Genetic diversity and population structure of the spot-nosed monkey (Cercopithecus petaurista) of the Bijagós Archipelago, Guinea-Bissau, West Africa

Genetic diversity and population structure of the spot-nosed monkey (Cercopithecus petaurista) of the Bijagós Archipelago, Guinea-Bissau, West Africa | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Genetic diversity and population structure of the spot-nosed monkey (Cercopithecus petaurista) of the Bijagós Archipelago, Guinea-Bissau, West Africa Ivo Colmonero-Costeira, Saidil Lamine Djaló, Nelson Fernandes, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9213843/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Insular populations are typically more vulnerable to the loss of genetic diversity than their mainland counterparts and are often of conservation concern. The Bijagós Archipelago in Guinea-Bissau is a West African biodiversity hotspot and a recently designated UNESCO World Heritage Site. It hosts the westernmost populations of the spot-nosed monkey ( Cercopithecus petaurista ), a species thought to have been extirpated from mainland and threatened by anthropogenic activities. Here, we conducted a non-invasive DNA survey across five of the largest islands with known occurrences. We used eleven microsatellite loci and a fragment of the mitochondrial d-loop to estimate genetic diversity and population structure. Using 64 individual profiles we found that populations may have lost genetic diversity but were not depauperated. Genetic diversity was heterogeneous and populations were structured by island. Higher levels of historical gene flow between distant islands than between nearby ones suggest a pattern that is inconsistent with stepwise colonisation typical of island systems. Our study suggests a complex colonisation history which may have been influenced by human movements in the area. Canhabaque Island holds the most diverse populations and may support reintroductions in the mainland. We suggest conservation management should be carried out by island to safeguard long-term persistence. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Evolution Biological sciences/Genetics guenon islands genetic survey gene flow non-invasive genetics UNESCO Figures Figure 1 Figure 2 Figure 3 Introduction Insular ecosystems in general, are particularly vulnerable to global change and increasing anthropogenic disturbances such as habitat destruction and wildlife exploitation 1 , 2 . The genetic diversity of insular populations is often reduced as a consequence of a small number of founding individuals, exacerbated genetic drift promoted by isolation and limited carrying capacity, further increasing their risk of extinction 3 – 6 . Sequential colonisation models (i.e., the “stepping-stone model” 7 predict declining genetic diversity and increasing differentiation with distance from the mainland) 8 – 10 . However, insular systems often deviate from these expectations due to complex dispersal pathways, as well as historical and contemporary connectivity between islands 11 , 12 . Therefore, establishing baseline knowledge on genetic diversity, population structure and gene flow dynamics between islands is critical for interpreting the colonisation history and present population dynamics, and to inform conservation strategies adapted to the local context. The Bijagós Archipelago, located off the coast of Guinea-Bissau, West Africa, illustrates the disconnection between high biodiversity value and limited scientific knowledge. Locally known as Bemba di vida ( i.e. , “the barn of life”– in Guinea-Bissau creole), this biodiversity hotspot in West Africa has recently gained UNESCO Heritage Status (2025). This archipelago (ca. 900 km 2 of land, 88 islands and islets of continental origin 13 ) is permanently inhabited by local communities, predominantly from the Bijagó ethnic group, whose animistic belief system is thought to contribute to the preservation of the islands’ ecosystems 14 . A minimum of twenty-two mammals have been registered 15 , yet their local conservation status remains poorly characterised. Furthermore, little is known about the colonisation history of the archipelago by terrestrial mammals, which may have happened naturally as early as 15,000 years ago 13 or even human-mediated, for instance, after the arrival of the first Bijagó around the XI th Century 16 . The spot-nosed monkey ( Cercopithecus petaurista Schreber, 1774) of the Bijagós Archipelago is of great conservation importance regionally. Although globally classified as Near Threatened by the International Union for Nature and Conservation (IUCN) 17 , the species’ distribution is likely fragmented, and the populations of Guinea-Bissau and Senegal (Fongoli 18 ), are the only ones recently confirmed in this region of West Africa (Fig. 1 ). In Guinea-Bissau, the species has not been observed on the mainland for over three decades and is therefore thought to persist exclusively in the Bijagós Archipelago 19 – 21 , making these populations the currently westernmost known. Within the archipelago, the spot-nosed monkey occurs in a limited number of islands 19 (Fig. 1 ), where populations have reportedly declined during the last decades likely due to habitat degradation and targeted commercial hunting 20 , 22 . A previous comparative genomic study showed that the Bijagós Archipelago’s primate populations, including the spot-nosed monkey, Campbell’s monkey ( Cercopithecus campbelli , Waterhouse, 1838) and the green monkey ( Chlorocebus sabaeus , Linnaeus, 1766), display signatures typical of long-term isolation compared to their mainland counterparts 5 . These include reduced effective population sizes, lower genetic diversity and increased realised genetic load suggesting that overall, while not yet under extreme genetic threat (i.e., mutational meltdown), these insular populations would benefit from pre-emptive conservation strategies to promote their long-term viability 5 . However, these analyses were based on a limited number of representative individuals (N = 8 spot-nosed monkeys). In the particular case of the spot-nosed monkey, the lack of comprehensive archipelago-wide sampling prevents an accurate assessment of local levels of genetic diversity, population structure and gene flow, crucial to guide conservation efforts. In this study we aimed to estimate i) the genetic diversity and ii) the population structure within five of the largest islands of the archipelago, and iii) characterise the gene flow dynamics between islands and determine the main axes of genetic differentiation using nuclear microsatellite markers and mitochondrial DNA. We hypothesised that the populations would conform to some degree to the expected genetic patterns for insular systems. Specifically, we predict i) higher genetic diversity in islands closer to the mainland with decreased diversity towards the edges of the archipelago and ii) spatially structured differentiation by island, although episodic gene flow may occur through dispersal across the existing intertidal sandflat bridges between islands. Our overarching goal was to provide baseline genetic information that may inform management to improve directed conservation actions. Figure 1 Distribution of the spot-nosed monkey ( Ceropithecus petaurista ) in the Bijagós Archipelago, Guinea-Bissau. The species distribution area was drawn based on IUCN polygon (accessed in 2025). Distributions based on regional surveys conducted in Guinea-Bissau 19 – 21 are represented as hatched areas. The maps depict protected areas established in the Bijagós Archipelago: i) UCMPA, Urok Communitarian Marine Protected Area; ii) ONP, Orango National Park; iii) JVPMNP, João Vieira and Poilão Marine National Park. Photo of a pet infant adapted from Colmonero-Costeira et al. (2023) 20 . Illustrations copyright 2022 Stephen D. Nash / IUCN SSC Primate Specialist Group. Used with permission. Results Sampling During the 26 expedition days (January to June 2016), we collected a total of 378 faecal samples from ranging groups of spot-nosed monkey from the islands of Caravela (n = 89), Uracane (n = 78), Uno (n = 90), Canhabaque (n = 61) and Galinha (n = 60). Of those, a subset of 145 faecal samples was selected to be analysed based on freshness and location in order to optimise amplification success and minimise the inclusion of repeated individuals in the dataset. Nuclear and Mitochondrial Datasets We obtained a microsatellite loci dataset that included a total of 64 spot-nosed monkey individual profiles genotyped at 8–11 microsatellite loci across the five islands (Fig. 1 ). The dataset had an average QI of 0.88 and 5% missing data across loci. We did not detect the presence of null alleles and scoring errors due to stuttering or considerable allele dropout. Significant departure from Hardy Weinberg Equilibrium (HWE) was found for all the loci when samples across islands were pooled. When divided by island, only locus D12s372 in Canhabaque Island was found to have a significant departure from HWE. Thirty-five loci pairs were found in linkage disequilibrium in the pooled dataset and none when divided by island. These results suggest that population structure was the underlying cause of departures from HWE, and we included all samples and loci in downstream analyses. The PI sib using the full set of 11 loci was of 1.0x10 − 12 . Individuals could be effectively distinguished using a minimum combination of eight loci (PI sib < 0.001). The mitochondrial dataset contained HVRI sequences for 56 individuals with a final length of 290 bp. We did not find overly divergent haplotypes or other evidence indicative of the presence of nuclear copies of mtDNA in our dataset. Genetic diversity All eleven microsatellite loci were polymorphic with a mean number of alleles of 8.27 ± 0.57 and an expected heterozygosity (H E ) of 0.56 ± 0.05 (Table 1 ). Regardless of the chosen genetic diversity metric, Caravela and Galinha yielded lower genetic diversity than the remaining islands, particularly compared to Canhabaque. Overall, observed heterozygosity (H O ) was similar to expected heterozygosity (H E ) except for Caravela and Canhabaque which showed a heterozygosity deficit, and consequently positive inbreeding coefficients (G IS = 0.19 and 0.13, respectively; Table 1 ). We found a total of 22 unique HVRI haplotypes across 41 polymorphic sites. The overall estimated mitochondrial diversity was high (Hd = 0.92 ± 0.02; π = 2.33 ± 0.11 x10 − 2 ; Table 2 ). The population of Canhabaque Island was the most diverse (Hd = 0.92 ± 0.06; π = 1.58 ± 0.20 x10 − 2 ) and the population of Galinha the least (Hd = 0.40 ± 0.16; π = 0.40 ± 0.22 x10 − 2 ). The population of Galinha showed a mitochondrial diversity pattern that significantly deviated from a neutral pattern of evolution (Tajima’s D = -2.05, p < 0.05), revealing an excess of low frequency polymorphisms (Table 2 ). Table 1 Genetic diversity of the spot-nosed monkey across eleven microsatellite loci. Island (N) n A n E AR H O H E G IS Caravela (4) 2.45 ± 0.31 1.96 ± 0.23 2.30 ± 0.86 0.39 ± 0.08 0.49 ± 0.09 0.19 ± 0.10 Uracane (15) 4.09 ± 0.44 2.75 ± 0.23 2.70 ± 0.89 0.59 ± 0.09 0.55 ± 0.09 -0.08 ± 0.04 Uno (18) 4.36 ± 0.43 2.65 ± 0.23 2.75 ± 0.51 0.64 ± 0.05 0.61 ± 0.03 -0.05 ± 0.05 Canhabaque (12) 5.00 ± 0.41 3.37 ± 0.28 3.24 ± 0.69 0.60 ± 0.06 0.69 ± 0.06 0.13 ± 0.04 Galinha (15) 3.55 ± 0.39 2.10 ± 0.29 2.24 ± 0.72 0.45 ± 0.08 0.45 ± 0.08 0.00 ± 0.06 Overall (64) 8.27 ± 0.57 2.28 ± 0.20 8.11 ± 1.80 0.54 ± 0.04 0.56 ± 0.05 0.04 ± 0.03 N – number of genotype profiles; n A – alleles per locus; n E – effective number of alleles; AR – allelic richness; H O – observed heterozygosity; H E – expected heterozygosity; G IS – inbreeding coefficient. Population structure Mean pairwise F ST between islands using microsatellite data was 0.32 ± 0.09. The lowest pairwise F ST was found between the populations of Uno and Canhabaque ( F ST = 0.17), and the largest between Caravela and Galinha ( F ST = 0.46; Fig. 2 b). In the Principal Components Analysis (PCA), the first and second Principal Components explained 34.80% of the total variance and revealed four main groups: Galinha, Uracane, Uno and a fourth group formed by individuals from Caravela, Canhabaque and a few individuals from Uno (Fig. 2 c). In the STRUCTURE analysis, the starting point of the log-likelihood plateau and the first Δ K peak was obtained at K = 4 (Supplementary Fig. 1), followed by a maximum log-likelihood and a second ΔK peak at K = 5. The STRUCTURE results for increasing values of K ( K = 1 to 5) suggested the existence of hierarchical population structure (Supplementary Fig. 2). Similar to the PCA, at K = 4, populations within each island were considered independent genetic clusters except for the individuals of Caravela and Canhabaque which were clustered together but later segregated at K = 5 (Supplementary Fig. 2). All individuals showed high probability of assignment to each genetic cluster (Fig. 2 d). STRUCTURE runs aimed at testing the effect of unbalanced sampling and the inclusion of significantly related individuals showed no differences to the standard runs (Supplementary Fig. 3). The haplotype network lacked a central highly frequent haplotype and instead displayed high levels of reticulation (Fig. 3 b). The sampled haplotypes were private to each of the islands (Fig. 3 b). The most divergent haplotypes (≥ 12 mutational steps) were found between Uno and Galinha and dominated the variation along the first two dimensions of the Multidimensional Scaling (MDS) analysis (Fig. 3 c). Table 2 Mitochondrial genetic diversity of the spot-nosed monkey (290 bp fragment of the hypervariable region I). Island (N) S H Hd π D Caravela (4) 8 2 0.50 ± 0.27 1.38 ± 0.73 x10 − 2 -0.82 NS Uracane (11) 7 4 0.67 ± 0.12 0.58 ± 0.22 x10 − 2 -1.22 NS Uno (15) 13 4 0.62 ± 0.12 1.14 ± 0.35 x10 − 2 -0.05 NS Canhabaque (12) 15 8 0.92 ± 0.06 1.58 ± 0.20 x10 − 2 -0.35 NS Galinha (14) 8 4 0.40 ± 0.16 0.40 ± 0.25 x10 − 2 -2.06 * Overall (56) 41 22 0.92 ± 0.02 2.33 ± 0.11 x10 − 2 -0.93 NS N – number of sequences; S – number of polymorphic positions; H – number of haplotypes; Hd – Haplotype diversity; π – nucleotide diversity; D – Tajima’s D. Asterisks represent significant deviations from neutrality (NS p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001). Gene flow and geographic genetic differentiation The redundancy analysis (RDA) detected significant spatially-induced genetic differentiation. The polynomial trend-surface of the geographic coordinates explained 43.58% of the total variance (r 2 = 0.39, ANOVA-like F (4, 52) = 10.04, p < 0.001). The estimated effective migration surfaces (EEMS) model was optimised at 400 demes which displayed the highest r 2 between the observed and estimated pairwise genetic dissimilarities between and within demes (r 2 between demes = 0.78 and r 2 within demes = 0.72; Supplementary Table 2). The obtained effective migration surface that suggested genetic differentiation across the archipelago violates a strict IBD model (Fig. 2 e). Areas of low historical gene flow relative to the expected under strict IBD were found across open sea barriers (between Uracane and Uno) but also over potential dispersal corridors (e.g., sandbanks between Canhabaque and Galinha). On the other hand, higher historical gene flow than expected was found between Uno and Canhabaque, more than 40 km apart. Discussion The Bijagós Archipelago in Guinea-Bissau is a recognised biodiversity hotspot exemplified by the relict populations of the spot-nosed monkey, a species thought recently extirpated from the mainland 19 , 21 . The long-term viability of the terrestrial mammals would benefit from baseline genetic information to aid local conservation strategies 5 , 20 . Here, we assessed genetic diversity and population structure of the spot-nosed monkey using nuclear and mitochondrial markers across 80% of the known distribution of the primate in the country. According to expectations, genetic diversity was heterogeneous across the archipelago, and populations were highly structured between islands, suggesting low or no recent gene flow. However, we did not find a gradual decrease of genetic diversity and increase of population differentiation with distance from mainland (i.e, a pattern of strictly sequential colonisation of islands 8 , 9 ), suggesting a more complex colonisation history. Insular populations are often of special concern as they are more prone to the loss of genetic diversity compared to contiguous continental populations 3 – 5 . The populations of spot-nosed monkey at the Bijagós Archipelago do not appear to be depauperated of genetic diversity. Although direct comparisons of genetic diversity between taxa often reflect species-specific evolutionary histories and may be unprecise, in the context of the remaining primates of Guinea-Bissau. Spot-nosed monkey genetic diversity was within the range of mainland species as estimated using 8–21 autosomal microsatellite loci and mitochondrial control-region markers (Supplementary Table 3) 23 – 26 . According to previous genome-wide estimates, intermediate to high levels of genetic diversity for the spot-nosed monkey of the Bijagós archipelago is not unexpected. Whole genomes of individuals from Canhabaque and Caravela showed relatively high genetic diversity but reduced in comparison to a reference individual from mainland Africa of unknown origin 5 . Indeed, guenons are the most genetically diverse group of African primates 27 , 28 . The retention of high levels of genetic diversity suggest that the founding populations of the Bijagós Archipelago carried significant diversity from the source population. Genetic diversity was heterogeneous across the sampled islands which could be an effect of sequential colonisation events within archipelagos since serial population bottlenecks further reduce the genetic diversity of the founding populations 3 – 5 . Another common pattern that arises from serial colonisation is high population structure as a result of pronounced genetic drift, driven by the long-term isolation and cessation of gene flow both between the islands and with the mainland 8 . Accordingly, the multiple analysis of population structure showed strong genetic differentiation among spot-nosed monkey populations, clearly corresponding to island boundaries, suggesting little or no recent gene flow between islands. Even though potential corridors for dispersal currently exist between some of the islands (e.g., sandbanks between Galinha and Canhabaque), we did not find evidence of episodic gene flow. The population at Canhabaque was the most genetically diverse and occupied a relatively central position in both nuclear and mitochondrial ordination analyses. Additionally, the lowest pairwise F ST were consistently observed for all island pairs involving Canhabaque. Based on the expectation that genetic diversity decreases and genetic differentiation increases further from the mainland 8 – 10 , Canhabaque, one of the closest islands to the mainland (ca. 20 km), may represent one of the initial points of colonisation, and may have served as the source population for the remaining islands. Although evidence supports Canhabaque as one primary source population, the subsequent colonisation dynamics remain more difficult to disentangle. The EEMS analysis shows areas of increased and decreased historical gene flow, contradicting the existence of a smooth, IBD-like pattern of genetic differentiation, commonly found in stepping-stone models of colonisation 9 . For instance, lower estimates of effective migration than the expected were found between geographically proximate islands, Uno and Uracane, which are only separated by approximately 6 km. Other observed patterns that deviate from the theoretical expectations for strictly sequential colonisation were: i) the clustering of individuals from Caravela and Canhabaque in the PCA along with late segregation in STRUCTURE at K = 5, and ii) lower values of pairwise F ST between Uno and Canhabaque, accompanied by a corridor of high effective migration between the two islands. These findings suggest these two island pairs Uno-Canhabaque, and Caravela-Canhabaque, likely have a more recent shared ancestry compared to the remaining islands, despite being located at opposite ends of the archipelago up to 100 km of distance. Overall, these results could suggest that historical gene flow dynamics within the archipelago may not have been solely dependent on the expected stepping-stone-like processes seen in other insular systems, where there is a clear directional axis of differentiation (e.g., Herman et al., 2024 29 ). Humans have been suggested as the vector for the translocation of terrestrial mammals to and across the Bijagós Archipelago 16 . Suggested potential translocation timings include after the co-colonisation with the local ethnic group, the Bijagó 16 (XI th Century), or, during the Trans-Atlantic enslaved people-trade (XV th Century) similarly to other guenon species, namely the mona monkey ( Cercopithecus mona Schreber, 1774) of the islands of Grenada and São Tomé and Príncipe 30 , 31 , and the green monkeys ( Chlorocebus sp. Gray, 1870), of the Caribbean and Cape Verde 32 – 34 . Translocated populations can readily become differentiated from their source populations over the course of a few generations 35 – 37 , which in the case of the spot-nosed monkey of the Bijagós archipelago, may represent between 90 − 50 generations ago, considering a generation time of 11 years 17 and the starting time of the suggested human-mediated translocation events. Under this alternative hypothesis, the patterns of population differentiation between islands would be related to the human-mediated movements of animals rather than gene flow dependent on the proximity between islands and/or the formation of sandflats. We highlight that the mtDNA does not provide an exact reflection of the population differentiation patterns obtained in the microsatellite dataset, which is expected under (historical) sex-biased dispersal38. Low mitochondrial genetic diversity within islands but high overall diversity is concordant with historical female-philopatry found in male-mediated dispersal systems 24 , 38 , 39 , characteristic for the spot-nosed monkey 40 . However, considering the mutation rate of the mitochondrial d-loop (humans, 2.4 x 10 − 7 substitutions/site/year 41 ), island-specific haplotypes would not be expected neither in relatively short life of the Bijagós Archipelago (ca. 15,000 years ago 13 ) nor after the putative human-mediated dispersal 500–900 years ago. However, bearing in mind that changes in the allelic frequencies across this system is mainly driven by genetic drift 5 , it can be argued that the mitochondrial diversity currently present is a result of stochastic fixation and extinction of haplotypes 4 . The local conservation status of the spot-nosed monkey in Guinea-Bissau is thought to be particularly dire as the last viable populations of the primate are likely the ones of the Bijagós Archipelago. We found that genetic diversity is maximal in Canhabaque and lowest in Caravela. These results are coincidental with a study based on whole-genome re-sequencing data that suggested lower effective population sizes and genetic diversity, and increased inbreeding and realised genetic load for both Canhabaque and Caravela when compared to a mainland individual of unknown origin, being particularly severe in Caravela 5 . Overall, our results of heterogeneous genetic diversity across the archipelago suggest that extinction risk by genetic factors is uneven and likely higher in Caravela and other less diverse populations than in Canhabaque. Considering the strong population differentiation between islands, heterogeneous and private genetic diversity found in this work, we suggest that each island should be managed as an independent unit 42 . As such, future works should prioritise generating island-specific key demographic parameters, such as recent changes in effective population size over time, inbreeding and mutational load, and estimation of census size, density and habitat integrity. On top of increased extinction risk by genetic factors suggested by lower genetic diversity, most populations are also threatened by mortality caused by commercial wildmeat trade which is thought to be an increasing practice on the islands 20 , 22 . The activity is likely motivated by unstable income sources in the region, which may encourage young men to engage in this fast-returning activity 20 , 43 . The extent to which hunting impacts insular populations of the spot-nosed monkey is currently unknown. Nevertheless, demographic changes potentially related to the increase of deforestation and hunting pressure in the last decades have been reported for other primates in the country. These included high mortality 44 , a reduction of the effective population size 45 , 46 , and a disruption of the dispersal patterns due to behavioural modifications to perceived threat 23 , 47 . Our work also provides further emphasis that the insular populations are not genetically depauperate and could potentially act as reservoirs, creating the opportunity for future re-introductions of the species to mainland Guinea-Bissau. The populations of Canhabaque could be particularly relevant for these efforts as they have retained considerable extant genetic diversity (this study and Colmonero-Costeira et al. 2025 5 ). Considering the importance of the islands for the long-term conservation of the spot-nosed monkey in Guinea-Bissau, we stress that measures should be adopted to reduce currently known conservation threats and instate some degree of formal protection, perhaps in the form of a terrestrial protected area that integrates both conservation and socio-cultural needs of local inhabitants, in alignment with the UNESCO Heritage Site conservation action plan. More broadly, our study suggests that unexpected patterns of genetic differentiation among islands considering what would be expected based on natural processes may reflect complex colonisation histories. Further work may estimate the timing of colonisation, frequency of translocation events and assess the natural and human-mediated components of these processes using alternative methodologies that integrate local ecological knowledge, historical, and ecological data. Such a framework would not only benefit other terrestrial mammals with similar ecological requirements whose colonisation history remains unexplored. In doing so, these efforts could provide a previously unknown window into the bio-cultural history of this globally recognised biodiversity hotspot. Methods Study site Our study site comprises five of the largest islands of the Bijagós Archipelago - Caravela, Uracane, Uno, Canhabaque, Galinha where spot-nosed monkeys were reported to occur 19 , 21 . The study area represents 80% of the species estimated distribution in Guinea-Bissau (Fig. 1 ). Of the sampled islands, Cambanhaque and Galinha Islands are closer to the mainland (ca. 20 km). Extensive intertidal sandflats connect some of the islands during low tides, namely Canhabaque and Galinha, but the great majority are surrounded by the deep-sea waters (Fig. 1 ). All islands are permanently inhabited by local communities distributed by small villages 14 . In most islands, the local economy is based on subsistence agriculture, fishing and hunting 14 , 20 , 48 . Ecotourism is present in Caravela. Sampling We carried out expeditions between January and June 2016. Areas frequently used by primates were identified by the local communities and the locations were subsequently visited by the team. Whenever a social group was detected, we collected faecal samples non-invasively, with minimal disturbance. To avoid the collection of multiple samples from the same individual, we only collected samples that spread more than 2 m apart. All the collected faecal samples were georeferenced using a Geographic Positioning System (GPS) device. Other types of metadata were collected during sampling, such as the freshness of samples and number of individuals in the group (when observed). The preservation of the faecal samples followed the two-step protocol in which samples are immersed in 96% ethanol for 24/48 hours and then transferred to a falcon tube containing silica gel until extraction 49 . Additionally, tissue samples were collected from carcasses of hunted individuals found opportunistically in local villages. These samples were preserved in 99% ethanol. Samples were stored at room temperature while in Guinea-Bissau after which samples were transported to Portugal and stored at -20 ℃ until DNA extraction. A sub-set of faecal samples were selected to be molecularly analysed, based on freshness and spatial distribution. DNA extraction Faecal samples were extracted using the QIAamp DNA Stool Mini Kit (Qiagen®, Germany) with few modifications to increase DNA yield as described in Ferreira da Silva et al. (2014) 23 . DNA from ten tissue samples was extracted using the DNeasy Blood & Tissue Kit (Qiagen®, Germany) according to the manufacturer’s protocol. DNA amplification Samples were genotyped using a panel of 11 autosomal microsatellite (STR) loci (Supplementary Table 1). The microsatellite loci were human-derived but known to cross-amplify in other Cercopithecidae species [Guinea baboon ( Papio papio Desmarest, 1820) 23 , king colobus ( Colobus polykomos Zimmermann, 1780) 24 , and the western red colobus ( Piliocolobus badius temminckii Kuhl, 1820) 24 ]. The microsatellite loci were amplified in three multiplex Polymerase Chain Reactions (PCRs) except for locus D7s503 (Supplementary Table 1). Each PCR reaction contained 1X MyTaq™ Mix (Bioline, UK), 0.6 µL of primer mix, 2 µL of DNA extract and molecular grade water for a final volume of 6 µL. The final concentration for each fluorescence-labelled primer pair varied across the microsatellite panel (Supplementary Table 1). The PCR reactions were performed in a T100™ 96 Well Thermal Cycler (Bio-Rad, USA). Cycling conditions started with a Taq activation step at 95 ℃ for 15 minutes, followed by 40 cycles of denaturing step at 94 ℃ for 30 seconds, annealing at 57–59 ℃ for between 40 and 90 seconds and extension at 72 ℃ for between 40 and 90 seconds (Supplementary Table 1). The PCR cycles ended with a final extension of 30 minutes at 72 ℃. The PCR products were analysed on a 3130xl automated sequencer (Applied Biosystems™, USA) using GeneScan™ 500 LIZ™ size standard (Thermo Fisher Scientific, USA). Alleles were scored using GeneMapper v4.0 (Applied Biosystems™, USA). A fragment of the hypervariable region I (HVRI) of the mitochondrial d-loop with an in silico predicted size of 388 bp was amplified for unique individuals (see below) by PCR using primers LCERCOHVRI (5’ CGTGCATTACTGCTAGCCAAC 3’) and HCERCOHVRI (5’ GGGATATTGATTTCACGGAGGA 3’) 19 . The PCR reactions were conducted in 10 µL of total volume, containing 1X MyTaq™ Mix (Bioline, UK), 0.2 µM of forward and reverse primer, 2 µL of DNA extract and 2 µL molecular grade water for a final volume of 10 µL. The PCR reactions were performed in a T100™ 96 Well Thermal Cycler (Bio-Rad, USA). The cycling conditions started with a Taq activation step at 95ºC for 15 minutes, followed by 40 cycles of denaturing step at 94ºC for 30 seconds, annealing at 58ºC for 30 seconds and extension at 72ºC for 30 seconds. The final cycling step corresponded to a final extension at 72ºC for 15 minutes. The amplified products were purified by enzymatic hydrolysis of nucleotides using 1 µL (1/4 ratio) of Exonuclease I (20 UµL-1) and FastAP (1 UµL-1) (Thermo Fisher Scientific™, USA). Fragments were sequenced on a 3130XL automated sequencer (Applied Biosystems™, USA). Data quality control Microsatellite loci from non-invasive samples are prone to systematic and stochastic errors such as null alleles (NA), false alleles (FA) and allelic dropout (ADO) 50 , 51 . To circumvent this limitation, the number of PCR repeats and the number of times an allele needs to be scored to obtain 95% confidence in genotypes was estimated using the simulation software GEMINI v1.3.0 52 . We estimated that the consensus genotype obtained from four independent PCR repeats across loci would produce 95% confidence genotypes (please see the Supplementary Information for additional details on consensus genotype calling). The Quality Index (QI) 53 was used to assess the reliability of consensus genotypes. We only included samples with a QI above 0.55 in the final dataset. The threshold of missing data across loci for a genotyped individual was defined based on the minimum combinations of loci that minimises the probability of identity between siblings (PI sib ) estimated using GenAlEx v6.5 54 . Duplicate genotype profiles were detected by identity analysis in Cervus v3.0.7 55 . Profiles differing by a single heterozygous locus were considered duplicates and were removed from the final database. The existence of null alleles and scoring errors due to stuttering or considerable ADO was checked using Micro-Checker v2.2.3 56 . Departures from HWE per locus and pairwise linkage disequilibrium (LD) were calculated using GENEPOP v4.7.5 57,58 . Mitochondrial DNA sequences were manually corrected using Geneious v4.8.5 59 . A consensus sequence was obtained by aligning the forward and reverse sequences. Additionally, all polymorphic positions (i.e., substitutions, insertions, and deletions) were checked by eye. All sequences were aligned using Geneious’ in-built algorithm. The final alignment was trimmed to the length of the shortest sequence. To confirm the species identity, mtDNA sequences were compared to an in-house DNA barcoding reference database 19 using the NCBI’s BLAST+ (Basic Local Alignment Search Tool) command line tools 60 . Genetic diversity We estimated the number of alleles per locus (n A ), the effective number of alleles (n E ), unbiased expected heterozygosity (uH E ), the observed heterozygosity (H O ), and the inbreeding coefficient (G IS ) per island and for the overall dataset using GenoDive v3.06 61,62 . Additionally, the rarefied allelic richness (AR) across loci was estimated using the hierfstat R package v0.5-11 63 . The number of haplotypes, haplotype diversity (Hd), and nucleotide diversity (π) and Tajima’s D was estimated using DNAsp v6.12.03 64 . To assess relationships between haplotypes, haplotype networks were constructed based on statistical parsimony using TCS v1.21 65 visualised using tcsBU 66 . To describe genetic variation, we also used Multidimensional Scaling analysis (MDS) on pairwise genetic distances between haplotypes. Genetic distances were calculated based on the best-fit model of molecular evolution which was identified using ModelFinder 67 restricted to the models available in ape 5.7.1 R package 68 . The model TN93 was selected based on the Bayesian Information Criteria (BIC). The MDS analysis was conducted using the vegan v2.6.4 R package 69 . R packages and statistical analysis were run under R v4.2.2 70 coupled with RStudio v2023.06.2 + 561 71 . Population structure Estimates of pairwise fixation index ( F ST ) between islands as estimated using microsatellite loci were obtained using hierfstat v0.5-11 R package. Genetic variation between samples was visualised by Principal Components Analysis (PCA) using adegenet v2.1.10 72 and vegan v2.6.4 R packages. Missing genotyped loci across individual profiles were replaced by the mean allelic frequencies. Allelic frequencies were left unscaled. Additionally, population structure was assessed using STRUCTURE v2.3.4 73 . STRUCTURE was run using the admixture model with correlated allele frequencies 74 . Ten independent runs were conducted with inferred genetic clusters ( K ) varying between one to eight, a burn-in period of 100,000 steps followed by 1,000,000 MCMC iterations. The most likely number of K was estimated using the log likelihood of the data 73 , and the degree of change of log likelihood between successive clusters (∆ K ) 75 . The individual probability of assignment to each genetic cluster (Q) across multiple K values were aligned across runs using the CLUMPP greedy algorithm 76 . All post-processing procedures of the STRUCTURE results were performed using pophelperShiny R package 77 . Two potential sources of bias were signalled a priori in this dataset, unbalanced sampling between putative structured populations 78 , and the inclusion of highly related individuals typical to non-invasive genetic datasets from arboreal primate species 24 . To test the effect of an unbalanced sample size between sampling locations in STRUCTURE, an alternative set of ancestry prior settings was employed 78 . This alternative set of priors included estimating the individual values of alpha for each genetic cluster with initial alpha set to 1/ K (expected), and uncorrelated allele frequencies between clusters 78 . To inspect whether population sub-structure was being detected due to the presence of highly related individuals, STRUCTURE was re-run with a reduced dataset where one individual from each significantly related dyad was removed. To assess relatedness between individuals, we used the Queller and Goodnight’s estimator 79 within islands in Kingroup v2_101202 80 . The contribution of geographic locations on genetic differentiation was estimated by combining redundancy analysis (RDA) and trend-surface analysis using vegan v2.6.4 R package. Redundancy analysis combines an ordination method (PCA) with multiple regressions of independent predictors, here a polynomial trend-surface of the geographic locations 81 . For the matrices of geographic variables, we generated a third-degree orthogonal polynomial trend-surface of the geographic coordinates ( long, lat, long * lat, long 2 , lat 2 , long 2 * lat, long * lat 2 , long 3 , lat 3 ). Third-degree orthogonal polynomials allow modelling of linear gradients and other more complex patterns over the trend-surface 81 . A forward selection procedure was applied to prevent a possible over-fitting of the multiple regression. We selected a stringent significance level of 0.01 and the adjusted determination coefficient ( R 2 adj ) as stopping criteria 82 to account for the increased type-I error rates due to multiple testing. Subsequently, the variance inflation factor (VIF) of the variables was estimated, and highly collinear variables (VIF > 5) were removed in a stepwise manner. After conducting the selection procedure, the geographic variables long, lat, long * lat, long 2 , were included as explanatory variables. Statistical significance of the multiple regression models and each of the resulting canonical axes was obtained by ANOVA-like permutation tests (9,999 permutations). To explore the existence of areas within the archipelago with historically higher or lower gene flow than expected under a strictly isolation-by-distance (IBD) model, we estimated Effective Migration Surfaces using EEMS software 83 . EEMS is expected to not to be affected by some degree of location uncertainty 83 . Thus, genotype profiles from tissue samples whose exact origin within the sampled island was unknown were included. For these genotype profiles, their sampling locations were estimated by jittering around the centroid of the islands. Initially, we explored EEMS models for increasing deme sizes (200, 400 and 800 demes) and optimised the variances for the proposal distributions. Optimisation runs consisted of three independent MCMC chains of 1,000,000 iterations, burn-in of 200,000, and thinning of 2,000. The optimal number of demes was selected based on the determination coefficient (r 2 ) between the observed and fitted pairwise genetic dissimilarities between and within demes. The final EEMS analysis was run for eight independent chains of 5,000,000 MCMC iterations, burn-in of 1,000,000, and thinning of 10,000. Plotting of the effective migration surfaces and visual inspection of the convergence of the MCMC chains was conducted using reemsplots2 v0.1.0 84 and maptools v1.1-8 85 R packages. Ethical note Our research complied with ethical guidelines, rules and protocols approved by the Institute for Biodiversity and Protected Areas (IBAP), Guinea-Bissau, and CIBIO-InBIO, Portugal, having adhered to the set legal requirements. All except ten samples were obtained non-invasively from unidentified individuals without manipulation or disruption of their daily behaviour. Invasive samples were collected opportunistically from animals already deceased. Collection of invasive samples were free of charge. The local CITES focal point (Direção Geral de Florestas e Fauna) authorised exportation of samples. IBAP authorised collection of biological samples and transportation to Portugal. Instituto para a Conservação da Natureza e Florestas (ICNF), and Direção Geral de Veterinária (DGV), Portugal, authorised importation of samples (CITES Import Permits 18PTLX005921). Nagoya protocol was not in place in Guinea-Bissau at the time of sample collection (2016). Declarations Acknowledgements We dedicate this chapter to the memory of Michael W Bruford - our mentor, colleague and friend. His enthusiasm, guidance, and support were key to the success of this work and to advance the knowledge on conservation genetics of Guinea-Bissau primates. We would like to acknowledge the Guinea-Bissau governmental agency Instituto de Biodiversidade e Áreas Protegidas (IBAP), namely to the former director Dr. Alfredo Silva and Dr. Justino Biai, and to the directors of protected areas and staff members - Dr. Abilio Said, Dr. Augusto Cá, Dr. Joãozinho Mané and Dr. Sadjo Danfa, for fieldwork and sampling permits and to Abel Vieira, Iaia Cassama, Benjamin Indeque, Braima Bemba Canté for the support in fieldwork logistics. We acknowledge the Direcção Geral de Florestas e Fauna (DGFF) and CITES focal person in Guinea-Bissau for sample exportation permits; to the research assistants and guides Sadjo Camará, Mamadu Soares, Mamadu Turé, Idrissa Camará; to Isabella Espinosa and Helena Foito for logistical support in Bissau. We are grateful to Luis Palma for facilitating samples. Funding Declaration This research was funded by Fundação para a Ciência e Tecnologia through the project PRIMATOMICS (PTDC/IVC-ANT/3058/2014) and project (LA/P/0048/2020), and by funders of the PRIMACTION project (the Born Free Foundation, Chester Zoo Conservation Fund, Primate Conservation Incorporated, Mohamed Bin Zayed - Project 232533027) and by sponsorship from the following Portuguese private companies - CAROSI, Cápsulas do Norte, Camarc, JA-Rolhas e Cápsulas). MJFS worked under an FCT contract (https://doi.org/10.54499/CEECIND/01937/2017/CP1423/CT0010). ICC, FB and IP were supported by FCT-doctoral fellowships (ICC: https://doi.org/10.54499/SFRH/BD/146509/2019; FB: https://doi.org/10.54499/2020.05839.BD. Author contributions Conceptualisation: MJFS, ICC, NF, SLD, TM, MWB; Investigation: ICC, NF, SLD, FB; Formal analysis: ICC; Data Curation: ICC, MJFS, FB; Visualisation: ICC; Writing - Original Draft: ICC, MJFS, IMR; Writing - Review & Editing: all authors; Supervision: MJFS, IMR, MWB; Project administration: MJFS, ICC, NF, SLD; Resources: MJFS, TM, FS, IMR, AR; Funding acquisition: MJFS, TM, FS. Data availability statement The data that supports the findings of this study will be made available at Cardiff University’s Open Data repository/Figshare (https://research-data.cardiff.ac.uk) upon acceptance. Competing Interests Statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Kueffer, C. & Kinney, K. What is the importance of islands to environmental conservation? Environ. Conserv. 44 , 311–322 (2017). Braje, T. J., Leppard, T. P., Fitzpatrick, S. M. & Erlandson, J. M. Archaeology, historical ecology and anthropogenic island ecosystems. Environ. Conserv. 44 , 286–297 (2017). Martin, C. A. et al. Runs of homozygosity reveal past bottlenecks and contemporary inbreeding across diverging populations of an island-colonizing bird. Mol. Ecol. 32 , 1972–1989 (2023). Allendorf, F. W., Luikart, G. & Aitken, S. N. Conservation and the Genetics of Populations (John Wiley & Sons, Ltd, 2013). Colmonero-Costeira, I. et al. Genomic Signatures of Island Colonisation in Highly Diverse Primates. Mol. Ecol. 34 , e17815 (2025). Santini, L. et al. Global drivers of population density in terrestrial vertebrates. Glob l Ecol. Biogeogr. 27 , 968–979 (2018). Kimura, M., Weiss, G. H., THE STEPPING STONE MODEL & OF POPULATION STRUCTURE AND THE DECREASE OF GENETIC CORRELATION WITH DISTANCE. Genetics 49 , 561–576 (1964). Vellend, M. Island Biogeography of Genes and Species. Am. Nat. 162 , 358–362 (2003). Orsini, L., Vanoverbeke, J., Swillen, I., Mergeay, J. & De Meester, L. Drivers of population genetic differentiation in the wild: Isolation by dispersal limitation, isolation by adaptation and isolation by colonization. Mol. Ecol. 22 , 5983–5999 (2013). Costanzi, J. M. & Steifetten, Ø. Island biogeography theory explains the genetic diversity of a fragmented rock ptarmigan (Lagopus muta) population. Ecol. Evol. 9 , 3837–3849 (2019). Papadopoulou, A. & Knowles, L. L. Genomic tests of the species-pump hypothesis: Recent island connectivity cycles drive population divergence but not speciation in Caribbean crickets across the Virgin Islands. Evolution 69 , 1501–1517 (2015). Kimura, T., Yamada, T., Sakaguchi, S., Ito, M. & Maki, M. Multiple colonizations and genetic differentiation in goldenrod populations on recently formed nearshore islands. J. Biogeogr. 49 , 836–852 (2022). Alves, P. H. A Geologia Sedimentar da Guiné-Bissau da Análise Geral e Evolução do Conhecimento ao Estudo do Cenozóico (Universidade de Lisboa, PhD, 2007). Madeira, J. P. Bijagos Archipelago: Impacts and Challenges for Environmental Sustainability. InterEspaço: Revista de Geografia e Interdisciplinaridade . 2 , 291–305 (2016). Rainho, A. & Palmeirim, J. Mamíferos Terrestres. in Parque Nacional Marinho de João Vieira e Poilão: Biodiversidade e Conservação (eds Catry, P. & Regalla, A.) (IBAP - Instituto da Biodiversidade e das Áreas Protegidas, (2018). Rebelo, R. & Catry, P. O arquipélago dos Bijagós (Guiné-Bissau) - valores de biodiversidade e potencialidades para a investigação científica. Ecologia 2 , 8–15 (2011). Matsuda Goodwin, R. et al. Cercopithecus petaurista. The IUCN Red List. Threatened Species 2020 (2020). Pruetz, J. D., Socha, A. & Kante New Range Record for the Lesser Spot-Nosed Guenon (Cercopithecus Petaurista) in Southeastern Senegal. Afr. Primates . 7 , 64–66 (2010). Colmonero-Costeira, I., Minhós, T., Djaló, B. & Fernandes, N. Ferreira da Silva, M. Confirmação da ocorrência de primatas não-humanos no Arquipélago dos Bijagós com base em técnicas de identificação molecular. Sintidus 2 , 145–179 (2019). Colmonero-Costeira, I. et al. Notes on the conservation threats to the western lesser spot-nosed monkey (Cercopithecus petaurista buettikoferi) in the Bijagós Archipelago (Guinea-Bissau, West Africa). Primates 64 , 581–587 (2023). Gippoliti, S. & Dell’Omo, G. Primates of Guinea-Bissau, West Africa: distribution and conservation status. Primate Conserv. 19 , 73–77 (2003). Ferreira da Silva, M. J. et al. Using miniaturized laboratory equipment and DNA barcoding to improve conservation genetics training and identify illegally traded species. Conserv Biol e70165 (2025). Ferreira da Silva, M. J. et al. Assessing the impact of hunting pressure on population structure of Guinea baboons (Papio papio) in Guinea-Bissau. Conserv. Genet. 15 , 1339–1355 (2014). Minhós, T. et al. Genetic evidence for spatio-temporal changes in the dispersal patterns of two sympatric African colobine monkeys. Am. J. Phys. Anthropol. 150 , 464–474 (2013). Gerini, F. Structure and connectivity of sympatric primate species across a human-dominated landscape: population genetics of Western Chimpanzee (Pan troglodytes verus) and Guinea Baboon (Papio papio) in Guinea Bissau (University of Pisa, MSc,, 2018). Borges, F. A country-level genetic survey of the IUCN critically endangered western chimpanzee (Pan troglodytes verus) in Guinea-Bissau (University of Porto, 2017). Jensen, A. et al. Complex Evolutionary History With Extensive Ancestral Gene Flow in an African Primate Radiation. Mol Biol. Evol 40 , (2023). Kuderna, L. F. K. et al. A global catalog of whole-genome diversity from 233 primate species. Sci. (1979) . 380 , 906–913 (2023). Herman, R. W. et al. Whole genome sequencing reveals stepping-stone dispersal buffered against founder effects in a range expanding seabird. Mol. Ecol. 33 , e17282 (2024). Horsburgh, K. A., Matisoo-Smith, E., Glenn, M. E. & Bensen, K. J. Genetic Study of Translocated Guenons: Cercopithecus mona on Grenada. in The Guenons: Diversity and Adaptation in African Monkeys 289–306 (Kluwer Academic, Boston, (2003). Glenn, M. E. & Bensen, K. J. The mona monkeys of Grenada, São Tomé and Príncipe: Long-term persistence of a guenon in permanent fragments and implications for the survival of forest primates in protected areas. Primates Fragments: Complex. Resilience 413–422 (2013). Van Der Kuyl, A. C., Dekker, J. T. & Goudsmit, J. St. Kitts green monkeys originate from West Africa: Genetic evidence from feces. Am. J. Primatol. 40 , 361–364 (1996). Hazevoet, C. J. & Masseti, M. On the history of the green monkey Chlorocebus sabaeus (L., 1766) in the Cape Verde Islands, with notes on other introduced mammals. Zool. Caboverdiana . 2 , 12–24 (2011). Almeida, L., Colmonero-Costeira, I., Silva, M. J. F., da, Veracini, C. & Vasconcelos, R. Insights into the Geographical Origins of the Cabo Verde Green Monkey. Genes 15, (2024). Martin, A. et al. Isolation, marine transgression and translocation of the bare-nosed wombat (Vombatus ursinus). Evol. Appl. 12 , 1114–1123 (2019). Grossen, C., Biebach, I., Angelone-Alasaad, S., Keller, L. F. & Croll, D. Population genomics analyses of European ibex species show lower diversity and higher inbreeding in reintroduced populations. Evol. Appl. 11 , 123–139 (2018). du Plessis, S. J. et al. Genetic diversity and cryptic population re-establishment: management implications for the Bojer’s skink (Gongylomorphus bojerii). Conserv. Genet. 20 , 137–152 (2019). ​​Kopp, G. H., Fischer, J., Patzelt, A., Roos, C. & Zinner, D. Population genetic insights into the social organization of Guinea baboons (Papio papio): Evidence for female-biased dispersal. Am. J. Primatol. 77 , 878–889 (2015). Kopp, G. H. et al. The Influence of Social Systems on Patterns of Mitochondrial DNA Variation in Baboons. Int. J. Primatol. 35 , 210–225 (2014). Rowe, N. & Myers, M. All the World’s Primates (Pogonias, 2016). Santos, C. et al. Understanding Differences Between Phylogenetic and Pedigree-Derived mtDNA Mutation Rate: A Model Using Families from the Azores Islands (Portugal). Mol. Biol. Evol. 22 , 1490–1505 (2005). Funk, W. C., McKay, J. K., Hohenlohe, P. A. & Allendorf, F. W. Harnessing genomics for delineating conservation units. Trends Ecol. Evol. 27 , 489–496 (2012). Ferreira da Silva, M. J., Minhós, T., Sá, R., Casanova, C. & Bruford, M. W. A Qualitative Assessment of Guinea-Bissau’s Hunting History and Culture-and Their Implications for Primate Conservation. Afr. Primates . 15 , 1–18 (2021). Minhós, T. et al. DNA identification of primate bushmeat from urban markets in Guinea-Bissau and its implications for conservation. Biol. Conserv. 167 , 43–49 (2013). Minhós, T. et al. Genetic consequences of human forest exploitation in two colobus monkeys in Guinea Bissau. Biol. Conserv. 194 , 194–208 (2016). Ferreira da Silva, M. J. et al. Estimating the Effective Population Size Across Space and Time in the Critically Endangered Western Chimpanzee in Guinea-Bissau: Challenges and Implications for Conservation Management. Evol. Appl. 18 , e70162 (2025). Ferreira da Silva, M. J. et al. Disrupted dispersal and its genetic consequences: Comparing protected and threatened baboon populations (Papio papio) in West Africa. PLoS One . 13 , e0194189 (2018). Cardoso, A. Saberes e práticas tradicionais da etnia Bijagós e suas relações com a organização, a gestão e a conservação da biodiversidade na Guiné-Bissau (Universidade Federal da Bahia, 2010). Roeder, A. D., Archer, F. I., Poinar, H. N. & Morin, P. A. A novel method for collection and preservation of faeces for genetic studies. Mol. Ecol. Notes . 4 , 761–764 (2004). Bonin, A. et al. How to track and assess genotyping errors in population genetics studies. Mol. Ecol. 13 , 3261–3273 (2004). Pompanon, F., Bonin, A., Bellemain, E. & Taberlet, P. Genotyping errors: causes, consequences and solutions. Nat. Rev. Genet. 6 , 847–859 (2005). Valière, N. & Berthier, P. GEMINI: software for testing the effects of genotyping errors and multitubes approach for individual identification. Mol. Ecol. 2 , 83–86 (2002). Miquel, C. et al. Quality indexes to assess the reliability of genotypes in studies using noninvasive sampling and multiple-tube approach. Mol. Ecol. Notes . 6 , 985–988 (2006). Peakall, R. & Smouse, P. E. GenALEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28 , 2537–2539 (2012). Kalinowski, S. T., Taper, M. L. & Marshall, T. C. Revising how the computer program cervus accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16 , 1099–1106 (2007). Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes . 4 , 535–538 (2004). Rousset, F. GENEPOP’007: A complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8 , 103–106 (2008). Raymond, M. & Rousset, F. GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism. J. Hered . 86 , 248–249 (1995). Kearse, M. et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28 , 1647–1649 (2012). Camacho, C. et al. BLAST+: Architecture and applications. BMC Bioinform. 10 , 1–9 (2009). Meirmans, P. G. genodive version 3.0: Easy-to-use software for the analysis of genetic data of diploids and polyploids. Mol. Ecol. Resour. 20 , 1126–1131 (2020). Meirmans, P. G. & Van Tienderen, P. H. genotype and genodive: two programs for the analysis of genetic diversity of asexual organisms. Mol. Ecol. Notes . 4 , 792–794 (2004). Goudet, J. & Jombart, T. Estimation and Tests of Hierarchical F-Statistics. (2022). https://cran.r-project.org/web/packages/hierfstat/hierfstat.pdf Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34 , 3299–3302 (2017). Templeton, A. R., Crandall, K. A. & Sing, C. F. A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics 132 , 619–633 (1992). Múrias, D. et al. tcsBU: a tool to extend TCS network layout and visualization. Bioinformatics 32 , 627–628 (2016). Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., Von Haeseler, A. & Jermiin, L. S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods . 14 , 587–589 (2017). Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35 , 526–528 (2019). Oksanen, J. et al. vegan: Community Ecology Package. (2022). https://cran.r-project.org/web/packages/vegan/vegan.pdf CoreTeam., R. R: A language and environment for statistical computing. (2022). https://www.r-project.org Posit team. RStudio: Integrated Development for R. (2023). https://posit.co Jombart, T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24 , 1403–1405 (2008). Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155 , 945–959 (2000). Falush, D., Stephens, M. & Pritchard, J. K. Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies. Genetics 164 , 1567–1587 (2003). Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14 , 2611–2620 (2005). Jakobsson, M., Rosenberg, N. A. & CLUMPP A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23 , 1801–1806 (2007). Francis, R. M. pophelper: an R package and web app to analyse and visualize population structure. Mol. Ecol. Resour. 17 , 27–32 (2017). Wang, J. The computer program structure for assigning individuals to populations: easy to use but easier to misuse. Mol. Ecol. Resour. 17 , 981–990 (2017). Queller, D. C. & Goodnight, K. F. Estimating Relatedness Using Genetic Markers. Evolution 43 , 258–275 (1989). Konovalov, D. A., Manning, C. & Henshaw, M. T. KINGROUP: A program for pedigree relationship reconstruction and kin group assignments using genetic markers. Mol. Ecol. Notes . 4 , 779–782 (2004). Legendre, P. & Legendre, L. Numerical Ecology . (Elsevier B.V., Oxford, UK, (2012). Blanchet, F. G., Legendre, P. & Borcard, D. Forward selection of explanatory variables. Ecology 89 , 2623–2632 (2008). Petkova, D., Novembre, J. & Stephens, M. Visualizing spatial population structure with estimated effective migration surfaces. Nat. Genet. 48 , 94–100 (2015). Petkova, D. reemsplots2: Generate plots to inspect and visualize the results of EEMS. (2023). https://github.com/dipetkov/reemsplots2 Bivand, R. & Lewin-Koh, N. maptools: Tools for Handling Spatial Object. (2023). https://CRAN.R-project.org/package=maptools Additional Declarations No competing interests reported. Supplementary Files PetauristaSciRep2025SupplMat.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 06 May, 2026 Reviews received at journal 05 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 07 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Editor invited by journal 06 Apr, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 02 Apr, 2026 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-9213843","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":621758865,"identity":"ed41c63c-cf3e-46b4-af64-bc13ffa4bbe7","order_by":0,"name":"Ivo Colmonero-Costeira","email":"","orcid":"","institution":"CIBIO, BIOPOLIS/InBIO Laboratório Associado","correspondingAuthor":false,"prefix":"","firstName":"Ivo","middleName":"","lastName":"Colmonero-Costeira","suffix":""},{"id":621758869,"identity":"df861f5a-0be4-429d-a305-095adc51bcc6","order_by":1,"name":"Saidil Lamine Djaló","email":"","orcid":"","institution":"PRIMACTION","correspondingAuthor":false,"prefix":"","firstName":"Saidil","middleName":"Lamine","lastName":"Djaló","suffix":""},{"id":621758870,"identity":"9254ee37-1564-491f-91db-cdcc225f1a32","order_by":2,"name":"Nelson Fernandes","email":"","orcid":"","institution":"PRIMACTION","correspondingAuthor":false,"prefix":"","firstName":"Nelson","middleName":"","lastName":"Fernandes","suffix":""},{"id":621758871,"identity":"987cca24-3461-4073-a662-eae51831ef1f","order_by":3,"name":"Filipa Borges","email":"","orcid":"","institution":"CIBIO, BIOPOLIS/InBIO Laboratório Associado","correspondingAuthor":false,"prefix":"","firstName":"Filipa","middleName":"","lastName":"Borges","suffix":""},{"id":621758873,"identity":"f77a84da-5f86-45b4-9c90-97bcc973eeb9","order_by":4,"name":"Aissa Regalla","email":"","orcid":"","institution":"IBAP, Instituto para a Biodiversidade e Áreas Protegidas","correspondingAuthor":false,"prefix":"","firstName":"Aissa","middleName":"","lastName":"Regalla","suffix":""},{"id":621758875,"identity":"cb016e2f-05bb-4130-abe8-1ae930a2dd67","order_by":5,"name":"Fernando Sequeira","email":"","orcid":"","institution":"CIBIO, BIOPOLIS/InBIO Laboratório Associado","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"","lastName":"Sequeira","suffix":""},{"id":621758876,"identity":"06497c22-e83f-456a-99db-9f8008bbf3a7","order_by":6,"name":"Michael W. Bruford","email":"","orcid":"","institution":"Cardiff University","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"W.","lastName":"Bruford","suffix":""},{"id":621758881,"identity":"15715b94-9b40-4e43-82cf-f05457ab09f2","order_by":7,"name":"Tânia Minhós","email":"","orcid":"","institution":"Centre for Research in Anthropology","correspondingAuthor":false,"prefix":"","firstName":"Tânia","middleName":"","lastName":"Minhós","suffix":""},{"id":621758882,"identity":"a543b404-4a97-4b65-a656-fdb4b5f1c037","order_by":8,"name":"Isa-Rita M. Russo","email":"","orcid":"","institution":"Cardiff University","correspondingAuthor":false,"prefix":"","firstName":"Isa-Rita","middleName":"M.","lastName":"Russo","suffix":""},{"id":621758883,"identity":"315f603e-27f8-4695-83bf-1a8d3b41a159","order_by":9,"name":"Maria Joana Ferreira da Silva","email":"data:image/png;base64,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","orcid":"","institution":"CIBIO, BIOPOLIS/InBIO Laboratório Associado","correspondingAuthor":true,"prefix":"","firstName":"Maria","middleName":"Joana Ferreira da","lastName":"Silva","suffix":""}],"badges":[],"createdAt":"2026-03-24 15:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9213843/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9213843/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106961044,"identity":"64f5edc6-1dcd-48d1-a85b-ddd688dc2f0c","added_by":"auto","created_at":"2026-04-15 09:24:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":211655,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the spot-nosed monkey (\u003cem\u003eCeropithecus petaurista\u003c/em\u003e) in the Bijagós Archipelago, Guinea-Bissau. The species distribution area was drawn based on IUCN polygon (accessed in 2025). Distributions based on regional surveys conducted in Guinea-Bissau\u003csup\u003e19–21\u003c/sup\u003e are represented as hatched areas. The maps depict protected areas established in the Bijagós Archipelago: i) UCMPA, Urok Communitarian Marine Protected Area; ii) ONP, Orango National Park; iii) JVPMNP, João Vieira and Poilão Marine National Park. Photo of a pet infant adapted from Colmonero-Costeira et al. (2023)\u003csup\u003e20\u003c/sup\u003e. Illustrations copyright 2022 Stephen D. Nash / IUCN SSC Primate Specialist Group. Used with permission.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9213843/v1/a0180996dcd320eaf9c8c41b.jpg"},{"id":106909795,"identity":"69a6f2f8-61eb-4752-8ef1-ce3e41ba43f2","added_by":"auto","created_at":"2026-04-14 16:16:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":946338,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation structure of the spot-nosed monkey in the Bijagós Archipelago based on eleven microsatellite loci. \u003cstrong\u003ea\u003c/strong\u003e Location of sampled individuals and landscape features of the archipelago. Sandbanks are represented in yellow. The bathymetry is represented as a grey-scale gradient towards increasing water depth (dark grey). \u003cstrong\u003eb \u003c/strong\u003ePairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e\u003csub\u003e \u003c/sub\u003ebetween islands. \u003cstrong\u003ec \u003c/strong\u003eIndividual-based principal components analysis. Individuals were coloured according to sampling island. The eigenvalues for each PC are in the bottom left corner.\u003cstrong\u003e d \u003c/strong\u003eSTRUCTURE plots depicting the average individual cluster assignment probabilities across 10 independent runs for \u003cem\u003eK\u003c/em\u003e = 4 and \u003cem\u003eK\u003c/em\u003e = 5. \u003cstrong\u003ee \u003c/strong\u003eeffective migration surface estimated by 8 independent EEMS runs. Colour gradient represents log migration rates and is a proxy of gene flow. Blue tones represent increased effective migration from the expected under IBD, which decreases towards lower effective migrations in red.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9213843/v1/53d02825e88e6f0fac255c0b.png"},{"id":106961240,"identity":"432793e1-7544-4ffd-8b32-cd76611032b5","added_by":"auto","created_at":"2026-04-15 09:24:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":289906,"visible":true,"origin":"","legend":"\u003cp\u003ePatterns of mitochondrial diversity of the spot-nosed monkey in the Bijagós Archipelago using a 290 bp fragment of the HVRI. \u003cstrong\u003ea\u003c/strong\u003e Location of sampled individuals and landscape features of the archipelago. Sandbanks are represented in yellow. The bathymetry is represented as a grey-scale gradient towards increasing water depth. \u003cstrong\u003eb \u003c/strong\u003eTCS haplotype network. \u003cstrong\u003ec \u003c/strong\u003eIndividual-based Multidimensional Scaling analysis. The eigenvalues for each dimension are plotted in the bottom right corner.\u003cstrong\u003e \u003c/strong\u003eHaplotypes and individuals are coloured according to the sampling location.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9213843/v1/0b36d2aea9de183694c7353d.png"},{"id":106963447,"identity":"0292d464-841f-4f7f-b830-df565171bb9c","added_by":"auto","created_at":"2026-04-15 09:44:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2260829,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9213843/v1/66c282db-119f-4b9f-b8f0-9be1f99a36b4.pdf"},{"id":106909794,"identity":"8aadafae-203f-458b-af26-fec40300d7b8","added_by":"auto","created_at":"2026-04-14 16:16:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":668906,"visible":true,"origin":"","legend":"","description":"","filename":"PetauristaSciRep2025SupplMat.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9213843/v1/de001f77fe9d1eb49eae9940.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eGenetic diversity and population structure of the spot-nosed monkey (Cercopithecus petaurista) of the Bijagós Archipelago, Guinea-Bissau, West Africa\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInsular ecosystems in general, are particularly vulnerable to global change and increasing anthropogenic disturbances such as habitat destruction and wildlife exploitation\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The genetic diversity of insular populations is often reduced as a consequence of a small number of founding individuals, exacerbated genetic drift promoted by isolation and limited carrying capacity, further increasing their risk of extinction\u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Sequential colonisation models (i.e., the \u0026ldquo;stepping-stone model\u0026rdquo;\u003csup\u003e7\u003c/sup\u003e predict declining genetic diversity and increasing differentiation with distance from the mainland)\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, insular systems often deviate from these expectations due to complex dispersal pathways, as well as historical and contemporary connectivity between islands\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, establishing baseline knowledge on genetic diversity, population structure and gene flow dynamics between islands is critical for interpreting the colonisation history and present population dynamics, and to inform conservation strategies adapted to the local context.\u003c/p\u003e \u003cp\u003eThe Bijag\u0026oacute;s Archipelago, located off the coast of Guinea-Bissau, West Africa, illustrates the disconnection between high biodiversity value and limited scientific knowledge. Locally known as \u003cem\u003eBemba di vida\u003c/em\u003e (\u003cem\u003ei.e.\u003c/em\u003e, \u0026ldquo;the barn of life\u0026rdquo;\u0026ndash; in Guinea-Bissau creole), this biodiversity hotspot in West Africa has recently gained UNESCO Heritage Status (2025). This archipelago (ca. 900 km\u003csup\u003e2\u003c/sup\u003e of land, 88 islands and islets of continental origin\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e) is permanently inhabited by local communities, predominantly from the \u003cem\u003eBijag\u0026oacute;\u003c/em\u003e ethnic group, whose animistic belief system is thought to contribute to the preservation of the islands\u0026rsquo; ecosystems\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. A minimum of twenty-two mammals have been registered\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003c/sup\u003e yet their local conservation status remains poorly characterised. Furthermore, little is known about the colonisation history of the archipelago by terrestrial mammals, which may have happened naturally as early as 15,000 years ago\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e or even human-mediated, for instance, after the arrival of the first \u003cem\u003eBijag\u0026oacute;\u003c/em\u003e around the XI\u003csup\u003eth\u003c/sup\u003e Century\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe spot-nosed monkey (\u003cem\u003eCercopithecus petaurista\u003c/em\u003e Schreber, 1774) of the Bijag\u0026oacute;s Archipelago is of great conservation importance regionally. Although globally classified as Near Threatened by the International Union for Nature and Conservation (IUCN)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, the species\u0026rsquo; distribution is likely fragmented, and the populations of Guinea-Bissau and Senegal (Fongoli\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e), are the only ones recently confirmed in this region of West Africa (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In Guinea-Bissau, the species has not been observed on the mainland for over three decades and is therefore thought to persist exclusively in the Bijag\u0026oacute;s Archipelago\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, making these populations the currently westernmost known. Within the archipelago, the spot-nosed monkey occurs in a limited number of islands\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), where populations have reportedly declined during the last decades likely due to habitat degradation and targeted commercial hunting\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA previous comparative genomic study showed that the Bijag\u0026oacute;s Archipelago\u0026rsquo;s primate populations, including the spot-nosed monkey, Campbell\u0026rsquo;s monkey (\u003cem\u003eCercopithecus campbelli\u003c/em\u003e, Waterhouse, 1838) and the green monkey (\u003cem\u003eChlorocebus sabaeus\u003c/em\u003e, Linnaeus, 1766), display signatures typical of long-term isolation compared to their mainland counterparts\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These include reduced effective population sizes, lower genetic diversity and increased realised genetic load suggesting that overall, while not yet under extreme genetic threat (i.e., mutational meltdown), these insular populations would benefit from pre-emptive conservation strategies to promote their long-term viability\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, these analyses were based on a limited number of representative individuals (N\u0026thinsp;=\u0026thinsp;8 spot-nosed monkeys). In the particular case of the spot-nosed monkey, the lack of comprehensive archipelago-wide sampling prevents an accurate assessment of local levels of genetic diversity, population structure and gene flow, crucial to guide conservation efforts.\u003c/p\u003e \u003cp\u003eIn this study we aimed to estimate i) the genetic diversity and ii) the population structure within five of the largest islands of the archipelago, and iii) characterise the gene flow dynamics between islands and determine the main axes of genetic differentiation using nuclear microsatellite markers and mitochondrial DNA. We hypothesised that the populations would conform to some degree to the expected genetic patterns for insular systems. Specifically, we predict i) higher genetic diversity in islands closer to the mainland with decreased diversity towards the edges of the archipelago and ii) spatially structured differentiation by island, although episodic gene flow may occur through dispersal across the existing intertidal sandflat bridges between islands. Our overarching goal was to provide baseline genetic information that may inform management to improve directed conservation actions.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Distribution of the spot-nosed monkey (\u003cem\u003eCeropithecus petaurista\u003c/em\u003e) in the Bijag\u0026oacute;s Archipelago, Guinea-Bissau. The species distribution area was drawn based on IUCN polygon (accessed in 2025). Distributions based on regional surveys conducted in Guinea-Bissau\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e are represented as hatched areas. The maps depict protected areas established in the Bijag\u0026oacute;s Archipelago: i) UCMPA, Urok Communitarian Marine Protected Area; ii) ONP, Orango National Park; iii) JVPMNP, Jo\u0026atilde;o Vieira and Poil\u0026atilde;o Marine National Park. Photo of a pet infant adapted from Colmonero-Costeira et al. (2023)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Illustrations copyright 2022 Stephen D. Nash / IUCN SSC Primate Specialist Group. Used with permission.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eSampling\u003c/h2\u003e\u003cp\u003eDuring the 26 expedition days (January to June 2016), we collected a total of 378 faecal samples from ranging groups of spot-nosed monkey from the islands of Caravela (n\u0026thinsp;=\u0026thinsp;89), Uracane (n\u0026thinsp;=\u0026thinsp;78), Uno (n\u0026thinsp;=\u0026thinsp;90), Canhabaque (n\u0026thinsp;=\u0026thinsp;61) and Galinha (n\u0026thinsp;=\u0026thinsp;60). Of those, a subset of 145 faecal samples was selected to be analysed based on freshness and location in order to optimise amplification success and minimise the inclusion of repeated individuals in the dataset.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eNuclear and Mitochondrial Datasets\u003c/h2\u003e \u003cp\u003eWe obtained a microsatellite loci dataset that included a total of 64 spot-nosed monkey individual profiles genotyped at 8\u0026ndash;11 microsatellite loci across the five islands (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The dataset had an average QI of 0.88 and 5% missing data across loci. We did not detect the presence of null alleles and scoring errors due to stuttering or considerable allele dropout. Significant departure from Hardy Weinberg Equilibrium (HWE) was found for all the loci when samples across islands were pooled. When divided by island, only locus D12s372 in Canhabaque Island was found to have a significant departure from HWE. Thirty-five loci pairs were found in linkage disequilibrium in the pooled dataset and none when divided by island. These results suggest that population structure was the underlying cause of departures from HWE, and we included all samples and loci in downstream analyses. The PI\u003csub\u003esib\u003c/sub\u003e using the full set of 11 loci was of 1.0x10\u003csup\u003e\u0026minus;\u0026thinsp;12\u003c/sup\u003e. Individuals could be effectively distinguished using a minimum combination of eight loci (PI\u003csub\u003esib\u003c/sub\u003e \u0026lt; 0.001).\u003c/p\u003e \u003cp\u003eThe mitochondrial dataset contained HVRI sequences for 56 individuals with a final length of 290 bp. We did not find overly divergent haplotypes or other evidence indicative of the presence of nuclear copies of mtDNA in our dataset.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenetic diversity\u003c/h3\u003e\n\u003cp\u003eAll eleven microsatellite loci were polymorphic with a mean number of alleles of 8.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57 and an expected heterozygosity (H\u003csub\u003eE\u003c/sub\u003e) of 0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Regardless of the chosen genetic diversity metric, Caravela and Galinha yielded lower genetic diversity than the remaining islands, particularly compared to Canhabaque. Overall, observed heterozygosity (H\u003csub\u003eO\u003c/sub\u003e) was similar to expected heterozygosity (H\u003csub\u003eE\u003c/sub\u003e) except for Caravela and Canhabaque which showed a heterozygosity deficit, and consequently positive inbreeding coefficients (G\u003csub\u003eIS\u003c/sub\u003e = 0.19 and 0.13, respectively; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe found a total of 22 unique HVRI haplotypes across 41 polymorphic sites. The overall estimated mitochondrial diversity was high (Hd\u0026thinsp;=\u0026thinsp;0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02; π\u0026thinsp;=\u0026thinsp;2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The population of Canhabaque Island was the most diverse (Hd\u0026thinsp;=\u0026thinsp;0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06; π\u0026thinsp;=\u0026thinsp;1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) and the population of Galinha the least (Hd\u0026thinsp;=\u0026thinsp;0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16; π\u0026thinsp;=\u0026thinsp;0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e). The population of Galinha showed a mitochondrial diversity pattern that significantly deviated from a neutral pattern of evolution (Tajima\u0026rsquo;s D = -2.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), revealing an excess of low frequency polymorphisms (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenetic diversity of the spot-nosed monkey across eleven microsatellite loci.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsland (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003csub\u003eA\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003csub\u003eE\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH\u003csub\u003eO\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH\u003csub\u003eE\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eG\u003csub\u003eIS\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaravela (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUracane (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e-0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUno (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e-0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanhabaque (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGalinha (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eN \u0026ndash; number of genotype profiles; n\u003csub\u003eA\u003c/sub\u003e \u0026ndash; alleles per locus; n\u003csub\u003eE\u003c/sub\u003e \u0026ndash; effective number of alleles; AR \u0026ndash; allelic richness; H\u003csub\u003eO\u003c/sub\u003e \u0026ndash; observed heterozygosity; H\u003csub\u003eE\u003c/sub\u003e \u0026ndash; expected heterozygosity; G\u003csub\u003eIS\u003c/sub\u003e \u0026ndash; inbreeding coefficient.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003ePopulation structure\u003c/h3\u003e\n\u003cp\u003eMean pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e between islands using microsatellite data was 0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09. The lowest pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e was found between the populations of Uno and Canhabaque (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e = 0.17), and the largest between Caravela and Galinha (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e = 0.46; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In the Principal Components Analysis (PCA), the first and second Principal Components explained 34.80% of the total variance and revealed four main groups: Galinha, Uracane, Uno and a fourth group formed by individuals from Caravela, Canhabaque and a few individuals from Uno (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eIn the STRUCTURE analysis, the starting point of the log-likelihood plateau and the first Δ\u003cem\u003eK\u003c/em\u003e peak was obtained at \u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4 (Supplementary Fig.\u0026nbsp;1), followed by a maximum log-likelihood and a second \u003cem\u003eΔK\u003c/em\u003e peak at \u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5. The STRUCTURE results for increasing values of \u003cem\u003eK\u003c/em\u003e (\u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1 to 5) suggested the existence of hierarchical population structure (Supplementary Fig.\u0026nbsp;2). Similar to the PCA, at \u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, populations within each island were considered independent genetic clusters except for the individuals of Caravela and Canhabaque which were clustered together but later segregated at \u003cem\u003eK\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5 (Supplementary Fig.\u0026nbsp;2). All individuals showed high probability of assignment to each genetic cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). STRUCTURE runs aimed at testing the effect of unbalanced sampling and the inclusion of significantly related individuals showed no differences to the standard runs (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eThe haplotype network lacked a central highly frequent haplotype and instead displayed high levels of reticulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The sampled haplotypes were private to each of the islands (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The most divergent haplotypes (\u0026ge;\u0026thinsp;12 mutational steps) were found between Uno and Galinha and dominated the variation along the first two dimensions of the Multidimensional Scaling (MDS) analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMitochondrial genetic diversity of the spot-nosed monkey (290 bp fragment of the hypervariable region I).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsland (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eπ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaravela (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.82 NS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUracane (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.22 NS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUno (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05 NS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanhabaque (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.35 NS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGalinha (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.06 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.93 NS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eN \u0026ndash; number of sequences; S \u0026ndash; number of polymorphic positions; H \u0026ndash; number of haplotypes; Hd \u0026ndash; Haplotype diversity; π \u0026ndash; nucleotide diversity; D \u0026ndash; Tajima\u0026rsquo;s D. Asterisks represent significant deviations from neutrality (NS p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGene flow and geographic genetic differentiation\u003c/h3\u003e\n\u003cp\u003eThe redundancy analysis (RDA) detected significant spatially-induced genetic differentiation. The polynomial trend-surface of the geographic coordinates explained 43.58% of the total variance (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.39, ANOVA-like F\u003csub\u003e(4, 52)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;10.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The estimated effective migration surfaces (EEMS) model was optimised at 400 demes which displayed the highest r\u003csup\u003e2\u003c/sup\u003e between the observed and estimated pairwise genetic dissimilarities between and within demes (r\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ebetween demes\u003c/sub\u003e = 0.78 and r\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ewithin demes\u003c/sub\u003e = 0.72; Supplementary Table\u0026nbsp;2). The obtained effective migration surface that suggested genetic differentiation across the archipelago violates a strict IBD model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Areas of low historical gene flow relative to the expected under strict IBD were found across open sea barriers (between Uracane and Uno) but also over potential dispersal corridors (e.g., sandbanks between Canhabaque and Galinha). On the other hand, higher historical gene flow than expected was found between Uno and Canhabaque, more than 40 km apart.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe Bijagós Archipelago in Guinea-Bissau is a recognised biodiversity hotspot exemplified by the relict populations of the spot-nosed monkey, a species thought recently extirpated from the mainland\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The long-term viability of the terrestrial mammals would benefit from baseline genetic information to aid local conservation strategies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Here, we assessed genetic diversity and population structure of the spot-nosed monkey using nuclear and mitochondrial markers across 80% of the known distribution of the primate in the country. According to expectations, genetic diversity was heterogeneous across the archipelago, and populations were highly structured between islands, suggesting low or no recent gene flow. However, we did not find a gradual decrease of genetic diversity and increase of population differentiation with distance from mainland (i.e, a pattern of strictly sequential colonisation of islands\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e), suggesting a more complex colonisation history.\u003c/p\u003e \u003cp\u003eInsular populations are often of special concern as they are more prone to the loss of genetic diversity compared to contiguous continental populations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The populations of spot-nosed monkey at the Bijagós Archipelago do not appear to be depauperated of genetic diversity. Although direct comparisons of genetic diversity between taxa often reflect species-specific evolutionary histories and may be unprecise, in the context of the remaining primates of Guinea-Bissau. Spot-nosed monkey genetic diversity was within the range of mainland species as estimated using 8–21 autosomal microsatellite loci and mitochondrial control-region markers (Supplementary Table\u0026nbsp;3)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccording to previous genome-wide estimates, intermediate to high levels of genetic diversity for the spot-nosed monkey of the Bijagós archipelago is not unexpected. Whole genomes of individuals from Canhabaque and Caravela showed relatively high genetic diversity but reduced in comparison to a reference individual from mainland Africa of unknown origin\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Indeed, guenons are the most genetically diverse group of African primates\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The retention of high levels of genetic diversity suggest that the founding populations of the Bijagós Archipelago carried significant diversity from the source population. Genetic diversity was heterogeneous across the sampled islands which could be an effect of sequential colonisation events within archipelagos since serial population bottlenecks further reduce the genetic diversity of the founding populations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnother common pattern that arises from serial colonisation is high population structure as a result of pronounced genetic drift, driven by the long-term isolation and cessation of gene flow both between the islands and with the mainland\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Accordingly, the multiple analysis of population structure showed strong genetic differentiation among spot-nosed monkey populations, clearly corresponding to island boundaries, suggesting little or no recent gene flow between islands. Even though potential corridors for dispersal currently exist between some of the islands (e.g., sandbanks between Galinha and Canhabaque), we did not find evidence of episodic gene flow.\u003c/p\u003e \u003cp\u003eThe population at Canhabaque was the most genetically diverse and occupied a relatively central position in both nuclear and mitochondrial ordination analyses. Additionally, the lowest pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e were consistently observed for all island pairs involving Canhabaque. Based on the expectation that genetic diversity decreases and genetic differentiation increases further from the mainland\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, Canhabaque, one of the closest islands to the mainland (ca. 20 km), may represent one of the initial points of colonisation, and may have served as the source population for the remaining islands.\u003c/p\u003e \u003cp\u003eAlthough evidence supports Canhabaque as one primary source population, the subsequent colonisation dynamics remain more difficult to disentangle. The EEMS analysis shows areas of increased and decreased historical gene flow, contradicting the existence of a smooth, IBD-like pattern of genetic differentiation, commonly found in stepping-stone models of colonisation\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. For instance, lower estimates of effective migration than the expected were found between geographically proximate islands, Uno and Uracane, which are only separated by approximately 6 km. Other observed patterns that deviate from the theoretical expectations for strictly sequential colonisation were: i) the clustering of individuals from Caravela and Canhabaque in the PCA along with late segregation in STRUCTURE at \u003cem\u003eK\u003c/em\u003e = 5, and ii) lower values of pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e between Uno and Canhabaque, accompanied by a corridor of high effective migration between the two islands. These findings suggest these two island pairs Uno-Canhabaque, and Caravela-Canhabaque, likely have a more recent shared ancestry compared to the remaining islands, despite being located at opposite ends of the archipelago up to 100 km of distance. Overall, these results could suggest that historical gene flow dynamics within the archipelago may not have been solely dependent on the expected stepping-stone-like processes seen in other insular systems, where there is a clear directional axis of differentiation (e.g., Herman et al., 2024\u003csup\u003e29\u003c/sup\u003e). Humans have been suggested as the vector for the translocation of terrestrial mammals to and across the Bijagós Archipelago\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Suggested potential translocation timings include after the co-colonisation with the local ethnic group, the Bijagó\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e (XI\u003csup\u003eth\u003c/sup\u003e Century), or, during the Trans-Atlantic enslaved people-trade (XV\u003csup\u003eth\u003c/sup\u003e Century) similarly to other guenon species, namely the mona monkey (\u003cem\u003eCercopithecus mona\u003c/em\u003e Schreber, 1774) of the islands of Grenada and São Tomé and Príncipe\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, and the green monkeys (\u003cem\u003eChlorocebus\u003c/em\u003e sp. Gray, 1870), of the Caribbean and Cape Verde\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTranslocated populations can readily become differentiated from their source populations over the course of a few generations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, which in the case of the spot-nosed monkey of the Bijagós archipelago, may represent between 90 − 50 generations ago, considering a generation time of 11 years\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e and the starting time of the suggested human-mediated translocation events. Under this alternative hypothesis, the patterns of population differentiation between islands would be related to the human-mediated movements of animals rather than gene flow dependent on the proximity between islands and/or the formation of sandflats.\u003c/p\u003e \u003cp\u003eWe highlight that the mtDNA does not provide an exact reflection of the population differentiation patterns obtained in the microsatellite dataset, which is expected under (historical) sex-biased dispersal38. Low mitochondrial genetic diversity within islands but high overall diversity is concordant with historical female-philopatry found in male-mediated dispersal systems\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, characteristic for the spot-nosed monkey\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. However, considering the mutation rate of the mitochondrial d-loop (humans, 2.4 x 10\u003csup\u003e− 7\u003c/sup\u003e substitutions/site/year\u003csup\u003e41\u003c/sup\u003e), island-specific haplotypes would not be expected neither in relatively short life of the Bijagós Archipelago (ca. 15,000 years ago\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e) nor after the putative human-mediated dispersal 500–900 years ago. However, bearing in mind that changes in the allelic frequencies across this system is mainly driven by genetic drift\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, it can be argued that the mitochondrial diversity currently present is a result of stochastic fixation and extinction of haplotypes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe local conservation status of the spot-nosed monkey in Guinea-Bissau is thought to be particularly dire as the last viable populations of the primate are likely the ones of the Bijagós Archipelago. We found that genetic diversity is maximal in Canhabaque and lowest in Caravela. These results are coincidental with a study based on whole-genome re-sequencing data that suggested lower effective population sizes and genetic diversity, and increased inbreeding and realised genetic load for both Canhabaque and Caravela when compared to a mainland individual of unknown origin, being particularly severe in Caravela\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Overall, our results of heterogeneous genetic diversity across the archipelago suggest that extinction risk by genetic factors is uneven and likely higher in Caravela and other less diverse populations than in Canhabaque.\u003c/p\u003e \u003cp\u003eConsidering the strong population differentiation between islands, heterogeneous and private genetic diversity found in this work, we suggest that each island should be managed as an independent unit\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. As such, future works should prioritise generating island-specific key demographic parameters, such as recent changes in effective population size over time, inbreeding and mutational load, and estimation of census size, density and habitat integrity.\u003c/p\u003e \u003cp\u003eOn top of increased extinction risk by genetic factors suggested by lower genetic diversity, most populations are also threatened by mortality caused by commercial wildmeat trade which is thought to be an increasing practice on the islands\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The activity is likely motivated by unstable income sources in the region, which may encourage young men to engage in this fast-returning activity\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The extent to which hunting impacts insular populations of the spot-nosed monkey is currently unknown. Nevertheless, demographic changes potentially related to the increase of deforestation and hunting pressure in the last decades have been reported for other primates in the country. These included high mortality\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, a reduction of the effective population size\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, and a disruption of the dispersal patterns due to behavioural modifications to perceived threat\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur work also provides further emphasis that the insular populations are not genetically depauperate and could potentially act as reservoirs, creating the opportunity for future re-introductions of the species to mainland Guinea-Bissau. The populations of Canhabaque could be particularly relevant for these efforts as they have retained considerable extant genetic diversity (this study and Colmonero-Costeira et al. 2025\u003csup\u003e5\u003c/sup\u003e). Considering the importance of the islands for the long-term conservation of the spot-nosed monkey in Guinea-Bissau, we stress that measures should be adopted to reduce currently known conservation threats and instate some degree of formal protection, perhaps in the form of a terrestrial protected area that integrates both conservation and socio-cultural needs of local inhabitants, in alignment with the UNESCO Heritage Site conservation action plan.\u003c/p\u003e \u003cp\u003eMore broadly, our study suggests that unexpected patterns of genetic differentiation among islands considering what would be expected based on natural processes may reflect complex colonisation histories. Further work may estimate the timing of colonisation, frequency of translocation events and assess the natural and human-mediated components of these processes using alternative methodologies that integrate local ecological knowledge, historical, and ecological data. Such a framework would not only benefit other terrestrial mammals with similar ecological requirements whose colonisation history remains unexplored. In doing so, these efforts could provide a previously unknown window into the bio-cultural history of this globally recognised biodiversity hotspot.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy site\u003c/h2\u003e\u003cp\u003eOur study site comprises five of the largest islands of the Bijagós Archipelago - Caravela, Uracane, Uno, Canhabaque, Galinha where spot-nosed monkeys were reported to occur\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The study area represents 80% of the species estimated distribution in Guinea-Bissau (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Of the sampled islands, Cambanhaque and Galinha Islands are closer to the mainland (ca. 20 km). Extensive intertidal sandflats connect some of the islands during low tides, namely Canhabaque and Galinha, but the great majority are surrounded by the deep-sea waters (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All islands are permanently inhabited by local communities distributed by small villages\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In most islands, the local economy is based on subsistence agriculture, fishing and hunting\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Ecotourism is present in Caravela.\u003c/p\u003e\u003ch3\u003eSampling\u003c/h3\u003e\u003cp\u003eWe carried out expeditions between January and June 2016. Areas frequently used by primates were identified by the local communities and the locations were subsequently visited by the team. Whenever a social group was detected, we collected faecal samples non-invasively, with minimal disturbance. To avoid the collection of multiple samples from the same individual, we only collected samples that spread more than 2 m apart. All the collected faecal samples were georeferenced using a Geographic Positioning System (GPS) device. Other types of metadata were collected during sampling, such as the freshness of samples and number of individuals in the group (when observed). The preservation of the faecal samples followed the two-step protocol in which samples are immersed in 96% ethanol for 24/48 hours and then transferred to a falcon tube containing silica gel until extraction\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Additionally, tissue samples were collected from carcasses of hunted individuals found opportunistically in local villages. These samples were preserved in 99% ethanol. Samples were stored at room temperature while in Guinea-Bissau after which samples were transported to Portugal and stored at -20 ℃ until DNA extraction. A sub-set of faecal samples were selected to be molecularly analysed, based on freshness and spatial distribution.\u003c/p\u003e\u003ch2\u003eDNA extraction\u003c/h2\u003e\u003cp\u003eFaecal samples were extracted using the QIAamp DNA Stool Mini Kit (Qiagen®, Germany) with few modifications to increase DNA yield as described in Ferreira da Silva et al. (2014)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. DNA from ten tissue samples was extracted using the DNeasy Blood \u0026amp; Tissue Kit (Qiagen®, Germany) according to the manufacturer’s protocol.\u003c/p\u003e\u003ch2\u003eDNA amplification\u003c/h2\u003e\u003cp\u003eSamples were genotyped using a panel of 11 autosomal microsatellite (STR) loci (Supplementary Table\u0026nbsp;1). The microsatellite loci were human-derived but known to cross-amplify in other Cercopithecidae species [Guinea baboon (\u003cem\u003ePapio papio\u003c/em\u003e Desmarest, 1820)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, king colobus (\u003cem\u003eColobus polykomos\u003c/em\u003e Zimmermann, 1780)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and the western red colobus (\u003cem\u003ePiliocolobus badius temminckii\u003c/em\u003e Kuhl, 1820)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e]. The microsatellite loci were amplified in three multiplex Polymerase Chain Reactions (PCRs) except for locus D7s503 (Supplementary Table\u0026nbsp;1). Each PCR reaction contained 1X MyTaq™ Mix (Bioline, UK), 0.6 µL of primer mix, 2 µL of DNA extract and molecular grade water for a final volume of 6 µL. The final concentration for each fluorescence-labelled primer pair varied across the microsatellite panel (Supplementary Table\u0026nbsp;1). The PCR reactions were performed in a T100™ 96 Well Thermal Cycler (Bio-Rad, USA). Cycling conditions started with a Taq activation step at 95 ℃ for 15 minutes, followed by 40 cycles of denaturing step at 94 ℃ for 30 seconds, annealing at 57–59 ℃ for between 40 and 90 seconds and extension at 72 ℃ for between 40 and 90 seconds (Supplementary Table\u0026nbsp;1). The PCR cycles ended with a final extension of 30 minutes at 72 ℃. The PCR products were analysed on a 3130xl automated sequencer (Applied Biosystems™, USA) using GeneScan™ 500 LIZ™ size standard (Thermo Fisher Scientific, USA). Alleles were scored using GeneMapper v4.0 (Applied Biosystems™, USA).\u003c/p\u003e\u003cp\u003eA fragment of the hypervariable region I (HVRI) of the mitochondrial d-loop with an in \u003cem\u003esilico\u003c/em\u003e predicted size of 388 bp was amplified for unique individuals (see below) by PCR using primers LCERCOHVRI (5’ CGTGCATTACTGCTAGCCAAC 3’) and HCERCOHVRI (5’ GGGATATTGATTTCACGGAGGA 3’)\u003csup\u003e19\u003c/sup\u003e. The PCR reactions were conducted in 10 µL of total volume, containing 1X MyTaq™ Mix (Bioline, UK), 0.2 µM of forward and reverse primer, 2 µL of DNA extract and 2 µL molecular grade water for a final volume of 10 µL. The PCR reactions were performed in a T100™ 96 Well Thermal Cycler (Bio-Rad, USA). The cycling conditions started with a Taq activation step at 95ºC for 15 minutes, followed by 40 cycles of denaturing step at 94ºC for 30 seconds, annealing at 58ºC for 30 seconds and extension at 72ºC for 30 seconds. The final cycling step corresponded to a final extension at 72ºC for 15 minutes. The amplified products were purified by enzymatic hydrolysis of nucleotides using 1 µL (1/4 ratio) of Exonuclease I (20 UµL-1) and FastAP (1 UµL-1) (Thermo Fisher Scientific™, USA). Fragments were sequenced on a 3130XL automated sequencer (Applied Biosystems™, USA).\u003c/p\u003e\u003ch2\u003eData quality control\u003c/h2\u003e\u003cp\u003eMicrosatellite loci from non-invasive samples are prone to systematic and stochastic errors such as null alleles (NA), false alleles (FA) and allelic dropout (ADO)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. To circumvent this limitation, the number of PCR repeats and the number of times an allele needs to be scored to obtain 95% confidence in genotypes was estimated using the simulation software GEMINI v1.3.0\u003csup\u003e52\u003c/sup\u003e. We estimated that the consensus genotype obtained from four independent PCR repeats across loci would produce 95% confidence genotypes (please see the Supplementary Information for additional details on consensus genotype calling). The Quality Index (QI)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e was used to assess the reliability of consensus genotypes. We only included samples with a QI above 0.55 in the final dataset. The threshold of missing data across loci for a genotyped individual was defined based on the minimum combinations of loci that minimises the probability of identity between siblings (PI\u003csub\u003esib\u003c/sub\u003e) estimated using GenAlEx v6.5\u003csup\u003e54\u003c/sup\u003e. Duplicate genotype profiles were detected by identity analysis in Cervus v3.0.7\u003csup\u003e55\u003c/sup\u003e. Profiles differing by a single heterozygous locus were considered duplicates and were removed from the final database. The existence of null alleles and scoring errors due to stuttering or considerable ADO was checked using Micro-Checker v2.2.3\u003csup\u003e56\u003c/sup\u003e. Departures from HWE per locus and pairwise linkage disequilibrium (LD) were calculated using GENEPOP v4.7.5\u003csup\u003e57,58\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMitochondrial DNA sequences were manually corrected using Geneious v4.8.5\u003csup\u003e59\u003c/sup\u003e. A consensus sequence was obtained by aligning the forward and reverse sequences. Additionally, all polymorphic positions (i.e., substitutions, insertions, and deletions) were checked by eye. All sequences were aligned using Geneious’ in-built algorithm. The final alignment was trimmed to the length of the shortest sequence. To confirm the species identity, mtDNA sequences were compared to an in-house DNA barcoding reference database\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e using the NCBI’s BLAST+ (Basic Local Alignment Search Tool) command line tools\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003ch2\u003eGenetic diversity\u003c/h2\u003e\u003cp\u003eWe estimated the number of alleles per locus (n\u003csub\u003eA\u003c/sub\u003e), the effective number of alleles (n\u003csub\u003eE\u003c/sub\u003e), unbiased expected heterozygosity (uH\u003csub\u003eE\u003c/sub\u003e), the observed heterozygosity (H\u003csub\u003eO\u003c/sub\u003e), and the inbreeding coefficient (G\u003csub\u003eIS\u003c/sub\u003e) per island and for the overall dataset using GenoDive v3.06\u003csup\u003e61,62\u003c/sup\u003e. Additionally, the rarefied allelic richness (AR) across loci was estimated using the hierfstat R package v0.5-11\u003csup\u003e63\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe number of haplotypes, haplotype diversity (Hd), and nucleotide diversity (π) and Tajima’s D was estimated using DNAsp v6.12.03\u003csup\u003e64\u003c/sup\u003e. To assess relationships between haplotypes, haplotype networks were constructed based on statistical parsimony using TCS v1.21\u003csup\u003e65\u003c/sup\u003e visualised using tcsBU\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. To describe genetic variation, we also used Multidimensional Scaling analysis (MDS) on pairwise genetic distances between haplotypes. Genetic distances were calculated based on the best-fit model of molecular evolution which was identified using ModelFinder\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e restricted to the models available in ape 5.7.1 R package\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. The model TN93 was selected based on the Bayesian Information Criteria (BIC). The MDS analysis was conducted using the vegan v2.6.4 R package\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. R packages and statistical analysis were run under R v4.2.2\u003csup\u003e70\u003c/sup\u003e coupled with RStudio v2023.06.2 + 561\u003csup\u003e71\u003c/sup\u003e.\u003c/p\u003e\u003ch2\u003ePopulation structure\u003c/h2\u003e\u003cp\u003eEstimates of pairwise fixation index (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e) between islands as estimated using microsatellite loci were obtained using hierfstat v0.5-11 R package. Genetic variation between samples was visualised by Principal Components Analysis (PCA) using adegenet v2.1.10\u003csup\u003e72\u003c/sup\u003e and vegan v2.6.4 R packages. Missing genotyped loci across individual profiles were replaced by the mean allelic frequencies. Allelic frequencies were left unscaled.\u003c/p\u003e\u003cp\u003eAdditionally, population structure was assessed using STRUCTURE v2.3.4\u003csup\u003e73\u003c/sup\u003e. STRUCTURE was run using the admixture model with correlated allele frequencies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Ten independent runs were conducted with inferred genetic clusters (\u003cem\u003eK\u003c/em\u003e) varying between one to eight, a burn-in period of 100,000 steps followed by 1,000,000 MCMC iterations. The most likely number of \u003cem\u003eK\u003c/em\u003e was estimated using the log likelihood of the data\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e, and the degree of change of log likelihood between successive clusters (∆\u003cem\u003eK\u003c/em\u003e)\u003csup\u003e75\u003c/sup\u003e. The individual probability of assignment to each genetic cluster (Q) across multiple \u003cem\u003eK\u003c/em\u003e values were aligned across runs using the CLUMPP greedy algorithm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. All post-processing procedures of the STRUCTURE results were performed using pophelperShiny R package\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTwo potential sources of bias were signalled a priori in this dataset, unbalanced sampling between putative structured populations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, and the inclusion of highly related individuals typical to non-invasive genetic datasets from arboreal primate species\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. To test the effect of an unbalanced sample size between sampling locations in STRUCTURE, an alternative set of ancestry prior settings was employed \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. This alternative set of priors included estimating the individual values of alpha for each genetic cluster with initial \u003cem\u003ealpha\u003c/em\u003e set to 1/\u003cem\u003eK\u003c/em\u003e (expected), and uncorrelated allele frequencies between clusters\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. To inspect whether population sub-structure was being detected due to the presence of highly related individuals, STRUCTURE was re-run with a reduced dataset where one individual from each significantly related dyad was removed. To assess relatedness between individuals, we used the Queller and Goodnight’s estimator\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e within islands in Kingroup v2_101202\u003csup\u003e80\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe contribution of geographic locations on genetic differentiation was estimated by combining redundancy analysis (RDA) and trend-surface analysis using vegan v2.6.4 R package. Redundancy analysis combines an ordination method (PCA) with multiple regressions of independent predictors, here a polynomial trend-surface of the geographic locations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. For the matrices of geographic variables, we generated a third-degree orthogonal polynomial trend-surface of the geographic coordinates (\u003cem\u003elong, lat, long * lat, long\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003elat\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003elong\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e* lat, long * lat\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003elong\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003elat\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e). Third-degree orthogonal polynomials allow modelling of linear gradients and other more complex patterns over the trend-surface \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. A forward selection procedure was applied to prevent a possible over-fitting of the multiple regression. We selected a stringent significance level of 0.01 and the adjusted determination coefficient (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eadj\u003c/em\u003e\u003c/sub\u003e) as stopping criteria\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e to account for the increased type-I error rates due to multiple testing. Subsequently, the variance inflation factor (VIF) of the variables was estimated, and highly collinear variables (VIF \u0026gt; 5) were removed in a stepwise manner. After conducting the selection procedure, the geographic variables \u003cem\u003elong, lat, long * lat, long\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, were included as explanatory variables. Statistical significance of the multiple regression models and each of the resulting canonical axes was obtained by ANOVA-like permutation tests (9,999 permutations).\u003c/p\u003e\u003cp\u003eTo explore the existence of areas within the archipelago with historically higher or lower gene flow than expected under a strictly isolation-by-distance (IBD) model, we estimated Effective Migration Surfaces using EEMS software\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. EEMS is expected to not to be affected by some degree of location uncertainty \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. Thus, genotype profiles from tissue samples whose exact origin within the sampled island was unknown were included. For these genotype profiles, their sampling locations were estimated by jittering around the centroid of the islands. Initially, we explored EEMS models for increasing deme sizes (200, 400 and 800 demes) and optimised the variances for the proposal distributions. Optimisation runs consisted of three independent MCMC chains of 1,000,000 iterations, burn-in of 200,000, and thinning of 2,000. The optimal number of demes was selected based on the determination coefficient (r\u003csup\u003e2\u003c/sup\u003e) between the observed and fitted pairwise genetic dissimilarities between and within demes. The final EEMS analysis was run for eight independent chains of 5,000,000 MCMC iterations, burn-in of 1,000,000, and thinning of 10,000. Plotting of the effective migration surfaces and visual inspection of the convergence of the MCMC chains was conducted using reemsplots2 v0.1.0\u003csup\u003e84\u003c/sup\u003e and maptools v1.1-8\u003csup\u003e85\u003c/sup\u003e R packages.\u003c/p\u003e\u003ch2\u003eEthical note\u003c/h2\u003e\u003cp\u003eOur research complied with ethical guidelines, rules and protocols approved by the Institute for Biodiversity and Protected Areas (IBAP), Guinea-Bissau, and CIBIO-InBIO, Portugal, having adhered to the set legal requirements. All except ten samples were obtained non-invasively from unidentified individuals without manipulation or disruption of their daily behaviour. Invasive samples were collected opportunistically from animals already deceased. Collection of invasive samples were free of charge. The local CITES focal point (Direção Geral de Florestas e Fauna) authorised exportation of samples. IBAP authorised collection of biological samples and transportation to Portugal. Instituto para a Conservação da Natureza e Florestas (ICNF), and Direção Geral de Veterinária (DGV), Portugal, authorised importation of samples (CITES Import Permits 18PTLX005921). Nagoya protocol was not in place in Guinea-Bissau at the time of sample collection (2016).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe dedicate this chapter to the memory of Michael W Bruford - our mentor, colleague and friend. His enthusiasm, guidance, and support were key to the success of this work and to advance the knowledge on conservation genetics of Guinea-Bissau primates. We would like to acknowledge the Guinea-Bissau governmental agency Instituto de Biodiversidade e \u0026Aacute;reas Protegidas (IBAP), namely to the former director Dr. Alfredo Silva and Dr. Justino Biai, and to the directors of protected areas and staff members - Dr. Abilio Said, Dr. Augusto C\u0026aacute;, Dr. Jo\u0026atilde;ozinho Man\u0026eacute; and Dr. Sadjo Danfa, for fieldwork and sampling permits and to Abel Vieira, Iaia Cassama, Benjamin Indeque, Braima Bemba Cant\u0026eacute; for the support in fieldwork logistics. We acknowledge the Direc\u0026ccedil;\u0026atilde;o Geral de Florestas e Fauna (DGFF) and CITES focal person in Guinea-Bissau for sample exportation permits; to the research assistants and guides Sadjo Camar\u0026aacute;, Mamadu Soares, Mamadu Tur\u0026eacute;, Idrissa Camar\u0026aacute;; to Isabella Espinosa and Helena Foito for logistical support in Bissau. We are grateful to Luis Palma for facilitating samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Funda\u0026ccedil;\u0026atilde;o para a Ci\u0026ecirc;ncia e Tecnologia through the project PRIMATOMICS (PTDC/IVC-ANT/3058/2014) and project (LA/P/0048/2020), and by funders of the PRIMACTION project (the Born Free Foundation, Chester Zoo Conservation Fund, Primate Conservation Incorporated, Mohamed Bin Zayed - Project 232533027) and by sponsorship from the following Portuguese private companies - CAROSI, C\u0026aacute;psulas do Norte, Camarc, JA-Rolhas e C\u0026aacute;psulas). MJFS worked under an FCT contract (https://doi.org/10.54499/CEECIND/01937/2017/CP1423/CT0010). ICC, FB and IP were supported by FCT-doctoral fellowships (ICC: https://doi.org/10.54499/SFRH/BD/146509/2019; FB: https://doi.org/10.54499/2020.05839.BD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation: MJFS, ICC, NF, SLD, TM, MWB; Investigation: ICC, NF, SLD, FB; Formal analysis: ICC; Data Curation: ICC, MJFS, FB; Visualisation: ICC; Writing - Original Draft: ICC, MJFS, IMR; Writing - Review \u0026amp; Editing: all authors; Supervision: MJFS, IMR, MWB; Project administration: MJFS, ICC, NF, SLD; Resources: MJFS, TM, FS, IMR, AR; Funding acquisition: MJFS, TM, FS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that supports the findings of this study will be made available at Cardiff University\u0026rsquo;s Open Data repository/Figshare (https://research-data.cardiff.ac.uk) upon acceptance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKueffer, C. \u0026amp; Kinney, K. What is the importance of islands to environmental conservation? \u003cem\u003eEnviron. Conserv.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e, 311\u0026ndash;322 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraje, T. J., Leppard, T. P., Fitzpatrick, S. M. \u0026amp; Erlandson, J. M. Archaeology, historical ecology and anthropogenic island ecosystems. \u003cem\u003eEnviron. Conserv.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e, 286\u0026ndash;297 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartin, C. A. et al. Runs of homozygosity reveal past bottlenecks and contemporary inbreeding across diverging populations of an island-colonizing bird. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e, 1972\u0026ndash;1989 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllendorf, F. W., Luikart, G. \u0026amp; Aitken, S. N. \u003cem\u003eConservation and the Genetics of Populations\u003c/em\u003e (John Wiley \u0026amp; Sons, Ltd, 2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColmonero-Costeira, I. et al. Genomic Signatures of Island Colonisation in Highly Diverse Primates. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e, e17815 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantini, L. et al. Global drivers of population density in terrestrial vertebrates. \u003cem\u003eGlob l Ecol. Biogeogr.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 968\u0026ndash;979 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKimura, M., Weiss, G. H., THE STEPPING STONE MODEL \u0026amp; OF POPULATION STRUCTURE AND THE DECREASE OF GENETIC CORRELATION WITH DISTANCE. \u003cem\u003eGenetics\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e, 561\u0026ndash;576 (1964).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVellend, M. Island Biogeography of Genes and Species. \u003cem\u003eAm. Nat.\u003c/em\u003e \u003cb\u003e162\u003c/b\u003e, 358\u0026ndash;362 (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrsini, L., Vanoverbeke, J., Swillen, I., Mergeay, J. \u0026amp; De Meester, L. Drivers of population genetic differentiation in the wild: Isolation by dispersal limitation, isolation by adaptation and isolation by colonization. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e, 5983\u0026ndash;5999 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCostanzi, J. M. \u0026amp; Steifetten, \u0026Oslash;. Island biogeography theory explains the genetic diversity of a fragmented rock ptarmigan (Lagopus muta) population. \u003cem\u003eEcol. Evol.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 3837\u0026ndash;3849 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapadopoulou, A. \u0026amp; Knowles, L. L. Genomic tests of the species-pump hypothesis: Recent island connectivity cycles drive population divergence but not speciation in Caribbean crickets across the Virgin Islands. \u003cem\u003eEvolution\u003c/em\u003e \u003cb\u003e69\u003c/b\u003e, 1501\u0026ndash;1517 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKimura, T., Yamada, T., Sakaguchi, S., Ito, M. \u0026amp; Maki, M. Multiple colonizations and genetic differentiation in goldenrod populations on recently formed nearshore islands. \u003cem\u003eJ. Biogeogr.\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e, 836\u0026ndash;852 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlves, P. H. \u003cem\u003eA Geologia Sedimentar da Guin\u0026eacute;-Bissau da An\u0026aacute;lise Geral e Evolu\u0026ccedil;\u0026atilde;o do Conhecimento ao Estudo do Cenoz\u0026oacute;ico\u003c/em\u003e (Universidade de Lisboa, PhD, 2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadeira, J. P. Bijagos Archipelago: Impacts and Challenges for Environmental Sustainability. \u003cem\u003eInterEspa\u0026ccedil;o: Revista de Geografia e Interdisciplinaridade\u003c/em\u003e. \u003cb\u003e2\u003c/b\u003e, 291\u0026ndash;305 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRainho, A. \u0026amp; Palmeirim, J. Mam\u0026iacute;feros Terrestres. in Parque Nacional Marinho de Jo\u0026atilde;o Vieira e Poil\u0026atilde;o: Biodiversidade e Conserva\u0026ccedil;\u0026atilde;o (eds Catry, P. \u0026amp; Regalla, A.) (IBAP - Instituto da Biodiversidade e das \u0026Aacute;reas Protegidas, (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRebelo, R. \u0026amp; Catry, P. O arquip\u0026eacute;lago dos Bijag\u0026oacute;s (Guin\u0026eacute;-Bissau) - valores de biodiversidade e potencialidades para a investiga\u0026ccedil;\u0026atilde;o cient\u0026iacute;fica. \u003cem\u003eEcologia\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 8\u0026ndash;15 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsuda Goodwin, R. et al. Cercopithecus petaurista. \u003cem\u003eThe IUCN Red List. Threatened Species\u003c/em\u003e \u003cb\u003e2020\u003c/b\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePruetz, J. D., Socha, A. \u0026amp; Kante New Range Record for the Lesser Spot-Nosed Guenon (Cercopithecus Petaurista) in Southeastern Senegal. \u003cem\u003eAfr. Primates\u003c/em\u003e. \u003cb\u003e7\u003c/b\u003e, 64\u0026ndash;66 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColmonero-Costeira, I., Minh\u0026oacute;s, T., Djal\u0026oacute;, B. \u0026amp; Fernandes, N. Ferreira da Silva, M. Confirma\u0026ccedil;\u0026atilde;o da ocorr\u0026ecirc;ncia de primatas n\u0026atilde;o-humanos no Arquip\u0026eacute;lago dos Bijag\u0026oacute;s com base em t\u0026eacute;cnicas de identifica\u0026ccedil;\u0026atilde;o molecular. \u003cem\u003eSintidus\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 145\u0026ndash;179 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColmonero-Costeira, I. et al. Notes on the conservation threats to the western lesser spot-nosed monkey (Cercopithecus petaurista buettikoferi) in the Bijag\u0026oacute;s Archipelago (Guinea-Bissau, West Africa). \u003cem\u003ePrimates\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 581\u0026ndash;587 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGippoliti, S. \u0026amp; Dell\u0026rsquo;Omo, G. Primates of Guinea-Bissau, West Africa: distribution and conservation status. \u003cem\u003ePrimate Conserv.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e, 73\u0026ndash;77 (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira da Silva, M. J. et al. Using miniaturized laboratory equipment and DNA barcoding to improve conservation genetics training and identify illegally traded species. \u003cem\u003eConserv Biol\u003c/em\u003e e70165 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira da Silva, M. J. et al. Assessing the impact of hunting pressure on population structure of Guinea baboons (Papio papio) in Guinea-Bissau. \u003cem\u003eConserv. Genet.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 1339\u0026ndash;1355 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinh\u0026oacute;s, T. et al. Genetic evidence for spatio-temporal changes in the dispersal patterns of two sympatric African colobine monkeys. \u003cem\u003eAm. J. Phys. Anthropol.\u003c/em\u003e \u003cb\u003e150\u003c/b\u003e, 464\u0026ndash;474 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGerini, F. \u003cem\u003eStructure and connectivity of sympatric primate species across a human-dominated landscape: population genetics of Western Chimpanzee (Pan troglodytes verus) and Guinea Baboon (Papio papio) in Guinea Bissau\u003c/em\u003e (University of Pisa, MSc,, 2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorges, F. \u003cem\u003eA country-level genetic survey of the IUCN critically endangered western chimpanzee (Pan troglodytes verus) in Guinea-Bissau\u003c/em\u003e (University of Porto, 2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJensen, A. et al. Complex Evolutionary History With Extensive Ancestral Gene Flow in an African Primate Radiation. \u003cem\u003eMol Biol. Evol\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuderna, L. F. K. et al. A global catalog of whole-genome diversity from 233 primate species. \u003cem\u003eSci. (1979)\u003c/em\u003e. \u003cb\u003e380\u003c/b\u003e, 906\u0026ndash;913 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerman, R. W. et al. Whole genome sequencing reveals stepping-stone dispersal buffered against founder effects in a range expanding seabird. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, e17282 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorsburgh, K. A., Matisoo-Smith, E., Glenn, M. E. \u0026amp; Bensen, K. J. Genetic Study of Translocated Guenons: Cercopithecus mona on Grenada. in The Guenons: Diversity and Adaptation in African Monkeys 289\u0026ndash;306 (Kluwer Academic, Boston, (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlenn, M. E. \u0026amp; Bensen, K. J. The mona monkeys of Grenada, S\u0026atilde;o Tom\u0026eacute; and Pr\u0026iacute;ncipe: Long-term persistence of a guenon in permanent fragments and implications for the survival of forest primates in protected areas. \u003cem\u003ePrimates Fragments: Complex. Resilience\u003c/em\u003e 413\u0026ndash;422 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Der Kuyl, A. C., Dekker, J. T. \u0026amp; Goudsmit, J. St. Kitts green monkeys originate from West Africa: Genetic evidence from feces. \u003cem\u003eAm. J. Primatol.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 361\u0026ndash;364 (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHazevoet, C. J. \u0026amp; Masseti, M. On the history of the green monkey Chlorocebus sabaeus (L., 1766) in the Cape Verde Islands, with notes on other introduced mammals. \u003cem\u003eZool. Caboverdiana\u003c/em\u003e. \u003cb\u003e2\u003c/b\u003e, 12\u0026ndash;24 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlmeida, L., Colmonero-Costeira, I., Silva, M. J. F., da, Veracini, C. \u0026amp; Vasconcelos, R. Insights into the Geographical Origins of the Cabo Verde Green Monkey. \u003cem\u003eGenes\u003c/em\u003e 15, (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartin, A. et al. Isolation, marine transgression and translocation of the bare-nosed wombat (Vombatus ursinus). \u003cem\u003eEvol. Appl.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 1114\u0026ndash;1123 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrossen, C., Biebach, I., Angelone-Alasaad, S., Keller, L. F. \u0026amp; Croll, D. Population genomics analyses of European ibex species show lower diversity and higher inbreeding in reintroduced populations. \u003cem\u003eEvol. Appl.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 123\u0026ndash;139 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003edu Plessis, S. J. et al. Genetic diversity and cryptic population re-establishment: management implications for the Bojer\u0026rsquo;s skink (Gongylomorphus bojerii). \u003cem\u003eConserv. Genet.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 137\u0026ndash;152 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e​​Kopp, G. H., Fischer, J., Patzelt, A., Roos, C. \u0026amp; Zinner, D. Population genetic insights into the social organization of Guinea baboons (Papio papio): Evidence for female-biased dispersal. \u003cem\u003eAm. J. Primatol.\u003c/em\u003e \u003cb\u003e77\u003c/b\u003e, 878\u0026ndash;889 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKopp, G. H. et al. The Influence of Social Systems on Patterns of Mitochondrial DNA Variation in Baboons. \u003cem\u003eInt. J. Primatol.\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e, 210\u0026ndash;225 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRowe, N. \u0026amp; Myers, M. \u003cem\u003eAll the World\u0026rsquo;s Primates\u003c/em\u003e (Pogonias, 2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos, C. et al. Understanding Differences Between Phylogenetic and Pedigree-Derived mtDNA Mutation Rate: A Model Using Families from the Azores Islands (Portugal). \u003cem\u003eMol. Biol. Evol.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e, 1490\u0026ndash;1505 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFunk, W. C., McKay, J. K., Hohenlohe, P. A. \u0026amp; Allendorf, F. W. Harnessing genomics for delineating conservation units. \u003cem\u003eTrends Ecol. Evol.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 489\u0026ndash;496 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira da Silva, M. J., Minh\u0026oacute;s, T., S\u0026aacute;, R., Casanova, C. \u0026amp; Bruford, M. W. A Qualitative Assessment of Guinea-Bissau\u0026rsquo;s Hunting History and Culture-and Their Implications for Primate Conservation. \u003cem\u003eAfr. Primates\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e, 1\u0026ndash;18 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinh\u0026oacute;s, T. et al. DNA identification of primate bushmeat from urban markets in Guinea-Bissau and its implications for conservation. \u003cem\u003eBiol. Conserv.\u003c/em\u003e \u003cb\u003e167\u003c/b\u003e, 43\u0026ndash;49 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinh\u0026oacute;s, T. et al. Genetic consequences of human forest exploitation in two colobus monkeys in Guinea Bissau. \u003cem\u003eBiol. Conserv.\u003c/em\u003e \u003cb\u003e194\u003c/b\u003e, 194\u0026ndash;208 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira da Silva, M. J. et al. Estimating the Effective Population Size Across Space and Time in the Critically Endangered Western Chimpanzee in Guinea-Bissau: Challenges and Implications for Conservation Management. \u003cem\u003eEvol. Appl.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, e70162 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira da Silva, M. J. et al. Disrupted dispersal and its genetic consequences: Comparing protected and threatened baboon populations (Papio papio) in West Africa. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, e0194189 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCardoso, A. \u003cem\u003eSaberes e pr\u0026aacute;ticas tradicionais da etnia Bijag\u0026oacute;s e suas rela\u0026ccedil;\u0026otilde;es com a organiza\u0026ccedil;\u0026atilde;o, a gest\u0026atilde;o e a conserva\u0026ccedil;\u0026atilde;o da biodiversidade na Guin\u0026eacute;-Bissau\u003c/em\u003e (Universidade Federal da Bahia, 2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoeder, A. D., Archer, F. I., Poinar, H. N. \u0026amp; Morin, P. A. A novel method for collection and preservation of faeces for genetic studies. \u003cem\u003eMol. Ecol. Notes\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 761\u0026ndash;764 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonin, A. et al. How to track and assess genotyping errors in population genetics studies. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 3261\u0026ndash;3273 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePompanon, F., Bonin, A., Bellemain, E. \u0026amp; Taberlet, P. Genotyping errors: causes, consequences and solutions. \u003cem\u003eNat. Rev. Genet.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 847\u0026ndash;859 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVali\u0026egrave;re, N. \u0026amp; Berthier, P. GEMINI: software for testing the effects of genotyping errors and multitubes approach for individual identification. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 83\u0026ndash;86 (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiquel, C. et al. Quality indexes to assess the reliability of genotypes in studies using noninvasive sampling and multiple-tube approach. \u003cem\u003eMol. Ecol. Notes\u003c/em\u003e. \u003cb\u003e6\u003c/b\u003e, 985\u0026ndash;988 (2006).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeakall, R. \u0026amp; Smouse, P. E. GenALEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, 2537\u0026ndash;2539 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalinowski, S. T., Taper, M. L. \u0026amp; Marshall, T. C. Revising how the computer program cervus accommodates genotyping error increases success in paternity assignment. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e, 1099\u0026ndash;1106 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. \u0026amp; Shipley, P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. \u003cem\u003eMol. Ecol. Notes\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 535\u0026ndash;538 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRousset, F. GENEPOP\u0026rsquo;007: A complete re-implementation of the GENEPOP software for Windows and Linux. \u003cem\u003eMol. Ecol. Resour.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 103\u0026ndash;106 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaymond, M. \u0026amp; Rousset, F. GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism. \u003cem\u003eJ. Hered\u003c/em\u003e. \u003cb\u003e86\u003c/b\u003e, 248\u0026ndash;249 (1995).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKearse, M. et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, 1647\u0026ndash;1649 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamacho, C. et al. BLAST+: Architecture and applications. \u003cem\u003eBMC Bioinform.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1\u0026ndash;9 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeirmans, P. G. genodive version 3.0: Easy-to-use software for the analysis of genetic data of diploids and polyploids. \u003cem\u003eMol. Ecol. Resour.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 1126\u0026ndash;1131 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeirmans, P. G. \u0026amp; Van Tienderen, P. H. genotype and genodive: two programs for the analysis of genetic diversity of asexual organisms. \u003cem\u003eMol. Ecol. Notes\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 792\u0026ndash;794 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoudet, J. \u0026amp; Jombart, T. Estimation and Tests of Hierarchical F-Statistics. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/hierfstat/hierfstat.pdf\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/hierfstat/hierfstat.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. \u003cem\u003eMol. Biol. Evol.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e, 3299\u0026ndash;3302 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTempleton, A. R., Crandall, K. A. \u0026amp; Sing, C. F. A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. \u003cem\u003eGenetics\u003c/em\u003e \u003cb\u003e132\u003c/b\u003e, 619\u0026ndash;633 (1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uacute;rias, D. et al. tcsBU: a tool to extend TCS network layout and visualization. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e, 627\u0026ndash;628 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., Von Haeseler, A. \u0026amp; Jermiin, L. S. ModelFinder: Fast model selection for accurate phylogenetic estimates. \u003cem\u003eNat. Methods\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e, 587\u0026ndash;589 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParadis, E. \u0026amp; Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e, 526\u0026ndash;528 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOksanen, J. et al. vegan: Community Ecology Package. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/vegan/vegan.pdf\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/vegan/vegan.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoreTeam., R. R: A language and environment for statistical computing. (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org\u003c/span\u003e\u003cspan address=\"https://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePosit team. RStudio: Integrated Development for R. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://posit.co\u003c/span\u003e\u003cspan address=\"https://posit.co\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJombart, T. adegenet: a R package for the multivariate analysis of genetic markers. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 1403\u0026ndash;1405 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePritchard, J. K., Stephens, M. \u0026amp; Donnelly, P. Inference of population structure using multilocus genotype data. \u003cem\u003eGenetics\u003c/em\u003e \u003cb\u003e155\u003c/b\u003e, 945\u0026ndash;959 (2000).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFalush, D., Stephens, M. \u0026amp; Pritchard, J. K. Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies. \u003cem\u003eGenetics\u003c/em\u003e \u003cb\u003e164\u003c/b\u003e, 1567\u0026ndash;1587 (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvanno, G., Regnaut, S. \u0026amp; Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. \u003cem\u003eMol. Ecol.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 2611\u0026ndash;2620 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJakobsson, M., Rosenberg, N. A. \u0026amp; CLUMPP A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 1801\u0026ndash;1806 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrancis, R. M. pophelper: an R package and web app to analyse and visualize population structure. \u003cem\u003eMol. Ecol. Resour.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e, 27\u0026ndash;32 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, J. The computer program structure for assigning individuals to populations: easy to use but easier to misuse. \u003cem\u003eMol. Ecol. Resour.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e, 981\u0026ndash;990 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQueller, D. C. \u0026amp; Goodnight, K. F. Estimating Relatedness Using Genetic Markers. \u003cem\u003eEvolution\u003c/em\u003e \u003cb\u003e43\u003c/b\u003e, 258\u0026ndash;275 (1989).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonovalov, D. A., Manning, C. \u0026amp; Henshaw, M. T. KINGROUP: A program for pedigree relationship reconstruction and kin group assignments using genetic markers. \u003cem\u003eMol. Ecol. Notes\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, 779\u0026ndash;782 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegendre, P. \u0026amp; Legendre, L. \u003cem\u003eNumerical Ecology\u003c/em\u003e. (Elsevier B.V., Oxford, UK, (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlanchet, F. G., Legendre, P. \u0026amp; Borcard, D. Forward selection of explanatory variables. \u003cem\u003eEcology\u003c/em\u003e \u003cb\u003e89\u003c/b\u003e, 2623\u0026ndash;2632 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetkova, D., Novembre, J. \u0026amp; Stephens, M. Visualizing spatial population structure with estimated effective migration surfaces. \u003cem\u003eNat. Genet.\u003c/em\u003e \u003cb\u003e48\u003c/b\u003e, 94\u0026ndash;100 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetkova, D. reemsplots2: Generate plots to inspect and visualize the results of EEMS. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/dipetkov/reemsplots2\u003c/span\u003e\u003cspan address=\"https://github.com/dipetkov/reemsplots2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBivand, R. \u0026amp; Lewin-Koh, N. maptools: Tools for Handling Spatial Object. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=maptools\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=maptools\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"guenon, islands, genetic survey, gene flow, non-invasive genetics, UNESCO","lastPublishedDoi":"10.21203/rs.3.rs-9213843/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9213843/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInsular populations are typically more vulnerable to the loss of genetic diversity than their mainland counterparts and are often of conservation concern. The Bijag\u0026oacute;s Archipelago in Guinea-Bissau is a West African biodiversity hotspot and a recently designated UNESCO World Heritage Site. It hosts the westernmost populations of the spot-nosed monkey (\u003cem\u003eCercopithecus petaurista\u003c/em\u003e), a species thought to have been extirpated from mainland and threatened by anthropogenic activities. Here, we conducted a non-invasive DNA survey across five of the largest islands with known occurrences. We used eleven microsatellite loci and a fragment of the mitochondrial d-loop to estimate genetic diversity and population structure. Using 64 individual profiles we found that populations may have lost genetic diversity but were not depauperated. Genetic diversity was heterogeneous and populations were structured by island. Higher levels of historical gene flow between distant islands than between nearby ones suggest a pattern that is inconsistent with stepwise colonisation typical of island systems. Our study suggests a complex colonisation history which may have been influenced by human movements in the area. Canhabaque Island holds the most diverse populations and may support reintroductions in the mainland. We suggest conservation management should be carried out by island to safeguard long-term persistence.\u003c/p\u003e","manuscriptTitle":"Genetic diversity and population structure of the spot-nosed monkey (Cercopithecus petaurista) of the Bijagós Archipelago, Guinea-Bissau, West Africa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-14 16:16:27","doi":"10.21203/rs.3.rs-9213843/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-06T13:39:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T16:46:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28497828750530204394417994135521815229","date":"2026-05-04T17:32:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198869904594382031397129790440258649578","date":"2026-04-23T04:47:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5486368788912738333483752406832146583","date":"2026-04-21T13:27:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-21T12:36:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112478968083504179988159957777725609183","date":"2026-04-12T17:10:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42115372490059034021009471034034511454","date":"2026-04-09T16:52:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330361263310319496089961365926597496433","date":"2026-04-09T08:52:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-07T16:21:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-07T16:15:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-06T06:04:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-02T11:18:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-02T10:10:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5a56b600-d7fe-44c5-8166-faedd1f1154a","owner":[],"postedDate":"April 14th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-06T13:39:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T16:46:01+00:00","index":113,"fulltext":""},{"type":"reviewerAgreed","content":"28497828750530204394417994135521815229","date":"2026-05-04T17:32:03+00:00","index":103,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":66312094,"name":"Biological sciences/Ecology"},{"id":66312095,"name":"Earth and environmental sciences/Ecology"},{"id":66312096,"name":"Biological sciences/Evolution"},{"id":66312097,"name":"Biological sciences/Genetics"}],"tags":[],"updatedAt":"2026-05-06T13:54:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-14 16:16:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9213843","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9213843","identity":"rs-9213843","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}