Maintenance of mitogenomic diversity despite recent population decline in a critically endangered Aotearoa New Zealand bird

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Forsdick, Alana Alexander, Liz Brown, Richard F. Maloney, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4457261/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2024 Read the published version in Conservation Genetics → Version 1 posted 9 You are reading this latest preprint version Abstract Mitochondrial genomes (mitogenomes) represent a relatively cost-effective tool for comparing diversity between contemporary and historical populations to assess impacts of past population processes, or the outcomes of conservation management. The Aotearoa New Zealand endemic kakī | black stilt ( Himantopus novaezelandiae ) is a critically endangered wading bird. Anthropogenic impacts contributed to kakī declining to ~ 23 individuals in 1981 and promoted interspecific hybridisation with their more common congener, the poaka | pied stilt ( H. himantopus leucocephalus ). Conservation management of kakī has resulted in the population increasing to 169 wild adults today. Here we use mitogenomes to enable comparisons of diversity between contemporary and historical (pre-1970s) stilts, and to understand the impacts of past interspecific hybridisation. We assemble a mitogenome for kakī and use this as a reference to facilitate downstream comparisons of mitochondrial diversity among kakī and poaka through time. Mitogenome haplotypes clearly differentiate kakī from poaka, and thus contribute to the behavioural, ecological, morphological and genetic evidence that conservation action has maintained the species integrity of this critically endangered bird. Furthermore, these results indicate conservation management aiming to maintain genetic diversity has been successful. threatened species phylogenetics divergence time Himantopus stilts interspecific hybridization mitochondrial diversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Conservation management programmes for intensively managed species generally aim to minimise the loss of genetic diversity over time to maintain evolutionary potential (Frankham et al. 2017 ). However, these programmes must often operate in lieu of knowledge of the impacts of population decline on genetic diversity prior to the initiation of conservation management. As genetic and genomic tools become increasingly available, management can then be fine-tuned to enhance conservation outcomes. One tool that can bridge this gap is paleogenomics, the sequencing of historical or ancient samples, revealing information about demographic processes and changes in genetic diversity from the past (Noonan et al. 2005 ; Krause et al. 2006 ; Miller et al. 2008 ). Temporal comparisons of mitochondrial diversity can inform assessments of the impacts of anthropogenic threats, assessing the success of past conservation management while informing future management in the face of impacts of climate change of species distributions (e.g., Wilmshurst et al. 2014 ). Obtaining complete mitogenomes from specimens in natural history collections through high-throughput sequencing (HTS) has become relatively efficient and cost-effective, adding to the genomic resources in the conservation toolbox (Forsdick et al. 2022 ). Perhaps nowhere is the need for temporal comparisons of mitogenomic diversity for conservation as pronounced as in island ecosystems. One such ecosystem is Aotearoa New Zealand where geographic isolation has given rise to a taxonomically distinct avifauna with high rates of endemicity (Holdaway et al. 2001 ; Checklist Committee (OSNZ) 2022 ). There were 14 species of endemic shorebirds present at the time of human arrival (Order Charadriiformes; Trewick and Gibb 2010 ) including kakī | black stilt ( Himantopus novaezelandiae ; Holdaway et al. 2001 ). The broadly-distributed (from the Philippines across to New Zealand) congeneric poaka | pied stilt ( H. himantopus leucocephalus ; taxonomy following Checklist Committee (OSNZ) ( 2022 )) self-introduced to Aotearoa probably in the 19th century, and now occurs in sympatry with kakī. To date, the sole estimate for the divergence time of kakī and poaka from a common ancestor is derived from sequence divergence at the mitochondrial control region, at approximately one million years ago (Chambers and Macavoy 1999 ; Wallis 1999 ). Kakī numbers declined during the 1900s due to anthropogenic habitat modification and the introduction of mammalian predators, while poaka numbers increased across the mainland to around 20,000 (Southey 2009 ; Riegen 2021 ). The contrasting demographic patterns for kakī and poaka are likely a result of their evolutionary history, with the same anthropogenic effects that contributed to kakī decline facilitating the expansion of poaka across the country (Pierce 1984b ). During kakī decline, hybridisation with poaka has occurred as a consequence of limited mate choice, resulting in the production of fertile hybrid offspring with intermediate plumage colouration between the completely black kakī and the black and white poaka (Pierce 1984a ). Conservation management for kakī began in 1981 when the species had declined to approximately 23 wild adults (Pierce 1984a ). Early conservation efforts included a small number of dark hybrids. In contrast, contemporary management utilises only black kakī, aimed at maintaining species integrity (Reed et al. 1993 ; Maloney and Murray 2001 ; Steeves et a. 2010; Forsdick et al. 2021 ). In combination with predator control and habitat restoration, genetics- and genomics-informed intensive management has seen kakī numbers increase to 169 wild adults in 2024. Nevertheless, kakī remain critically endangered, with the species primarily limited to Te Manahuna/the Mackenzie Basin in the central South Island of Aotearoa, a tiny fragment of their former distribution across both main islands of Aotearoa (Maloney and Murray 2001 ; BirdLife International 2018). Genetic and genomic resources have been used in the management of kakī to assess the extent and impacts of inbreeding (Hagen et al. 2011 ), hybridisation (Steeves et al. 2010 ; Forsdick et al. 2021 ), and to inform captive pairing decisions (Galla et al. 2020 ). Specifically, a 291 bp fragment of the mitochondrial cytochrome b gene and nuclear microsatellite markers have been used to assess the presence introgression resulting from hybridisation between kakī and poaka (Steeves et al. 2010 ). While this and subsequent genomic analyses indicated that the species integrity of kakī had been maintained despite extensive hybridisation (Steeves et al. 2010 ; Forsdick et al. 2021 ), there is no data on the historical diversity of kakī available to explore what may have been lost due to species decline, or maintained since conservation management began. Here we compare mitogenome diversity of modern and historical kakī, poaka, kakī-poaka hybrids, and Australian pied stilts ( H. leucocephalus ) as an outgroup. We make comparisons between kakī and poaka in terms of modern and historical mitogenome diversity providing insights into historical kakī diversity, the impacts of the recent population bottleneck, and a baseline of diversity which can be used to assess the effectiveness of conservation strategies. 2. Materials and methods 2.1 Sampling Contemporary (2010–2018) stilt samples (including kakī, poaka, kakī-poaka hybrids, and Australian pied stilts; n = 32) were collected for whole genome (WGS) and/or mitogenome sequencing under relevant ethics approvals as part of aligned projects (Galla et al. 2019 ; Galla et al. 2020 ; Supplementary Table 1). In addition, 27 samples dating from 1843–2011 were collected from stilt specimens in national museum collections (Supplementary Table 2). Catalogue information recorded these specimens as twelve kakī, twelve poaka, and three hybrids, although there were some discrepancies between catalogued and morphological species identification based on plumage following Steeves et al. ( 2010 ; Supplementary Table 2). Specimens from both the North Island and South Island were included, along with one individual from Chatham Island (Rēkohu/Wharekauri, Fig. 1 ). Five specimens dated from the 1800s, with the earliest collected in 1843. Of the nine specimens from Te Papa Tongarewa – Museum of New Zealand with no recorded collection dates, catalogue numbers in the range OR000001-OR008000 were used to classify specimens as having been collected and catalogued prior to the early 1950s (T. Schultz, Te Papa Tongarewa Science Collection manager, pers. comm.). Tissue from toe pads was collected from all skins and mounted specimens, and desiccated tissue collected from skeletal specimen MS11001, following protocols to avoid cross-contamination. 2.2 Primer design and mitogenome amplification from modern samples We designed primers to amplify the mitogenome of birds included in this study in four overlapping sections using long-range PCR. To identify conserved regions that could be used as primer sites for amplification of stilt mitogenomes in the absence of a reference mitogenome for kakī, we constructed a conordinal proxy mitogenome from the consensus alignment of complete mitogenomes for six species within the Order Charadriiformes using MUSCLE v3.8.425 (Edgar 2004 ) in Geneious® v11.1.5. This consensus included two mitogenomes from pied avocets ( Recurvirostra avosetta ; NCBI Accession No.: KY623657.1 and NC_027420.1), one black-winged stilt ( Himantopus himantopus ; NC_035423.1), one blackish oystercatcher ( Haematopus ater ; AY074886.2), one Eurasian oystercatcher ( Haematopus ostralegus ; NC_034237.1), and one long-billed plover ( Charadrius placidus ; KY419888.1). We identified potential primer sites in conordinal conserved regions with Invitrogen™ Primer3-based OligoPerfect™ in the Thermo Fisher Cloud with default parameters, with target regions customised to produce four sets of primer pairs overlapping across the mitogenome. We required a ≥ 50 bp overlap between the four fragments, and assessed melting temperatures and potential for self- or cross-primer diimerization with Thermo Fisher Multiple Primer Analyzer. For each primer pair, following optimisation for amplification, the final 50 µL amplification reaction consisted of 10 µL 5✕ KAPA magnesium-free Long Range buffer (KAPA Biosystems), 1.75 mM MgCl 2 , 0.3 mM dNTPs, 0.5 µM each of the forward and reverse primer, 0.5 U KAPA Long Range Hotstart Polymerase, and 2 µL 1:10 diluted template DNA. Thermocycling conditions were: initial denaturation of 94°C for 180 s, ten cycles of 94°C for 25 s, 54°C for 15 s, and 68°C for 60 s per expected kilobase (either 4 kb or 6 kb) of fragment length, followed by 25 cycles of 94°C for 25 s, 54°C for 15 s, and 68°C for 60 s per expected kilobase plus 20 s per cycle, with a final extension step of 72°C for 60 s per expected kilobase. The four primer sets were used to amplify the mitogenome from eight modern stilt samples (LR-PCR samples; Supplementary Table 1). Amplified products were prepared for direct sequencing and were also used as baits for hybridisation-capture of historical samples. Amplified products were purified using a QiaQuick® PCR Purification Kit (QIAGEN) with binding buffer (PB) equal to 5✕ the reaction volume eluted into 30 µL elution buffer. Purified products were quantified via Qubit, and visualised on a 1% agarose gel run at 80 V for 45 min. For sequencing, double-stranded barcoded libraries were produced following Kircher et al. (2012; see Supplementary Methods). Final DNA quantity was confirmed via Qubit. The pooled library was sequenced at the Otago Genomics and Bioinformatics Facility (OGBF) on one lane of an Illumina MiSeq Nano run with 2 x 250 bp paired-end sequencing. 2.3 DNA preparation and sequencing from museum samples All gDNA extractions and library preparations of museum samples were performed in a dedicated aDNA facility at the University of Otago using strict protocols to minimise contamination (Knapp et al. 2012 ). DNA was extracted using the QIAGEN DNeasy® Blood and Tissue kit (QIAGEN) spin-column protocol for tissue, with an overnight digestion step. gDNA was extracted in batches of 6–7 samples. To assess potential contamination, one negative control was processed in parallel with each batch. gDNA was eluted into 50 µL elution buffer. Double-stranded libraries were produced for all historical samples and negative controls using in-solution hybridisation capture and paired-end sequencing on an Illumina platform (detailed in Supplementary Methods), following Greig et al. ( 2015 ). Between each library preparation step, libraries were purified over a MinElute PCR Purification Kit (QIAGEN) according to manufacturer’s specifications, with two PE wash steps. To ensure successful hybridisation capture for all historical samples including kakī, poaka, and interspecific hybrids, a combined ‘Himantopus’ mitochondrial bait set was prepared from one modern kakī (DNA1044) and one modern poaka (B40279) following a modified protocol based on Maricic et al. ( 2010 ) (see Supplementary Methods). Hybridisation of libraries to the modern DNA bait then followed Maricic et al. ( 2010 ) with modification (detailed in Supplementary Methods). Final prepared libraries were quantified via Qubit and pooled equimolarly prior to being concentrated through a MinElute spin column with a single PE wash step and eluted into 20 µL 0.1✕ TE. The fragment length distribution of the pooled library was assessed with a QIAxcel Advanced (QIAGEN) using a DNA High Resolution kit and QIAxcel ScreenGel® software. The final pooled library was diluted to 10 nM and sequenced on one lane of a MiSeq v2 with 2 ✕ 75 bp paired-end sequencing. Negative controls, having been processed in the same manner alongside individual samples, were pooled with a series of negative controls from other aDNA projects within the lab and sequenced independently from sample libraries (see Supplementary Methods). 2.4 Reference mitogenome assembly from whole-genome sequencing data We assembled a kakī mitogenome from whole-genome sequencing data of one kakī individual (DNA1914; Galla et al. 2019 ) to use as a reference for sequence mapping and downstream analyses. Following sequence processing as described in Galla et al. ( 2019 ), whole-genome sequences from kakī DNA1914 were passed to NOVOPlasty v2.7.1 (Dierckxsens et al. 2016 ) with the black-winged stilt mitogenome (NC_035423.1) used as seed and reference to initiate assembly. Read length of 150 bp and an average insert size of 350 bp were specified. Mitogenome size was estimated based on published mitogenomes of confamilial species at 16–20 kb, and an estimated k -mer of 39 was used based on that for nuclear genome assembly (Galla et al. 2019 ). Output contigs were manually assessed and overlapping regions between contigs were merged to produce a single contig. Whole-genome sequence data from DNA1914 was mapped against this draft mitogenome assembly to correct errors and produce a consensus mitogenome sequence. The resulting mitogenome was annotated using MITOS (Bernt et al. 2013 ). 2.5 Bioinformatic processing Contemporary samples were demultiplexed by OGBF and sequence quality was confirmed via FastQC v0.11.5 (Andrews 2010 ). To increase the sample size for kakī, whole-genome resequencing data for 24 additional modern kakī generated as part of an aligned project (Galla et al. 2019 ) were incorporated in analyses (Fig. 1 , Supplementary Table 5). We processed the modern stilt targeted mitochondrial data and modern kakī WGS data independently using a custom pipeline implementing AdapterRemoval v2.1.7, BWA v0.7.17 (Li and Durbin 2009 ), Picard v2.18.0 (Picard Toolkit 2019), and SAMtools v1.7 (Li et al. 2009 ) to produce complete mitochondrial genomes for each individual. Museum samples and negative controls were processed independently of modern samples. Data were demultiplexed by OGBF, and sequence quality was confirmed via FastQC v 0.11.5. Data were then processed using a custom pipeline implementing AdapterRemoval, BWA, SAMtools, Picard, PALEOMIX (Schubert et al. 2014 ), and MapDamage (Jónsson et al. 2013 ). Samples were retained for downstream analyses if coverage across the mitogenome exceeded 90%. Scripts associated with sample processing and variant calling for modern and historical samples are available at https://github.com/natforsdick/Himantopus/tree/master/Mitogenomes . 2.6 Variant calling We conducted variant-calling for the museum samples, modern LR-PCR, and modern WGS data sets independently. The reference mitogenome was indexed with SAMtools v1.9 faidx , and a sequence dictionary created with Picard CreateSequenceDictionary . GATK v3.8.0 (McKenna et al. 2010 ) HaplotypeCaller was used to call variants for haploid mitochondrial data from individual sample BAM files (sorted, indexed BAMs with duplicates removed for modern samples, or the merged, sorted, rescaled BAM files with duplicates removed for historical samples). Joint genotyping based on the group variant files was then conducted with GATK’s GenotypeGVCFs . SNPs and indels were independently identified using SelectVariants and filtered using VariantFiltration . Variants were filtered to exclude SNPs with quality by depth (QD) 60, MQ (root mean-square mapping quality) < 40, and to exclude indels with QD 200, or ReadPosRankSum < -20.0 (indels found near ends of reads more often than expected). All SNPs and indels were then recombined with GATK RecombineVariants , with priority given to SNPs, and variants that had failed the filtering were removed with SelectVariants . The group VCF generated was then used to produce individual VCFs with GATK SelectVariants , excluding variants that failed to pass the filters. GATK DepthOfCoverage was used to add coverage information for sample VCFs, and a custom R script was used to exclude sites with coverage < 10✕ for all samples. Final FASTA files were generated from the filtered individual VCFs with GATK FastaAlternateReferenceMaker . 2.7 Bayesian phylogenetic analysis To estimate the time to the most recent common ancestor (TMRCA) for kakī and Australian pied stilts (the source population for poaka) and confirm their position within the Order Charadriiformes, we used BEAST v2.6.0 (Bouckaert et al. 2019 ) to conduct Bayesian phylogenetic analyses in a two-phase approach (as in Morin et al. 2015 , 2018 ). In Phase I, we estimated TMRCA for stilts by implementing a time-calibrated phylogenetic analysis for all Charadriiformes. We randomly selected one kakī and one Australian pied stilt individual from among the modern samples and aligned these mitogenomes with forty Charadriiformes mitogenomes available on GenBank, along with the chicken ( Gallus gallus ; NCBI Accession No.: MH732978) and Australasian grebe ( Tachybaptus novaehollandiae , Order Podicipediformes; NCBI Accession No.: EF532936) as outgroups using MUSCLE implemented in Geneious® with default settings (Supplementary Table 2). We identified a potential duplication in the mitogenome of kakī from 14,242 bp onwards based on anomalous coverage depth (see Results, Supplementary Fig. 3, Supplementary Material), so alignments were truncated to 1–14,239 bp to exclude the anomalous region, avoiding many of the problems identified by (Sangster and Luksenburg 2021 ). The Vega gull ( Larus vegae ) mitogenome was excluded from analyses due to preliminary maximum likelihood analysis ascribing it as sister to Charadriidae rather than within the Laridae clade, consistent with previous research (Yang et al. 2017 ). To determine the appropriate site partitioning scheme, the alignment was passed to PartitionFinder2 (Lanfear et al. 2017 ) with four models assessed (GTR, GTR + G, GTR + I + G, and JC + I + G) using corrected AIC for model selection and implementing the Greedy algorithm (Guindon and Gascuel 2003 ; Lanfear et al. 2012 ). Based on results from PartitionFinder2 (scheme AICc = 296810.201, scheme lnL = -148244.294), coding genes were partitioned into first-, second-, and third-codon positions; tRNAs into a combined partition of the first- and second-‘codon’ positions and a partition with the third-‘codon’ positions, and sRNAs were also partitioned into a combined partition of the first- and second-‘codon’ positions and a partition with the third-‘codon’ positions of the combined sRNAs. In reference to the tRNAs and sRNAs, it should be noted that the ‘codon’ partitioning is a limitation of PartitionFinder2, as unlike protein-coding genes, there is not an a priori reason to expect codon-like variation in substitution patterns. We used BEAUti v2.6.0 to generate input files for BEAST, linking tree and clock models across all partitions. The Gamma site model (with five categories) was used across all partitions. Initially, all partitions identified by PartitionFinder2 were allocated a separate site model, with GTR (Generalised Time Reversible) defined as the substitution model. However, the failure of initial runs to reach stationarity due to over-parameterization led to all tRNA positions being included in a single partition and assigned the TN93 (Tamura and Nei 1993 ) substitution model. GTR was used for all other partitions. The analysis was implemented with a relaxed log normal clock model to allow for among-lineage rate variation (Drummond et al. 2006 ), and using a calibrated Yule model so we could extract divergence time information (Heled and Drummond 2012 ). To calibrate the analysis, we used log normal priors (mean in real space) based on fossil evidence (Smith 2015 ): crown Charadriiformes (divergence of Charadrii from the other Charadriiformes) were given a mean and minimum (using offsets) age of 41.3 Mya, and the divergence of skuas (Stercorariidae) and auks (Pan-Alcidae) a mean and minimum age of 34.2 Mya. The standard deviation of the log-transformed distribution for both priors was 1.25. Log normal priors were given for both calibration points (Supplementary File 1). Two chains of 100 million states were logged at every 1000 states. The first 50% of each run was discarded as burn-in, and Tracer v1.7.1 (Rambaut et al. 2018 ) was used to confirm both runs had reached stationarity and convergence. To further assess convergence, maximum clade credibility trees were constructed for the two chains independently with TreeAnnotator v2.5.1, with a burn-in of 50%. Once convergence was confirmed, the two log and tree files were combined with LogCombiner v2.6.1 after removing the first 50% as burn-in and visualised with FigTree v1.4.3. In Phase II, a subsequent Bayesian analysis was conducted to assess congeneric relationships among kakī, poaka, hybrid individuals, and Australian pied stilts using parameter estimates obtained in Phase I to inform the analysis (Supplementary Files 1 and 2). Complete mitogenomes for 49 stilts comprising 34 kakī, 8 poaka, 5 hybrids, and 2 Australian pied stilts were aligned with MUSCLE using default settings in Geneious®. All individuals were classified by morphological identification rather than catalogue records, except for the stilt skeletal specimen MS11001 (plumage not available). Partitions were implemented as in the conordinal Bayesian analysis, including exclusion of non-coding sites (i.e., trimming the total alignment to a length of 14,239 bp). We implemented a relaxed log-normal clock with free rates (Drummond et al. 2006 ) as the Phase I conordinal analysis indicated rate variation between the kakī and pied stilt lineages (see Results, Fig. 2 , Supplementary File 1). As for the conordinal analysis, clock and tree models were linked across all partitions. However, as multiple individuals were sampled per species, the Coalescent Bayesian Skyline tree model (Drummond et al. 2005 ) was implemented instead of the Calibrated Yule tree model. The tree height was given a uniform prior with lower and upper bounds (0.4157–1.1633 Mya) based on the credibility interval for the divergence of kakī and Australian pied stilts determined from conordinal analysis (see Results, Fig. 2 and Supplementary File 3). Two chains of 10 million states were logged at every 1,000 states. Outputs were assessed for stationarity and convergence, combined using a 10% burn-in, annotated and visualised as for the conordinal analysis. 2.8 Maximum likelihood phylogenetic analysis For comparison with the results of Bayesian analysis, we used maximum likelihood analysis to construct a phylogenetic tree for the Order Charadriiformes. First, we selected the optimal nucleotide-substitution model for the aligned mitogenomes using jModelTest v2.1 (Guindon and Gascuel 2003 ; Darriba et al. 2012 ), with 88 candidate models and 11 substitution schemes, using the Bayesian Information Criterion (BIC) to select the most appropriate model (determined as GTR + I + G, General Time Reversible model with I = proportion of invariable sites and G = Gamma distribution). We then used IQ-Tree v1.6.6 (Nguyen et al. 2015 ) to generate a maximum likelihood consensus tree with the nucleotide-substitution model selected, and ultrafast bootstrapping for 10,000 bootstraps (Hoang et al. 2018 ). We visualised the consensus tree with FigTree v.1.4.3. To assess whether using the truncated mitogenomes resulted in any substantial differences in taxonomic relationships within the order, we compared the output trees with published Charadriiformes phylogenies (e.g., Baker et al. 2007 ; Barth et al. 2013 ; Hu et al. 2017 ; Yang et al. 2017 ). 2.9 Haplotype network analysis To assess haplotype diversity and differentiation among the sampled stilts, we produced Median Joining Networks of haplotypes in PopART (Bandelt et al. 1999 ; Leigh and Bryant 2015 ). Traits blocks were created based on morphological species identification information (kakī, poaka, interspecific hybrids, Australian pied stilts). Temporal separation of haplotype networks based on statistical parsimony were visualised with TempNet (Prost and Anderson 2011 ). We classified samples as ‘Historical’ (catalogued prior to the early 1950s) or ‘Modern’ (catalogued after the 1950s). Samples without recorded collection dates were designated ‘Historical’ or ‘Modern’ based on museum ID number. We selected the 1960 as the cut-off between historical and modern samples because no individuals were known to have been collected in the period 1960–1975. Therefore, collection dates post-1950s correspond to the crux of the kakī decline towards the end of the 1970s. Individuals collected after 1975 are assumed to be representative of the diversity remaining among contemporary kakī. 2.10 Mitochondrial diversity and differentiation between species We used DnaSP v6 (Rozas et al. 2017 ) to generate a point estimate of nucleotide diversity (𝜋) across the truncated mitogenome. The alignment was specified as a haploid mitochondrial sequence and the 14,239 bp region was regarded as a single locus for diversity estimates. Overall statistics for the number of haplotypes, haplotype diversity, nucleotide diversity, and related metrics were produced, and then each species was assessed independently. All Australian pied stilts and poaka individuals were grouped due to limited sample sizes. In addition, we assessed differences in haplotype and nucleotide diversity between species and the two time categories implementing a permutation test with 10,000 replicates via genetic_diversity_diffs v1.0.7 in R v4.2.2 (Alexander et al. 2016 ). Following the visualisation of haplotype networks, we excluded individuals with haplotypes that did not correspond to their classified group (e.g., kakī skeletal specimen MS11001) and those with discordant catalogue-morphology classifications estimates to avoid overestimating species-specific diversity metrics due to inclusion of interspecific hybrids. 3. Results 3.1 Historical sample morphological identification Species designation of museum specimens based on plumage morphology produced several discrepancies between catalogued species identification and morphological species identification. Four individuals recorded as poaka were identified as kakī based on plumage (MS10991, MS10992, MS10994, MS10995; Supplementary Table 2, Supplementary Methods). Two of these individuals with some white breast feathers were identified as sub-adult kakī. Kakī only gain full black plumage at their second summer, which may complicate identification of black and white sub-adults that often resemble poaka. One individual label as kakī (MS11004) was identified by plumage as a kakī-poaka hybrid, and one individual recorded as a kakī-poaka hybrid (MS11010) was classified as either poaka or a very light hybrid based on plumage. These discrepancies were primarily of specimens that entered museum collections prior to the categorisation of stilts by plumage as described by Pierce ( 1984a ). The remaining 19 specimens (excluding skeletal specimen MS11001 for which plumage classification was not available) had concordant morphological and catalogued species identifications. 3.2 Mitogenome assembly from whole genome sequence data The NOVOPlasty mitogenome assembler subsampled 32.01% of the input kakī DNA1914 whole genome sequence reads, totalling 134 million reads. Of these, 9,106 reads were aligned to the reference black-winged stilt mitogenome, with 8,062 subsequently assembled producing two contigs of length 15,754 and 1,849 bp, with 78✕ average coverage depth. Visual assessment of these contigs detected a region of overlap of 37 bp, and the two contigs were thus merged at this point to produce a single circular mitochondrial genome of 17,566 bp (Supplementary Fig. 1), within the expected length for Charadriiformes mitogenomes (~ 16–18 kb; Supplementary Table 6). Base composition was 31.91% A, 30.97% C, 13.22% G, and 23.82% T. The top match from the BLAST nucleotide database was to the black-winged stilt mitogenome, with 99% query cover and 99% identity, followed by 94% query cover and 93% identity to the confamilial pied avocet, the two closest relatives with available mitogenomes. Mitogenome annotation with MITOS identified 22 tRNAs, two rRNAs, and 13 protein-coding genes in the typical avian order (Supplementary Fig. 1). 3.3 Sequencing outputs Primers were designed for long-read amplification of four regions comprising the complete kakī mitogenome (Supplementary Fig. 1). An average of 254,904.5 ± SD 56,661.93 sequence reads were produced per sample (Supplementary Table 3). Sequence yield for museum samples MS10993, MS11008, MS11012 and MS11013 was very low (< 1000 reads per sample; Supplementary Table 4) MapDamage results revealed the expected damage patterns for DNA extracted from historical samples (see Supplementary Fig. 2), consistent with the relatively recent ages of these samples being associated with less pronounced misincorporation frequencies than would be observed from ancient samples (Ginolhac et al. 2011 ). Sequencing of a pool of 29 aDNA negative controls (including 21 unrelated to this study) produced 1.3 Gb sequence data (Supplementary Table 8). Only one negative control, DNA-ve2 (sequence ID OG5003-13-0-1) had > 50 reads mapped to the kakī mitogenome, with 16.23% of reads mapping. This resulted in 97.7% coverage of the mitogenome, at 27✕ depth. Given the evident contamination, the seven samples prepared in the batch associated with this negative were excluded from downstream analyses. For modern stilts where long-read amplification was utilised for library preparation, an average of 99.7% of the mitogenome was covered at a depth of 403.79✕ (Supplementary Table 3). For museum samples, where bait capture was utilised alongside library preparation, mitogenomes had > 97% coverage for all samples except MS10993, MS11008, MS11012, and MS11013, which had coverage between 0-0.4✕ due to low sequence yield of these samples (Supplementary Table 6). Excluding these four samples, average coverage for the museum samples was 97.89% with an average depth of 233.89✕ across all samples. Processing of the WGS resequencing data from the 24 modern kakī samples resulted in 100% sequence coverage for all individuals, with an average depth of 250.93✕ (Supplementary Table 8). Mapping results identified a region from 14,239 bp onwards (including the NAD6 gene and the control region) with twice the mapping depth compared with the rest of the mitochondrial genome (Supplementary Fig. 3). We hypothesised this to represent a region of mitogenome duplication in kakī. This was supported by preliminary investigation using ONT long-read sequencing (see Supplementary Material section 4 ). One consequence of this newly discovered region of duplication is that mean coverage depth of resequenced individuals, calculated across the entire mitogenome including the duplicated region, is likely inflated. 3.4 Bayesian and maximum likelihood phylogenetic analyses Bayesian phylogenetic analysis and maximum likelihood analysis on the mitogenome alignment of forty members of the Order Charadriiformes, with the Australasian grebe ( Tachybaptus novaehollandiae , Order Podicipediformes) and chicken ( Gallus gallus , Order Galliformes) as outgroups, and one representative kakī and Australian pied stilt (total n = 44; Supplementary Table 6) produced trees with identical topologies (Fig. 2 ), consistent with those of previous phylogenetic studies of the Order Charadriiformes using mitochondrial data (e.g., Baker et al. 2007 ; Yang et al. 2017 ). The black-winged stilt ( H. himantopus ) was sister to the combined clade of kakī and Australian pied stilts. Based on the Bayesian analysis, TMRCA for kakī and Australian pied stilts was approximately 0.750 Mya (95% highest posterior density (HPD) = 0.416–1.163 Mya), and the TMRCA for the Himantopus clade was estimated at approximately 1.480 Mya (95% HPD = 0.883–2.214 Mya; Fig. 3 ). The divergence estimate for kakī and Australian pied stilts was more recent than all other congeneric species pairs within Charadriiformes, except those of plovers Charadrius placidus and C. alexandrinus (Charadriidae, TMRCA estimated at 0.118 Mya (95% HPD = 0.041–0.209 Mya)) and gulls Chroicocephalus brunnicephalus and C. ridibundus (Laridae, TMRCA estimated at 0.473 Mya (95% HPD = 0.240–0.754 Mya)). Minimal impacts of hybridisation were observed between the well-supported kakī and pied stilt clades in the congeneric Bayesian analysis (posterior probability = 1, estimated divergence 0.663 Mya (95% HPD = 0.416–1.062 Mya; Fig. 4 ), with a single kakī sample found in the pied stilt clade, and a single poaka (and no Australian pied stilts) found in the kakī clade. One kakī-hybrid individual occurred in the kakī clade, with two occurring in the pied stilt clade, along with the skeletal sample originally recorded as kakī (MS11001, Fig. 4 ). Diversification of lineages within the kakī and pied stilt clade appear to have occurred during a similar time period approximately 0.010–0.193 Mya, potentially associated with the end of the Ōtira glacial period. 3.5 Haplotype networks Median-joining networks produced with PopART further confirmed differentiation between species, with 64 fixed difference found between the four kakī (A-D) and eight pied stilt haplotypes identified (E-L; Fig. 5 ). One poaka (MS11006) and one hybrid (MS11002) were observed to have kakī-type haplotypes A and C respectively. The skeletal specimen (MS11001) was the only individual classified as kakī that was observed to have a pied stilt-type haplotype (F), indicating potential specimen misclassification. The remaining three hybrid individuals all had pied stilt-type haplotypes. Among the two Australian pied stilts, one had a haplotype shared by two poaka (G), while the other possessed a unique haplotype (E). When individuals were categorised as modern or historical, one kakī haplotype was present in historical samples that was not represented among the modern samples, while one haplotype was observed among modern samples but not captured among the historical samples (Fig. 5 ). 3.6 Mitochondrial diversity metrics Diversity and differentiation metrics were estimated from 49 kakī, Australian pied stilts, poaka, and kakī-poaka hybrids across the extracted 14,239 bp of the mitogenome. In this region, 45 sites contained gaps or missing data, with 98 biallelic sites. Following classification of individuals by morphology and assessing haplotypes for discordance between catalogued species identity and haplotype identity, known hybrids and individuals with unknown/uncertain plumage were excluded, leaving 34 kakī and 9 pied stilts (including both Australian pied stilts and poaka) for interspecific comparison. Among kakī, there were 13 polymorphic sites, representing four unique haplotypes ( Hd = 0.4849, 𝜋 = 0.00034 ± SD 0.00005), while among pied stilts, there were 19 polymorphic sites and six unique haplotypes ( Hd = 0.8889, 𝜋 = 0.00046 ± SD 0.00006). There were an average of 4.870 nucleotide differences among kakī individuals and 6.500 among pied stilts, with an average of 74.261 nucleotide differences between the two species. Permutation tests revealed a significant reduction in haplotype diversity from historical to modern kakī, but no significant reduction in nucleotide diversity (Supplementary Table 9). 4. Discussion Here we produced the first annotated mitogenome assembly for kakī and used this as a reference for investigating mitochondrial diversity and divergence between kakī and Australian pied stilts. Analyses supported differentiation between these congeners, with divergence from a common ancestor estimated at 750,000 ya (95% HPD = 0.415–1.163 Mya) based on Bayesian inference. Utilisation of the mitogenome dataset revealed greater mitochondrial diversity among kakī than previously detected through single-gene mitochondrial analyses (Steeves et al. 2010 ), with contrasts between the modern and historical samples here indicating that mitogenome diversity has been largely maintained among kakī despite the species decline and subsequent recovery. 4.1 Mitogenome assembly and identification of a potential mitochondrial gene duplication Mitogenome assembly for kakī using NOVOPlasty produced an assembly of the expected length (16–18 kb), with close similarity to the published mitogenome of the congeneric black-winged stilt. Mapping high-coverage whole-genome resequencing data to the assembled kakī mitogenome revealed a region of the mitogenome covered at twice the depth of the remaining assembly, suggesting a mitochondrial gene duplication collapsed during assembly due to the close similarity between the duplicated sequences. This hypothesis was confirmed with ONT long-reads that spanned the putative duplication (Supplementary Material section 4 ). Similar duplications have been observed in a wide range of avian species (Bucerotiformes (Sammler et al. 2011 ), Passeriformes (Singh et al. 2008 ; Gibb et al. 2015 ), Pelecaniformes (Cho et al. 2009 ; Gibb et al. 2013 ), Procellariiformes (Abbott et al. 2005 ; Eda et al. 2010 ; Torres et al. 2019 ), Psittaciformes (Eberhard et al. 2001 ; Schirtzinger et al. 2012 ; Eberhard and Wright 2016 ), and Sulliformes (Morris-Pocock et al. 2010 )), including the conordinal ruff ( Calidris pugnax ; Verkuil et al. 2010 ). Unresolved mitochondrial gene duplication may result in incorrect estimation of diversity and inference of phylogeny when apparent nucleotide differences are the result of differences between duplicated regions within an individual. Thus, detecting such regions is important to ensure accurate haplotype detection and diversity estimation. 4.2 Stilt divergence dating and diversification of lineages Here we used mitogenomes to provide the first calibrated estimate of the timing of divergence for kakī and Australian pied stilts using Bayesian phylogenetic analysis. These results indicated a TMRCA for kakī and Australian pied stilts of approximately 750 Kya, 250Kya more recent than previous estimates, and one of the most recent estimates of divergence for a congeneric species pair within the order Charadriiformes. Such a recent split makes kakī and poaka highly susceptible to hybridisation, and so conservation efforts to maintain the species integrity of kakī are warranted. These data also contribute to our knowledge of the drivers of species diversification. Here, we find that deep lineage splits within both kakī and pied stilt lineages appear to correspond with the ending of the Eemian warm period (130 − 115 kya; Fig. 4 ). More recent and extensive lineage expansion following the Last Glacial Maximum (26 − 20 kya), which greatly impacted much of Aotearoa’s biodiversity (as reviewed by Marske and Boyer 2024 ), suggesting populations became isolated across different glacial refugia. Furthermore, the lineage diversity among poaka is suggestive of multiple invasions of pied stilts to Aotearoa, leading to greater diversity in comparison with kakī. 4.3 Comparison of kakī and poaka mitochondrial diversity and identification of mitochondrial introgression Although the maintenance of shared mitochondrial haplotypes in contemporarily isolated lineages could be a signature of recent shared ancestry, mitochondrial variation in these isolated lineages is expected to rapidly assort, leading to reciprocal monophyly within ~ 2 generations (Hudson and Coyne, 2002 ). Therefore, given the estimated divergence data between poaka and kakī, the few instances of mismatch between mitochondrial haplotype and plumage observed in this dataset are far more likely to be due to contemporary introgression. Although there are many known instances of hybridisation within the Order Charadriiformes (McCarthy 2006 ), the northern and wattled jacanas ( Jacana spinosa and J. jacana ) are the only other species known to hybridise with one another among the species represented in the conordinal comparative phylogenetic analyses here (Miller et al. 2014 ). These jacanas have a more distant estimated TMRCA (2.1362 Mya, 95% HPD = 1.905–4.969 Mya) than kakī and pied stilts (~ 1.4 Mya), and hybridisation between these congeners across the range overlap in Western Panama has resulted in mitochondrial introgression, as assessed using a 651 bp region of the mitochondrial COI gene (Miller et al. 2014 ). In comparison, potential mitochondrial introgression was observed in only a single poaka individual (MS11006). Only one individual classified as kakī showed evidence of introgression from poaka, and this was skeletal specimen MS11001, lacking plumage for confident morphological classification. This conforms with the pattern observed from nuclear genetic and genomic data (Steeves et al. 2010 ; Forsdick et al. 2021 ). When assessing haplotype diversity in stilts, four distinct haplotypes were identified among kakī doubling the number observed with single-gene mitochondrial analysis (Steeves et al. 2010 ). This supports our prediction that mitogenome analysis would reveal greater diversity than previously detected in single-gene mitochondrial studies. Nevertheless, we found relatively low haplotype diversity with historical small population size combined with a recent, severe bottleneck likely to have contributed to this low diversity (Pierce 1984b ; Forsdick 2020 ). Haplotype diversity among modern pied stilts was more than twice that of kakī, and nucleotide diversity was also considerably higher, despite the estimate of pied stilt diversity likely being an underestimate due to the relatively small sample size and limited sampling locations from its broad distribution. The greater number of haplotypes detected among pied stilts compared with the previous study (Steeves et al. 2010 ) is due to the wider sampling distribution, including individuals from Australia and the North Island of Aotearoa, as well as South Island sites outside Te Manahuna. Haplotype E is shared by an Australian pied stilt, a poaka, and a morphological kakī-poaka hybrid, which indicates that pied stilts and poaka have not yet become genetically differentiated at the mitogenome level. This may be due to a large, genetically diverse founding population arriving in Aotearoa relatively recently with little loss of diversity following arrival, or due to ongoing migration maintaining gene flow. The observation of one poaka with a kakī haplotype (individual MS11006 with Haplotype A) is most likely due to mitochondrial introgression resulting from hybridisation. This individual was a museum specimen collected prior to the early 1950s, demonstrating genetic evidence of hybridisation during this period in addition to the morphological evidence described by Pierce ( 1984b ). Similar mitochondrial introgression is observed in individual MS11002, a specimen with hybrid plumage collected in 1981. 4.4 Temporal changes in haplotype diversity Sequencing and downstream analyses incorporating historical museum specimens were informative for investigating temporal changes in patterns of diversity. All except one kakī haplotype present in the modern population was detected in the historical population (Haplotype D), with one haplotype observed among historical samples that was not present among the modern individuals assessed (Haplotype B). As the sample of modern kakī represents ~ 20% of the modern wild adult population, Haplotype B either occurs at very low frequency in the population, and thus is likely to be lost due to stochastic processes associated with small population size, or has already been lost. 4.5 Limitations of this study Limitations of this study include those inherent to using a single marker for analysis, and limited sample sizes, especially for historical material. Nevertheless, these results are consistent with estimates of nuclear diversity from nuclear microsatellite and whole-genome SNP data, and with analyses of introgression (Steeves et al. 2010 ; Forsdick et al. 2021 ), providing no evidence of introgression from poaka into kakī despite past hybridisation. Museum samples used here included all known historical kakī samples held in national museum collections, with the exception of a small number of fossil samples (Holdaway and Worthy 1997 ; Worthy 1998a , b ) and two kakī skins collected by early naturalist Sir Walter Buller, whose rarity and significance precluded their use in genomic analyses here. WGS techniques successfully enabled the inclusion of mitogenome data from historical stilt samples in this study. Mitogenome sequencing can provide representative estimates of diversity and population structure in an efficient manner, with utility for questions involving taxonomic uncertainty, population differentiation, and interspecific hybridisation. The reduced costs associated with mitogenome sequencing, combined with the ability to include temporal assessments of diversity due to high-copy number facilitating capture even in degraded samples, ensure that the analysis of mitogenomes remains valuable for informing conservation management of non-model species. Conclusions In this study we used mitogenomes to compare genetic diversity through time for kakī and Australian pied stilts (including poaka). We resolved the timing of divergence for kakī and Australian pied stilts at approximately 0.750 Mya and confirmed mitochondrial differentiation between kakī and poaka/Australian pied stilts, and no evidence of mitochondrial introgression from poaka/Australian pied stilts into kakī. We found previously undetected mitochondrial diversity among kakī. These results suggest that mitochondrial diversity may have already been limited prior to kakī decline, and provide evidence that kakī conservation management based on genetic data (Maloney and Murray 2001 ; Steeves et al. 2010 ; Hagen et al. 2011 ) has successfully maintained mitochondrial diversity. Overall these results suggest that active conservation management has assisted in helping maintain the distinct evolutionary trajectories of these two species, and, in combination with nuclear data (Forsdick et al. 2021 ), that genetics and genomics informed conservation management of kakī has achieved the goals of maintaining genetic diversity. Declarations Funding This research was funded by a Royal Society of New Zealand Rutherford Discovery Fellowship (MK), a Birds New Zealand Research Fund grant (NJF), and NJF was supported by a University of Otago Doctoral Scholarship and the Department of Anatomy. Ethics All samples were collected and held under appropriate permits. Samples from Australian black-winged stilts were provided under the Royal Zoological Society of South Australia Specimen Licence Agreement (Import Permit: 2016061954). Samples from poaka held at Auckland Zoo were collected with approval from the Auckland Zoo Animal Ethics Committee. All modern kakī, poaka, or hybrid samples were collected under approval of the New Zealand Department of Conservation (DOC) Animal Ethics Committee (AEC #283), or as part of routine captive management (DOC). Competing interests The authors have no relevant financial or non-financial interests to disclose. Author contributions NJF, MK, and TES contributed to study conception and design. Samples were provided from the DOC Kakī Recovery Programme by LB. Data were generated by NJF. Analyses were performed by NJF and AA. The first draft of the manuscript was written by NJF, and all authors contributed to subsequent versions. All authors read and approved the final manuscript. Data availability Kakī are a taonga (treasured) species for Māori (the Indigenous Peoples of Aotearoa), and as such, genomic data derived from kakī are recognised as taonga in their own right. Due to the tapu (sacred) nature of these data, tikanga (customary practices, protocols, and ethics) determines how people interact how people interact with them. Consistent with FAIR and CARE data principles, the data presented here are hosted on a password-protected database at www.ucconsert.org/data/, and can be made available at the discretion of the kaitiaki of the iwi (tribes) and hapū (subtribes) associated with kakī. These data include the kakī mitochondrial genome assembly presented here, raw demultiplexed mitochondrial sequence reads for each individual, and the VCF files produced from sequence mapping for each of the resequencing, modern targeted, and historical museum sequencing sets. Scripts associated with the bioinformatic pipelines for this manuscript are detailed in the GitHub repository at https://github.com/natforsdick/Himantopus/tree/master/Mitogenomes. Acknowledgements We extend our gratitude to the mana whenua who are kaitiaki for kakī, namely Te Rūnanga o Ngāi Tahu, Te Ngāi Tūāhuriri Rūnanga, Te Rūnanga o Arowhenua, Te Rūnanga o Waihao, and Te Rūnanga o Moeraki. We are grateful to the Aotearoa New Zealand Department of Conservation’s Kakī Recovery Team, additional sample providers including Colin Miskelly and Alan Tennyson at Te Papa Tongarewa – Museum of New Zealand, Matt Rayner at Auckland War Memorial Museum, Richard Jakob-Hoff at Auckland Zoo, David McLelland at Adelaide Zoo, and John Berry; sequencing provider the Otago Genomics Facility; and NeSI for access to computational resources. 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Syst Biol 67:901–904. https://doi.org/10.1093/sysbio/syy032 Reed CEM, Butler D, Murray DP (1993) Black Stilt Recovery Plan ( Himantopus novaezealandiae ). Department of Conservation, Wellington, New Zealand Riegen A (2021) Birds New Zealand National Wader Census 2021. Birds New Zealand Rozas J, Ferrer-Mata A, Sánchez-DelBarrio JC, et al (2017) DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol 34:3299–3302. https://doi.org/10.1093/molbev/msx248 Sammler S, Bleidorn C, Tiedemann R (2011) Full mitochondrial genome sequences of two endemic Philippine hornbill species (Aves: Bucerotidae) provide evidence for pervasive mitochondrial DNA recombination. BMC Genomics 12:35. https://doi.org/10.1186/1471-2164-12-35 Sangster G, Luksenburg JA (2021) Sharp increase of problematic mitogenomes of birds: causes, consequences, and remedies. 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Department of Conservation, Wellington Steeves TE, Maloney RF, Hale ML, et al (2010) Genetic analyses reveal hybridization but no hybrid swarm in one of the world’s rarest birds. Molecular Ecology 19:5090–5100. https://doi.org/10.1111/j.1365-294X.2010.04895.x Tamura K, Nei M (1993) Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol 10:512–526. https://doi.org/10.1093/oxfordjournals.molbev.a040023 Torres L, Welch AJ, Zanchetta C, et al (2019) Evidence for a duplicated mitochondrial region in Audubon’s shearwater based on MinION sequencing. Mitochondrial DNA Part A 30:256–263. https://doi.org/10.1080/24701394.2018.1484116 Trewick SA, Gibb GC (2010) Vicars, tramps and assembly of the New Zealand avifauna: a review of molecular phylogenetic evidence. Ibis 152:226–253. https://doi.org/10.1111/j.1474-919X.2010.01018.x Verkuil YI, Piersma T, Baker AJ (2010) A novel mitochondrial gene order in shorebirds (Scolopacidae, Charadriiformes). Molecular Phylogenetics and Evolution 57:411–416. https://doi.org/10.1016/j.ympev.2010.06.010 Wallis G (1999) Genetic status of New Zealand black stilt ( Himantopus novaezelandiae ) and impact of hybridisation. Conservation Advisory Science Notes 239:1–22 Wilmshurst JM, Moar NT, Wood JR, et al (2014) Use of pollen and ancient DNA as conservation baselines for offshore islands in New Zealand. Conservation Biology 28:202–212. https://doi.org/10.1111/cobi.12150 Worthy TH (1998a) A remarkable fossil and archaeological avifauna from Marfells Beach, Lake Grassmere, South Island, New Zealand. Records of the Canterbury Museum 12:79–176 Worthy TH (1998b) Quaternary fossil faunas of Otago, South Island, New Zealand. Journal of the Royal Society of New Zealand 28:421–521. https://doi.org/10.1080/03014223.1998.9517573 Yang C, Wang Q-X, Li X-J, et al (2017) Characterization of the mitogenomes for two sympatric breeding species in Recurvirostridae (Charadriiformes) and their phylogenetic implications. Mitochondrial DNA Part B 2:182–184. https://doi.org/10.1080/23802359.2017.1307704 Yang C, Wang Q-X, Li X-J, et al (2017) The mitogenomes of Gelochelidon nilotica and Sterna hirundo (Charadriiformes, Sternidae) and their phylogenetic implications. Mitochondrial DNA Part B 2:601–603. https://doi.org/10.1080/23802359.2017.1372709 Additional Declarations No competing interests reported. Supplementary Files ForsdicketalKakimtDNASupplementaryMaterial20240422.docx Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2024 Read the published version in Conservation Genetics → Version 1 posted Editorial decision: Revision requested 22 Aug, 2024 Reviews received at journal 04 Aug, 2024 Reviewers agreed at journal 04 Aug, 2024 Reviews received at journal 02 Jul, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers invited by journal 17 Jun, 2024 Submission checks completed at journal 22 May, 2024 Editor assigned by journal 22 May, 2024 First submitted to journal 21 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4457261","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308552751,"identity":"9d17ffbc-0852-45be-b9c7-06275534ed50","order_by":0,"name":"Natalie J. Forsdick","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYLCCBwYM/CBaIoEhQQ7EOPAAr3pmBoYEAwbJBqgWY7CWBIJaGKBagMxEEIMBnxZz9vMHPyQU2EjwSx9/eONBTVr6/LDDD4G22MnpNmDXYtmTzCyRYJAmIdmXY2yRcCwnd+PtNAOglmRjswPYtRgcSAZ6weBwncEZHjaJxIaK3I2zE0BaDiRuw6Xl/GPmHwkG/yUMzrA/A2lJN5yd/gG/lhvJbEBbDgC1MJgBteQkyEvnELDlxmMziwSDZAnJHh6QX9IMN0jnFBwAiuD2y/nExzc+/LGT4Odhf3jzR02yvPzs9M0fPlTYyeHSgi1AwCSxykFAvoEU1aNgFIyCUTASAACxtGFQIxTi6QAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Anatomy, University of Otago","correspondingAuthor":true,"prefix":"","firstName":"Natalie","middleName":"J.","lastName":"Forsdick","suffix":""},{"id":308552752,"identity":"f9aded98-51e6-4a06-aaa7-f8dd33e5fd9b","order_by":1,"name":"Alana Alexander","email":"","orcid":"","institution":"Department of Anatomy, University of Otago","correspondingAuthor":false,"prefix":"","firstName":"Alana","middleName":"","lastName":"Alexander","suffix":""},{"id":308552753,"identity":"5025bac1-3f56-42c4-8553-7fcfef7b87cd","order_by":2,"name":"Liz Brown","email":"","orcid":"","institution":"Department of Conservation","correspondingAuthor":false,"prefix":"","firstName":"Liz","middleName":"","lastName":"Brown","suffix":""},{"id":308552754,"identity":"c591757d-399c-43ba-ac2c-92779da0e55a","order_by":3,"name":"Richard F. Maloney","email":"","orcid":"","institution":"Department of Conservation","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"F.","lastName":"Maloney","suffix":""},{"id":308552755,"identity":"f54f45b3-9871-45d6-8d62-46d4a3c16e52","order_by":4,"name":"Tammy E. Steeves","email":"","orcid":"","institution":"School of Biological Sciences, University of Canterbury","correspondingAuthor":false,"prefix":"","firstName":"Tammy","middleName":"E.","lastName":"Steeves","suffix":""},{"id":308552756,"identity":"2d0edcec-9520-43b7-b9e7-011c73feca14","order_by":5,"name":"Michael Knapp","email":"","orcid":"","institution":"Department of Anatomy, University of Otago","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Knapp","suffix":""}],"badges":[],"createdAt":"2024-05-21 22:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4457261/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4457261/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10592-024-01661-3","type":"published","date":"2024-11-28T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57625379,"identity":"128fd309-e422-4d61-a984-ec08abfc344a","added_by":"auto","created_at":"2024-06-03 13:55:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120574,"visible":true,"origin":"","legend":"\u003cp\u003eKnown locations of origin of all utilised modern (1970s onwards) and historical (pre-1950s) stilt samples in Aotearoa New Zealand. All circles represent single individuals except for those within the kakī modern breeding distribution.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/9ca4e611e70db39858431c0c.png"},{"id":57626275,"identity":"07416781-8793-4921-9d67-4907cd91d316","added_by":"auto","created_at":"2024-06-03 14:03:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":391451,"visible":true,"origin":"","legend":"\u003cp\u003eBEAST maximum clade credibility tree (MCC tree, left) and maximum likelihood tree (ML tree, right) constructed with IQ-Tree v1.6.6 for the Order Charadriiformes based on a region of 14,239 bp of the aligned mitogenomes. Bayesian posterior probability (BPP) values \u0026gt; 0.95 indicate strong node support in the MCC tree, while maximum likelihood bootstrap node support (MLBS) values \u0026gt; 70% indicate strong node support in the ML tree. Trees are visualised with FigTree v1.4.3. The domestic chicken (Order Galliformes, Gallus gallus) and Australasian grebe (Order Podicipediformes, Tachybaptus novaehollandiae) are included as outgroups. The representative kakī (Himantopus novaezelandiae) included here is individual H01384, and the representative Australian pied stilt (H. himantopus leucocephalus) is individual B60480. Species are coloured by family within the Order Charadriiformes. Branches on the MCC tree are coloured according to the rate median. The scale bar on the left represents time since the present in million years for the MCC tree, and the scale bar on the right represents the number of substitutions per site for the ML tree.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/66b10d58c5136b3bad14fcbb.png"},{"id":57625383,"identity":"a03da91f-dd1f-4f82-9c84-d7e864895d6d","added_by":"auto","created_at":"2024-06-03 13:55:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":403266,"visible":true,"origin":"","legend":"\u003cp\u003eBEAST maximum clade credibility tree produced from the truncated mitogenome alignment for the Order Charadriiformes, visualised with FigTree v1.4.3. Estimated divergence times (million years ago, Mya) are displayed at branch nodes, with 95% highest posterior density intervals around these estimated times visualised as horizontal grey bars. Species are coloured by family within the Order Charadriiformes. The scale bar represents time since the present (Mya). The calibrated nodes (indicated by asterisks) were divergence of Stercorariidae from Alcidae, and the divergence of the clade comprising Charadriidae, Haematopodidae, and Recurvirostridae from all other Charadriiformes.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/00f437b8cbd19a2ce4c3f5dc.png"},{"id":57625381,"identity":"f13f7ff2-0203-4c6f-9db7-5a055ae26547","added_by":"auto","created_at":"2024-06-03 13:55:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":211977,"visible":true,"origin":"","legend":"\u003cp\u003eBEAST maximum clade credibility tree produced from congeneric analysis of the mitogenome region 1–14,239 bp of pre-defined kakī, pied stilts, poaka, and interspecific hybrids, visualised with FigTree v1.4.3. Circle colour represents the posterior probability (PP) associated with that node for nodes with PP \u0026gt;= 0.95. Numbers at nodes and branch lengths represent estimated time since divergence (TMRCA; Mya). Letter codes correspond to haplotypes identified in network analysis (see Fig. 5). Individuals are coloured according to morphological species identity. Scale bar represents time (Mya).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/3c9cb01fca1cd99f35d6565b.png"},{"id":57625385,"identity":"da917868-e7d5-404c-b62c-7e8eaea7c733","added_by":"auto","created_at":"2024-06-03 13:55:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":160967,"visible":true,"origin":"","legend":"\u003cp\u003eVisual representation of the mitochondrial haplotype diversity among all kakī (n = 34), poaka (n = 8), Australian pied stilts (n = 2), and kakī-poaka hybrids (n = 5) for the mitogenome region 1-14,239 bp, visualised in two different ways. In A) a median-joining network produced with PopArt shows two distinct haplogroups: kakī-type haplotypes A–D, and pied stilt-type haplotypes E–L. Haplotypes are coloured according to morphological species identification of individuals within that haplotype. Cross-hatched lines represent the number of variant sites differentiating haplotypes. Circle size represents the number of individuals sharing haplotypes. B) The same data was visualised with TempNet to compare diversity of modern and historical populations. Note, the networks differ between A) and B) as TempNet does not infer the presence of ancestral/missing haplotypes. Kakī-type haplotypes are highlighted in the blue box. Samples collected prior to 1960 were categorised as ‘Historical’, while those collected from the 1960s onwards were classed as ‘Modern’. Dark shading distinguishes the presence of modern haplotypes from the light shaded historical haplotypes. White circles represent haplotypes that were absent among the from a specific time period. Numbers within circles indicate the number of individuals with that haplotype. Hatch-marks represent the number of variant sites differentiating haplotypes.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/07de4e257256924be60002af.png"},{"id":70388731,"identity":"cdcad5fb-aadc-46ca-8846-a178fd468e81","added_by":"auto","created_at":"2024-12-02 17:27:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1770655,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/590b37cf-8075-45e1-9794-2eb7b66b21a2.pdf"},{"id":57626274,"identity":"7127b666-0c96-491e-906d-841ce2344bf9","added_by":"auto","created_at":"2024-06-03 14:03:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1968706,"visible":true,"origin":"","legend":"","description":"","filename":"ForsdicketalKakimtDNASupplementaryMaterial20240422.docx","url":"https://assets-eu.researchsquare.com/files/rs-4457261/v1/11c559c9c26ed9157b3ceaac.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maintenance of mitogenomic diversity despite recent population decline in a critically endangered Aotearoa New Zealand bird","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eConservation management programmes for intensively managed species generally aim to minimise the loss of genetic diversity over time to maintain evolutionary potential (Frankham et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, these programmes must often operate in lieu of knowledge of the impacts of population decline on genetic diversity prior to the initiation of conservation management. As genetic and genomic tools become increasingly available, management can then be fine-tuned to enhance conservation outcomes. One tool that can bridge this gap is paleogenomics, the sequencing of historical or ancient samples, revealing information about demographic processes and changes in genetic diversity from the past (Noonan et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Krause et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Miller et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTemporal comparisons of mitochondrial diversity can inform assessments of the impacts of anthropogenic threats, assessing the success of past conservation management while informing future management in the face of impacts of climate change of species distributions (e.g., Wilmshurst et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Obtaining complete mitogenomes from specimens in natural history collections through high-throughput sequencing (HTS) has become relatively efficient and cost-effective, adding to the genomic resources in the conservation toolbox (Forsdick et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePerhaps nowhere is the need for temporal comparisons of mitogenomic diversity for conservation as pronounced as in island ecosystems. One such ecosystem is Aotearoa New Zealand where geographic isolation has given rise to a taxonomically distinct avifauna with high rates of endemicity (Holdaway et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Checklist Committee (OSNZ) \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). There were 14 species of endemic shorebirds present at the time of human arrival (Order Charadriiformes; Trewick and Gibb \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) including kakī | black stilt (\u003cem\u003eHimantopus novaezelandiae\u003c/em\u003e; Holdaway et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The broadly-distributed (from the Philippines across to New Zealand) congeneric poaka | pied stilt (\u003cem\u003eH. himantopus leucocephalus\u003c/em\u003e; taxonomy following Checklist Committee (OSNZ) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)) self-introduced to Aotearoa probably in the 19th century, and now occurs in sympatry with kakī. To date, the sole estimate for the divergence time of kakī and poaka from a common ancestor is derived from sequence divergence at the mitochondrial control region, at approximately one million years ago (Chambers and Macavoy \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Wallis \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Kakī numbers declined during the 1900s due to anthropogenic habitat modification and the introduction of mammalian predators, while poaka numbers increased across the mainland to around 20,000 (Southey \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Riegen \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The contrasting demographic patterns for kakī and poaka are likely a result of their evolutionary history, with the same anthropogenic effects that contributed to kakī decline facilitating the expansion of poaka across the country (Pierce \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1984b\u003c/span\u003e). During kakī decline, hybridisation with poaka has occurred as a consequence of limited mate choice, resulting in the production of fertile hybrid offspring with intermediate plumage colouration between the completely black kakī and the black and white poaka (Pierce \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1984a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConservation management for kakī began in 1981 when the species had declined to approximately 23 wild adults (Pierce \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1984a\u003c/span\u003e). Early conservation efforts included a small number of dark hybrids. In contrast, contemporary management utilises only black kakī, aimed at maintaining species integrity (Reed et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Maloney and Murray \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Steeves et a. 2010; Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In combination with predator control and habitat restoration, genetics- and genomics-informed intensive management has seen kakī numbers increase to 169 wild adults in 2024. Nevertheless, kakī remain critically endangered, with the species primarily limited to Te Manahuna/the Mackenzie Basin in the central South Island of Aotearoa, a tiny fragment of their former distribution across both main islands of Aotearoa (Maloney and Murray \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; BirdLife International 2018).\u003c/p\u003e \u003cp\u003eGenetic and genomic resources have been used in the management of kakī to assess the extent and impacts of inbreeding (Hagen et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), hybridisation (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and to inform captive pairing decisions (Galla et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Specifically, a 291 bp fragment of the mitochondrial cytochrome \u003cem\u003eb\u003c/em\u003e gene and nuclear microsatellite markers have been used to assess the presence introgression resulting from hybridisation between kakī and poaka (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). While this and subsequent genomic analyses indicated that the species integrity of kakī had been maintained despite extensive hybridisation (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), there is no data on the historical diversity of kakī available to explore what may have been lost due to species decline, or maintained since conservation management began.\u003c/p\u003e \u003cp\u003eHere we compare mitogenome diversity of modern and historical kakī, poaka, kakī-poaka hybrids, and Australian pied stilts (\u003cem\u003eH. leucocephalus\u003c/em\u003e) as an outgroup. We make comparisons between kakī and poaka in terms of modern and historical mitogenome diversity providing insights into historical kakī diversity, the impacts of the recent population bottleneck, and a baseline of diversity which can be used to assess the effectiveness of conservation strategies.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sampling\u003c/h2\u003e \u003cp\u003eContemporary (2010\u0026ndash;2018) stilt samples (including kakī, poaka, kakī-poaka hybrids, and Australian pied stilts; n\u0026thinsp;=\u0026thinsp;32) were collected for whole genome (WGS) and/or mitogenome sequencing under relevant ethics approvals as part of aligned projects (Galla et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Galla et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Supplementary Table\u0026nbsp;1). In addition, 27 samples dating from 1843\u0026ndash;2011 were collected from stilt specimens in national museum collections (Supplementary Table\u0026nbsp;2). Catalogue information recorded these specimens as twelve kakī, twelve poaka, and three hybrids, although there were some discrepancies between catalogued and morphological species identification based on plumage following Steeves et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Supplementary Table\u0026nbsp;2). Specimens from both the North Island and South Island were included, along with one individual from Chatham Island (Rēkohu/Wharekauri, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Five specimens dated from the 1800s, with the earliest collected in 1843. Of the nine specimens from Te Papa Tongarewa \u0026ndash; Museum of New Zealand with no recorded collection dates, catalogue numbers in the range OR000001-OR008000 were used to classify specimens as having been collected and catalogued prior to the early 1950s (T. Schultz, Te Papa Tongarewa Science Collection manager, pers. comm.). Tissue from toe pads was collected from all skins and mounted specimens, and desiccated tissue collected from skeletal specimen MS11001, following protocols to avoid cross-contamination.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Primer design and mitogenome amplification from modern samples\u003c/h2\u003e \u003cp\u003eWe designed primers to amplify the mitogenome of birds included in this study in four overlapping sections using long-range PCR. To identify conserved regions that could be used as primer sites for amplification of stilt mitogenomes in the absence of a reference mitogenome for kakī, we constructed a conordinal proxy mitogenome from the consensus alignment of complete mitogenomes for six species within the Order Charadriiformes using MUSCLE v3.8.425 (Edgar \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) in Geneious\u0026reg; v11.1.5. This consensus included two mitogenomes from pied avocets (\u003cem\u003eRecurvirostra avosetta\u003c/em\u003e; NCBI Accession No.: KY623657.1 and NC_027420.1), one black-winged stilt (\u003cem\u003eHimantopus himantopus\u003c/em\u003e; NC_035423.1), one blackish oystercatcher (\u003cem\u003eHaematopus ater\u003c/em\u003e; AY074886.2), one Eurasian oystercatcher (\u003cem\u003eHaematopus ostralegus\u003c/em\u003e; NC_034237.1), and one long-billed plover (\u003cem\u003eCharadrius placidus\u003c/em\u003e; KY419888.1). We identified potential primer sites in conordinal conserved regions with Invitrogen\u0026trade; Primer3-based OligoPerfect\u0026trade; in the Thermo Fisher Cloud with default parameters, with target regions customised to produce four sets of primer pairs overlapping across the mitogenome. We required a\u0026thinsp;\u0026ge;\u0026thinsp;50 bp overlap between the four fragments, and assessed melting temperatures and potential for self- or cross-primer diimerization with Thermo Fisher Multiple Primer Analyzer.\u003c/p\u003e \u003cp\u003eFor each primer pair, following optimisation for amplification, the final 50 \u0026micro;L amplification reaction consisted of 10 \u0026micro;L 5✕ KAPA magnesium-free Long Range buffer (KAPA Biosystems), 1.75 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 0.3 mM dNTPs, 0.5 \u0026micro;M each of the forward and reverse primer, 0.5 U KAPA Long Range Hotstart Polymerase, and 2 \u0026micro;L 1:10 diluted template DNA. Thermocycling conditions were: initial denaturation of 94\u0026deg;C for 180 s, ten cycles of 94\u0026deg;C for 25 s, 54\u0026deg;C for 15 s, and 68\u0026deg;C for 60 s per expected kilobase (either 4 kb or 6 kb) of fragment length, followed by 25 cycles of 94\u0026deg;C for 25 s, 54\u0026deg;C for 15 s, and 68\u0026deg;C for 60 s per expected kilobase plus 20 s per cycle, with a final extension step of 72\u0026deg;C for 60 s per expected kilobase.\u003c/p\u003e \u003cp\u003eThe four primer sets were used to amplify the mitogenome from eight modern stilt samples (LR-PCR samples; Supplementary Table\u0026nbsp;1). Amplified products were prepared for direct sequencing and were also used as baits for hybridisation-capture of historical samples. Amplified products were purified using a QiaQuick\u0026reg; PCR Purification Kit (QIAGEN) with binding buffer (PB) equal to 5✕ the reaction volume eluted into 30 \u0026micro;L elution buffer. Purified products were quantified via Qubit, and visualised on a 1% agarose gel run at 80 V for 45 min. For sequencing, double-stranded barcoded libraries were produced following Kircher et al. (2012; see Supplementary Methods). Final DNA quantity was confirmed via Qubit. The pooled library was sequenced at the Otago Genomics and Bioinformatics Facility (OGBF) on one lane of an Illumina MiSeq Nano run with 2 x 250 bp paired-end sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 DNA preparation and sequencing from museum samples\u003c/h2\u003e \u003cp\u003eAll gDNA extractions and library preparations of museum samples were performed in a dedicated aDNA facility at the University of Otago using strict protocols to minimise contamination (Knapp et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). DNA was extracted using the QIAGEN DNeasy\u0026reg; Blood and Tissue kit (QIAGEN) spin-column protocol for tissue, with an overnight digestion step. gDNA was extracted in batches of 6\u0026ndash;7 samples. To assess potential contamination, one negative control was processed in parallel with each batch. gDNA was eluted into 50 \u0026micro;L elution buffer.\u003c/p\u003e \u003cp\u003eDouble-stranded libraries were produced for all historical samples and negative controls using in-solution hybridisation capture and paired-end sequencing on an Illumina platform (detailed in Supplementary Methods), following Greig et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Between each library preparation step, libraries were purified over a MinElute PCR Purification Kit (QIAGEN) according to manufacturer\u0026rsquo;s specifications, with two PE wash steps.\u003c/p\u003e \u003cp\u003eTo ensure successful hybridisation capture for all historical samples including kakī, poaka, and interspecific hybrids, a combined \u0026lsquo;Himantopus\u0026rsquo; mitochondrial bait set was prepared from one modern kakī (DNA1044) and one modern poaka (B40279) following a modified protocol based on Maricic et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) (see Supplementary Methods).\u003c/p\u003e \u003cp\u003eHybridisation of libraries to the modern DNA bait then followed Maricic et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) with modification (detailed in Supplementary Methods). Final prepared libraries were quantified via Qubit and pooled equimolarly prior to being concentrated through a MinElute spin column with a single PE wash step and eluted into 20 \u0026micro;L 0.1✕ TE. The fragment length distribution of the pooled library was assessed with a QIAxcel Advanced (QIAGEN) using a DNA High Resolution kit and QIAxcel ScreenGel\u0026reg; software. The final pooled library was diluted to 10 nM and sequenced on one lane of a MiSeq v2 with 2 ✕ 75 bp paired-end sequencing. Negative controls, having been processed in the same manner alongside individual samples, were pooled with a series of negative controls from other aDNA projects within the lab and sequenced independently from sample libraries (see Supplementary Methods).\u003c/p\u003e \u003cp\u003e2.4 Reference mitogenome assembly from whole-genome sequencing data\u003c/p\u003e \u003cp\u003eWe assembled a kakī mitogenome from whole-genome sequencing data of one kakī individual (DNA1914; Galla et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to use as a reference for sequence mapping and downstream analyses. Following sequence processing as described in Galla et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), whole-genome sequences from kakī DNA1914 were passed to NOVOPlasty v2.7.1 (Dierckxsens et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) with the black-winged stilt mitogenome (NC_035423.1) used as seed and reference to initiate assembly. Read length of 150 bp and an average insert size of 350 bp were specified. Mitogenome size was estimated based on published mitogenomes of confamilial species at 16\u0026ndash;20 kb, and an estimated \u003cem\u003ek\u003c/em\u003e-mer of 39 was used based on that for nuclear genome assembly (Galla et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Output contigs were manually assessed and overlapping regions between contigs were merged to produce a single contig. Whole-genome sequence data from DNA1914 was mapped against this draft mitogenome assembly to correct errors and produce a consensus mitogenome sequence. The resulting mitogenome was annotated using MITOS (Bernt et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Bioinformatic processing\u003c/h2\u003e \u003cp\u003eContemporary samples were demultiplexed by OGBF and sequence quality was confirmed via FastQC v0.11.5 (Andrews \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). To increase the sample size for kakī, whole-genome resequencing data for 24 additional modern kakī generated as part of an aligned project (Galla et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) were incorporated in analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary Table\u0026nbsp;5). We processed the modern stilt targeted mitochondrial data and modern kakī WGS data independently using a custom pipeline implementing AdapterRemoval v2.1.7, BWA v0.7.17 (Li and Durbin \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), Picard v2.18.0 (Picard Toolkit 2019), and SAMtools v1.7 (Li et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) to produce complete mitochondrial genomes for each individual.\u003c/p\u003e \u003cp\u003eMuseum samples and negative controls were processed independently of modern samples. Data were demultiplexed by OGBF, and sequence quality was confirmed via FastQC v 0.11.5. Data were then processed using a custom pipeline implementing AdapterRemoval, BWA, SAMtools, Picard, PALEOMIX (Schubert et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and MapDamage (J\u0026oacute;nsson et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Samples were retained for downstream analyses if coverage across the mitogenome exceeded 90%. Scripts associated with sample processing and variant calling for modern and historical samples are available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/natforsdick/Himantopus/tree/master/Mitogenomes\u003c/span\u003e\u003cspan address=\"https://github.com/natforsdick/Himantopus/tree/master/Mitogenomes\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Variant calling\u003c/h2\u003e \u003cp\u003eWe conducted variant-calling for the museum samples, modern LR-PCR, and modern WGS data sets independently. The reference mitogenome was indexed with SAMtools v1.9 \u003cem\u003efaidx\u003c/em\u003e, and a sequence dictionary created with Picard \u003cem\u003eCreateSequenceDictionary\u003c/em\u003e. GATK v3.8.0 (McKenna et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) \u003cem\u003eHaplotypeCaller\u003c/em\u003e was used to call variants for haploid mitochondrial data from individual sample BAM files (sorted, indexed BAMs with duplicates removed for modern samples, or the merged, sorted, rescaled BAM files with duplicates removed for historical samples). Joint genotyping based on the group variant files was then conducted with GATK\u0026rsquo;s \u003cem\u003eGenotypeGVCFs\u003c/em\u003e. SNPs and indels were independently identified using \u003cem\u003eSelectVariants\u003c/em\u003e and filtered using \u003cem\u003eVariantFiltration\u003c/em\u003e. Variants were filtered to exclude SNPs with quality by depth (QD)\u0026thinsp;\u0026lt;\u0026thinsp;2.0, Fisher Strand (FS; Phred-scale probability of strand bias)\u0026thinsp;\u0026gt;\u0026thinsp;60, MQ (root mean-square mapping quality)\u0026thinsp;\u0026lt;\u0026thinsp;40, and to exclude indels with QD\u0026thinsp;\u0026lt;\u0026thinsp;2.0, FS\u0026thinsp;\u0026gt;\u0026thinsp;200, or ReadPosRankSum \u0026lt; -20.0 (indels found near ends of reads more often than expected). All SNPs and indels were then recombined with GATK \u003cem\u003eRecombineVariants\u003c/em\u003e, with priority given to SNPs, and variants that had failed the filtering were removed with \u003cem\u003eSelectVariants\u003c/em\u003e. The group VCF generated was then used to produce individual VCFs with GATK \u003cem\u003eSelectVariants\u003c/em\u003e, excluding variants that failed to pass the filters. GATK \u003cem\u003eDepthOfCoverage\u003c/em\u003e was used to add coverage information for sample VCFs, and a custom R script was used to exclude sites with coverage\u0026thinsp;\u0026lt;\u0026thinsp;10✕ for all samples. Final FASTA files were generated from the filtered individual VCFs with GATK \u003cem\u003eFastaAlternateReferenceMaker\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Bayesian phylogenetic analysis\u003c/h2\u003e \u003cp\u003eTo estimate the time to the most recent common ancestor (TMRCA) for kakī and Australian pied stilts (the source population for poaka) and confirm their position within the Order Charadriiformes, we used BEAST v2.6.0 (Bouckaert et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to conduct Bayesian phylogenetic analyses in a two-phase approach (as in Morin et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In Phase I, we estimated TMRCA for stilts by implementing a time-calibrated phylogenetic analysis for all Charadriiformes. We randomly selected one kakī and one Australian pied stilt individual from among the modern samples and aligned these mitogenomes with forty Charadriiformes mitogenomes available on GenBank, along with the chicken (\u003cem\u003eGallus gallus\u003c/em\u003e; NCBI Accession No.: MH732978) and Australasian grebe (\u003cem\u003eTachybaptus novaehollandiae\u003c/em\u003e, Order Podicipediformes; NCBI Accession No.: EF532936) as outgroups using MUSCLE implemented in Geneious\u0026reg; with default settings (Supplementary Table\u0026nbsp;2). We identified a potential duplication in the mitogenome of kakī from 14,242 bp onwards based on anomalous coverage depth (see Results, Supplementary Fig.\u0026nbsp;3, Supplementary Material), so alignments were truncated to 1\u0026ndash;14,239 bp to exclude the anomalous region, avoiding many of the problems identified by (Sangster and Luksenburg \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Vega gull (\u003cem\u003eLarus vegae\u003c/em\u003e) mitogenome was excluded from analyses due to preliminary maximum likelihood analysis ascribing it as sister to Charadriidae rather than within the Laridae clade, consistent with previous research (Yang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo determine the appropriate site partitioning scheme, the alignment was passed to PartitionFinder2 (Lanfear et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) with four models assessed (GTR, GTR\u0026thinsp;+\u0026thinsp;G, GTR\u0026thinsp;+\u0026thinsp;I\u0026thinsp;+\u0026thinsp;G, and JC\u0026thinsp;+\u0026thinsp;I\u0026thinsp;+\u0026thinsp;G) using corrected AIC for model selection and implementing the Greedy algorithm (Guindon and Gascuel \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Lanfear et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Based on results from PartitionFinder2 (scheme AICc\u0026thinsp;=\u0026thinsp;296810.201, scheme lnL = -148244.294), coding genes were partitioned into first-, second-, and third-codon positions; tRNAs into a combined partition of the first- and second-\u0026lsquo;codon\u0026rsquo; positions and a partition with the third-\u0026lsquo;codon\u0026rsquo; positions, and sRNAs were also partitioned into a combined partition of the first- and second-\u0026lsquo;codon\u0026rsquo; positions and a partition with the third-\u0026lsquo;codon\u0026rsquo; positions of the combined sRNAs. In reference to the tRNAs and sRNAs, it should be noted that the \u0026lsquo;codon\u0026rsquo; partitioning is a limitation of PartitionFinder2, as unlike protein-coding genes, there is not an \u003cem\u003ea priori\u003c/em\u003e reason to expect codon-like variation in substitution patterns.\u003c/p\u003e \u003cp\u003eWe used BEAUti v2.6.0 to generate input files for BEAST, linking tree and clock models across all partitions. The Gamma site model (with five categories) was used across all partitions. Initially, all partitions identified by PartitionFinder2 were allocated a separate site model, with GTR (Generalised Time Reversible) defined as the substitution model. However, the failure of initial runs to reach stationarity due to over-parameterization led to all tRNA positions being included in a single partition and assigned the TN93 (Tamura and Nei \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) substitution model. GTR was used for all other partitions. The analysis was implemented with a relaxed log normal clock model to allow for among-lineage rate variation (Drummond et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), and using a calibrated Yule model so we could extract divergence time information (Heled and Drummond \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). To calibrate the analysis, we used log normal priors (mean in real space) based on fossil evidence (Smith \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2015\u003c/span\u003e): crown Charadriiformes (divergence of Charadrii from the other Charadriiformes) were given a mean and minimum (using offsets) age of 41.3 Mya, and the divergence of skuas (Stercorariidae) and auks (Pan-Alcidae) a mean and minimum age of 34.2 Mya. The standard deviation of the log-transformed distribution for both priors was 1.25. Log normal priors were given for both calibration points (Supplementary File 1). Two chains of 100\u0026nbsp;million states were logged at every 1000 states. The first 50% of each run was discarded as burn-in, and Tracer v1.7.1 (Rambaut et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) was used to confirm both runs had reached stationarity and convergence. To further assess convergence, maximum clade credibility trees were constructed for the two chains independently with TreeAnnotator v2.5.1, with a burn-in of 50%. Once convergence was confirmed, the two log and tree files were combined with LogCombiner v2.6.1 after removing the first 50% as burn-in and visualised with FigTree v1.4.3.\u003c/p\u003e \u003cp\u003eIn Phase II, a subsequent Bayesian analysis was conducted to assess congeneric relationships among kakī, poaka, hybrid individuals, and Australian pied stilts using parameter estimates obtained in Phase I to inform the analysis (Supplementary Files 1 and 2). Complete mitogenomes for 49 stilts comprising 34 kakī, 8 poaka, 5 hybrids, and 2 Australian pied stilts were aligned with MUSCLE using default settings in Geneious\u0026reg;. All individuals were classified by morphological identification rather than catalogue records, except for the stilt skeletal specimen MS11001 (plumage not available). Partitions were implemented as in the conordinal Bayesian analysis, including exclusion of non-coding sites (i.e., trimming the total alignment to a length of 14,239 bp). We implemented a relaxed log-normal clock with free rates (Drummond et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) as the Phase I conordinal analysis indicated rate variation between the kakī and pied stilt lineages (see Results, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary File 1). As for the conordinal analysis, clock and tree models were linked across all partitions. However, as multiple individuals were sampled per species, the Coalescent Bayesian Skyline tree model (Drummond et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) was implemented instead of the Calibrated Yule tree model. The tree height was given a uniform prior with lower and upper bounds (0.4157\u0026ndash;1.1633 Mya) based on the credibility interval for the divergence of kakī and Australian pied stilts determined from conordinal analysis (see Results, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplementary File 3). Two chains of 10\u0026nbsp;million states were logged at every 1,000 states. Outputs were assessed for stationarity and convergence, combined using a 10% burn-in, annotated and visualised as for the conordinal analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Maximum likelihood phylogenetic analysis\u003c/h2\u003e \u003cp\u003eFor comparison with the results of Bayesian analysis, we used maximum likelihood analysis to construct a phylogenetic tree for the Order Charadriiformes. First, we selected the optimal nucleotide-substitution model for the aligned mitogenomes using jModelTest v2.1 (Guindon and Gascuel \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Darriba et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), with 88 candidate models and 11 substitution schemes, using the Bayesian Information Criterion (BIC) to select the most appropriate model (determined as GTR\u0026thinsp;+\u0026thinsp;I\u0026thinsp;+\u0026thinsp;G, General Time Reversible model with I\u0026thinsp;=\u0026thinsp;proportion of invariable sites and G\u0026thinsp;=\u0026thinsp;Gamma distribution). We then used IQ-Tree v1.6.6 (Nguyen et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) to generate a maximum likelihood consensus tree with the nucleotide-substitution model selected, and ultrafast bootstrapping for 10,000 bootstraps (Hoang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). We visualised the consensus tree with FigTree v.1.4.3. To assess whether using the truncated mitogenomes resulted in any substantial differences in taxonomic relationships within the order, we compared the output trees with published Charadriiformes phylogenies (e.g., Baker et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Barth et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hu et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Haplotype network analysis\u003c/h2\u003e \u003cp\u003eTo assess haplotype diversity and differentiation among the sampled stilts, we produced Median Joining Networks of haplotypes in PopART (Bandelt et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Leigh and Bryant \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Traits blocks were created based on morphological species identification information (kakī, poaka, interspecific hybrids, Australian pied stilts). Temporal separation of haplotype networks based on statistical parsimony were visualised with TempNet (Prost and Anderson \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). We classified samples as \u0026lsquo;Historical\u0026rsquo; (catalogued prior to the early 1950s) or \u0026lsquo;Modern\u0026rsquo; (catalogued after the 1950s). Samples without recorded collection dates were designated \u0026lsquo;Historical\u0026rsquo; or \u0026lsquo;Modern\u0026rsquo; based on museum ID number. We selected the 1960 as the cut-off between historical and modern samples because no individuals were known to have been collected in the period 1960\u0026ndash;1975. Therefore, collection dates post-1950s correspond to the crux of the kakī decline towards the end of the 1970s. Individuals collected after 1975 are assumed to be representative of the diversity remaining among contemporary kakī.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Mitochondrial diversity and differentiation between species\u003c/h2\u003e \u003cp\u003eWe used DnaSP v6 (Rozas et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) to generate a point estimate of nucleotide diversity (\u0026#120587;) across the truncated mitogenome. The alignment was specified as a haploid mitochondrial sequence and the 14,239 bp region was regarded as a single locus for diversity estimates. Overall statistics for the number of haplotypes, haplotype diversity, nucleotide diversity, and related metrics were produced, and then each species was assessed independently. All Australian pied stilts and poaka individuals were grouped due to limited sample sizes. In addition, we assessed differences in haplotype and nucleotide diversity between species and the two time categories implementing a permutation test with 10,000 replicates via genetic_diversity_diffs v1.0.7 in R v4.2.2 (Alexander et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Following the visualisation of haplotype networks, we excluded individuals with haplotypes that did not correspond to their classified group (e.g., kakī skeletal specimen MS11001) and those with discordant catalogue-morphology classifications estimates to avoid overestimating species-specific diversity metrics due to inclusion of interspecific hybrids.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Historical sample morphological identification\u003c/h2\u003e \u003cp\u003eSpecies designation of museum specimens based on plumage morphology produced several discrepancies between catalogued species identification and morphological species identification. Four individuals recorded as poaka were identified as kakī based on plumage (MS10991, MS10992, MS10994, MS10995; Supplementary Table\u0026nbsp;2, Supplementary Methods). Two of these individuals with some white breast feathers were identified as sub-adult kakī. Kakī only gain full black plumage at their second summer, which may complicate identification of black and white sub-adults that often resemble poaka. One individual label as kakī (MS11004) was identified by plumage as a kakī-poaka hybrid, and one individual recorded as a kakī-poaka hybrid (MS11010) was classified as either poaka or a very light hybrid based on plumage. These discrepancies were primarily of specimens that entered museum collections prior to the categorisation of stilts by plumage as described by Pierce (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1984a\u003c/span\u003e). The remaining 19 specimens (excluding skeletal specimen MS11001 for which plumage classification was not available) had concordant morphological and catalogued species identifications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Mitogenome assembly from whole genome sequence data\u003c/h2\u003e \u003cp\u003eThe NOVOPlasty mitogenome assembler subsampled 32.01% of the input kakī DNA1914 whole genome sequence reads, totalling 134\u0026nbsp;million reads. Of these, 9,106 reads were aligned to the reference black-winged stilt mitogenome, with 8,062 subsequently assembled producing two contigs of length 15,754 and 1,849 bp, with 78✕ average coverage depth. Visual assessment of these contigs detected a region of overlap of 37 bp, and the two contigs were thus merged at this point to produce a single circular mitochondrial genome of 17,566 bp (Supplementary Fig.\u0026nbsp;1), within the expected length for Charadriiformes mitogenomes (~\u0026thinsp;16\u0026ndash;18 kb; Supplementary Table\u0026nbsp;6). Base composition was 31.91% A, 30.97% C, 13.22% G, and 23.82% T. The top match from the BLAST nucleotide database was to the black-winged stilt mitogenome, with 99% query cover and 99% identity, followed by 94% query cover and 93% identity to the confamilial pied avocet, the two closest relatives with available mitogenomes. Mitogenome annotation with MITOS identified 22 tRNAs, two rRNAs, and 13 protein-coding genes in the typical avian order (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sequencing outputs\u003c/h2\u003e \u003cp\u003ePrimers were designed for long-read amplification of four regions comprising the complete kakī mitogenome (Supplementary Fig.\u0026nbsp;1). An average of 254,904.5\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 56,661.93 sequence reads were produced per sample (Supplementary Table\u0026nbsp;3). Sequence yield for museum samples MS10993, MS11008, MS11012 and MS11013 was very low (\u0026lt;\u0026thinsp;1000 reads per sample; Supplementary Table\u0026nbsp;4) MapDamage results revealed the expected damage patterns for DNA extracted from historical samples (see Supplementary Fig.\u0026nbsp;2), consistent with the relatively recent ages of these samples being associated with less pronounced misincorporation frequencies than would be observed from ancient samples (Ginolhac et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSequencing of a pool of 29 aDNA negative controls (including 21 unrelated to this study) produced 1.3 Gb sequence data (Supplementary Table\u0026nbsp;8). Only one negative control, DNA-ve2 (sequence ID OG5003-13-0-1) had\u0026thinsp;\u0026gt;\u0026thinsp;50 reads mapped to the kakī mitogenome, with 16.23% of reads mapping. This resulted in 97.7% coverage of the mitogenome, at 27✕ depth. Given the evident contamination, the seven samples prepared in the batch associated with this negative were excluded from downstream analyses.\u003c/p\u003e \u003cp\u003eFor modern stilts where long-read amplification was utilised for library preparation, an average of 99.7% of the mitogenome was covered at a depth of 403.79✕ (Supplementary Table\u0026nbsp;3). For museum samples, where bait capture was utilised alongside library preparation, mitogenomes had\u0026thinsp;\u0026gt;\u0026thinsp;97% coverage for all samples except MS10993, MS11008, MS11012, and MS11013, which had coverage between 0-0.4✕ due to low sequence yield of these samples (Supplementary Table\u0026nbsp;6). Excluding these four samples, average coverage for the museum samples was 97.89% with an average depth of 233.89✕ across all samples. Processing of the WGS resequencing data from the 24 modern kakī samples resulted in 100% sequence coverage for all individuals, with an average depth of 250.93✕ (Supplementary Table\u0026nbsp;8). Mapping results identified a region from 14,239 bp onwards (including the NAD6 gene and the control region) with twice the mapping depth compared with the rest of the mitochondrial genome (Supplementary Fig.\u0026nbsp;3). We hypothesised this to represent a region of mitogenome duplication in kakī. This was supported by preliminary investigation using ONT long-read sequencing (see Supplementary Material section \u003cspan refid=\"Sec19\" class=\"InternalRef\"\u003e4\u003c/span\u003e). One consequence of this newly discovered region of duplication is that mean coverage depth of resequenced individuals, calculated across the entire mitogenome including the duplicated region, is likely inflated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Bayesian and maximum likelihood phylogenetic analyses\u003c/h2\u003e \u003cp\u003eBayesian phylogenetic analysis and maximum likelihood analysis on the mitogenome alignment of forty members of the Order Charadriiformes, with the Australasian grebe (\u003cem\u003eTachybaptus novaehollandiae\u003c/em\u003e, Order Podicipediformes) and chicken (\u003cem\u003eGallus gallus\u003c/em\u003e, Order Galliformes) as outgroups, and one representative kakī and Australian pied stilt (total n\u0026thinsp;=\u0026thinsp;44; Supplementary Table\u0026nbsp;6) produced trees with identical topologies (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), consistent with those of previous phylogenetic studies of the Order Charadriiformes using mitochondrial data (e.g., Baker et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The black-winged stilt (\u003cem\u003eH. himantopus\u003c/em\u003e) was sister to the combined clade of kakī and Australian pied stilts. Based on the Bayesian analysis, TMRCA for kakī and Australian pied stilts was approximately 0.750 Mya (95% highest posterior density (HPD)\u0026thinsp;=\u0026thinsp;0.416\u0026ndash;1.163 Mya), and the TMRCA for the \u003cem\u003eHimantopus\u003c/em\u003e clade was estimated at approximately 1.480 Mya (95% HPD\u0026thinsp;=\u0026thinsp;0.883\u0026ndash;2.214 Mya; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The divergence estimate for kakī and Australian pied stilts was more recent than all other congeneric species pairs within Charadriiformes, except those of plovers \u003cem\u003eCharadrius placidus\u003c/em\u003e and \u003cem\u003eC. alexandrinus\u003c/em\u003e (Charadriidae, TMRCA estimated at 0.118 Mya (95% HPD\u0026thinsp;=\u0026thinsp;0.041\u0026ndash;0.209 Mya)) and gulls \u003cem\u003eChroicocephalus brunnicephalus\u003c/em\u003e and \u003cem\u003eC. ridibundus\u003c/em\u003e (Laridae, TMRCA estimated at 0.473 Mya (95% HPD\u0026thinsp;=\u0026thinsp;0.240\u0026ndash;0.754 Mya)).\u003c/p\u003e \u003cp\u003eMinimal impacts of hybridisation were observed between the well-supported kakī and pied stilt clades in the congeneric Bayesian analysis (posterior probability\u0026thinsp;=\u0026thinsp;1, estimated divergence 0.663 Mya (95% HPD\u0026thinsp;=\u0026thinsp;0.416\u0026ndash;1.062 Mya; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with a single kakī sample found in the pied stilt clade, and a single poaka (and no Australian pied stilts) found in the kakī clade. One kakī-hybrid individual occurred in the kakī clade, with two occurring in the pied stilt clade, along with the skeletal sample originally recorded as kakī (MS11001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Diversification of lineages within the kakī and pied stilt clade appear to have occurred during a similar time period approximately 0.010\u0026ndash;0.193 Mya, potentially associated with the end of the Ōtira glacial period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Haplotype networks\u003c/h2\u003e \u003cp\u003eMedian-joining networks produced with PopART further confirmed differentiation between species, with 64 fixed difference found between the four kakī (A-D) and eight pied stilt haplotypes identified (E-L; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). One poaka (MS11006) and one hybrid (MS11002) were observed to have kakī-type haplotypes A and C respectively. The skeletal specimen (MS11001) was the only individual classified as kakī that was observed to have a pied stilt-type haplotype (F), indicating potential specimen misclassification. The remaining three hybrid individuals all had pied stilt-type haplotypes. Among the two Australian pied stilts, one had a haplotype shared by two poaka (G), while the other possessed a unique haplotype (E). When individuals were categorised as modern or historical, one kakī haplotype was present in historical samples that was not represented among the modern samples, while one haplotype was observed among modern samples but not captured among the historical samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Mitochondrial diversity metrics\u003c/h2\u003e \u003cp\u003eDiversity and differentiation metrics were estimated from 49 kakī, Australian pied stilts, poaka, and kakī-poaka hybrids across the extracted 14,239 bp of the mitogenome. In this region, 45 sites contained gaps or missing data, with 98 biallelic sites. Following classification of individuals by morphology and assessing haplotypes for discordance between catalogued species identity and haplotype identity, known hybrids and individuals with unknown/uncertain plumage were excluded, leaving 34 kakī and 9 pied stilts (including both Australian pied stilts and poaka) for interspecific comparison. Among kakī, there were 13 polymorphic sites, representing four unique haplotypes (\u003cem\u003eHd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4849, \u0026#120587; = 0.00034\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 0.00005), while among pied stilts, there were 19 polymorphic sites and six unique haplotypes (\u003cem\u003eHd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8889, \u0026#120587; = 0.00046\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 0.00006). There were an average of 4.870 nucleotide differences among kakī individuals and 6.500 among pied stilts, with an average of 74.261 nucleotide differences between the two species. Permutation tests revealed a significant reduction in haplotype diversity from historical to modern kakī, but no significant reduction in nucleotide diversity (Supplementary Table\u0026nbsp;9).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHere we produced the first annotated mitogenome assembly for kakī and used this as a reference for investigating mitochondrial diversity and divergence between kakī and Australian pied stilts. Analyses supported differentiation between these congeners, with divergence from a common ancestor estimated at 750,000 ya (95% HPD\u0026thinsp;=\u0026thinsp;0.415\u0026ndash;1.163 Mya) based on Bayesian inference. Utilisation of the mitogenome dataset revealed greater mitochondrial diversity among kakī than previously detected through single-gene mitochondrial analyses (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), with contrasts between the modern and historical samples here indicating that mitogenome diversity has been largely maintained among kakī despite the species decline and subsequent recovery.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Mitogenome assembly and identification of a potential mitochondrial gene duplication\u003c/h2\u003e \u003cp\u003eMitogenome assembly for kakī using NOVOPlasty produced an assembly of the expected length (16\u0026ndash;18 kb), with close similarity to the published mitogenome of the congeneric black-winged stilt. Mapping high-coverage whole-genome resequencing data to the assembled kakī mitogenome revealed a region of the mitogenome covered at twice the depth of the remaining assembly, suggesting a mitochondrial gene duplication collapsed during assembly due to the close similarity between the duplicated sequences. This hypothesis was confirmed with ONT long-reads that spanned the putative duplication (Supplementary Material section \u003cspan refid=\"Sec19\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Similar duplications have been observed in a wide range of avian species (Bucerotiformes (Sammler et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Passeriformes (Singh et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gibb et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Pelecaniformes (Cho et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gibb et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Procellariiformes (Abbott et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Eda et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Torres et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Psittaciformes (Eberhard et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Schirtzinger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Eberhard and Wright \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and Sulliformes (Morris-Pocock et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)), including the conordinal ruff (\u003cem\u003eCalidris pugnax\u003c/em\u003e; Verkuil et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Unresolved mitochondrial gene duplication may result in incorrect estimation of diversity and inference of phylogeny when apparent nucleotide differences are the result of differences between duplicated regions within an individual. Thus, detecting such regions is important to ensure accurate haplotype detection and diversity estimation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Stilt divergence dating and diversification of lineages\u003c/h2\u003e \u003cp\u003eHere we used mitogenomes to provide the first calibrated estimate of the timing of divergence for kakī and Australian pied stilts using Bayesian phylogenetic analysis. These results indicated a TMRCA for kakī and Australian pied stilts of approximately 750 Kya, 250Kya more recent than previous estimates, and one of the most recent estimates of divergence for a congeneric species pair within the order Charadriiformes. Such a recent split makes kakī and poaka highly susceptible to hybridisation, and so conservation efforts to maintain the species integrity of kakī are warranted. These data also contribute to our knowledge of the drivers of species diversification. Here, we find that deep lineage splits within both kakī and pied stilt lineages appear to correspond with the ending of the Eemian warm period (130\u0026thinsp;\u0026minus;\u0026thinsp;115 kya; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). More recent and extensive lineage expansion following the Last Glacial Maximum (26\u0026thinsp;\u0026minus;\u0026thinsp;20 kya), which greatly impacted much of Aotearoa\u0026rsquo;s biodiversity (as reviewed by Marske and Boyer \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), suggesting populations became isolated across different glacial refugia. Furthermore, the lineage diversity among poaka is suggestive of multiple invasions of pied stilts to Aotearoa, leading to greater diversity in comparison with kakī.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Comparison of kakī and poaka mitochondrial diversity and identification of mitochondrial introgression\u003c/h2\u003e \u003cp\u003eAlthough the maintenance of shared mitochondrial haplotypes in contemporarily isolated lineages could be a signature of recent shared ancestry, mitochondrial variation in these isolated lineages is expected to rapidly assort, leading to reciprocal monophyly within ~\u0026thinsp;2 generations (Hudson and Coyne, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Therefore, given the estimated divergence data between poaka and kakī, the few instances of mismatch between mitochondrial haplotype and plumage observed in this dataset are far more likely to be due to contemporary introgression. Although there are many known instances of hybridisation within the Order Charadriiformes (McCarthy \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), the northern and wattled jacanas (\u003cem\u003eJacana spinosa\u003c/em\u003e and \u003cem\u003eJ. jacana\u003c/em\u003e) are the only other species known to hybridise with one another among the species represented in the conordinal comparative phylogenetic analyses here (Miller et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These jacanas have a more distant estimated TMRCA (2.1362 Mya, 95% HPD\u0026thinsp;=\u0026thinsp;1.905\u0026ndash;4.969 Mya) than kakī and pied stilts (~\u0026thinsp;1.4 Mya), and hybridisation between these congeners across the range overlap in Western Panama has resulted in mitochondrial introgression, as assessed using a 651 bp region of the mitochondrial COI gene (Miller et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In comparison, potential mitochondrial introgression was observed in only a single poaka individual (MS11006). Only one individual classified as kakī showed evidence of introgression from poaka, and this was skeletal specimen MS11001, lacking plumage for confident morphological classification. This conforms with the pattern observed from nuclear genetic and genomic data (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen assessing haplotype diversity in stilts, four distinct haplotypes were identified among kakī doubling the number observed with single-gene mitochondrial analysis (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This supports our prediction that mitogenome analysis would reveal greater diversity than previously detected in single-gene mitochondrial studies. Nevertheless, we found relatively low haplotype diversity with historical small population size combined with a recent, severe bottleneck likely to have contributed to this low diversity (Pierce \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1984b\u003c/span\u003e; Forsdick \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHaplotype diversity among modern pied stilts was more than twice that of kakī, and nucleotide diversity was also considerably higher, despite the estimate of pied stilt diversity likely being an underestimate due to the relatively small sample size and limited sampling locations from its broad distribution. The greater number of haplotypes detected among pied stilts compared with the previous study (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) is due to the wider sampling distribution, including individuals from Australia and the North Island of Aotearoa, as well as South Island sites outside Te Manahuna.\u003c/p\u003e \u003cp\u003eHaplotype E is shared by an Australian pied stilt, a poaka, and a morphological kakī-poaka hybrid, which indicates that pied stilts and poaka have not yet become genetically differentiated at the mitogenome level. This may be due to a large, genetically diverse founding population arriving in Aotearoa relatively recently with little loss of diversity following arrival, or due to ongoing migration maintaining gene flow. The observation of one poaka with a kakī haplotype (individual MS11006 with Haplotype A) is most likely due to mitochondrial introgression resulting from hybridisation. This individual was a museum specimen collected prior to the early 1950s, demonstrating genetic evidence of hybridisation during this period in addition to the morphological evidence described by Pierce (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1984b\u003c/span\u003e). Similar mitochondrial introgression is observed in individual MS11002, a specimen with hybrid plumage collected in 1981.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Temporal changes in haplotype diversity\u003c/h2\u003e \u003cp\u003eSequencing and downstream analyses incorporating historical museum specimens were informative for investigating temporal changes in patterns of diversity. All except one kakī haplotype present in the modern population was detected in the historical population (Haplotype D), with one haplotype observed among historical samples that was not present among the modern individuals assessed (Haplotype B). As the sample of modern kakī represents\u0026thinsp;~\u0026thinsp;20% of the modern wild adult population, Haplotype B either occurs at very low frequency in the population, and thus is likely to be lost due to stochastic processes associated with small population size, or has already been lost.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Limitations of this study\u003c/h2\u003e \u003cp\u003eLimitations of this study include those inherent to using a single marker for analysis, and limited sample sizes, especially for historical material. Nevertheless, these results are consistent with estimates of nuclear diversity from nuclear microsatellite and whole-genome SNP data, and with analyses of introgression (Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), providing no evidence of introgression from poaka into kakī despite past hybridisation. Museum samples used here included all known historical kakī samples held in national museum collections, with the exception of a small number of fossil samples (Holdaway and Worthy \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Worthy \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e1998a\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003eb\u003c/span\u003e) and two kakī skins collected by early naturalist Sir Walter Buller, whose rarity and significance precluded their use in genomic analyses here.\u003c/p\u003e \u003cp\u003eWGS techniques successfully enabled the inclusion of mitogenome data from historical stilt samples in this study. Mitogenome sequencing can provide representative estimates of diversity and population structure in an efficient manner, with utility for questions involving taxonomic uncertainty, population differentiation, and interspecific hybridisation. The reduced costs associated with mitogenome sequencing, combined with the ability to include temporal assessments of diversity due to high-copy number facilitating capture even in degraded samples, ensure that the analysis of mitogenomes remains valuable for informing conservation management of non-model species.\u003c/p\u003e \u003c/div\u003e "},{"header":"Conclusions","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003cp\u003eIn this study we used mitogenomes to compare genetic diversity through time for kakī and Australian pied stilts (including poaka). We resolved the timing of divergence for kakī and Australian pied stilts at approximately 0.750 Mya and confirmed mitochondrial differentiation between kakī and poaka/Australian pied stilts, and no evidence of mitochondrial introgression from poaka/Australian pied stilts into kakī. We found previously undetected mitochondrial diversity among kakī. These results suggest that mitochondrial diversity may have already been limited prior to kakī decline, and provide evidence that kakī conservation management based on genetic data (Maloney and Murray \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Steeves et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hagen et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) has successfully maintained mitochondrial diversity. Overall these results suggest that active conservation management has assisted in helping maintain the distinct evolutionary trajectories of these two species, and, in combination with nuclear data (Forsdick et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), that genetics and genomics informed conservation management of kakī has achieved the goals of maintaining genetic diversity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by a Royal Society of New Zealand Rutherford Discovery Fellowship (MK), a Birds New Zealand Research Fund grant (NJF), and NJF was supported by a University of Otago Doctoral Scholarship and the Department of Anatomy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll samples were collected and held under appropriate permits. Samples from Australian black-winged stilts were provided under\u0026nbsp;the Royal Zoological Society of South Australia Specimen Licence Agreement (Import Permit: 2016061954). Samples from poaka held at Auckland Zoo were collected with approval from the Auckland Zoo Animal Ethics Committee. All modern kakī, poaka, or hybrid samples were collected under approval of the New Zealand Department of Conservation (DOC) Animal Ethics Committee (AEC #283), or as part of routine captive management (DOC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNJF, MK, and TES contributed to study conception and design. Samples were provided from the DOC Kakī Recovery Programme by LB. Data were generated by NJF. Analyses were performed by NJF and AA. The first draft of the manuscript was written by NJF, and all authors contributed to subsequent versions. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKakī are a taonga (treasured) species for Māori (the Indigenous Peoples of Aotearoa), and as such, genomic data derived from kakī are recognised as taonga in their own right. Due to the tapu (sacred) nature of these data, tikanga (customary practices, protocols, and ethics) determines how people interact how people interact with them. Consistent with FAIR and CARE data principles, the data presented here are hosted on a password-protected database at www.ucconsert.org/data/, and can be made available at the discretion of the kaitiaki of the iwi (tribes) and hapū (subtribes) associated with kakī. These data include the kakī mitochondrial genome assembly presented here, raw demultiplexed mitochondrial sequence reads for each individual, and the VCF files produced from sequence mapping for each of the resequencing, modern targeted, and historical museum sequencing sets. Scripts associated with the bioinformatic pipelines for this manuscript are detailed in the GitHub repository at https://github.com/natforsdick/Himantopus/tree/master/Mitogenomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to the mana whenua who are kaitiaki for kakī, namely Te Rūnanga o Ngāi Tahu, Te Ngāi Tūāhuriri Rūnanga, Te Rūnanga o Arowhenua, Te Rūnanga o Waihao, and Te Rūnanga o Moeraki. We are grateful to the Aotearoa New Zealand Department of Conservation\u0026rsquo;s Kakī Recovery Team, additional sample providers including Colin Miskelly and Alan Tennyson at Te Papa Tongarewa \u0026ndash; Museum of New Zealand, Matt Rayner at Auckland War Memorial Museum, Richard Jakob-Hoff at Auckland Zoo, David McLelland at Adelaide Zoo, and John Berry; sequencing provider the Otago Genomics Facility; and NeSI for access to computational resources. NJF is grateful to Olga Kardailsky, Anna Gosling, Catherine Collins, and Denise Martini for advice and assistance with lab work and bioinformatics, and to Peter Dearden, Mary Morgan-Richards, Paul Sunnucks, and Erica Hendrikse for helpful feedback on early versions of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbott CL, Double MC, Trueman JWH, et al (2005) An unusual source of apparent mitochondrial heteroplasmy: duplicate mitochondrial control regions in \u003cem\u003eThalassarche\u003c/em\u003e albatrosses. Molecular Ecology 14:3605\u0026ndash;3613. https://doi.org/10.1111/j.1365-294X.2005.02672.x\u003c/li\u003e\n\u003cli\u003eAlexander A, Steel D, Hoekzema K, et al (2016) What influences the worldwide genetic structure of sperm whales (\u003cem\u003ePhyseter macrocephalus\u003c/em\u003e)? 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The Aotearoa New Zealand endemic kakī | black stilt (\u003cem\u003eHimantopus novaezelandiae\u003c/em\u003e) is a critically endangered wading bird. Anthropogenic impacts contributed to kakī declining to ~\u0026thinsp;23 individuals in 1981 and promoted interspecific hybridisation with their more common congener, the poaka | pied stilt (\u003cem\u003eH. himantopus leucocephalus\u003c/em\u003e). Conservation management of kakī has resulted in the population increasing to 169 wild adults today. Here we use mitogenomes to enable comparisons of diversity between contemporary and historical (pre-1970s) stilts, and to understand the impacts of past interspecific hybridisation. We assemble a mitogenome for kakī and use this as a reference to facilitate downstream comparisons of mitochondrial diversity among kakī and poaka through time. Mitogenome haplotypes clearly differentiate kakī from poaka, and thus contribute to the behavioural, ecological, morphological and genetic evidence that conservation action has maintained the species integrity of this critically endangered bird. Furthermore, these results indicate conservation management aiming to maintain genetic diversity has been successful.\u003c/p\u003e","manuscriptTitle":"Maintenance of mitogenomic diversity despite recent population decline in a critically endangered Aotearoa New Zealand bird","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 13:55:05","doi":"10.21203/rs.3.rs-4457261/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-22T08:19:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-05T03:35:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51711775967154791505362088121770351395","date":"2024-08-05T00:23:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-02T12:40:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166352728920284867135159641151669951892","date":"2024-06-17T10:30:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-17T08:36:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-22T07:49:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-22T07:49:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Conservation Genetics","date":"2024-05-21T22:47:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"conservation-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"coge","sideBox":"Learn more about [Conservation Genetics](https://www.springer.com/journal/10592)","snPcode":"10592","submissionUrl":"https://submission.nature.com/new-submission/10592/3","title":"Conservation Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"46c3964a-5f6f-4952-a115-cea451abfc10","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T17:22:03+00:00","versionOfRecord":{"articleIdentity":"rs-4457261","link":"https://doi.org/10.1007/s10592-024-01661-3","journal":{"identity":"conservation-genetics","isVorOnly":false,"title":"Conservation Genetics"},"publishedOn":"2024-11-28 15:58:02","publishedOnDateReadable":"November 28th, 2024"},"versionCreatedAt":"2024-06-03 13:55:05","video":"","vorDoi":"10.1007/s10592-024-01661-3","vorDoiUrl":"https://doi.org/10.1007/s10592-024-01661-3","workflowStages":[]},"version":"v1","identity":"rs-4457261","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4457261","identity":"rs-4457261","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}