Over the last two centuries, researchers developed several assessments to evaluate the multidimensional construct of imagery. However, no comprehensive systematic review (SR) exists for imagery ability evaluation methods and an in-depth quality evaluation of their psychometric properties.We performed a comprehensive systematic search in six databases in the disciplines of sport, psychology, medicine, education: SPORTDiscus, PsycINFO, Cochrane Library, Scopus, Web of Science, and ERIC. Two reviewers independently identified and screened articles for selection. COSMIN checklist was used to evaluate the methodological quality of the studies. All included assessments were evaluated for quality using criteria for good measurement properties. The evidence synthesis was summarised by using the GRADE approach.n = 15), (2) mental imagery (n = 48) and (3) mental chronometry (n = 2). Methodological quality of studies was mainly doubtful or inadequate. The psychometric properties of most assessments were insufficient or indeterminate. The best rated assessments with sufficient psychometric properties were MIQ, MIQ-R, MIQ-3, and VMIQ-2 for evaluation of motor imagery ability. Regarding mental imagery evaluation, only SIAQ and VVIQ showed sufficient psychometric properties.In total, 121 articles reporting 155 studies and describing 65 assessments were included. We categorised assessments based on their construct on: (1) motor imagery (Various assessments exist to evaluate an individual’s imagery ability within different dimensions or modalities of imagery in different disciplines. However, the psychometric properties of most assessments are insufficient or indeterminate. Several assessments should be revised and further validated. Moreover, most studies were only evaluated with students. Further cross-disciplinary validation studies are needed including older populations with a larger age range. Our findings allow clinicians, coaches, teachers, and researchers to select a suitable imagery ability assessment for their setting and goals based on information about the focus and quality of the assessments.CRD42017077004.PROSPERO The online version contains supplementary material available at 10.1186/s12916-022-02295-3. Imagery, defined as the representation and the accompanying experience of any sensory information without a direct external stimulus , or ‘seeImagery is a multidimensional construct  with widWatt  and CummThe measurement of this multidimensional and multimodal construct has proven to be complex  and eachThe aim of the present extensive and comprehensive systematic literature review was therefore to evaluate all available imagery ability assessments across four disciplines, regardless of the imagery technique used to answer the question: What imagery ability assessments exist in the fields of sports, psychology, medicine, and education, and what are their psychometric properties? For the interested clinician, coach, teacher, and researcher, our review provides (1) a systematic classification of the imagery ability assessments based on its construct, (2) a summary of the current level of evidence for the psychometric properties of the selected imagery ability assessments, and (3) all specific characteristics of the imagery ability assessment: version, subscales, scoring, equipment needed, etc.In order to provide a comprehensive overview, we included all assessments that cover any aspect of imagery process and ability to vividly generate, transform, inspect, and maintain a mental image. Moreover, we included also assessments, which evaluated the frequency of use of imagery, the preference to think in words or images, and the temporal coupling of mental and physical practice.This systematic review provides interested readers with a quick overview to select an appropriate imagery ability assessment for their current setting and goals based on information provided regarding the focus and quality of the imagery ability assessments.https://www.crd.york.ac.uk/prospero/, registration number CRD42017077004) and published [The protocol for this review was registered with the International Prospective Register of Systematic Reviews  and a librarian from the medical library of the University of Zurich independently performed the electronic search between September and October, 2017, in SPORTDiscus (1892 to current date of search), PsycINFO (1887 to current date of search), Cochrane Library (current issue), Scopus (1996 to current date of search), Web of Science (1900 to current date of search) and ERIC (1966 to current date of search). The search strategy included (1) construct: motor imagery, mental imagery, mental rehearsal, movement imagery, mental practice, mental training; (2) instrument: measure, questionnaire, scale, assessment; and (3) the filter for measurement properties by Terwee et al.  adapted There was no limitation on a specific population . Additionally, there was no restriction on age, gender, or health status. We included all original articles published in English and German, which either developed mental or motor imagery assessments or validated their psychometric properties.Articles were excluded if the authors only used neurophysiological methods to evaluate imagery ability .Figure Four researchers  performed the data extraction into Microsoft Excel . ZS checked all data for accuracy. The following data were extracted: (1) characteristics of included articles: first author, year of publication, country of origin, study design, and number and main characteristics of participants ; (2) general characteristics of the assessment instrument: name, language, version, construct of evaluation, number of items, subscales, scoring, assessment format, time and equipment needed, examiner qualifications, and costs; and (3) data on the psychometric properties of the assessments: validity, reliability, and responsiveness.Two researches (ZS and CSA) carried out the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) evaluation independently. One study was evaluated by ZS and FB, because CSA was the first author. The COSMIN Risk of Bias checklist was applied to assess the methodological quality of studies on measurement properties . The COSBased on the quality criteria for measurement properties proposed by Terwee et al.  and updaStrong correlation (at least 0.50) was expected if a related construct was measured with the comparator instrument.Correlation between different modalities or dimensions of imagery, e.g. between vividness and auditory imagery, should be very low (< 0.30).Correlation between subjective and objective assessments of imagery ability should be very low (< 0.30).Regarding known-group validity based on previous evidence, no any sex differences regarding imagery ability were expected.Regarding the testing for construct validity, some hypotheses about expected differences between instruments were formulated by the reviewer team:Just recently, a modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach for grading the quality of the evidence in systematic reviews of PROMs was introduced . Four ofIn total, 3922 references were retrieved in October, 2017. The search update in January 2021 resulted in 1616 additional references. We identified 78 additional references through reference list screening. The kappa statistic after screening of titles and abstracts was 0.83 , and the percentage agreement between the raters was 98%. After selecting the full texts, the kappa was 0.76  and 85% percentage agreement was established. All distinguish between reviews have been discussed and the reviews agree on a decision.Motor imagery = movement imagery without engaging in its physical executionGeneral mental imagery in any sensorial modality,Spatial imagery or mental rotation = ability to rotate or manipulate mental images),Distinguish between use of different cognitive style , andUse of mental imagery (frequency of use in daily life).Mental imagery in four sub-categories:Mental chronometry as temporal coupling between real and imagined movements.Finally, 121 articles reporting 155 studies and describing 65 assessments from four disciplines were included in the present review. We categorised assessments based on their construct:Most studies were carried out in the fields of psychology and sport. We identified many assessments, which have been evaluated only with psychology students. Therefore, it was unclear whether those assessments should accordingly only be applied in the field of psychology. We defined such assessments as ‘not discipline specific’. Moreover, most studies evaluated different psychometric properties and according to COSMIN, each evaluation of a measurement property was separately assessed on its methodological quality. The overall rating of the quality of each study should be determined by taking the lowest rating of any standard in the box (e.g. ‘the worst score counts’ principle) . FurtherIn total, 33 out of the 121 articles focused on 15 motor imagery assessments: Florida Praxis Imagery Questionnaire (FPIQ), Imaprax, Kinesthetic and Visual Imagery Questionnaire (KVIQ-20) and short version KVIQ-10, Movement Imagery Questionnaire (MIQ), Revised Movement Imagery Questionnaire (MIQ-R), Movement Imagery Questionnaire-Revised second version (MIQ-RS), Movement Imagery Questionnaire-3 (MIQ-3), Movement Imagery Questionnaire for Children (MIQ-C), Test of Ability in Movement Imagery (TAMI), Test of Ability in Movement Imagery with Hands (TAMI-H), Vividness of Movement Imagery Questionnaire (VMIQ), Vividness of Haptic Movement Imagery Questionnaire (VHMIQ), Revised Vividness of Movement Imagery Questionnaire-2 (VMIQ-2) and the Wheelchair Imagery Ability Questionnaire (WIAQ). The characteristics of the included studies, their ‘risk of bias assessment/rating’, and their psychometric properties are presented in Tables In total, 30 out of the 33 motor imagery articles reported structural, criterion or construct validity. Only ten studies , 83, 89 N < 15) and were therefore downgraded for imprecision. Moreover, structural and construct validity of the MIQ-RS, TAMI, TAMI-H and VMIQ reported in several studies were rated as indeterminate.There is high evidence for sufficient structural validity regarding the MIQ-R, MIQ-3 and VMIQ-2 assessments. The MIQ-C showed also sufficient structural validity but with moderate evidence . Construct validity of the MIQ and WIAQ was sufficient, but with low evidence . The FPIQ and Imaprax were not evaluated for validity. Further, the structural and construct validity of the KVIQ  for different language versions ranged from insufficient to sufficient between studies. These psychometric properties were evaluated with different populations , multiple sclerosis (MS), or patients with orthopaedic problems). However, only one study per subgroup was identified, which meant that pooling the data was not feasible. Furthermore, the construct validity of the KVIQ was sufficient in two studies (with PD or with MS patients), but both studies had a very small sample size  and stated that a ‘reliability coefficient’ or ‘reliabilities’ were calculated without specific description on the types of coefficients that were calculated . In most cases, internal consistency was insufficient or indeterminate due to low evidence for sufficient structural validity. Only the MIQ-R, MIQ-3 and VMIQ-2 revealed a very clear sufficient internal consistency with a high evidence  which corresponds to a sufficient structural validity. The KVIQ showed sufficient test-retest reliability but with low evidence. However, the results were summarised only for patients after a stroke.Only two studies , 83 repon = 24): Auditory Imagery Scale (AIS), Auditory Imagery Questionnaire (AIQ), Bucknell Auditory Imagery Scale (BAIS), Betts Questionnaire Upon Mental Imagery , Betts Questionnaire Upon Mental Imagery , Clarity of Auditory Imagery Scale (CAIS), Gordon Test of Visual Imagery Control (TVIC), Imaging Ability Questionnaire (IAQ), Imagery Questionnaire by Lane, Kids Imaging Ability Questionnaire (KIAQ), Mental Imagery Scale (MIS), Plymouth sensory imagery Questionnaire (Psi-Q), Sport Imagery Ability Measure (SIAM), Revised Sport Imagery Ability Measure (SIAM-R), Sport Imagery Ability Questionnaire (SIAQ), Survey of mental imagery, Visual Elaboration Scale (VES), Vividness of Olfactory Imagery Questionnaire (VOIQ), Vividness of Object and Spatial Imagery Questionnaire (VOSI), Vividness of Visual Imagery Questionnaire (VVIQ), Revised version Vividness of Visual Imagery Questionnaire (VVIQ-2), Vividness of Visual Imagery Questionnaire- Revised version (VVIQ-RV), Vividness of Visual Imagery Questionnaire-Modified (VVIQ-M), Vividness of Wine Imagery Questionnaire (VWIQ).General mental imagery ability assessments (n = 12): Card Rotation Test, Cube-cutting Task (CCT), German Test of the Controllability of Motor Imagery (TKBV), Hand laterality task, Judgement test of foot and trunk laterality, Map Rotation Ability Test (MRAT), Mental Paper Folding (MPF), Mental Rotation of Three-Dimensional Objects, Measure of the Ability to Form Spatial Mental Imagery (MASMI), Measure of the Ability to Rotate Mental Images (MARMI), Shoulder specific left right judgement task (LRJT), Spatial Orientation Skills Test (SOST).Assessments to evaluate ability to rotate or manipulate mental images- mental rotation (n = 7): Object-Spatial Imagery Questionnaire (OSIQ), Object-Spatial Imagery and Verbal Questionnaire (OSVIQ), Paivio’s Individual Differences Questionnaire , Sussex Cognitive Styles Questionnaire (SCSQ), Verbalizer-Visualizer Questionnaire (VVQ).Assessments of mental imagery to distinguish between the use of different cognitive styles (n = 5): Children’s Active Play Imagery Questionnaire (CAPIQ), Exercise Imagery Questionnaire - Aerobic Version (EIQ-AV), Sport Imagery Questionnaire (SIQ), Sport Imagery Questionnaire for Children (SIQ-C), Spontaneus Use of Imagery Scale (SUIS).Assessments to evaluate use of imagery . Test-retest reliability was insufficient or indeterminate for most assessments due to an inappropriate time interval between the measurement sessions, and a poor reporting on the reliability coefficient calculation.Only one study  evaluateThe aim of this systematic review was to evaluate all available assessments measuring individual imagery ability and their psychometric properties. Assessments were categorised based on their construct: motor imagery, mental imagery, and mental chronometry. A summary of the current level of evidence regarding the psychometric properties of the selected assessments is provided in the Tables We included in our SR only assessments that comprise items that solely focus on imagery ability. Assessments like the Sport Mental Training Questionnaire (SMTQ)  were excThe methodological quality of most included studies was rated low. The reasons for this rating were for instance: a small sample size, inadequate statistical analysis or insufficient information reported. In particular, several studies calculated Cronbach’s alpha as multidimensional total score for internal consistency and not for each subscale of the assessment. The lack of reporting could lead to inaccuracy, because it is important to know the degree of inter-item correlation among the items for each subscale. Furthermore, some studies calculated the split-half reliability to report internal consistency. With this method, the correlation coefficient may not represent an accurate measure of reliability due to the fact that a single scale is being split into two scales, decreasing the reliability of the measure as a whole . As propOne possible reason for poor reporting is that the majority of the instruments were developed during the early 90s. A practical guide for conducting and reporting of such studies was published much later , 64, 174Further, reporting deficits in the selected studies resulted in an only substantial agreement with regard to the kappa statistic calculated between the ratings of ZS and CSA after full texts’ selection. For example, some reports did not use the usual terms for psychometric properties when describing the study aim , 167. ThThe psychometric properties for most of the assessments regarding construct validity (e.g. correlation with other measures) and criterion validity were rated as indeterminate or insufficient. These findings corresponded to previous studies , 48. A pAlmost all studies, when reporting psychometric properties of the comparator instrument or the ‘gold standard’ instrument, only reported about reliability , which is in most cases very high. Such assessments often lacked structural or criterion validity but authors did not critically discuss that. In addition, most studies were only conducted with students aged 12–28 years, who received a course credit for study participation.The best-evaluated assessments with sufficient psychometric properties were the MIQ, MIQ-R, MIQ-3 and VMIQ-2 for evaluation of motor imagery ability. They are mostly applied in the field of sport. All assessments are self-reports, very easy to use and evaluate vividness in two modalities: visual and kinaesthetic. Moreover, the MIQ-3 and VMIQ-2 evaluate also the perspective used during imagination: external or internal. The MIQ-3 is translated into several languages, which enables a wide use. The SIAQ as mental imagery assessment in sport showed sufficient psychometric properties, but the SIAQ is not able to distinguish between ease of imaging and vividness. The VVIQ was evaluated only with psychology students, and only internal consistency was sufficient. In the field of medicine, the KVIQ is the most evaluated assessment, focusing on vividness in two modalities: visual and kinaesthetic. The original version KVIQ-20 is translated into several languages, but due to the number of items, applying the KVIQ-20 can be quite time-consuming. Structural validity is particularly critical and further studies with large sample sizes and the use of a CFA are needed. Although all assessments described above are self-report, easy to use and cost-effective, a general limitation of these assessments is that they do not allow to control for imagery ability before or during an experiment.Our results demonstrate that there are a number of published instruments for measuring the imagery ability in different disciplines. We categorised all assessments based on their construct and a clear differentiation between the terms ‘motor imagery’ and ‘mental imagery’. These terms are often confused in the literature.n = ≤30 due to their different subgroups of patients, different language versions and inconsistency of results. Therefore, we downgraded every study with a small sample size for imprecision as having a risk of bias. We used the ‘other flaws’ option to take this into account. For other psychometric properties like content validity or structural validity, there are standards concerning the sample size. However, some measures were developed and evaluated only for a specific population (e.g. patients) [As proposed by COSMIN, sample sizes are not taken into account when assessing study quality in terms of reliability. It is recommended, however, that sample size should be taken into account at a later step of the review process when the results of all available studies can be summarised . Hence, the pooled evidence from many small studies together can provide strong evidence for good reliability . Howeveratients) , 69. Theatients) –69. On tatients) , 142.In our opinion, the studies with healthy individuals  or with patients should be more differentiated during evaluation following the COSMIN guideline.A limitation of our systematic review is that we did not emphasize on content validity of the evaluated assessments. We rated content validity only in case the authors did specify this as one of their study aims and included a sufficient description of the performed procedures. However, there were some questionnaire development studies, which could be considered assessing content validity. Nevertheless, most of the questionnaire development studies lacked important information about whether the target population was asked about relevance, comprehensiveness and comprehensibility of the questionnaire under development. The authors focused on reporting the validation steps. Therefore, we could not conclude, if the evaluation of content validity was not performed or not reported. Furthermore, we used the COSMIN evaluation tool, a widely accepted and valid tool for rating the methodological quality of studies. However, the COSMIN evaluation of methodology is strictly based on information published in the studies. As most identified articles were published more than 20 years ago, authors could not be contacted to request additional details. Therefore, some ratings as ‘doubtful’ could have been inequitable. In addition, our search was limited to English or German, so relevant articles may have been excluded. We applied the filter published by Terwee et al.  and adapOver the last century, various assessments were developed to evaluate an individual’s imagery ability within different dimensions or modalities of imagery: vividness or image clarity, controllability, ease and accuracy of how an image can be mentally manipulated, perspective used, frequency of use of imagery and imagery preferences . However, the validity of many assessments is insufficient or indeterminate. Although reliability, in particular internal consistency, of most assessments was reported as high , due to insufficient or indeterminate structural validity this property of imagery assessment should also be regarded very critically. Furthermore, the COSMIN recommendations classified most studies as inadequate or doubtful due to small sample sizes, inadequate statistical analyses used, or an insufficient reporting. Most studies were conducted with young students and further studies are needed in other fields and wider age ranges.Despite the limitations described, the present systematic review enables clinicians, coaches, teachers, and researchers to select a suitable imagery ability assessment for their settings and goals based on information provided regarding the assessment’s focus and quality.Additional file 1. Example search strategy for web of science.Additional file 2. COSMIN Risk of Bias checklist.Additional file 3: Table 1S. Characteristics of the Included Measurement Tools for Motor Imagery.Additional file 4: Table 2S. Motor imagery: Summary of Findings using modified GRADE.Additional file 5: Table 3S. Characteristics of the Included Measurement Tools for Mental Imagery.Additional file 6: Table 4S. Mental imagery Assessments: Summary of Findings using modified GRADE.


Carcharhinus leucas) faces varying levels of exploitation around the world due to its coastal distribution. Information regarding population connectivity is crucial to evaluate its conservation status and local fishing impacts. In this study, we sampled 922 putative Bull Sharks from 19 locations in the first global assessment of population structure of this cosmopolitan species. Using a recently developed DNA‐capture approach (DArTcap), samples were genotyped for 3400 nuclear markers. Additionally, full mitochondrial genomes of 384 Indo‐Pacific samples were sequenced. Reproductive isolation was found between and across ocean basins  with distinct island populations in Japan and Fiji. Bull Sharks appear to maintain gene flow using shallow coastal waters as dispersal corridors, whereas large oceanic distances and historical land‐bridges act as barriers. Females tend to return to the same area for reproduction, making them more susceptible to local threats and an important focus for management actions. Given these behaviors, the exploitation of Bull Sharks from insular populations, such as Japan and Fiji, may instigate local decline that cannot readily be replenished by immigration, which can in turn affect ecosystem dynamics and functions. These data also supported the development of a genetic panel to ascertain the population of origin, which will be useful in monitoring the trade of fisheries products and assessing population‐level impacts of this harvest.The Bull Shark ( In this study, 922 putative Bull Sharks were obtained from 19 locations for the first global assessment of population structure of this cosmopolitan coastal species. Nuclear DNA identified distinct populations in each ocean basin, with distinct island populations in Japan and Fiji. While nuclear DNA indicated that the Indo‐West Pacific is well‐connected, mitochondrial DNA—only inherited from the mother—showed that females return to the same locations for breeding. This is especially true for species of commercial importance  shows genetic connectivity along the continental margins, yet limited gene flow across the East Pacific barrier, the Mid‐Atlantic barrier, and the Isthmus of Panama  is a cosmopolitan species that occupies tropical, subtropical, and temperate coastal waters and has an important ecological role in freshwater, estuarine, and marine environments  to investigate the population genetic structure of Bull Sharks at global and local scales. We hypothesize that gene flow is limited by large‐scale biogeographic barriers, but that connectivity occurs along continuous coastlines. We further evaluate the forensic power of genomic data to assign sample provenance and establish a diagnostic SNP panel to aid monitoring the origin and trade of fisheries products and assess population‐level impacts of this trade. To achieve these goals, we analyze a global set of samples with three different genomic sequencing approaches , which allows us to assess population structure and gene flow across putative barriers for dispersal . At a smaller spatial scale, contemporary reproductive connectivity is estimated by examining the spatial distribution of closely related individuals, such as full siblings and cross‐cohort half siblings.22.1n = 175; Glaus et al., A total of 922 putative Bull Shark samples (muscle or fin clip) were collected between 1980 and 2019 from 19 different countries or water bodies (termed ‘sampling locations’) around the globe in all major ocean basin regions: the eastern Pacific (E‐PAC), western Atlantic (W‐ATL), eastern Atlantic (E‐ATL), and the Indo‐West Pacific . The DArTcap‐enriched libraries were sequenced on a HiSeq 2500  as described by Feutry et al.  and the reads were paired. The Nextera adapters were removed, and the reads were quality trimmed at a phred score < 20 for a k‐mer of 20 using the BBDuk tool as implemented in Geneious. Reads shorter than 60 bp after trimming were discarded from subsequent analyses. Merged reads for each individual were then mapped onto a previously published Bull Shark reference sequence  in Geneious against the GenBank nr/nt database. All sequences with a match of identity ≥98% to a database entry were assigned as that species. Samples without mitogenome information  were assigned to species using a principal component analysis (PCA) as implemented in adegenet v2.1.1 , observed heterozygosity (HO), and unbiased expected heterozygosity (HE) were calculated for each sampling location with n > 1 using the R package diveRsity v1.9.90  were calculated with hierfstat v0.04–22  and haplotype (h) diversities per location, and parsimony haplotype networks were calculated with the pegas v0.14 package  were calculated between all sampling locations (n ≥ 1) and between/across ocean basins with the ‘popStructTest’ function in the strataG v2.4.905 package  to train the assignment model. Similarly, the assignment accuracy of simulated mixed groups, based on a reference leave‐one‐out dataset, was evaluated with rubias  were excluded from these analyses. We also examined the minimum number of informative markers needed to assign provenance by subsampling 5–500 markers based on loading contributions of each principal component from the DAPC analysis and testing the assignment accuracy with rubias.The provenance assignment success of the DArTcap markers was tested with a2.10To investigate fine‐scale contemporary connectivity, close‐kin relationships were examined in each identified genetic cluster with >100 individuals to allow accurate allele frequency estimation, namely W‐ATL and IWP. Kinship was tested using a log‐likelihood‐ratio (LLR) approach developed by Bravington et al.  and appl33.1One sample from Papua New Guinea (PNG) failed DArTseq library construction, resulting in 187 samples for DArTseq sequencing and genotyping. An average of 2,182,162 reads (of 69 bp length) per sample were obtained from the sequencing and a total of 250,945 SNPs, located on 168,810 unique RAD‐tags, were called by the DArTsoft14 program. Data filtering discarded 233,916 SNPs and 33 sharks, leaving a total of 17,029 high‐quality SNPs. Of those, we randomly selected 3200 loci with at least one SNP  and were subsequently removed from analyses . All reads that mapped to the reference genome were checked for ambiguous base calls at an 85% threshold  to detect DNA cross‐contamination, barcode slippage, or heteroplasmy. Seven individuals that had ambiguous base calls were removed due to signs of DNA contamination . Overall, the mitogenome length was 16,707–16,708 bp , Spinner Shark , Graceful Shark , Gray Reef Shark , Pacific Smalltail Shark , Dusky Shark , and Speartooth Shark . Furthermore, in the PCA analysis carried out on DATA1 an additional 54 individuals grouped with one of these species and another four individuals were neither these nor Bull Shark  and the W‐ATL (HO range = 0.048–0.052) were lower than those for the E‐ATL and IWP .More than half the DArTseq and DArTcap DATA2) markers were monomorphic at almost all locations , we identified four major genetic clusters and additional hierarchical structure within these clusters . We saw high divergence between the two Japan locations , where individuals from Okinawa clustered closer to the IWP group and individuals from the Urauchi River were split into two groups. While the DAPC grouped the E‐ATL  with the IWP cluster, FST showed this location as distinctly different (Table ST < 0.007), although the DAPC and PCA analyses showed signs of differentiation between the southern (Brazil) and the northern locations , while the northern Indian Ocean locations  showed intermediate divergence  and Fiji (n = 8) grouped with the E‐IO/W‐PAC cluster, where the Japanese haplotypes did not correspond to the three Japanese clusters identified with the nuclear SNPs. Within Australia, the mitochondrial ΦST showed structure between western (Fitzroy River), northern , and eastern Australian sites . Seven of those eight ‘cross‐river’ HSPs were juveniles (<150 cm TL) from different age cohorts, and six pairs had different mitochondrial haplotypes.In total, 102 duplicate individuals were identified in the dataset. Most represented the technical replicates that were purposely included, but we also detected six recaptured sharks from Sydney Harbor, Japan, and Fiji (time‐at‐liberty = 38–741 days). These recaptures were always assigned to the same age‐cohort where length data were available, thus providing confidence in the length‐at‐age function from Tillett et al. . Within 4This study provides the first global assessment of genetic population structure of the Bull Shark, a cosmopolitan coastal predator, using thousands of SNP markers and full mitogenome data. We identify distinct genetic divergence driven by significant biogeographic barriers and philopatric behavior. These results further facilitate the development of a SNP panel for species, sex, provenance, and kinship identification.4.1Population structure in large coastal sharks tends to be driven by environmental barriers, movement ecology, and habitat preference  forms a stronger and more enduring barrier than the Benguela Upwelling System . The permeability of the latter barrier may fluctuate over time due to oscillations in climate . Here, the Torres Strait land‐bridge between Australia and Papua New Guinea has been implicated for genetic structuring in a variety of marine taxa across this region , and we estimated that a minimum of 100 markers are needed to achieve an accuracy of >80%. Few studies have specifically investigated the power of genetic markers to assign samples from traded shark products to their population of origin, and, to date, most forensic studies of shark trade have employed mtDNA to identify broad geographic origins ; data curation (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); project administration (supporting); resources (supporting); visualization (lead); writing – original draft (lead); writing – review and editing . Christopher Burridge: Conceptualization ; funding acquisition ; investigation (supporting); project administration ; supervision ; writing – review and editing . Peter Kyne: Conceptualization ; funding acquisition ; project administration ; resources ; supervision ; writing – review and editing . Juerg Brunnschweiler: Resources ; writing – review and editing . Demian Chapman: Resources ; writing – review and editing . Patricia Charvet: Resources ; writing – review and editing . Xiao Chen: Resources ; writing – review and editing . Geremy Cliff: Resources ; writing – review and editing . Ryan Daly: Resources ; writing – review and editing . J. Marcus Drymon: Resources ; writing – review and editing . Mario Espinoza: Resources ; writing – review and editing . Daniel Fernando: Resources ; writing – review and editing . Laura Garcia Barcia: Resources ; writing – review and editing . Kerstin Glaus: Resources ; writing – review and editing . Blanca I. Gonzalez‐Garza: Resources ; writing – review and editing . Michael Grant: Resources ; writing – review and editing . Rasanthi M. Gunasekera: Investigation ; project administration (supporting); writing – review and editing . Sebastian Hernandez: Resources ; writing – review and editing . Susumu Hyodo: Resources ; writing – review and editing . Rima W. Jabado: Resources ; writing – review and editing . Sébastien Jaquemet: Resources ; writing – review and editing . Grant Johnson: Resources ; writing – review and editing . James T. Ketchum: Resources ; writing – review and editing . Hélène Magalon: Funding acquisition ; resources ; writing – review and editing . James R. Marthick: Investigation ; writing – review and editing . Frederik Mollen: Resources ; writing – review and editing . Stefano Mona: Conceptualization ; funding acquisition ; supervision (supporting); writing – review and editing . Gavin J.P. Naylor: Conceptualization (supporting); resources ; writing – review and editing . John E.G. Nevill: Resources ; writing – review and editing . Nicole M. Phillips: Resources ; writing – review and editing . Richard D. Pillans: Funding acquisition ; resources ; writing – review and editing . Bautisse D. Postaire: Conceptualization ; data curation (supporting); funding acquisition (supporting); writing – review and editing . Amy F. Smoothey: Resources ; writing – review and editing . Katsunori Tachihara: Resources ; writing – review and editing . Bree J. Tillett: Resources ; writing – review and editing . Jorge A. Valerio‐Vargas: Resources ; writing – review and editing . Pierre Feutry: Conceptualization ; funding acquisition ; investigation (supporting); project administration (lead); supervision (lead); writing – review and editing .We note no conflict or competing interests among the authors in relation to the information provided in this manuscript.https://doi.org/10.5061/dryad.4qrfj6qdg].This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at [Data S1.Click here for additional data file.


These results, with evidence that feral honey bees find niches within highly modified and human-dominated urban landscapes, lead us to conclude that urbanization is a driver of the genetic diversity of feral honey bees in the city.Urbanization can change biodiversity in both directions, positive and negative, and despite the rising global trend of urban beekeeping, little is known about the impact of urbanization on the genetic diversity of honey bees. We investigate how urbanization affects the genetic variability of feral and managed honey bee colonies that are spread throughout the entire city, even in highly urban areas, through genetic analysis of 82 worker bees. We found convincing evidence of high genetic differentiation between these two groups. Additionally, by comparing city samples with 241 samples from 46 apiaries in rural parts of the country, variations in mitochondrial  The future of our planet is heading to urbanization as the world’s population increasingly moves from rural to urban centres, causing cities to grow with greater population density, even more in less developed regions2. Urban settlements are a highly complex and heterogeneous mosaic patchwork of habitat resources, where species face multiple challenges, from elevated pollution and noise, artificial and night illumination, and urban microclimate, to an accelerated reduction in habitat quality, including both abundance and diversity of many native species4. Cities often contain a high-density human population, a high number of exotic, invasive, or accidentally introduced species, few top predators, and inappropriate levels of nutrients and pollutants. Urbanization is related to global habitat degradation and loss, as evidenced by the increase in the amount of land occupied by urban expansion, and this trend is expected to accelerate in the coming decades. Land conversion and urbanization are perceived as major anthropogenic drivers of decline in the biodiversity of terrestrial species and act through a variety of mechanisms that decrease both reproduction and survival6.Urban areas today are a frequent landscape feature and since 2010 more than half of the world’s population lives in cities9. Special concern is given to pollinators such as bees, mainly due to their essential ecosystem services, their importance for modern agriculture, and the global pollination crisis where pollinating insect populations across multiple geographic locations and taxonomic groups are facing a significant decline in biomass and abundance14. Despite the generally negative factor of urbanization on pollinators, cities can support a surprising degree of bee biodiversity compared to other landscapes, reconsidering the traditional view of urban areas as “biological deserts”. The largest global analysis of the impact of land-use type and intensity on invertebrate pollinator biodiversity has shown significant pollinator species richness and changes in total abundance with both negative and positive effects15 further demonstrating that urban areas can support species-richness and abundant pollinator populations since some groups of bees might persist or even thrive in cities (e.g.20).The same trend is also evident in insects’ populations and is generally driven by land-use intensification and the conversion of natural habitats into agricultural or urban areas21. A possible explanation for the higher diversity and abundance of bees in urban areas compared to rural areas is a greater number and variety of flowering plant species that provide more diverse nectar and pollen22. Additionally, urban species are often considered broad generalists, and honey bees fit this trend.The presence of bee communities within cities does not imply that urban landscapes can compensate for lost natural habitats, they rather reveal that the heterogeneous landscape of urban systems creates a patchwork of potential habitats. Habitat resources in urban landscapes may not be equivalent to natural habitats regarding overall quality, patch size, connectivity, resource distribution, and resource phenology, but the presence of diverse and functional pollinator habitats cannot be denied. This variety of foraging and nesting sites can become a refuge for some bee species from increasingly less hospitable rural and suburban areas and the key to ecosystem function and resilience in cities under global climate change scenarios. For pollinators, agricultural intensification with high pesticide exposure, low floral diversity, and monocultures throughout the year may pose a greater risk than urbanisation itselfApis mellifera, globally the most prominent pollinator, dates back to at least nine thousand years23. Unlike other domestic animals, this species has not changed much because it was not as much “managed” but rather “kept” due to its biology24. Today, except in Africa, honey bees are maintained predominately in managed agricultural populations supported by beekeeping activity26. It was generally accepted that unmanaged  honey bee populations have disappeared in Europe since the 1980s after the introduction and spread of Varroa mites and the associated pathogens (e.g.26), but recent studies have shown that naturally nesting colonies of A. mellifera in its natural areal can still be found31. A honey bee colony is considered feral (FC) if it has returned to the wild, living naturally in an unmanaged state, and surviving without human intervention. However, it is very difficult to find and even estimate the number of colonies in the wild. Estimates based on predictions or derived from direct counting of wild/FCs can be unreliable due to several factors, making the assessment of their number, density, survival, and genetic background rather challenging28. Honey bees are cavity dwellers, and wild/FCs can find a range of suitable habitats. In nature, free-living colonies of A. mellifera are scattered, mostly in woodland areas, usually high in the trees, in inaccessible nesting sites. In urban areas, they can be found in natural and man-made cavities, such as trees, walls, and roofs, but also in most unlikely places such as shutter boxes and steel tubular electric poles32.The history of human connection with western honey bee, 31. However, only one case of numerous unmanaged colonies is reported in urban areas in Europe32. The presence of wild/feral honey bee populations in Europe implores the need to increase knowledge about free-living A. mellifera populations34. For this study we used the existing database with reports of the numerous thriving honey bee colonies, living free and completely without human interference or treatment in Belgrade (more in32). The city of Belgrade, the capital and the largest city in Serbia and the second in Southeast Europe, has faced extreme overdevelopment and overbuilding in the past decade. Rapid development has induced unprecedented pressure on limited open and green space that must have had a negative effect on native species through fragmentation, isolation, and habitat destruction. In 2018, Belgrade had only 14.6% green spaces and only about 1.74% protected areas of the total city area35. Although the trend of careless urban growth, high pollution levels and environmental degradation is not declining, urban beekeeping in Belgrade is flourishing. In 2020 Belgrade had 80,000 beehives36. In the last 10 years, the number of hives and beekeepers in Belgrade has increased more than three times partially due to the financial support of both State and City Governments for beekeeping. Numerous workshops and practices for new urban beekeepers were organized within various beekeeping associations with the main goal of promoting urban beekeeping. The native honey bee A. mellifera carnica is productive and well adapted to specific local conditions, and Serbian legislation allows breeding of only this subspecies in order to preserve its autochthonous status37.Even though wild/feral honey bee populations are often not considered and their existence is neglected in Europe, the presence of wild/FCs in European natural habitats is confirmed in several studies38. Although there is a rapidly growing interest in the effects of urbanization on genetic diversity, to our knowledge, studies that have focused on genetic differences between FCs and managed native honey bee colonies (MCs) in urban areas are almost non-existent. To expand the knowledge of the impact of urbanization on the genetic diversity of honey bees, we investigated feral and managed honey bees in the urban ecosystem and compared them with the data from rural areas. Urbanization poses challenges and opportunities for both MCs and FCs, but its evolutionary and ecological effects do not receive enough attention even though they are crucial due to their implications for conservation biology and understanding of ecosystem functions.Urban areas are recognized as hotspots that drive changes in the environment and biodiversity on many levels. Urbanization is regarded as a new selective force, which imposes unique pressures that alter patterns of genetic variation in populations occupying urban habitatsIn this study, we analysed 40 samples  from 40 different urban FCs and 42 samples from seven urban apiaries (MCs). All samples with their origin , geographical coordinates, and determined mtDNA haplotypes are presented in Suppl. Table NcoI and StyI enzymes did not show characteristic recognition sites for the mtDNA lineage found in A. m. macedonica and it can be concluded that all individuals in our sample belong to A. m. carnica.The PCR-amplified COI segment for RFLP analysis was 1029 bp long. Digestion with both the The standard parameters of genetic diversity for 14 microsatellite loci used in this study are presented in Table All studied microsatellite loci were polymorphic, ranging from 2 alleles for the locus A28 to 15 alleles for the locus A107 (Suppl. Table H) half of the loci in one of the types of honey bee colonies analysed  exhibited higher values compared to the other, while the θ from mean homozygosity was almost equal in both FCs and MCs from Belgrade  analysis showed that the F values are highly dependent on the estimator used for the analysis  in MCs , was detected only in FCs. Sequences generated in this paper are deposited in GenBank, accession numbers ON187787-ON187868.Analysis of intergenic sequence variability of ade Fig. . Seven oAlthough both groups share a similar number of haplotypes, three were found only in FCs and two exclusively in MCs, while the most frequent haplotypes were found in both groups Table . FCs exhFST distances, and the results are presented in Suppl. Table FST values between the Belgrade FCs and all MCs colonies exhibit the highest and statistically significant pairwise differences, including a statistically significant pairwise difference with Belgrade MCs , while the statistically significant FST values were observed between Belgrade MCs and two managed colonies (S and Vr). Other tested pairwise FST values were low and statistically unsupported , i.e. colonies. TrioML exhibited the second-lowest variance and together with the DyadML estimator (an estimator with the fourth-lowest variance) showed the highest correlation, further supporting its usage as the estimator of choice , were studied. These molecular markers are widely used in population genetics, taxonomy, systematics, and biology of honey bee conservation, and, in our study, they clearly show that two species of bee colonies from the same territory differ from a molecular point of view.This study represents the first population genetics study on honey bee colonies in highly urban landscapes based on their managed status. Our results provide important evidence to the scientists and beekeepers interested in free-living wild/feral colonies that survive and thrive despite the degradation and loss of natural forest habitat, numerous pests and pathogensA. m. carnica in urban ecosystems possess relatively high levels of genetic variability, but values for both microsatellite and mtDNA genetic markers are slightly higher in urban FCs. Genetic diversity defined as any measure that quantifies the magnitude of genetic variability within a population is a crucial source of biodiversity and as such recognized as one of three major components of biodiversity worthy of conservation under IUCN44. It provides raw material for evolution that through natural selection drives the process of speciation and contributes to the tight relationship between heterozygosity and population fitness. Genetic diversity is essential for the long-term survival of populations47. The presence of broad genetic variation is crucial in overcoming challenges, particularly in a rapidly changing environment threatened by growing human impacts and accompanying habitat loss and climate change. In honey bees, there is a strong body of evidence that within-colony genetic diversity reduces the negative impacts of pathogens and parasites53, increases pollen foraging efficiency54, and improves the control of hive temperature56. The reduction in genetic diversity within colony may also affect the capacity of honey bee populations to adapt to new threats, which is in line with the global decline of managed colonies. Microsatellite analysis showed that, compared to all other types of colonies analysed in Serbia, FCs in most cases have higher values for different parameters of genetic diversity. Results based on the analysis of 14 microsatellite loci show that when FCs are compared with MCs from Belgrade and the Serbian countryside57, in most cases they possess higher values of genetic diversity parameters. These results are not entirely unexpected—from the last decades of the twentieth century, commercial beekeeping has dominated in Serbia and has completely suppressed more sustainable traditional ways. Modern beekeeping practices, such as commercial breeding, the introduction of non-native queens and colony trade, selection and migratory beekeeping, rapidly change the genetic diversity of managed honey bees in Serbia59. A similar impact of migratory beekeeping and honey bee trade on the genetic diversity of managed honey bees has been observed in Turkey with the admixture of different subspecies and local honey bee populations of Anatolia and Thrace60. The AMOVA analysis based on microsatellite loci revealed a high level of variation both within individual bees from colonies and within individual bees from a group of colonies from the same populations/locality. This reveals a population structure with genetically distinct individuals and more sexual outcrossing than we would expect. The results indicate that the local colonies maintain specific allelic variants, and a small amount of variation shown among groups (1.39%) indicates a genetic similarity, homogeneity between the populations/localities, and gene flow between them. Serbian honey bee breeders occasionally import A. m. carnica queens, usually from Slovenia, and widely exchange them and their selected queens with beekeepers from all parts of Serbia. The queen trade is very intensive in this region, and introductions of queens of different origins, not locally adapted, could be the source of the less relatedness detected for MCs  and depend on pesticides and antibiotics treatment multiple times per year. These control treatments limit the selective pressure, preventing coevolutionary processes towards a stable host-parasite relationship63. Additionally, modern beekeeping practices rely on the selective breeding of queens with desirable traits, while resistance to pathogens and parasites is recognized as a highly valuable trait64. Owing to treatments against parasites and mites, the selection pressure in MCs is not as strong as in FCs and it could be a reason for the greater variability of these adaptive alleles in FCs. Strong selection by breeders and beekeepers for these favourable traits may be one of the reasons for the existence of linkage disequilibrium at these loci. Simultaneously, managed honey bees are protected from other selective pressures as beekeepers provide supplemental food, shelter, and therapies against pathogens and parasites. Feral bees, however, experience various selective pressures relative to managed honey bees and thus may provide insight into the processes of adaptation to local conditions, in this case, to an urban area, which highlights the need for long-term honey bee studies across a variety of urban settings. Although both managed and feral honey bees experience different sets of selective pressures, honey bees from Serbia have the same genetic history and share the same ancestry  Fig. . Belgrad32. In the period 2020–2021, we have sampled 40 FCs and 7 different apiaries with 42 beehives (MCs). Sampled FCs represent the colonies that were able to survive independently for at least two years at the same location without the help of the beekeepers. From each sampled colony, we collected 5–8 worker bees that were immediately frozen and stored at − 20 °C. For genetic analysis, a worker bee was chosen as a representative sample for the colony.For the purpose of this study, we have collected samples from two types of honey bee colonies: feral and managed colonies (beehives from apiaries) with the participation of the Belgrade Beekeepers Society which collects the locations and citizen reports of requests for removal of honey bee colonies40 and57.For the comparison with other localities in Serbia, we used data from 241 samples from 46 apiaries from the countryside published in66. PCR–RFLP method described in61 was used to distinguish mitochondrial lineages characteristic for A. m. carnica and A. m. macedonica. PCR amplification of the COI fragment and following digestion with NcoI and StyI restriction enzymes was performed according to the protocol described in40.Whole-genomic DNA was extracted using the protocol described in57.For comparison of different honey bee colonies at the autosomal level, we used the 14 most frequent microsatellite loci previously published in various studies. A detailed primer list and primer specification, together with a comprehensive protocol description, can be found intRNAleu and cox2 genes67. The PCR program, primers used for the amplification of this region, and the sequencing protocol are described in40.To determine the maternal relationship between different colonies, we have amplified and sequenced a segment of mitochondrial DNA known as the intergenic region located between the 68. Standard parameters of genetic diversity for the intergenic region mtDNA tRNAleu-cox2 and microsatellite loci , number of alleles, number of alleles based on a minimal sample size (obtained by rarefaction), number of private alleles based on a minimal sample size (obtained by rarefaction), observed heterozygosity (HO) and expected (HE), random match probability (RMP) and the mean number of pairwise differences (MPD)) were calculated using the Arlequin ver. 3.5.2.2 software69 and HP-Rare 1.170. The RMP parameter is used for expressing the probability that two randomly sampled individuals from a population have a matching genotype and is calculated as the sum of square frequencies71. The MPD is a parameter that represents the measure of differences between all pairs of haplotypes in the sample. The Arlequin ver. 3.5.2.2 software was used to assess genetic differentiation among populations by molecular variances analysis (AMOVA) and to estimate pairwise population and overall FST and FIS values. The statistical significance of all tests performed was assessed with 10,000 permutations. The matrix of pairwise population FST values was visualized using the multidimensional scaling method (nonmetric MDS) implemented in the PAST 3.25 software72 and R functions connected with the Arlequin ver. 3.5.2.2 software. Hardy–Weinberg equilibrium (HW) was tested using Arlequin software with 1000,000 steps in MC and 100,000 dememorization steps. The effect of the recent bottleneck was also evaluated based on the Garza–Williamson index (G–W) which represents the ratio between the number of alleles and the allelic range and was calculated using the Arlequin software. Linkage disequilibrium between the pairs of loci was estimated using the likelihood ratio test in Arlequin with 10,000 numbers of steps in MCs and 10,000 dememorization steps.All sequences used in the analyses were aligned using MEGA 10.0.4 softwareA. mellifera (Suppl. Table https://www.fluxus-engineering.com/network_terms.htm). Substitutions were equally weighted as no data of different evolutionary rates are available for the tRNAleu-cox2 intergenic region for A. mellifera.Phylogeographic analysis was performed using 82 mtDNA haplotypes found in two different types of colonies of 73.Substitutions specific for each haplotype were determined as the difference in nucleotide positions compared to the reference mitogenome NC_00156677. For the analysis, the admixture model was used with a burn length of 10,000 and a Markov Chain Monte Carlo (MCMC) of 100,000 randomizations. The range of the possible number of clusters (K) ranged from 1 to 14, with a series of 10 runs for each K. The results obtained by STRUCTURE were analysed by the STRUCTURE harvester78. To detect the number of K groups that best fits the data set, this software uses results generated by the STRUCTURE software to create a plot of the mean likelihood value per K value and calculates the highest value of the second-order rate of change (Delta K) using the Evanno’s method79. The model choice criterion, LnP (D), implemented in the STRUCTURE which detects the true K as an estimate of the posterior probability of the data for a given K was also evaluated. The most likely scenario was chosen and used to graphically plot both the analysed individuals and populations.The structure of the population was assessed using DAPC and STRUCTURE analysis. The number of genetic clusters represented in the FCs and MCs from Belgrade was estimated with STRUCTURE v 2.3.4 software77, DAPC is a more convenient approach for populations that are clonal or partially clonal, and we used DAPC for the presentation of observed distances among samples. The DAPC method performs linear discriminant analysis (LDA) on the transformed matrix of principal component analysis (PCA)80. LDA was performed on the first 62 PCs, which cumulatively conserved 98.9% of the total variance. The number of PCs retained was estimated using randomly repeated cross-validation (100 iterations). Additionally, the PCA transformed matrix  was used to find the optimal number of clusters using Ward's method81.A STRUCTURE-like approach assumes that markers are not linked and that populations are panmicticr, among the pair of colonies (dyads). Estimation was performed using the COANCESTRY program41. For this analysis, we used all seven relatedness estimators  including three inbreeding estimators  implemented in the COANCESTRY41. Bootstrapping of 10,000 samples over loci was performed to obtain the 95% confidence interval (95CI) of each estimator for each dyad. The inbreeding coefficient (F) for each honey bee colony was estimated using the same parameter settings. We used the following threshold values of the rxy coefficient: rxy values lower than 0.09375 marked unrelated colonies, rxy values lower than 0.1875 and higher or equal to 0.09375 were considered as third-order relatives (relationship), rxy values lower than 0.375 and higher or equal to 0.1875 were considered as second-order relatives, rxy values higher or equal to 0.375 were considered as having full-sibling or parent–offspring relationship89. ML-Relate70 software package was used to confirm acquired parent-offspring, full-siblings, and half-sibling relationships.In order to assess the general gene flow among different colonies, we have estimated the relatedness, Supplementary Figures.Supplementary Tables.


The ability of natural selection to optimize traits depends on the topology of the genotype-fitness map (fitness landscape). Epistatic interactions produce rugged fitness landscapes, where adaptation is constrained by the presence of low-fitness intermediates. Here, we used simulations to explore how evolvability in rugged fitness landscapes is influenced by genetic complementation, a process whereby different sequence variants mutually compensate for their deleterious mutations. We designed our model inspired by viral populations, in which genetic variants are known to interact frequently through coinfection. Our simulations indicate that genetic complementation enables a more efficient exploration of rugged fitness landscapes. Although this benefit may be undermined by genetic parasites, its overall effect on evolvability remains positive in populations that exhibit strong relatedness between interacting sequences. Similar processes could operate in contexts other than viral coinfection, such as in the evolution of ploidy. With no epistasis, gradual evolutionary optimization is straightforward because selection can operate on a succession of mutations, each conferring a certain fitness benefit independent of other mutations. In contrast, when traits are encoded by multiple genes exhibiting abundant epistasis, maladaptive allele combinations introduce low-fitness valleys between local fitness peaks. Such ruggedness represents a major obstacle to evolutionary optimization, since natural selection per se cannot favor intermediate, low-fitness states. Evidence from experimental evolution and mutant analysis studies suggests that epistasis is widespread and that, consequently, most fitness landscapes are rugged8. Epistasis among positions within a gene  may also play a key role in protein evolution9.Evolvability is determined by the topology of the genotype-fitness map (fitness landscape), among other factors such as populations size, reproduction mode, and mutation rate. The topology of fitness landscapes depends on gene-by-gene interactions (epistasis)10. However, high mutation rates are unlikely to supply complex adaptations in a single step, and would strongly increase mutational load, which in turn burdens adaptation. Second, episodes of random genetic drift may allow populations to traverse local fitness valleys and subsequently reach new fitness peaks under the action of natural selection11. Third, theoretical and experimental work has revealed that organisms exhibit certain features such as genetic redundancy, and other mutational tolerance mechanisms, that favor the accumulation of cryptic genetic variation in populations. These conditionally neutral variants can promote evolvability, as they may become beneficial upon changes in genetic background or environment13. It has also been shown that the very action of natural selection can promote evolvability by increasing mutational robustness14. Finally, mechanisms of phenotypic plasticity, stochastic gene expression, epigenetics and resiliency under adverse conditions (e.g. latency) might facilitate the evolution of novel traits in the long term1. However, the genetic and population-level determinants of evolvability remain to be investigated further.Evolutionary innovation often requires exploration of rugged fitness landscapes, since novel traits need not to be reached by gradual modification of pre-existing ones. Several explanations have been put forward to explain how the adaptation process takes place in epistatic fitness landscapes and, thus, how populations are able to jump from local maxima to higher fitness peaks. First, with sufficiently high mutation rates, certain combinations of favorable alleles could appear simultaneously, avoiding low-fitness intermediates17. Second, coinfections are relatively frequent20. Coinfection of a given cell with multiple viral particles of the same species can occur when there is a high local ratio of viral particles to susceptible cells (multiplicity of infection), but also when groups of viral infectious particles are jointly transmitted21. An example of the later process is provided by extracellular vesicles containing multiple viral particles22, which have been described in widely different types of viruses including hepatitis A virus23, enteroviruses24, rotaviruses25, noroviruses25, and marseilleviruses26. Baculovirus occlusion bodies constitute another example of collective viral spread in which transmission between insect hosts involves pools of nucleocapsids embedded in polyhedrin protein crystals27. Yet another example of collective viral spread is aggregation of infectious particles in the extracellular milieu, which has been described in different types of viruses including human immunodeficiency virus particles in semen28, and vesicular stomatitis virus particles in saliva29. The delivery of multiple genetic variants of a given virus to the same cell allows different viral genomes to share gene products in cooperative or antagonistic manners30.Here, we examine whether complementation between different genetic variants can foster evolvability in rugged fitness landscapes. To this end, we simulated populations in which groups of sequences mutually compensate their genetic defects. We contextualized our hypothesis within the field of viral evolution. This allowed us to investigate the implications and limitations of the model in a specific type of biological system, although the model should in principle be applicable to other systems. There are at least two reasons why viruses should be particularly prone to genetic complementation. First, they typically exhibit extremely high levels of sequence diversity as a result of their high rates of spontaneous mutationOur simulations show that genetic complementation can increase evolvability by allowing low-fitness allele combinations to be maintained in the population. In this way, populations gain the ability to traverse fitness valleys and reach high-fitness peaks that are not directly accessible through a simple mutation-selection process. We also investigate the stability of this form of cooperation in the face of genetic parasites and find that, although parasites severely undermine population fitness and evolvability, this interference can be overcome in highly structured populations where interactions take place preferentially among genealogically related sequences.N. Each string had a certain probability of being selected for the next generation depending on its fitness (selection), and each of the N positions had probability α of undergoing mutation by changing '0' to '1', or vice versa (mutation). The population was composed of S sequences , and in each generation S new sequences were selected by drawing S times a sequence from the population. In each draw, a sequence i had a probability fi is fitness. Thus, each sequence had a probability We developed a stochastic model in which haplotypes or sequences consist of a binary string of length NK models31. These fitness landscapes are built randomly, creating sequences of length N with K epistatic interactions per site. The fitness values of the sequences are calculated as a random contribution of each of the N positions, depending not only on its state (0 or 1), but also on the state of other K random positions. K = 0 produces a purely additive (non-epistatic) fitness landscape, while K = N–1 produces a random landscape with zero correlation between neighboring sequences (House of Cards). Increasing K increases the ruggedness of the landscape and, consequently, the number of local peaks.The simplest scenario considered was a two-locus system with two alleles per locus. In this model, there were only four possible sequences: 0–0, 0–1, 1–0 and 1–1  and (0–0), there are four possible allele combinations: (1–1), (1–0), (0–1) and (0–0). Group fitness was calculated in two alternative ways: as the fitness of the fittest allele combination present in the group . We called this ‘cis-complementation’. Here, we no longer considered all possible combinations of alleles, but only each actual sequence present in a group Fig. d–e. Conffg) using the above-defined rules. The probability that a group contributed to the next generation, in a single draw, was i within group g of being selected in each draw was i within group g was drawn became βi = 1 for ‘normal’ (helper) sequences and βi = 5 for genetic parasites. The simulations started with a population of helper sequences but, in each generation, helpers had a certain probability of mutating to parasites (αC). In viruses, genetic parasites often consist of genomes with large deletions33, called defective interfering particles, which are unable to successfully infect cells on their own or to complement deleterious genes from other viruses. To capture these features, we made the following assumptions: first, fitness was null for groups containing parasites only. Second, parasitic sequences contained a random number of deleted genes  such that, for these genes, the parasites were unable to complement deleterious alleles present in other sequences.When groups of complementing sequences were defined, we calculated the fitness of each sequence in a two-step manner. First, we computed the fitness of each group  individually each allele in each sequence of the population.Simulations were implemented in MATLAB R2018. Scripts are available upon request.m = 2), which yields four possible individual sequences  and 10 different sequence pairs. This will be later generalized to multiple loci and larger groups. To investigate how evolutionary optimization takes place in the presence of deleterious intermediates, we assigned each of the four sequences the following fitness values: f11 = 1, f00 = 0.2 and f10 = f01 = 0 , the number of generations required for the population to reach the high-fitness sequence 1–1 was reduced . For βC > 3, the positive effect of genetic complementation on evolvability was fully cancelled by the presence of parasites since, above this threshold, populations forming groups of two sequences (m = 2) no longer adapted faster than those formed by individual sequences (m = 1).We then allowed for genetic parasites, which function as social cheaters. Similar to defective interfering particles in viruses, these were defined as sequences that contained large deletions and hence contributed only partially to complementation (defective), but in addition took a greater share of group-associated fitness to the detriment of helper sequences (interfering). Simulations were started from 0–0 sequences capable of complementing but, in each generation, helper sequences had a certain probability of mutating to parasites. We found that parasites took over the population and reduced the average fitness Fig. a–c. The 34. In all these types of collective spread, group members are viral particles derived from the same producer cell. Unless cells are coinfected with multiple of such groups or free viral particles, the resulting virus-virus interactions are necessarily restricted to progeny derived from a common parental group. We found that, by restricting the interactions to sibling genomes, this type of structures increased genetic relatedness enough to prevent parasite invasion, yet allowed trans-complementation to promote evolvability , in which the fitness assigned to a given group  was equal to the average fitness of all allele combinations in the group. For instance, in interactions involving 0–1 and 1–0 sequences, the resulting fitness was equal to the average of fitness values for 0–1, 1–0, 0–0, and 1–1 sequences whereas, in the full trans-complementation model, the resulting fitness was determined solely by the fittest possible combination, that is, the one for 1–1. We found that evolvability was substantially reduced compared to the full trans-complementation case, but that partial complementation still had a positive effect on evolvability . By analyzing the average fitness effect of mutations, we found that, as opposed to the full complementation case, this system was unable to establish a neutrality scenario that would promote the emergence of the 1–1 sequence.9. Since this concerns variants of a given locus, effects in trans are excluded. Thus, the main difference between this situation and the previous complementation model is that, here, the fitness of the group was a function of the individual performance of each existing sequence, rather than being determined by all combinations of alleles present in different sequences. As above, we allowed for genetic parasites but assumed that populations were structured in kin groups. We first considered a situation in which the fitness value associated with a group was equal to the fitness of the best sequence present in the group (full cis-complementation), and found that under these conditions, evolvability was promoted  keeping the number of genes constant (N = 5). The number of loci that we could consider was subject to computational limitations, since simulation times increased exponentially with N. Even if the number of genes in real genomes is typically much higher than five, the actual number of loci determining a given trait and capable of establish epistatic interactions among them should be much smaller than the total number of genes present in a genome. Therefore, N = 5 might capture a sufficient level of complexity. As expected, increasing K generally hampered evolutionary optimization. With minimal epistasis (K = 1), full trans-complementation was slightly detrimental for evolvability , full trans-complementation strongly favored evolvability despite the presence of parasites  or by the average fitness value of all group members . The results were qualitatively similar to those obtained with the trans-complementation model, since evolvability was fostered under full complementation, but not when complementation was partial. We conclude that the main benefit of sequence interactions does not reside in the ability to explore novel allele combinations, as this was not possible in the cis-complementation case. Instead, complementation promotes evolvability by allowing low-fitness sequences to be maintained in the population, thereby increasing the ability of the population to traverse rugged fitness landscapes.We also applied the N = 5, K = 4). As above, in these simulations we allowed for parasites, but populations were structured in kin groups. We plotted mean population fitness along the 150-generation simulations as a function of the mean Hamming distance of the population to the highest-fitness sequence , starting each simulation from a different position in the landscape. In the absence of interactions (m = 1), populations were systematically trapped in local sub-optimal peaks. In contrast, when full trans-complementation was allowed, populations reached maximal fitness. This positive effect was stronger as group size, m, increased , the adaption process is restricted to the path allowed by additive mutations, which usually traps the system in local maxima. With abundant complementation (m = 5 or m = 10), new evolutionary trajectories emerge, since now the system is able to accumulate low fitness sequences. The analysis of the average fitness effect (the same way as in the cases of the simple system), confirmed that, in populations displaying complementation, mutations had much smaller fitness effects than in populations of non-interacting sequences, as expected in a relaxed-selection scenario (Fig. To better understand how complementation promoted evolvability, we inspected evolutionary trajectories in the rugged fitness landscape (sed Fig. a–b. Thisrio Fig. c. We rep44, how cooperation feeds back on evolvability is a less explored topic. Moreover, many previous studies have analyzed how populations evolve in complex fitness landscapes14, but these have not addressed how cooperation among genetically distinct individuals determines evolvability. Only in45 is this connection explored, where the authors determine that cooperation by public goods enhances adaptability by promoting peak shifts in complex fitness landscapes. Our results continue this line, showing a clear connection between cooperation and adaptability.We have shown through simulations that a form of cooperation based on compensation of genetic defects promotes adaptability by enhancing the capacity of the population to explore complex fitness landscapes. While the population and genetic factors that determine the evolutionary stability of cooperation have been extensively investigated42. In general, for cooperation to be evolutionarily stable, cheaters need to be segregated from cooperative interactions. In the absence of such assortment, cheaters are favored by selection because they reap the benefits of cooperation but do not pay the costs of helping others. Cheater invasion leads to a reduction of mean population fitness and, potentially, to loss of the cooperative trait. Both kin and group selection models show that cheater invasion can be avoided when interactions occur preferentially between genetically related individuals. Not surprisingly, we also found that genetic complementation was severely jeopardized by genetic parasites, and that restricting interactions to groups of genealogically related sequences could prevent parasite invasion. Intuitively, it may be expected that, by increasing relatedness, such assortment should also curtail the benefits of genetic complementation for adaptation in rugged landscapes. However, interestingly, our model shows that there is room to avoid parasites while still promoting evolvability.A fundamental question in evolutionary biology is how cooperation can be favored by natural selection despite the costs associated with helping others. This conundrum has been addressed by different approaches, introducing kin and group selection, and solved using frequency-dependent selection models and game theory, among other approaches21, increasing coinfection probability and, thus, the opportunities for genetic complementation. This possibility was suggested verbally in previous work47, but the effects of complementation on evolvability were not explored by simulations, models, or experiments, and the problem of genetic parasites was not addressed.In our simulations, we have referred to individual sequences that establish pairwise or higher-order interactions involving different types of genetic complementation. As discussed, the model could be applied to highly diverse RNA virus populations exhibiting frequent coinfections. Recent work has shown that viruses often undergo inter-host transmission and intra-host dissemination as groups of viral particles50. The potential evolutionary advantages and disadvantages of diploids over haploids have been investigated52, including with respect to evolvability. Genetic algorithm models have pointed out that sexual reproduction in diploid organisms can accelerate optimization due to recombination, which allows for a more rapid emergence of novel allelic combinations54. However, to our knowledge, previous work has not considered genetic complementation as a process that increases the evolvability of diploids relative to haploids. On the other hand, the role of gene or genome duplications in promoting long-term evolvability has been addressed previously. Provided that the original gene function is conserved in at least one copy, duplicated genes can accumulate cryptic variation that can lead to the evolution of novel functions in the long term57. It has also been pointed out that duplicated genes can be preserved if different copies undergo mutually compensable deleterious mutations58. However, as we have shown, increased ploidy may not per se foster evolvability unless selfish DNA elements are prevented.Although we have discussed our model in the context of viral evolution, there may be other biological systems that exhibit similar interactions. For instance, by sharing gene products encoded on different chromosomes, sexually-reproducing diploid or polyploid organisms tend to buffer the effects of maladaptive alleles, as evidenced by the fact that most strongly deleterious alleles are recessive59, and in the zoonotic transmission of influenza A virus60. Furthermore, complementation could be relevant to the evolution of symbiotic relationships in which certain metabolic pathways become redundant61, allowing one or both partners to evolve new functions. Finally, in complex social species, compensation of deleterious mutations through community-level interactions might allow the accumulation of genetic diversity that could yield new adaptations.Genetic complementation has also been suggested to play a role in evolutionary transitions such as from unsegmented to segmented virusesSupplementary Information.


Historical concerns over the exploitation of the Global South’s genetic biodiversity framed the importance of creating global governance mechanisms to ensure fair access to and benefit-sharing of genetic resources worldwide. The Convention on Biological Diversity (CBD) and International Treaty on Plant Genetic Resources for Food and Agriculture (Plant Treaty) came into existence over the past three decades to redress the centuries of genetic exploitation of the Global South. Both of the treaties explicitly regulate and facilitate the exchange of physical genetic material. The recent emergence of relevant digital technologies, such as digital sequencing information (DSI), could make both treaties irrelevant. This article analyses the current state of the CBD and Plant Treaty as it relates to global agricultural research in light of DSI. I argue that DSI presents less of a threat to exacerbating historical gene flows than it does to the further displacement of public sector research by the private sector. The article then suggests looking at the lessons from open-source approaches to counter the privatisation of DSI and related gene flows. I draw on 11 key informant interviews with country negotiators involved with the CBD and Plant Treaty as well as a review of official reports from both frameworks. In 1876, Henry Wickham arrived in the Brazilian Amazon under contract with the Royal Botanic Gardens at Kew in London. He collected around 70,000 rubber seeds which were highly perishable due to their moisture sensitivity as so-called ‘recalcitrant seeds’.With the collapse of formal European colonialism throughout the nineteenth and twentieth centuries, newly independent countries moved to establish sovereignty over their genetic resources. Genetic diversity was a hopeful source of national wealth as much as it was a national security issue, as in the case of Brazilian rubber. Centuries of social domination and ecological extraction under colonialism resulted in a legacy of deeply unequal exchanges of people and plants. Historians have labelled this historical trend as a ‘south–north gene drain’ or ‘Columbian Exchange’ Crosby , where band technological capacity over the biological barriers of transcontinental travel.One of the common narratives of the South–North gene flow is that the majority of the world’s biodiversity is located in the Global South but it is the Global North that maintains the technological capacity and political power to exploit it economically  of 1992. The CBD was based on the idea that interdependence of genetic resources was the most environmentally sustainable and politically desirable way to conserve global genetic biodiversity for the future. Article 2 of the CBD defines genetic resources as ‘genetic material of actual or potential value’. Benefit-sharing under the CBD was later established under the Nagoya Protocol ‘to ensure that the ers’ CBD  put it, Benefit-sharing has been hotly contested since the inception of the CBD almost three decades ago. The Nagoya Protocol was envisioned to be part of the solution to redress historical trends of material genetic transfers from the Global South to the Global North. However, despite ongoing negotiations, the transfer of genetic resources has been rapidly digitising: physical access to genetic material is being superseded by the increasing availability of digital sequencing information (DSI). A digital future for the exchange of genetic resources presents new challenges for the ways in which historically exploited ‘gene-rich’ countries can implement mechanisms based on the fair and equitable sharing of benefits. In particular, the determination of ‘origin status’ for any sample is increasingly difficult as databases lack traceability mechanisms and the cost of gene sequencing is rapidly decreasing. Importantly, the CBD explicitly states that it applies only to ‘physical access of genetic resources’ and not ‘genetic information’ or a similar broad term. This wording has caused significant confusion among policymakers and the Contracting Parties of the CBD regarding whether and under what conditions DSI is included within the CBD governance framework  as the primary governance mechanisms for the sustainable access to, and use and benefit-sharing of, global genetic resources for agricultural research. The next section introduces the recent explosion and controversy of DSI as an emerging set of technological tools, as well as the challenges DSI poses for the CBD and Plant Treaty. Lastly, this article will offer the example of open-source seed networks as a ‘protected commons’ approach that provides one potential avenue to safeguard DSI tools for global public agricultural research.The research presented in this article draws on 11 semi-structured key informant interviews with plant breeders and Contracting Party negotiators involved in the CBD and Plant Treaty. All of the interviews were conducted in March or April 2021 via virtual conferencing software. Eight of these interviews were with professionals based in or representing countries in the Global South. Three interviews were with scientists working within the global governance framework who have been active in arguing for reforms to both the CBD and Plant Treaty as it relates to DSI. The interviews were conducted to provide information on the motivations and strategies of Contracting Party negotiators, while interviews with the scientists revealed how they work within the CBD/Plant Treaty rules and how they utilise DSI on an everyday basis for their research. This research also draws significantly on a review of expert reports from the CBD and Plant Treaty governing bodies.The treatment of genetic resources as a static concept of nature to be collected, catalogued and then conserved emerged at the end of the nineteenth and into the early twentieth century. Bonneuil  calls thIn 1974, the International Board for Plant Genetic Resources was established to manage and regulate genebanks around the world. National governments argued over the best way to manage global genetic resources with claims that the US was not making materials available under the International Board Mooney . At the It was only in 1992 at the United Nations Conference on Environment and Development in Rio de Janeiro, Brazil that the CBD was established by 196 countries to consider genetic resources as under national sovereignty. Just over a decade later, in 2014, the Nagoya Protocol of the CBD established international access to and the sharing of benefit from genetic resources in accordance with prior informed consent of the country and under mutually agreed terms. The Nagoya Protocol was specifically the result of concerns from countries in the Global South that felt the CBD was incomplete by not ensuring compliance with Access and Benefits Sharing (ABS)  and Plant Treaty provide a substantial advance in the governance of genetic resources worldwide. However, they only apply to material, and not necessarily digital, genetic resources. And the MLS only applies to a select 64 crops. Perhaps most importantly, the Plant Treaty does not have legally binding contracts to enforce payments from private-sector users Tvedt . All of The overarching historical narrative behind the development of the CBD and Plant Treaty was based on redressing genetic flows from the Global South to the Global North. Despite the limitations of both frameworks, they do provide a means through which access and benefit-sharing of genetic resources can be negotiated. Nevertheless, there is a fear amongst the Contracting Parties of the two agreements that the dematerialisation of genetic resources, facilitated by DSI, will completely sideline any further negotiations or the relevance under a digitised world of genetic resource sharing. This presents an obstacle for negotiating parties to now define DSI and how it can be integrated within the existing governance frameworks. Recent scholarship on the question of DSI as it relates to both frameworks has determined that the original agreements themselves have to be reimagined if they are to maintain relevance in this new digital age of genetic resources  in Mexico and in Africa and with landrace rice varieties at the International Rice Research Institute (IRRI) in the Philippines . In their terms, the ‘users’ are largely countries in the Global North whereas the ‘providers’ are Global South countries. Although the CBD and Plant Treaty were established precisely to redress historical transfers of genetic resources from the Global South to the Global North, DSI is threatening to circumvent the access and benefit-sharing tools that have been established since the Nagoya Protocol.Downstream effects of DSI are also involving other global governance frameworks. The World Intellectual Property Organization (WIPO) is working with the CBD and Plant Treaty to assess the role of DSI in issuing patents that utilise genetic resources and are subject to access and benefit-sharing. For WIPO, the issue of DSI has been increasingly involved in the debate over whether and how patentability can be claimed when traditional knowledge (TK) is involved if an indigenous group [WIPO has been involved in determining how and the extent to which benefits can be shared under TK terms once patents are potentially issued downstream see WIPO . As willTechnological advances in DSI have outgrown the CDB and Plant Treaty, and the topic of DSI is now overrunning the ongoing negotiations involved in ratifying them. Not only is the country of origin status complicated by the broad trend in the digitisation of genetic resources but, through synthetic biology and other uses of DSI, it is becoming completely irrelevant. Nevertheless, DSI infrastructure is largely available under open-access conditions, despite being managed and funded primarily by only a few countries. The CBD and Plant Treaty were envisioned to shift the tide in the historical transfer of genetic material from ‘gene rich’ countries to ‘gene poor’ ones , with over 100,000 users annually  and/or the ability to add a multilateral system for DSI (ie Plant Treaty). One or both of those options could also fit within different definitions of DSI  to a range of downstream applications (including patenting). I suggest that an open-source approach offers a pathway for public research to contribute to and draw from the future of DSI for food and agriculture.Open-source approaches to innovation have origins in the software industry see Hope . In the You have the freedom to use these OSSI-Pledged seeds in any way you choose. In return, you pledge not to restrict others’ use of these seeds or their derivatives by patents or other means, and to include this pledge with any transfer of these seeds or their derivatives.The OSSI pledge operates as a ‘protected commons’ which offers public access to plant, save and improve any cultivar but without limitations on further downstream use. Plant breeders wishing to access or submit seeds are identifiable and providers receive credit for their effort in submitting an improved cultivar. Beyond receiving the credit, Luby and Goldman  explain libre) DSI databases. For one, the INSDC serves as a repository of data for researchers willing to submit DSI and allows for open access (libre) but the INSDC does not own or control the ownership over the data. There is no way to control what happens with DSI downstream. The Human Genome Project offers another interesting case of the blurred relationship between public and private ownership over sequence data. Celera Genomics, a private company, famously sequenced human DNA in part by relying on data from the Human Genome Project. Celera made their data ‘freely available’ but only under a ‘non-redistribution agreement’ . BiOS was started in 2004 by Cambia, an Australian-based non-profit that has a vision to ‘democratise, decentralise and diversify’ research and research materials Historical concerns of genetic exploitation by the Global North are also now less relevant than they were during the framing of global governance mechanisms in the twentieth century and up until a few decades ago. Global gene flows have actually reversed. The current concern, therefore, is over the public–private divide that is threatening access to and control over DSI for all. DSI provides new opportunities for the private sector to exploit genetic diversity while simultaneously restricting access and benefit-sharing from the results of research. The public sector, on the other hand, must operate within the existing CBD/Plant Treaty framework to gain access to and share the benefits of genetic resources. This leaves them at a disadvantage. An open-source platform for DSI would benefit all (including the private sector), and at least it would not limit the access to and benefit-sharing of data under the current rules of the CBD and the Plant Treaty.According to some of the country negotiators I spoke to, the issue of DSI is restructuring the coalitions in the CBD and Plant Treaty. The previous divide in Global North and Global South is getting more complicated as many countries, such as China, Brazil and India, are major users and providers of both physical genetic resources and DSI. Nevertheless, countries in the Global South are largely opposed to the idea of an open-source platform for DSI on a worldwide scale. The reasons negotiators expressed to me were primarily based on the technological capacity – both public and private – to utilise emerging DSI tools. While the current state of private-sector agricultural research as in relates to DSI is beyond the scope of this paper, public-sector research is reliant on the access and benefit-sharing system established by the Nagoya Protocol (CBD) and the Plant Treaty.There are ongoing concerns over the North–South divide in countries’ technological capacity to exploit new tools such as DSI under an open-source arrangement Leonelli . But per