# Uncovering genetic population structure in the Endangered northern rockhopper penguin (Eudyptes moseleyi) across islands in the Southern Atlantic and Indian oceans

Heather Ritchie-Parker, Alex Ball, Trevor Glass, Jean-Marc Costanzi, Thierry Boulinier, Amandine Gamble, Muhammad Ghazali, Karen Keegan, Christophe Barbraud, Charly Bost, et al.

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Heather Ritchie-Parker, Alex Ball, Trevor Glass, Jean-Marc Costanzi, Thierry Boulinier, et al. Uncovering genetic population structure in the Endangered northern rockhopper penguin (Eudyptes moseleyi) across islands in the Southern Atlantic and Indian oceans. BMC Genomics, 2026, 27 (134), 10.1186/s12864-025-12487-9. http://dx.doi.org/10.1186/s12864-025-12487-9

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# Uncovering genetic population structure in the Endangered northern rockhopper penguin (*Eudyptes moseleyi*) across islands in the Southern Atlantic and Indian oceans

Heather Ritchie-Parker¹* ID, Alex Ball¹ ID, Trevor Glass², Jean-Marc Costanzi¹ ID, Thierry Boulinier³ ID, Amandine Gamble³ ID, Muhammad Ghazali¹, Karen Keegan¹, Christophe Barbraud⁴ ID, Charly Bost⁴, Caroline Bost⁴ ID, Jaimie Cleeland⁵ ID, Augustin Clessin³ ID, Maelle Connan⁶ ID, Karine Delord⁴ ID, Ben Dilley⁷, Tristan Glass², Christopher W. Jones⁸ ID, Peta Moore⁹, Kate Lawrence⁸, Fabrice LeBouard⁸, Alexis Osborne⁸, Richard A. Phillips⁵ ID, Norman Ratcliffe⁵ ID, Julian Repetto², Michelle Risi⁸ ID, Peter G. Ryan⁷ ID, Brandon Spolander¹⁰, Shannon Swain², Wayne Swain², Jérémy Tornos³ ID, Alex Whittle¹¹ ID, Helen Senn¹ and Antje Steinfurth⁸ ID

## Abstract

**Background** The northern rockhopper penguin (*Eudyptes moseleyi*) is a threatened species, listed as Endangered globally by the IUCN owing to rapid population decreases in the past, combined with a limited distributional range. Their breeding is confined to five islands in the central South Atlantic Ocean (Gough, Nightingale, Inaccessible, Alex (= Middle), and Tristan da Cunha) and two islands in the southern Indian Ocean (Amsterdam and Saint Paul). Non-breeding birds forage widely in these oceans and vagrant individuals have been recorded in the Falkland Islands/ Malvinas, South Africa, Kerguelen Archipelago, Australia, and New Zealand. The origins of these vagrant birds are largely unknown, and it remains unclear to what extent northern rockhopper penguins move between islands and oceans. Understanding connectivity between populations is essential for developing appropriate conservation strategies, especially as some populations may be at greater extinction risk than others.

**Results** Northern rockhopper penguins from the two oceanic basins are genetically distinct, with minimal evidence of migration between ocean basins. No substructure was detected within ocean island groups and although low, the level of migration between islands was sufficient to prevent genetic differentiation. Differential signatures of genetic diversity and inbreeding may also suggest some island populations are at higher risk of inbreeding depression.

**Conclusions** This study provides the first comprehensive genetic population structure analysis of the entire breeding range of the Endangered northern rockhopper penguin. This gives an unparalleled understanding of the connectivity within and between populations breeding in the Atlantic and Indian oceans, and highlights areas for further investigation. Knowledge of genetic structure and population dynamics can inform effective conservation

Full list of author information is available at the end of the article

<footnote>*Correspondence:
Heather Ritchie-Parker
hritchieparker@rzss.org.uk</footnote>
management by predicting a species' ability to adapt and remain resilient to local or global threats, including the increasing impacts of climate-driven changes in marine environments. Our results suggest that northern rockhopper penguins should be managed as two conservation management units to maximise the conservation of genetic diversity within the species and allow strategies to be developed that consider the different pressures affecting the populations in each ocean basin.

**Keywords** Penguin, Conservation, Connectivity, Gene flow, Migration, Management, ddRAD, mtDNA

**Background**

Northern rockhopper penguins (*Eudyptes moseleyi*) are classified as Endangered on the IUCN Red List [1] due to extensive population declines over the last century, including a > 50% decline in the Atlantic population between 1975 and 2005 [2]. The species breeds on seven islands; five in the Tristan da Cunha island group in the central South Atlantic Ocean and two in the Indian Ocean, with vagrants also reported in the Falkland Islands/Malvinas [3, 4], Kerguelen Archipelago [5], Australia [6], New Zealand [7] and South Africa [8]. The last population assessment suggests a global total of around 200,000 breeding pairs remain in the wild [1]. Most individuals breed in the Atlantic (~ 90%) and population sizes vary from ~ 3600 pairs on Tristan da Cunha (hereafter Tristan) to ~ 64,700 pairs on Gough Island [1]. Population trends vary between islands with Saint Paul showing an increase [9, 10], Amsterdam and Gough showing decreases [2, 9–11], and Alex (= Middle), Inaccessible, Nightingale and Tristan remaining largely stable [12].

Like many other seabirds, northern rockhopper penguins are threatened by changes in their marine environment but the exact causes of their population decline are not fully understood [1] and the reasons for their decline may be island-specific and influenced by local factors. Broadly, they are thought to be affected by the consequences of climate change including changes in sea surface temperatures causing the reduction and displacement of prey, as well as possible depredation by growing populations of fur seals (*Arctocephalus tropicalis*) [1, 13–15]. Some populations have been affected by catastrophic events such as the 2011 incident where the bulk carrier MS Oliva ran aground on Nightingale Island resulting in the spillage of 300,000 gallons of heavy fuel oil which affected penguins on Nightingale, Alex and Inaccessible Islands [16] and resulted in the deaths of thousands of penguins [17]. Population declines on Amsterdam Island have been attributed to recurrent outbreaks of avian cholera, with the bacterium *Pasteurella multocida* posited to be responsible for low breeding success and complete breeding failure between 2013 and 2016 [18]. A more recent survey on Amsterdam Island revealed an accelerated decline in the population, likely caused by a major fire at one of the primary breeding sites [11].

Conservation management of the northern rockhopper penguin requires these threats to be better understood

and addressed. Direct action has been taken to remove feral cattle (*Bos taurus*) on Amsterdam that may have indirectly affected the habitat due to grazing [19] as well as the eradication of predatory invasive species such as feral cats (*Felis catus*), brown rats (*Rattus norvegicus*) and house mice (*Mus musculus*) on Amsterdam Island [20]. Across all islands the birds are protected by law where populations in the Indian Ocean have been encompassed within the Réserve Naturelle Nationale des Terres Australes Françaises since 2006 [21, 22], and important foraging areas for northern rockhopper penguins in the Atlantic Ocean are embedded in the Tristan da Cunha Marine Protection Zone that was designated in 2020 [23]. Management plans have been implemented for many of the islands which include actions related to population monitoring, mitigation of the impact of human activities, and improving knowledge of the species to facilitate more effective management [24, 25]. In 2017, a species action plan was published to guide the ongoing conservation management of the species [26].

The northern rockhopper species action plan details key challenges in the conservation management of the species and outlines goals and objectives required for their recovery. A key objective is to fully understand the ecology and life history of northern rockhopper penguins by examining the causes of breeding failure, developing a better understanding of their diet and trophic ecology, and investigating connectivity between islands [26]. Connectivity is especially important in disparately located populations as it can be challenging to delineate management units [27]. Specifying suitable management units is particularly crucial when there is a source-sink dynamic between populations, as resources directed towards a source population will have a higher impact than those directed towards a sink population [28]. Understanding connectivity is also pertinent for identifying the risk of disease transfer between populations [29].

Previous genetic studies investigating the connectivity between populations of northern rockhopper penguins have been limited. The majority of these studies have focused on one island population in the Atlantic Ocean and one in the Indian Ocean. Studies that utilised nuclear data have shown low but significant levels of differentiation between birds on Amsterdam in the Indian Ocean and both Gough [30] and Nightingale [31] in the Atlantic Ocean. An investigation of connectivity between
Amsterdam and Nightingale using a small number of mitochondrial and nuclear loci produced conflicting results with one mitochondrial marker showing differentiation between the populations, but one nuclear marker showed no such differentiation [32]. The single study of connectivity between island populations in the same ocean showed no differentiation between birds on Gough and Nightingale in the Atlantic Ocean based on one mitochondrial and six nuclear markers [33]. No study to date has examined connectivity across the entire species' range with either mitochondrial or nuclear data.

Here we use molecular techniques to gain a better understanding of connectivity between island populations of northern rockhopper penguins to better advise on effective conservation management of the species. We utilised both mitochondrial markers (mtDNA) and double-digest Restriction site-associated DNA (ddRAD) to investigate connectivity between the islands of Tristan da Cunha (Alex, Gough, Inaccessible, Nightingale, and Tristan) in the central South Atlantic Ocean, and the islands of Amsterdam and Saint Paul in the southern Indian Ocean. Using these data, we (1) investigate patterns of gene flow within and between the islands in the Atlantic and Indian oceans, (2) estimate the extent and direction of migration between the island populations, and (3) determine the origin of vagrant individuals from western Australia and South Africa.

# Methods

## Sample collection and DNA extraction

A total of 181 northern rockhopper penguins were sampled at five islands in the central South Atlantic (n = 125) and two islands in the southern Indian oceans (n = 56). Other birds sampled were a single vagrant found off the coast of Perth, western Australia, and 12 penguins housed at the Two Oceans Aquarium in Cape Town, South Africa which were vagrants to South Africa or their captive-bred descendants. Full details of sample locations are available in Fig. 1 and Supplementary Table 1.

Blood samples were stored in either EDTA, ethanol, or fixed onto FTA cards. In all cases, samples were extracted using a QIAGEN® DNeasy Blood and Tissue kit following the manufacturer's standard protocol. DNA quantity was assessed using a Qubit 2.0 fluorometer and DNA quality was examined for the presence of high molecular weight DNA via electrophoresis on a 1% agarose gel.

## mtDNA sequencing and analysis

Samples were sequenced at two regions, a section of the mtDNA control region (CR) using the RockCR_F (5'-TGG CTT TTC TCC AAG ACC TG-3') and RockCR_R (5'-TGG CTC TGT GAA GAG CAA GA-3') primers [32] and a portion of the NADH dehydrogenase 2 (ND2) gene using the primers PEN_ND2_L5216_F (5'- GCC CAT ACC CCR AMA ATG-3') and PEN_ND2_H5766_R (5'- GGA TGA GAA GGC TAG GAT TTT KCG-3') [31] following the methods described by Frugone et al. (2018) [32] and Sorenson et al. (1999) [34], respectively. PCR products were visualised on a 1.5% agarose gel and

<figure><img src="image_3.png" /><figcaption>**Fig. 1** Map of sampling locations of northern rockhopper penguins. Red circles indicate penguins sampled at breeding colonies in the South Atlantic and southern Indian Ocean. Green squares indicate vagrants sampled from South Africa and western Australia. Insert photo shows a northern rockhopper penguin.</figcaption></figure>
purified using exoFAP before sequencing in both direc-
tions on an AB3130 XL sequencer (Eurofins, Germany).

Sequence quality was checked visually, primer
sequences were trimmed, and sequence reads were
assembled using Geneious Prime version 2025.0.1.
Consensus sequences were aligned using the default
parameters in MAFFT version 7.450 [35]. The resulting
sequences were then compared to determine the haplo-
type identity of each sample. Haplotype networks were
constructed in R using the ‘pegas’ package [36] for the
control region only, ND2 only, and a combined dataset.

ddRAD sequencing

A total of 134 individuals were prepared for ddRAD sequencing across two ddRAD libraries, each containing up to 96 individually barcoded samples. Inter- and intra-plate positive controls were used to check for sequencing quality and batch effects. Libraries were constructed using the method outlined by Peterson et al. (2012) [37], with slight adjustments as described in Dicks et al. (2023) [38], using SphI and Sbfl restriction enzymes. Each sample was barcoded using a 5–7 bp barcode before being pooled and size-selected (400–700 bp). Libraries were sequenced as 150 bp paired-end reads on an Illumina HiSeq 4000 system.

Sequenced libraries were demultiplexed in STACKS version 2.52 [39] using *process_radtags*. Samples with fewer than 250,000 reads were removed due to insufficient coverage. Read adapters were removed by trimming reads to 135 bp in length, and low-quality reads were removed using default parameters. Retained reads were quality checked using FastQC [40] before being aligned to the northern rockhopper penguin draft genome (GCA_010082375.1 [41]) using BWA-MEM version 0.7.17 [42] with default parameters. Unmapped reads were removed using Samtools version 1.10 [43].

SNPs were identified within STACKS using *gstacks*
with default parameters and only the first encountered
SNP was kept in instances where multiple SNPs were
identified in a single locus (--write-single-snp). Loci were
filtered using VCFtools version 0.1.16 [44] to have a mini-
mum read depth of 5, a minimum mean read depth of 15,
and a minor allele count of ≥ 3. Genotypes were also fil-
tered using PLINK 1.9 [45] where SNPs were excluded if
they had more than 20% missing genotypes (--geno 0.2),
and individuals were removed if they had more than 20%
missing genotypes (--mind 0.2). For population genomic
analyses, SNPs were further excluded if they were shown
to have high levels of linkage (r² ≥ 0.25) or if they were
significantly out of Hardy-Weinberg equilibrium (--hwe
0.001) in at least three populations, excluding the vagrant
individuals.

ddRAD analysis

Genetic diversity summary statistics were calculated for
each island population. Nucleotide diversity (π) was cal-
culated using PLINK v.1.9 [45] using only polymorphic
sites. Observed (H<sub>O</sub>) and expected (H<sub>S</sub>) heterozygosity,
and the inbreeding fixation index (F<sub>IS</sub>) were calculated
using the R package ‘hierfstat’ [46]. Weir and Cocker-
ham’s weighted F-statistic (F<sub>ST</sub>) was calculated for each
pair of island populations also using ‘hierfstat’ [46] and
re-sampled with 1000 permutations to generate estimates
of statistical significance.

Genetic structure was analysed using a Principal Com-
ponent Analysis (PCA) performed using the R pack-
age ‘adegenet’ [47], a maximum likelihood estimation of
individual ancestries in ADMIXTURE [48] using default
parameters for number of clusters (K) from one to seven,
and MCMC clustering based on co-ancestry inference
in fineRADstructure [49] with a burn-in of 10,000 and
1,000,000 iterations, retaining every 100th iteration. In
all instances the analysis was run on three datasets: all
individuals including vagrants, individuals sampled from
only the Atlantic Ocean, and individuals sampled only
from the Indian Ocean.

Migration estimates were calculated between the
Atlantic and Indian oceans, as well as among all island
populations using BayesAss v.3.0.5 [50]. For comparison
between the two oceans, all individuals were assigned
to either the Atlantic Ocean or the Indian Ocean popu-
lations and allele frequency, inbreeding coefficient, and
migration rate were set to 0.30, 0.50, and 0.1, respec-
tively. For analyses between islands all individuals were
assigned to their respective island population and allele
frequency, inbreeding coefficient, and migration rate
were set to 0.30, 0.70, and 0.1, respectively. Allele fre-
quencies, inbreeding coefficients and migration rates
were determined by parameter mixing tests where suit-
able values had an acceptance rate between 20% and
60%. In both instances two runs were conducted with a
1,000,000 burn-in and 10,000,000 iterations retaining
every 100th iteration. Duplicate runs were checked to
ensure convergence using Tracer [51].

Historical relationships between populations were
investigated using TreeMix [52]. Allele frequencies were
calculated using PLINK v.1.9[45] and transformed into
a suitable TreeMix input file with *plink2treemix.py* (http
://bitbucket.org/nygcresearch/treemix/downloads/). A
total of 10 unrooted runs were performed for each value
of migration events (M), ranging from one to seven. As
all migration event values explained > 99.8% of the vari-
ance, the best fit model (m = 3) was selected based on the
pairwise residual values.
# Results

## mtDNA sequencing and analysis

Both mitochondrial loci were successfully sequenced in all 194 individuals (Supplementary Table 2). A total of 417 bp were resolved for ND2 and 299 bp were resolved for CR. A total of 15 unique ND2 haplotypes and 76 unique CR haplotypes were identified, and when combined this resulted in 86 unique haplotypes combinations. The haplotype network comprising of both ND2 and CR showed a divide between the populations in the Atlantic and the Indian oceans, although some haplotypes were shared across oceans (Fig. 2). A single branch separates the haplotypes mostly characterised in Atlantic Ocean populations and those in the Indian Ocean suggesting an initial migration event from one ocean to the other. Given the dominance of haplotypes typically seen in Atlantic Ocean populations, alongside additional satellite branches that originate with Atlantic Ocean haplotypes and terminate with haplotypes only found in the

Indian Ocean, this suggests that Indian Ocean populations may have been colonised by individuals from the Atlantic Ocean. This split between oceans was more pronounced in the haplotype network comprised of just the CR locus, whereas the ND2 locus was dominated by a single haplotype with a small number of individuals possessing alternative haplotypes (Supplementary Fig. 1). In all instances, only one haplotype was shared across populations from both oceans. All vagrants sampled from South Africa clustered with the Atlantic Ocean individuals, except for one individual that clustered with birds from the Indian Ocean. The vagrant sampled from western Australia also clustered with individuals from the Indian Ocean.

## ddRAD sequencing

The number of reads sequenced per individual ranged from 9532 to 22,285,594 with an average of 6,958,427 reads. A total of six individuals did not reach the defined

<figure><img src="image_4.png" /><figcaption>**Fig. 2** Parsimony haplotype network based on fragments of the NADH dehydrogenase 2 (ND2) gene and the control region (CR). Each of the 86 haplotypes are represented by a circle, which are not scaled by frequency of occurrence, where strikes on branches indicate the number of mutational changes between haplotypes. Haplotypes are coloured by location with Atlantic Ocean populations represented in warm colours, Indian Ocean populations represented in blues, and vagrant individuals represented in greens</figcaption></figure>
minimum limit of 250,000 reads and were removed from downstream analysis. The remaining 128 samples were mapped to the northern rockhopper penguin genome before a further six individuals were removed during SNP QC. An additional five individuals from South Africa were removed due to high relatedness (parent-offspring) suggesting these were captive-bred offspring. After checking genotyping rate concordance between-and within-plate control samples, only the best genotyped repeated sample was retained. This resulted in a final dataset comprising 117 individuals and 3,538 SNPs, with an average per-locus coverage ranging from 28x to 1257x.

## ddRAD analysis

Nucleotide diversity (π) ranged from 0.185 in Amsterdam and Saint Paul to 0.198 in Nightingale, with an average of 0.191 (Table 1). Values were largely consistent across all populations although values in populations in the Indian Ocean were lower than those in the Atlantic Ocean. Observed heterozygosity (H<sub>O</sub>) ranged from 0.143 to 0.191, with an average of 0.170. All populations exhibited H<sub>O</sub> values that were lower than the expected (H<sub>S</sub>) values of heterozygosity, although the severity was variable across islands. Estimates of inbreeding (F<sub>IS</sub>) ranged from 0.039 in Amsterdam to 0.234 in Inaccessible with an average value of 0.120. In the Atlantic Ocean, low F<sub>IS</sub> values were reported at Tristan da Cunha (0.051) and Alex (0.067), suggesting that there is low to no inbreeding occurring. However, F<sub>IS</sub> values were markedly higher in the populations of Gough (0.219), Inaccessible (0.234), and Nightingale (0.181), suggesting that there may be some inbreeding occurring on these islands. No signature of inbreeding was detected in the Indian Ocean, where F<sub>IS</sub> values were low in both the Amsterdam (0.039) and Saint Paul (0.046) populations. It is important to note that these fixation indices may be affected by overall low sequencing coverage associated with reduced representation datasets [53] although the average per-locus

sequencing coverage reported here is sufficient to produce high quality genotyping.

All methods used to analyse population structure indicated differentiation between the penguins in the Atlantic and Indian oceans. Pairwise F<sub>ST</sub> values calculated between all island populations showed population differentiation ranging from -0.003 to 0.051 with the only significant values of pairwise F<sub>ST</sub> seen between populations in the Atlantic and the Indian oceans (F<sub>ST</sub> = 0.046, p ≤ 0.05; Table 1). In the Principal Component Analysis (PCA) the first axis split the samples between the penguins in the two oceans (Fig. 3) and the ADMIXTURE analysis also clustered the samples into Atlantic Ocean and Indian Ocean clades at k = 2 (Fig. 4). No further substructure was observed in any of the analyses, suggesting geneflow between the islands within each ocean (Fig. 4; Supplementary Fig. 2).

FineRADstructure corroborated the lack of further structure, showing that individuals only clustered by ocean (Supplementary Fig. 3). The vagrant individual from western Australia clustered with the Indian Ocean populations in all analyses, while all but one vagrant individual sampled from South Africa clustered with the Atlantic Ocean populations (Figs. 3 and 4A).

Migration estimates within and between the islands in the Atlantic and Indian Ocean were low overall (Fig. 5; Supplementary Table 3). Migration between the two identified genetic clusters of the Atlantic and Indian oceans was low in both directions with slightly higher migration from the Indian to the Atlantic Ocean (0.0178) than from the Atlantic to the Indian Ocean (0.0045) although the 95% confidence intervals included zero so it may also be possible that there is no gene flow between the oceans. Migration estimates between islands in the Atlantic Ocean ranged from 0.0118 (Gough to Nightingale) to 0.2228 (Tristan to Nightingale). Within the Atlantic Ocean, the largest number of migrants to other populations were from Tristan, and there was little immigration, although this may be an artifact of very low F<sub>ST</sub> (< 0.05) producing unreliable migration estimates [54].

<table><caption>**Table 1** Summary statistics for each population including nucleotide diversity (π), observed heterozygosity (H<sub>O</sub>±SE), expected heterozygosity (H<sub>S</sub>±SE), and inbreeding coefficient (F<sub>IS</sub>). The fixation index (F<sub>ST</sub>) between pairs of populations is also shown where an asterisk indicates significance at p ≤ 0.05</caption><thead><tr><th rowspan="2"></th><th rowspan="2">π</th><th rowspan="2">H<sub>O</sub></th><th rowspan="2">H<sub>S</sub></th><th rowspan="2">F<sub>IS</sub></th><th colspan="6">Atlantic</th><th colspan="2">Indian</th></tr><tr><th>F<sub>ST</sub></th><th>Alex</th><th>Gough</th><th>Inaccessible</th><th>Nightingale</th><th>Tristan</th><th>Amsterdam</th><th>Saint Paul</th></tr></thead><tbody><tr><td>Alex</td><td>0.187±0.003</td><td>0.184±0.003</td><td>0.204±0.003</td><td>0.067±0.007</td><td>-</td><td>0.000*</td><td>0.000</td><td>-0.003</td><td>0.001</td><td>0.048*</td><td>0.049*</td><td></td></tr><tr><td>Gough</td><td>0.194±0.003</td><td>0.150±0.003</td><td>0.204±0.003</td><td>0.219±0.007</td><td>-</td><td>0.007*</td><td>0.004*</td><td>0.005</td><td>0.005</td><td>0.049*</td><td>0.051*</td><td></td></tr><tr><td>Inaccessible</td><td>0.191±0.003</td><td>0.143±0.003</td><td>0.203±0.003</td><td>0.234±0.007</td><td>-</td><td>-</td><td>0.003</td><td>0.003</td><td>0.051*</td><td>0.051*</td><td>0.051*</td><td></td></tr><tr><td>Nightingale</td><td>0.198±0.003</td><td>0.161±0.003</td><td>0.205±0.003</td><td>0.181±0.006</td><td>-</td><td>-</td><td>-</td><td>0.000</td><td>0.047*</td><td>0.048*</td><td>0.048*</td><td></td></tr><tr><td>Tristan</td><td>0.197±0.003</td><td>0.191±0.003</td><td>0.204±0.003</td><td>0.051±0.005</td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.047*</td><td>0.049*</td><td>0.049*</td><td></td></tr><tr><td>Amsterdam</td><td>0.185±0.003</td><td>0.181±0.003</td><td>0.191±0.003</td><td>0.039±0.005</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.000</td><td>-</td><td></td></tr><tr><td>Saint Paul</td><td>0.185±0.003</td><td>0.180±0.003</td><td>0.191±0.003</td><td>0.046±0.005</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td></td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Fig. 3** Principal components analysis of 117 northern rockhopper penguins sampled from five islands in the Atlantic Ocean, two islands in the Indian Ocean, and vagrant individuals from South Africa and western Australia. Individuals are coloured by location with Atlantic Ocean populations represented in warm colours, Indian Ocean populations represented in blues, and vagrant individuals represented in greens. Eigenvalues showing the proportion of variance explained by each principal component are presented in the insert</figcaption></figure>

In contrast, Gough received migrants from all the other Atlantic islands with little emigration. In the Indian Ocean, considerably more emigration occurred from Saint Paul to Amsterdam (0.2539) than from Amsterdam to Saint Paul (0.0132).

The TreeMix phylogeny grouped the Atlantic Ocean islands except for Gough, the most distant population, and grouped the Indian Ocean islands together (Fig. 6). A large migration event from an ancestral population to the Atlantic Ocean, specifically to Alex Island, was identified; however, this may be an artefact of the small number of samples from that island. A smaller degree of reciprocal migration was also found between the two oceans, particularly between Inaccessible Island in the Atlantic Ocean and Saint Paul Island in the Indian Ocean.

## Discussion

This study provides the first comprehensive genetic population structure analysis of northern rockhopper penguins across all seven islands inhabited with breeding birds, and provides vital knowledge for conservation

management of the species. Here we show using molecular data that island populations in the Atlantic Ocean are genetically differentiated from those in the Indian Ocean, and that there is very little migration between the ocean basins. However, vagrant individuals found in Cape Town, South Africa have been shown to originate from both the Atlantic and the Indian Ocean populations suggesting there is potential for occasional mixing. No distinct substructure was shown between island populations within each ocean basin, although the extent of gene flow between these islands is unclear. These findings emphasise the need to fully understand connectivity between island populations for determining appropriate management units for effective conservation management strategies.

Several lines of investigation suggest the northern rockhopper penguin is split into two genetically distinct clusters grouped by ocean. Mitochondrial haplotype data showed an overall split between oceans with some shared haplotypes where the control region alone showed a rosette shape formed from individuals in the Atlantic Ocean with a single branch extending to haplotypes only
<figure><img src="image_6.png" /><figcaption>**Fig. 4** ADMIXTURE plots for all colonies and vagrant individuals at two (A) and three (B) clustering groups, only Atlantic Ocean colonies at two (C) and three (D) clustering groups, and only Indian Ocean colonies at two (E) and three (F) clustering groups. Each vertical bar represents one individual where the proportion of colour indicates inferred membership proportions to genetic clusters. The vagrants denoted as SA are from South Africa, and the va- grant individual denoted as A is from western Australia</figcaption></figure>

found in individuals from the Indian Ocean. This sug-
gests that the geologically younger islands of Amsterdam
and Saint Paul in the Indian Ocean (0.4 and < 0.2 MYA,
respectively) were colonised by individuals from the
Atlantic Ocean which has previously been hypothesised
as a colonisation route due to prevailing easterly surface
currents [55]. Nuclear data showed very clear segregation
based on ocean provenance which is likely maintained
due to the relatively small intra-ocean geographical dis-
tances between breeding islands (c. 0.25 to 400 km in the

Atlantic Ocean, and c. 100 km in the Indian Ocean) com-
pared to the large inter-ocean geographical distance (> 
5000 km). A limited amount of contemporary admixture
was detected alongside low levels of gene flow between
island groups suggesting that long-distance sporadic dis-
persal may still occur, although at a low level.

Notwithstanding, vagrant individuals were found to
have originated from colonies in both the Atlantic and
Indian oceans. South Africa is located between the two
ocean island groups and vagrants were found to have
<figure><img src="image_7.png" /><figcaption>**Fig. 5** Migration estimates between (A) the two identified genetic clusters in the Atlantic and Indian oceans, (B) all islands in the Atlantic Ocean, and (C) all islands in the Indian Ocean. Arrows show the direction of migration and ribbons are scaled by the relative amount of migration estimated</figcaption></figure>

originated from both ocean basins, with the majority originating from the Atlantic Ocean, as might be expected from the much larger Atlantic population [1] and prevailing easterly ocean current systems [55]. The vagrant penguin from western Australia originated from one of the islands in the Indian Ocean which is intuitive given their geographical proximity and that penguins from Amsterdam have been shown to forage longitudinally as far as the south-western coast of Australia [56]. Long ranging migration events have been previously documented where a vagrant northern rockhopper penguin found on the Kerguelen Archipelago (southern Indian Ocean) was genetically identified as having originated from the Atlantic Ocean island group situated over 6000

km away [5]. In addition, penguins from Amsterdam Island have been tracked as far as 2200 km away from the colony post-moult [57] suggesting they are capable of traversing large geographical distances. Nevertheless, long-distance migrations are likely to be infrequent as tracking of rockhopper penguins from Tristan and Gough indicates that the birds remain predominantly within the South Atlantic [57, 58]. No evidence of within-ocean substructure was detected but estimates of migration between islands were relatively low and uneven between populations. Within both ocean basins migration estimates between islands were low overall but even one migrant per generation should be sufficient to maintain gene flow [59]. The level and direction of migration
<figure><img src="image_8.png" /><figcaption>**Fig. 6** Bifurcating maximum likelihood tree produced by TreeMix with three migration events. The migration weight scale depicts the relative amount of migration with arrows indicating direction of migration. The SE scale bar represents 10 times the average standard error within the sample covariance matrix. Populations are coloured by location with Atlantic Ocean populations represented in warm colours and Indian Ocean populations represented in blues</figcaption></figure>

varied between islands with the most notable signature being considerably more migrants shown to move from Saint Paul to Amsterdam than vice-versa. While this signature contradicts a previous pattern showing penguins migrating in a south easterly direction from Amsterdam after breeding [56] it may, in part, be due to population expansion in the smaller island of Saint Paul (8 km²) which increased 95.6% between 1971 and 2018 [9, 10] coupled with the population decline on the larger island of Amsterdam (58 km²) where penguin numbers decreased ~ 80% between 1972 and 2015 (9) with a further decrease of 66% between 2015 and 2022 [11]. However, it is important to note that our migration estimates exhibited large 95% confidence intervals due to the low levels of differentiation between island populations.

These patterns of population structure are similar to those reported for some populations of northern rockhopper penguins and for many other penguin species. The low but significant levels of differentiation between ocean basin populations of northern rockhopper penguins calculated here are in line with FST values previously reported between the islands of Amsterdam in the Indian Ocean and Gough [30] and Nightingale [31] in the Atlantic Ocean, and the lack of differentiation between island populations in the same ocean basin was also previously reported between Gough and Nightingale in the Atlantic Ocean [33]. While strong signatures of population structuring have been observed in Humboldt (Spheniscus humboldti) [60] and gentoo penguins (Pygoscelis papua) [61], other penguin species including emperor

(Aptenodytes forsteri) [61, 62], king (A. patagonicus) [61], chinstrap (P. antarcticus) [61], Adélie (P. adeliae) [61] and southern rockhopper (E. chrysocome) [32, 63] exhibit low but significant differentiation between populations comparable to our results. Notably, southern rockhopper penguins were shown to differentiate into two major clades with no evidence of any further fine-scale structuring [63] similar to the patterns of differentiation seen here in the northern rockhopper penguins.

Genetic diversity and estimates of inbreeding varied among islands and between oceans. Estimates of genetic diversity were in agreement with previous values calculated for northern rockhopper penguins on the islands of Nightingale and Amsterdam [32] which showed their genetic diversity to be lower than values seen in the southern rockhopper and the eastern rockhopper (E. filholi) [32]. Genetic diversity was estimated to be lower for populations in the Indian Ocean compared to those in the Atlantic, which may be due to smaller population sizes in the Indian Ocean islands [2]. The overall trend of low genetic diversity may be a signature of loss of genetic diversity due to extensive population declines and genetic bottlenecks with the number of birds breeding on Gough Island estimated to have declined by 98% between 1955 and 2006(2, 9, 10) and global trends show an overall decline of > 50% decline in the Atlantic population between 1975 and 2005(2). This might also explain the evidence of inbreeding seen in several of these populations with Gough, Inaccessible and Nightingale showing the most pronounced signatures of inbreeding.

## Conclusions

Our results indicate that the northern rockhopper penguin populations breeding in each ocean basin should be managed as separate management units reflecting their clear genetic differentiation and geographical separation. By recognising them as distinct management units this provides a clear framework for assessing and mitigating risks specific to each ocean basin. As an example, the potential disease risk from Pasteurella multocida and Erysipelothrix amsterdamsensis on Amsterdam island [18, 64] is likely to only affect islands within the Indian Ocean. Nevertheless, continued monitoring and risk assessment is necessary as the populations on each island face a different suite of demographic and environmental pressures; differential signatures of inbreeding suggest some colonies are at higher risk of reduced genetic fitness where maintaining genetically healthy populations across all islands is imperative to the persistence of these colonies. Continued monitoring of demographic trends within management units and across all islands will be essential to identify emerging risks and guide species management decisions.
## Abbreviations

<table><tr><td>BWA</td><td>Burrow-Wheeler Aligner</td></tr><tr><td>CEFAS</td><td>Centre for Environment, Fisheries and Aquaculture Science</td></tr><tr><td>CR</td><td>Control Region</td></tr><tr><td>ddRAD</td><td>double-digest Restriction-site Associated DNA</td></tr><tr><td>DNA</td><td>Deoxyribonucleic Acid</td></tr><tr><td>EDTA</td><td>Ethylenediaminetetraacetic acid</td></tr><tr><td>FTA</td><td>Fast Technology for Analysis</td></tr><tr><td>IUCN</td><td>International Union for Conservation of Nature</td></tr><tr><td>MAFFT</td><td>Multiple Alignment using Fast Fourier Transform</td></tr><tr><td>mtDNA</td><td>mitochondrial DNA</td></tr><tr><td>MYA</td><td>Millions of Years Ago</td></tr><tr><td>ND2</td><td>NADH dehydrogenase 2</td></tr><tr><td>PCA</td><td>Principal Component Analysis</td></tr><tr><td>PCR</td><td>Polymerase Chain Reaction</td></tr><tr><td>RNN</td><td>Réserve Naturelle Nationale</td></tr><tr><td>RSPB</td><td>Royal Society for the Protection of Birds</td></tr><tr><td>RZSS</td><td>Royal Zoological Society of Scotland</td></tr><tr><td>SNP</td><td>Single Nucleotide Polymorphism</td></tr><tr><td>TAAF</td><td>Terres Australes et Antarctiques Françaises</td></tr></table>

## Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12864-025-12487-9.

Supplementary Material 1.

## Acknowledgements

All methods were carried out in accordance with the Environmental Research permit provided by the Government of Tristan da Cunha. This study was supported by the South African Department of Forestry, Fisheries and the Environment, the South African National Antarctic Programme and the Institut Polaire Français Paul Emile Victor (projects IPEV n°109, 394, 1151). The Comité de l'Environnement Polaire, and the Ministry of Research Ethics Committee approved protocols and activities undertaken in this study. This study is part of the long-term Studies in Ecology and Evolution (SEE-Life) program of the CNRS. We are grateful to the crews on the SA 'Agulhas II' and the MFV 'Edinburgh' for their logistic support. We would also like to thank the wider RZSS WildGenes team for support at various stages, including Jennifer Kaden, Elizabeth Heap and Magda Butowska.

## Authors' contributions

HRP analysed and interpreted all data, generated all figures, undertook data curation, and wrote the original draft manuscript. AB participated in conceiving and designing the study, undertook data curation and project administration, secured funding and was a major contributor in writing the manuscript. TreG participated in conceptualised the project and supported sample collection. ChaB, TB provided administrative support for sample collection on Saint Paul and Amsterdam islands. MG and KK undertook data curation and laboratory work. JMC analysed mitochondrial data and undertook data curation. HS participated in conceiving and designing the study. AS conceived and designed the study, collected samples on Tristan da Cunha and Alex, undertook data curation and project administration, secured funding and was a major contributor in writing the manuscript. ChrB, KD, CaB, MC, PGR, NR, RP, MR, CJ, AO, JC, KKL, FL collected samples. All authors read, reviewed and approved the final manuscript.

## Funding

Sequencing, storage and archiving of the study samples at https://www.cryoarks.org/ was supported via BBSRC grant BB/R015260/1. The work was also supported by the Truell Conservation Foundation and the BAS/NERC Official Development Assistance Atlantic Islands Project grant NE/R000 107/1. Studies in Amsterdam and Saint Paul were logistically and financially supported by the Institut Polaire Français Paul Emile Victor (IPEV projects 109 ORNITHO2E, PI C. Barbraud & 1151 ECOPATH, PI T Boulinier), Terres Australes et Antarctiques Françaises, and Zone Atelier Antarctique et Terres Australes (LTSER France, CNRS). The RZSS WildGenes team would like to thank the People's Postcode Lottery for their financial support via the Postcode Planet Trust.

## Data availability

All data used in this study are available via NCBI GenBank and the Tristan Data portal. Mitochondrial data are found in accession numbers PX216465-PX216555 and Supplementary Table 2. Raw ddRAD sequences are found in BioProject: PRJNA1309037 (BioSamples: SAMN50726567– SAMN50726683).

## Declarations

### Ethics approval and consent to participate

Animal ethics approval was given by the Royal Society for the Protection of Birds' Animal Ethics Advisory Committee for samples collected in the Tristan da Cunha island group, complying with the laws and regulations of the UK government and the guidance of the UK Animals (Scientific Procedures) Act 2013/63. Animal handling and sample collection on Saint Paul and Amsterdam islands were conducted under French Ministry of Research licence (APAFIS#10257-2018011712301381_v6) and TAAF Préfecture permits (A-2019-112, A-2019-127, A-2019-132, A-2019-). The Comité de l'Environnement Polaire, and the Ministry of Research Ethics Committee approved protocols and activities undertaken in this study on the Saint Paul and Amsterdam islands.

### Consent for publication

Not applicable.

### Competing interests

The authors declare no competing interests.

### Author details

¹RZSS WildGenes, Conservation Department, Royal Zoological Society of Scotland, Edinburgh, UK

²Tristan da Cunha Government, Conservation, Edinburgh of the Seven Seas, Tristan da Cunha, United Kingdom

³CEFE, CNRS, Université Montpellier, EPHE, IRD, Montpellier, France

⁴Centre d'Etudes Biologiques de Chizé (CEBC), UMR 7372CNRS-La Rochelle Université, Villiers-en-Bois, France

⁵British Antarctic Survey, Cambridge, UK

⁶Department of Zoology, Marine Apex Predator Research Unit, Institute for Coastal and Marine Research, Nelson Mandela University, Gqeberha, South Africa

⁷FitzPatrick Institute of African Ornithology, University of Cape Town, Cape Town, South Africa

⁸Centre for Conservation Science, The Royal Society for the Protection of Birds, Cambridge, UK

⁹Perth Zoo, South Perth, Western Australia

¹⁰Two Oceans Aquarium, Cape Town, South Africa

¹¹Cambridge Conservation Initiative, The Royal Society for the Protection of Birds, Cambridge, UK

Received: 13 August 2025 / Accepted: 23 December 2025

Published online: 06 January 2026

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