from the captive breeding program and data divided into Historical (1898–1949), Mid (1950–1999), and Contemporary (2000–2004). Total individuals (N) = 303. * indicates not significant at p >0.05 based on 999 permutations in the AMOVA function of GenAlEx 6.501. Location/ Time Period
N
MainHist MainMid MainCont ClemHist ClemMid ClemCont CatIsHist CatIsMid CatIsCont CruzIsHist RosaIsHist RosaIsMid
MainHist MainMid MainCont ClemHist ClemMid ClemCont CatIsHist CatIsMid CatIsCont CruzIsHist RosaIsHist RosaIsMid
46 57 30 22 11 61 24 10 4 21 12 5
– 0.018 0.021 0.103 0.173 0.131 0.069 0.047 0.046 0.086 0.113 0.094
0.034 – 0.008 0.110 0.172 0.113 0.083 0.061 0.050 0.099 0.125 0.092
0.053 0.020 – 0.127 0.185 0.127 0.083 0.065 0.057 0.091 0.118 0.088
0.289 0.367 0.397 – 0.089 0.065 0.092 0.054 0.033 0.111 0.135 0.094
0.478 0.459 0.440 0.088 – 0.060 0.178 0.154 0.097 0.208 0.225 0.200
0.397 0.321 0.333 0.115 0.048 – 0.129 0.094 0.067 0.146 0.183 0.144
0.209 0.275 0.292 0.215 0.293 0.277 – 0.038 0.028* 0.100 0.112 0.072
0.155 0.200 0.237 0.126 0.225 0.162 0.074 – 0.019* 0.046 0.056 0.039
0.116 0.099 0.183 0.075 0.067 0.080 0.020 0.044 – 0.055 0.097 0.013*
0.192 0.265 0.238 0.302 0.402 0.338 0.240 0.117 0.117 – 0.028 0.015*
0.290 0.403 0.333 0.307 0.366 0.417 0.214 0.130 0.140 0.030 – 0.028*
0.171 0.174 0.143 0.168 0.245 0.279 0.126 0.044 0.001 0.039 0.027 –
United States (Vallianatos et al., 2001, 2002), so finding it within an historical Mainland California sample (which was not categorized to species morphologically) and especially within the captive breeding population of L. l. mearnsii with relatively high frequency is very unexpected. The data show several cases of heteroplasmy in the mtDNA control region. The state of mtDNA heteroplasmy, where more than one mitochondrial sequence occurs in a single individual, was once thought to be rare. Current thinking has changed, however, as mtDNA heteroplasmy is documented more frequently in both plant and animal taxa and arises due to recombination, small-scale mutation, or paternal leakage (Kmiec et al., 2006; McLeod and White, 2010). Although more common in plant mtDNA, recombination has been noted in humans (Kajander et al., 2000, 2001) but remains controversial. Paternal leakage of mtDNA has been noted in birds (Kvist et al., 2003), with heteroplasmy of tandem repeat patterns in the mtDNA control region documented in San Clemente Island shrike collected between 1991 and 1992 (Mundy et al., 1996).
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Fig. 1. Map of locations for samples used in this study.
The heteroplasmy observed in our data involves transitions from T → C (based on Haplotype A). Although DNA degradation can result in identification of false transitions, the most common sequencing error is due to deamination of cytosine residues such that C → T, with T → C transitions in contemporary samples being infrequent (Hofreiter et al., 2001). The rare occurrence of this transition combined with our multiple extractions and sequencing of heteroplasmic individuals, suggests the results are not due to sequencing error associated with DNA degradation. As well, the LluN4 heteroplasmic haplotype is a combination of Haplotype A and L2, both of which we tracked through the pedigrees based on the San Diego Zoo studbook. We hypothesize the heteroplasmy may be due to paternal leakage, although further sequencing of complete pedigrees would help resolve this more completely. Documenting multiple copies of mtDNA in individuals may be important for the captive breeding program since mtDNA heteroplasmy has been linked to phenotypic variation and disease in humans (Wallace and Chalkia, 2013). 4.2. Microsatellite & clustering analysis We identified relatively high genetic diversity in the San Clemente Island population, and both the historical and contemporary heterozygosity is higher than reported in Mundy et al. (1997a) and Eggert et al. (2004), but this is likely due to larger sample sizes and more markers used in our dataset. Although measures of genetic differentiation were low, the low level of allele sharing suggests limited gene flow between the Mainland and San Clemente Island, which is consistent with data reported in Mundy et al. (1996, 1997a). The lack of allele sharing, however, may be due in part to controlled breeding in the San Clemente population and the lack of dispersal from the islands to the mainland. Clustering analysis with Structure and PCA supports previous reports of three primary genetic types: Mainland (L. l. gambeli), Northern Channel Islands (L. l. anthonyi), and San Clemente Island (L. l. mearnsi) (Caballero and Ashley, 2011) but is in contrast to the suggestion by Eggert et al. (2004) that Santa Catalina is a separate cluster. Our dataset utilizes 11 new microsatellite loci and a larger sample size from all populations and may, therefore, provide more accurate genetic clustering estimates. Also, the genetic analysis confirms that the San Clemente subspecies can be identified morphologically, which is in contrast to that suggested by Patten and Campbell (2000). We do note that Santa Catalina shows little admixture at K = 3 with more admixture evident at K = 5 in the Mid and Contemporary sampling periods. Of particular importance is that
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Fig. 2. Bayesian phylogenetic analysis of North American Loggerhead Shrike (Lanius ludovicianus) common (n ≥ 5) mtDNA control region haplotypes. Data compiled from Vallianatos et al. (2002), Eggert et al. (2004), Mundy et al. (1997a, b, c), Caballero and Ashley, (2011), and this study. Values above lines are substitutions per site, node values below lines represent posterior probability scores >0.5. * indicates haplotype common only to San Clemente Island population.
Fig. 3. North American Loggerhead Shrike (L. ludovicianus) mtDNA haplotype distribution map showing common (n ≥ 5) mtDNA control region haplotype distribution. distribution of haplotype A; central/western/island distribution of haplotype C; Channel Islands distribution of haplotype B; and San Clemente Island distribution of haplotype L2. Data compiled from Vallianatos et al. (2002), Eggert et al. (2004), Mundy et al. (1997a, b, c), Caballero and Ashley (2011), and this study. Legend shows color codes for the different haplotypes.
historically the Santa Catalina population appears to have been the same as the San Clemente population, and only diverged after the San Clemente population dwindled, forcing the implementation of the captive breeding program. Additionally, the Santa Rosa and Santa Cruz populations appear distinct, which when combined with the recent decline in population size (Hicks and Walter, 2009) suggests that those populations of L. l. anthonyi warrant further conservation efforts.
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Fig. 4. Histogram of clustering assignments at K = 2, K = 3, and K = 5 from the I-model in STRUCUTRE. Populations are: 1 = Mainland Historical, 2 = Mainland Mid, 3 = Mainland Contemporary, 4 = San Clemente Island Historical, 5 = San Clemente Island Mid, 6 = San Clemente Island Contemporary, 7 = Catalina Island Historical, 8 = Santa Catalina Island Mid, 9 = Santa Catalina Island Contemporary, 10 = Santa Cruz Island Historical, 11 = Santa Rosa Island Historical, 12 = Santa Rosa Island Mid.
Fig. 5. Histogram of clustering assignments at K = 5 with samples ordered according to field subspecies identification. 1 = L.l.anthonyi, 2 = L.l.gambeli, 3 = L.l.grinelli, 4 = L.l.mearnsi, 5 = L.l.sonoriensis, 6 = unknown. Pink sections are historic Santa Catalina Island and Historic San Clemente Islands populations. Red in Group 1 is from Santa Cruz and Santa Rosa Islands. The blue in Group 4 is from San Clemente Island sampled after 1991.
5. Conclusions Our results, which are based on the largest sample size and highest number of genetic markers to date, support previous claims that the San Clemente Island loggerhead shrike is a separate subspecies that has been genetically differentiated from the mainland and other island populations for over 100 years. There has, however, been a shift in allele frequencies in the population due to a bottleneck associated with small population size at the start of the captive breeding program. Samples collected prior to 1992 are closely associated with the shrike population from Santa Catalina Island. Migration between the Mainland – Santa Catalina – San Clemente occurs, but is rare, and gene flow appears limited. Patterns of mtDNA haplotype distribution indicate that maternal gene flow is directional from mainland to the islands with an east–west continental division of haplotypes. Overall, these results suggest that Santa Catalina Island is an important geographic link and could be considered a potential secondary location for San Clemente shrike restoration efforts. Such an undertaking, however, could negatively impact the declining population of L. l. anthonyi currently located on Santa Catalina (Hicks and Walter, 2009). There is no evidence of a cline between Mainland – San Clemente through Santa Catalina and it seems more likely that birds from the Mainland are ending up on San Clemente Island without necessarily leaving their genes behind on Santa Catalina. Overall, the captive breeding program has been successful in maintaining genetic diversity in the San Clemente population, which will be important as conservation efforts continue. We recommend, however, a balanced ecosystem management approach that includes conservation of endangered predators on the island, namely the San Clemente Island fox
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Fig. 6. Principal Components Analysis (PCA) of all 381 samples with all siblings from the captive breeding program included.
(Urocyon litteralis clementae) (Roemer and Wayne, 2003) to ensure a naturally-regulated balance of predator–prey dynamics for long-term persistence of all endemic species. Acknowledgments Thank you to the United States Navy Region Southwest for funding the project and providing logistics and access to San Clemente Island. We also acknowledge the contributions of Point Reyes Bird Observatory, United States Fish and Wildlife, San Diego Zoo, the San Diego Zoo Center for the Reproduction of Endangered Species, San Diego Museum of Natural History, Los Angeles County Museum of Natural History, Santa Barbara Museum of Natural History, and the University of California at Los Angeles. Much gratitude to Gary Santolo for the collection of wild samples, and to the Santa Catalina Conservancy. Thank you to the technicians at the Natural Resources DNA Profiling and Forensic Center at Trent University, and to Kevin Middel for creating the sampling map figure. Data Accessibility All new sequence data is available on Genbank (Accession MF101793-MF101801). Microsatellite data is available upon request from the corresponding author. Author Contributions LYR consolidated data, conducted data analysis, created the figures, and drafted the manuscript. AC collected samples, conducted lab work, analyzed sequence data, generated microsatellite data, wrote lab methods and reviewed the manuscript. BNW supervised the research, guided lab work and study design, and reviewed the manuscript. Appendix. Supplementary data Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.gecco.2017.04.002. References Caballero, I.C., Ashley, M.V., 2011. Genetic analysis of the endemic island loggerhead shrike. Lanius Ludovicianus Anthonyi. Conserv. Genet. 12, 1485–1493. Cade, T.J., Woods, C.P., 1997. Changes in distribution and abundance of the loggerhead shrike. Conserv. Biol. 11, 21–31. Coxon, A., Chabot, A.A., Lougheed, S.C., Dávila, J.A., White, B.N., 2012. Characterization of 17 microsatellite loci for use in population genetic and mating system studies of the endangered North American passerine, loggerhead shrike (Lanius ludovicianus). Conserv. Genet. Res. 4, 503–506. Crawford, N.G., 2010. SMOGD: software for the measurement of genetic diversity. Mol. Ecol. Res. 10, 556–557. Dabrowski, M.J., Pilot, M., Kruczyk, M., Zmihorski, M., Umer, H.M., Gliwicz, J., 2014. Reliability assessment of null allele detection: inconsistencies between and within different methods. Mol. Ecol. Res. 14, 361–373. Dent, E.A., vonHoldt, B.M., 2012. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Res. 4, 359–361.
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