The co-editor networks of academic journals are generally examined at the journal level. This paper investigates the geographies of the global co-editor network in oncology through the lens of cities. After using different network methods to analyze the global co-editor network, we found that the network can be characterized by a core-periphery structure. The dense core is occupied by many highly interconnected cities, whereas the periphery contains many cities maintaining loose connections with the core cities. The core shows an asymmetric dual sub-core structure. The greater sub-core is constituted by Northern American cities with New York, Washington DC, Boston, Houston, and Los Angeles in the center, whereas the smaller sub-core is formed by Asian cities and centered on Tokyo, Seoul, Osaka, Beijing, and Shanghai. The European core cities do not form a well-outlined sub-core but produce a ringlike shape around the Northern American core. This structure of the co-editor network is a consequence of the prestige effect still characterizing global science. Many European and Chinese journals tend to employ Northern American editors (US-based editors in the first place) to help increase the reputation of the journal. However, US-based journals are more interested in recruiting American editors from the top-ranked national cancer centers and universities rather than outside of the country. Science in our age is characterized by such fundamental attributes as collaboration, internationalization, and multipolarity. It has been widely demonstrated that the ratio of co- and multi-authored papers has been growing rapidly  ,2. In thThe above attributes of science  are most often observed and evaluated through the lens of scientific publications. Collaboration is investigated based on co-authorship characteristics, the increasing number of countries that participate in the production of publications reflects on the internationalization of science, and the multipolarity of the system is generally expressed by comparing the number of publications produced or citations received by different countries. Science production  is, however, only one side of the coin, whereas less attention is given to the attributes of gatekeepers, who control the main communication channels of scientific information ,12. The The editorial board of a scientific journal can be understood as a network of professionals representing a particular discipline (or a couple of related disciplines) . The netRecently, the investigation of the characteristics of interlocking editorship networks has gained widespread attention. In the field of financial economics, Andrikopoulos and Economou  detectedThe current studies investigating the interlocking editorship network are alike in that they almost exclusively focus on the journal level. We have, however, no information regarding the geographical patterns of the co-editor network. The main goal of this paper is to map the geography of the global co-editor network in the field of oncology; we analyze this latter research field using network techniques in this study due to the following reasons: Cancer is a leading cause of death worldwide , making We investigated the geography of oncology journals’ co-editor network through the lens of cities. We involved 244 Web of Science–indexed oncology journals in the analysis that, in 2020, were edited by 13,342 scholars from 878 cities across the world occupying a total of 17,774 editorial board positions. By using network analysis techniques, we examined and mapped the interrelations between cities. We sought to answer the following research questions: 1) By which structure can the oncology journals’ co-editor network be described? 2) Which cities are the most interconnected in the network? 3) Can we characterize the network with a multipolar pattern?The data collection of oncology journals’ editorial boards was conducted in 2020. Oncology journals were selected based on the research area classification of Web of Science (WoS), which, in the 2019 edition of the Journal Citation Reports, listed 244 journals under the heading “Oncology”. The affiliation data of editors were collected manually from the journals’ websites. When compiling the dataset, we excluded the inactive editorial board positions  and the journals’ administrative staff  [After implementing all the necessary corrections and modifications, a total of 17,774 editorial board positions remained in the dataset. The 17,774 editorial board positions were occupied by a total of 13,342 scholars, which implies that many served as editor for more than one journal . In The oncology journals are edited by an average of 73 scholars. The editorial boards’ size varies from journal to journal; for example, Advances in Cancer Research is edited by only two persons, whereas the editorial board of BMC Cancer consists of 590 editors.The editors of the 244 journals are affiliated with 2,554 organizations being located in 1,329 settlements worldwide. These settlements are highly different in terms of size and population, and they occupy various hierarchical positions in the urban network. To increase consistency, we investigated the network connectivity of metropolitan areas rather than any type of settlement.The delineation methodology of metropolitan areas to increase the comparability of the data was crucial. In spatial scientometrics, different methods are employed to merge localities into larger spatial units . Some reAfter carefully reviewing the geographical location of the 1,329 settlements , we merged them into 878 metropolitan areas.i and j are connected if they co-edit a journal. Because the size of journal editorial boards varies on a large scale, we weight co-editor links with the formula wij stands for the strength of the tie between editors i and j, i and editor j co-edit journal m and zero otherwise and nm is the number of editors in the journal’s editorial board. This method suggested by Newman [To characterize the inter-related system of the global co-editor network in oncology, we created a network in which two editors y Newman  attributWPQ is the edges weight between cities P and Q that host editors i and j.We aggregate the individual co-editor links to the city level bySP = ∑QWPQ);we rank cities in decreasing order in terms of their strength  of co-edited journals by resident editors in cities that are part of the community. AIF is the mean of impact factors of all journals that are co-edited between cities The editors of the oncology journals are located in 878 cities worldwide. Most cities (385) are in Europe, followed by Asia (245) and Northern America (171), whereas the rest of the world  hosts 77 cities only. Considering the geographical distribution of the editors across cities, it turns out that most editors are located in Northern American cities . The European cities are home to 5,400 editors, and 3,466 editors are from Asian cities . The aveWe consider a journal’s editorial board to be a network of interconnected co-editors. Most oncology journals maintain international editorial boards; that is, the editorial boards have members from at least two countries. Notably, previous works define journal editorial boards to be international if they contain scholars from at least five or even eight countries ,41. FurtSome journals, however, are edited by scholars from a single country. Even in the latter case, the editors are generally located in different cities. In the co-editor network, the cities are interconnected by the journal’s editorial boards. Each city contains at least one editor, but the facts that the top 15 cities concentrate 35 percent of the editors, and 30 percent of the cities host 90 percent of the editors, indicate that the network is highly centralized. Four journals are edited by a single editor; thus, those journals are not part of the network analysis.As can be seen in The 109 European core cities do not form such a well-delineated sub-core as the Northern American and the Asian cities but show a ringlike shape around the Northern American sub-core. The major European city in terms of editorship is London, followed by Milan, Paris, Rome, Amsterdam, Barcelona, Munich, and Heidelberg . The proThe 242 core cities establish a total of 2,120,601 co-editor links, out of which only 327,753 links (15.46 percent) are built with peripheral cities. The co-editor link distribution is characterized by the dominance of Northern America. The Northern American cities represent 30.58 percent of the core cities and host 51.69 percent of the editors affiliated with the core cities. In addition, 51.24 percent of the core cities’ co-editor links are built by the Northern American core cities .As Most Northern American co-editor links start from New York , Washington , Boston , Houston , Los Angeles , and Philadelphia , ensuring the central position of these cities in the Northern American sub-core. With 6,483 and 6,453 co-links, the New York‒Boston and New York‒Washington co-editor connection is the strongest in the world. In terms of co-editorship, the most significant international co-editor connection in the world exists between New York and Tokyo .Only 23.58 percent of the Northern American co-editor links are built with European cities and 14.45 percent of them with Asian cities.The ringlike pattern created by the European cities around the Northern American sub-core  is essenConsidering the composition of the journals’ editorial boards in terms of the editors’ origins, we can conclude that the European editors represent the majority in 62 journals’ editorial boards, which is only 55.86 percent of the value characterizing Northern America . Hence, The major European countries in terms of editorship are Germany, Italy, the United Kingdom (UK), and France. These four countries account for 57.80 percent of the number of European core cities, 63.19 percent of the number of editors, and 64.63 percent of the co-editor links established by European cities. In As for France, it is one of the handful of countries that publish non-English language WoS-indexed oncology journals. These journals  are platforms for mostly French-language cancer research publications and are dominantly edited by France-based scholars (more precisely: 87.78 percent of the editors are from France). However, as can be seen in The United Kingdom traditionally maintains strong ties in science with the United States , as also reflected in the high ratio of UK−US co-editor links. The Italian core cities maintain almost equal ratios of co-editor links between European and Northern American cities. However, as compared to the major European countries in terms of editorship, the Italian core cities have the strongest co-editor links with Asian cities .Most co-editor links are established by London , followed by Rome , Milan , Paris , and Naples . In terms of the number of co-editor links, the European cities lag the Northern American ones. Considering the number of editors and the number of co-editor links, London is the top-ranked European core city. London, however, occupies a less dominant position in Europe than New York in Northern America due to differences in such indicators as the number of editors (London: 312 vs. New York: 905) and co-editor links . Furthermore, whereas the co-editor links built between London and European cities, and London and Northern American cities account for 33.47 percent and 45.24 percent of all of London’s co-editor links, respectively; New York is more involved in constructing intracontinental co-editor connections: the proportion of New York’s co-editor links with Northern American cities is 56.45 percent. With 485 co-editor links, the London‒Milan co-editor connection is the strongest in Europe, but the magnitude of the London‒New York connection in terms of co-editor links is 3.78 times higher.Although there are a couple of oncology journals being dominantly edited by European scholars , the European editors more often have positions in such journals’ editorial boards, of which the majority are occupied by Northern American scholars .At first glance, the Asian sub-core is characterized by a highly integrated pattern. However, if we dig more deeply, it turns out that among the major countries of the region , only loose intracontinental connections exist. By being home to the most core cities (18 out of 49) and editors  and by building the most co-editor links , Japan is undoubtedly the major actor in the co-editor network of Asia. The Asian sub-core is centered around Tokyo. The Japanese capital built 79,792 co-editor links, which is 18.29 percent of all links established by Asian core cities. Tokyo constructs strong ties with its national and regional peers . The number of Tokyo‒Osaka co-editor links  is the third-highest in the world, surpassed by only the New York‒Boston and New York‒Washington connections. In addition, with 3,437 co-editor links, the Tokyo‒Seoul city dyad produces the strongest international co-editor connection globally. 48.64 percent of Tokyo’s co-editor connections are built with Asian cities, a ratio that exceeds the Asian average . ConsideIn South Korea, the co-editor network is more centralized than in Japan because Seoul, the major South Korean hub in terms of editorship, is not followed by such dominant second-tier hubs than in the case of Japan, Tokyo is followed by Osaka, and Nagoya. Seoul hosts 342 editors, whereas Daegu, the second-ranked South Korean city, is home to 28 editors only. For Seoul, the intracontinental co-editor link ratio is less than 40 percent, and this ratio is naturally slightly higher for second-tier South Korean cities .Surprisingly, China is characterized by a less-developed domestic co-editorship network. Considering the co-editor link distribution of the Chinese core cities, it turns out that the ratio of the intra-Asian co-editor links (31.54 percent) is lower than those built with Northern American cities (37.85 percent). Hence, the Chinese editors more frequently occupy positions in such journals’ editorial boards (regardless of being published by US- or Chinese-based publishing houses) that employ many Northern American editors but a relatively lower number of non-Chinese Asian editors. For example, Cancer Biology & Medicine, the journal of the China Anti-cancer Association, employs 50 editors from China, 13 editors from other Asian countries, and 34 editors from Northern America . This quasi-balanced structure of the editorial board does not characterize the Japanese journals for which the editorial boards contain mostly Japanese editors.The major Chinese hubs of editorship are Beijing and Shanghai, followed by Hong Kong and Guangzhou . Most coBy conducting hierarchical clustering using the Louvain community detection algorithm , we grouThe core cities can be classified into six major communities that are labeled by their largest city in terms of the number of editors . Such major Chinese cities as Beijing, Guangzhou, Hong Kong, and Shanghai are also part of the Tokyo community. This is an astonishing finding because earlier we found that the Chinese cities constructed more intensive co-editor connections with Northern American cities than with their Asian peers. However, this pattern may change in the close future, and Chinese cities might become part of some US communities or establish their own community.The smallest community in terms of the number of core cities is the Mumbai community, which includes four Indian and three Central and Eastern European cities.Considering the number and geographical diversity of cities encompassed by a particular community, we can conclude that the New York City and Tokyo communities are the largest integrators for cities across the world. These mega-centers in the US and Asia integrate the gatekeeping function of editors residing on other continents as well. In contrast, the European communities of the co-editor network do not cross the continental borders. This is an important insight and signals the limited capacity of the European scientific system to control and monitor progress in other research areas.In the final step of the analysis, we characterize communities by the impact of the journals edited within them and in collaboration with editors in other communities . EditorsAn interesting observation in In this paper, we mapped the global co-editor network in oncology. Our main goals were to identify the major hubs of the network  to investigate whether the network could be characterized by a core-periphery structure and to examine whether the co-editor network showed a multipolar (tripolar) pattern.We found that the co-editor network in oncology is constituted by two main parts: a core being occupied by 242 highly interconnected cities and a periphery containing 636 cities that are loosely interconnected with the core cities. Most of the peripheral cities are not connected with each other. The core of the network shows an asymmetric dual sub-core structure. The greater sub-core is constituted by Northern American cities with New York City, Washington DC, Boston, Houston, and Los Angeles in the center, whereas the smaller cub-core is formed by Asian cities and is centered on Tokyo, Seoul, Osaka, Beijing, and Shanghai. Although many European cities are located in the core, they do not produce a well-outlined sub-core but rather form a ringlike shape around the Northern American sub-core. Even the most dominant European core cities  contain a significantly smaller number of editors and construct a lower number of co-editor links than their Northern American and Asian peers. The weak positions of the European cities in the co-editor network are also demonstrated by the community detection analysis: whereas the major Northern American and Asian communities  include many European cities, the two European communities—London and Milan—encompass only European cities (the New York City community contains more European cities than London and Milan combined).To give a reasonable explanation of the characteristics of the co-editor network with a particular focus on the core, we must go down the journal level.Most editors, more precisely, 44.1 percent of them, are located in the United States, followed by Japan, Italy, China, and Germany with ratios of 7.7, 5.7, 5.3, and 5.1 percent, respectively. In 111 oncology journals , the Northern American editors represent the majority of the journal’s editorial board. In the case of 11 journals, the editorial boards are constituted by Northern American editors exclusively . There aThe hegemony of the United States in global science is a well-known phenomenon. However, as Heinze et al.  point ouHowever, we found that, despite its declining share in the global publication output, the United States still occupies the leading position in the control of global science. This finding reinforces the results of Braun and Dióspatonyi’s work published in 2005 , which dWe can conclude that the articulation of the global co-editor network in oncology is impacted by a sort of prestige effect. For many journals across the world, primarily for those published in China and Europe, this is a strategy to involve more American scholars in the journal’s editorial board to increase the journal’s prestige. For US-based journals, however, the additional value of employing non-American editors is uncertain. For example, the editorial board of CA-A Cancer Journal for Clinicians, the most impactful journal in 2020, is constituted by American editors exclusively. US-based oncology journals are more interested in employing American editors from the leading national cancer centers and universities, of which most are located in such metropolitan areas as New York, Boston, Houston, Los Angeles, and San Francisco. These metropolitan areas concentrate many top-ranked oncology institutions. The New York metropolitan area, for instance, is home to seven institutions involved in cancer research with more than 50 editors, respectively ; that is, besides the prestige effect, which favors editors from the United States, the geographical concentration of editors is supported by the size effect as well. These two effects combined help large US cities occupy the central position in the core of the co-editor network.The limitation of this research is that we investigated the geographies of the co-editor network in the case of a single research field. Although we chose to analyze the spatial aspects of the co-editor network in oncology, a research field with wide geographical coverage, we assume that other research fields can be characterized by a different co-editor network pattern. In addition, it would be interesting to examine the temporal dynamics of co-editor networks; however, because data acquisition even back to some years is rather problematic, such an analysis would appear to be highly challenging.The network methods and mapping were made with R (version number 4.0.5) and Gephi (version number 0.9.2).S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S1 Material(PDF)Click here for additional data file.


Avena sativa L.) genotypes selected from the collection of genetic resources. The set of genotypes included oats with white, yellow, and brown seeds as well as a subgroup of naked oat (Avena sativa var. nuda Koern). Variation at these loci was used to form potential heterotic groups potentially used in the oat breeding program. Seven from 20 analyzed microsatellite loci revealed polymorphism. Altogether, 35 microsatellite alleles were detected (2–10 per locus). Polymorphic patterns completely differentiated all genotypes within the subgroups of white, brown, and naked oats, respectively. Only within the greatest subgroup of yellow genotypes, four pairs of genotypes remained unseparated. Genetic differentiation between the oat subgroups allowed the formation of seven potential heterotic groups using the STRUCTURE analysis. The overall value of the fixation index (Fst) suggested a high genetic differentiation between the subgroups and validated a heterotic grouping. This approach can be implemented as a simple predictor of heterosis in parental crosses prior to extensive field testing or development and implementation of more accurate genomic selection.An evaluation of polymorphism at the microsatellite loci was applied in distinguishing 85 oat ( Avena sativa L.) is an economically important crop, ranking sixth in world cereal production after wheat, rice, maize, barley, and sorghum. Oat is used as green fodder, straw, hay, or silage with good balanced feed components for livestock. Oat grains are also part of humans’ diet, either directly as raw food  or as raw material and ingredients in food production. They possess unique and important nutritive characteristics, particularly high contents of lipids, proteins, and micronutrients [Cultivated oat  genotypes from a maintained collection of genetic resources using the microsatellite polymorphism for selection of genetically different genotypes and formation of potential heterotic groups for the oat breeding program.Plant breeders frequently use genetically similar parents in crosses to generate progenies to create new cultivars. Such an approach is also common among oat breeders. Elite but genetically very similar parents have the potential to generate advanced offspring without an undesirably changed genetic background. However, if breeders need to substantially extend genetic diversity and introduce new genes, they must select and cross parents genetically as different as possible. Genetically divergent parents can generate advanced hybrids with higher heterozygosity and manifested heterotic effects. Genetic diversity as well as unrelatedness is usually determined by pedigree analysis, morphological, physiological, agronomical traits, and biometric analysis. These approaches are limited mainly by low variation in these parameters and have been enriched gradually after the introduction of molecular, especially DNA markers. Molecular markers can effectively contribute to the formation of heterotic groups. Subsequently, parental genotypes can be selected from distinct groups with the expectation of greater heterosis effect in offspring. However, the reliability of molecular markers to confirm the relationship between genetic diversity and heterosis in offspring is neither completely clear nor universal. It depends on the type of molecular markers used, the plant species, the observed phenotypic traits, and other factors. Melchinger  accumulaTwenty pairs of primers for the polymorphism analysis at the microsatellite loci were tested. Only seven  revealed polymorphism within the set of 85 analyzed oat genotypes. Altogether, 35 alleles were detected, 2–10 alleles per locus, and on average 5 alleles per locus. The most polymorphic one was the locus AM1  where the highest number of different microsatellite patterns (31) were found. A heterozygote status was detected at several loci.The genetic variation at all polymorphic microsatellite loci was declared by several parameters . The hetavp and should reveal the distinguishing power of markers or techniques. It predicts the relative utility of various marker systems [avp values.The marker index (MI) is the product of the effective multiplex ratio (E) and H systems . The MI  systems ,21. Prev systems  argued tThe parameter resolving power (R) compared the diagnostic effectiveness of used primers within the analyzed set of oats. The most effective was the marker locus AM1 with the highest R value (4.1176). According to the equation of Prevost and Wilkinson  0.15x + The Discriminating power (D) described by Tessier et al.  can be aGenerally, the polymorphism revealed at the genomic microsatellite loci in the oat genome tends to be high. It is characterized by heterozygosity and a high number of alleles per locus, which usually results in high PIC values, diversity indices, and a high ability to differentiate genotypes ,17,24,25The relationships between subgroups of oat genotypes differing in seed parameters (glume color and hull/naked) faithfully demonstrated the principal component analysis (PCA). This type of statistical analysis is suitable for the discrimination of genotypes into groups and subgroups based on selected parameters. The classification of oat genotypes by PCA into subgroups according to seed parameters  was created in this case. Four subgroups, white, yellow, brown, and naked oats, contained a different number of genotypes. A relatively high variation in analyzed microsatellite loci was revealed within each of these four subgroups. Nevertheless, it should be noted that separate subgroups overlapped and no boundaries and no separation between them were evident . TherefoAlthough the PCA did not show the formation of separate subgroups, it revealed the differentiation ability of microsatellite markers. This analysis apparently demonstrated the suitability for differentiating genotypes of a relatively large group as a whole and individuals within four subgroups . All genotypes within the subgroups of white, brown, and naked oats were completely differentiated from each other. Only four pairs remained unseparated within the subgroup of yellow genotypes: Hecht-Hron (PS-100), Auron-Senator, Ardo-Cyril, and Expander-Expo, respectively. Pairwise comparisons based on the PCA analysis revealed that only the brown oats were not statistically different from other subgroups of oats A high differentiation competence of the microsatellite markers is better demonstrated though a cluster analysis that also indicates the possible grouping of genotypes into smaller groups/subgroups . It reveK determining the best fitted value was at K = 2  from the STRUCTURE analysis helped to know how different subgroups can be from each other. The overall fixation index Fst was 0.367, suggesting high genetic differentiation between the subgroups in the frame of the assayed germplasm and validated heterotic grouping suitable for development of advanced offspring. In addition, the Fst values of seven individual subgroups were: Fst1 = 0.181, Fst2 = 0.412, Fst3 = 0.498, Fst4 = 0.434, Fst5 = 0.214, Fst6 = 0.490, and Fst7 = 0.343, indicating high variation found within subgroups, especially in those included in clusters 2, 3, 4, and 6. This can suggest that the separation of genotypes according to genetic diversity at microsatellite loci can continue into even more heterotic groups. This is also supported by the ∆K plot  according to genetic similarity. Molecular markers have been marked as extremely powerful tools for grouping of germplasm for a long time [1 progenies. They suggested that the genetic distance between parents determined by molecular markers can be helpful in heterosis prediction for some traits, and categorization for heterotic groups and parental selection would be beneficial in cotton hybrid breeding. Similar statements were presented in sorghum and maize [Melchinger and Gumber  in theirong time . This thong time ,37,38,39ong time . Howeverong time  and Melcong time . Geng etong time  found thnd maize ,43, rye nd maize , barley nd maize , wheat [nd maize , rice [4nd maize , and in nd maize  concludend maize ,49,50.Avena sativa L.) contained registered cultivars and breeding lines from the period of 1952–2007 originating from 18 countries  and differed in the color of the glume . Seeds of all oat genotypes were obtained from the Avena sp. collection of genetic resources maintained in the Gene Bank of the Slovak Republic .The set of 85 oats , using the Euclidean distance measure and the cluster analysis using the neighbor joining clustering and Jaccard similarity index were performed using the Paleontological Statistics (PAST) software version 3.19 . This soK-values ranging from one to fifteen with ten independent runs each. The Burn-in and Markov Chain Monte Carlo iterations were set to 100,000. The number of clusters was chosen by plotting the LnP(D) values against ∆K values with the K value selected according to the Evanno test [The population structure was evaluated through the STRUCTURE v. 2.3.4 software  using thnno test . The trenno test . The plonno test ,57,58,59The analysis of genetic distance using genomic microsatellite markers revealed a relatively high degree of polymorphism and heterozygosity at given loci. This can be used for the almost perfect mutual differentiation of genotypes as well as for the classification of genotypes into several subgroups. Microsatellite polymorphism dominated in the way these subgroups were discriminated, but signs of grouping by seed parameters were also identifiable. High genetic differentiation between the subgroups supported a heterotic grouping. Moreover, the high heterozygosity found within subgroups suggests that microsatellite polymorphism can also be used in the formation of other heterotic groups. This approach can be implemented as a simple predictor of heterosis in parental crosses prior to extensive field testing or the development and implementation of more accurate genomic selection.


The broad continuum between tropical and temperate floras in Eastern Asia (EAS) are thought to be one of the main factors responsible for a prominent species diversity anomaly of temperate plants between EAS and eastern North America (ENS). However, how the broad continuum and niche evolution between tropical and temperate floras in EAS contributes to lineage divergence and species diversity remains largely unknown.Machilus thunbergii Sieb. et Zucc. (Lauraceae) were evaluated by examining sequence variation of ten low-copy nuclear genes across 43 populations in southeast China. Climatic niche difference and potential distributions across four periods  of two genetic clusters were determined by niche modelling. North and south clusters of populations in M. thunbergii were revealed and their demarcation line corresponds well with the northern boundary of tropical zone in China of Zhu & Wan. The divergence time between the clusters and demographic expansion of M. thunbergii occurred after the mid-Pleistocene climate transition . Migration rates between clusters were asymmetrical, being much greater from north to south than the reverse. Significant effects of IBE, but non-significant effects of IBD and IBR on population genetic divergence were detected. The two clusters have different ecological niches and require different temperature regimes.Population genetic structure, demography, and determinants of genetic structure  of The north-south genetic differentiation may be common across the temperate-tropical boundary in southeast China. Divergent selection under different temperature regimes (possibly above and below freezing temperature in winter) could account for this divergence pattern. The broad continuum between tropical and temperate floras in EAS may have provided ample opportunities for tropical plant lineages to acquire freezing tolerance and to colonize the temperate regions during the late-Cenozoic global cooling. Our findings shed deeper insights into the high temperate plant species diversity in EAS.The online version contains supplementary material available at 10.1186/s12870-021-03420-9. Owing to the general similarities in climate, vegetation types, and floristic composition between Eastern Asia (EAS) and eastern North America (ENA), a prominent species diversity anomaly of temperate plants between them has been bewildering generations of evolutionary biologists and ecologists –7. This The India-Eurasia collision since 55–40 million years ago (Ma) leads to the formation of the highest plateau of the world  and creates huge topographic and climatic heterogeneity in Eastern Asia . Higher According to the theory of niche conservatism, species will always inhabit environments that exhibit some similarities to those of their close relatives, for example, half of flowering plant families are strictly tropical and have not spread out of the tropics  , 20. ForIt is widely known that a relatively continuous, homogenous flora with many tropical and subtropical taxa   covered Machilus Nees is a species-rich genus in Lauraceae containing ca. 100 evergreen tree or shrub species distributed in tropical and warm-temperate  south Asia, with most species (ca. 82) occurring in south and southeast China  using IMa2 Table . This ti56) Fig. .Fig. 2PoM. thunbergii as a whole, clusters N and S all conformed to scenario 2  was estimated at 0.68 Ma (95% CI: 0.25–0.98 Ma), 0.52 Ma (95% CI: 0.12–0.94 Ma) and 0.46 Ma (95%CI: 0.09–0.93 Ma), respectively, and the other (T1) was at 0.10 Ma (95% CI: 0.02–0.19 Ma), 0.15 Ma (95% CI: 0.02–0.28 Ma) and 0.07 Ma (95% CI: 0.01–0.14 Ma), respectively   but non-significant effects of isolation by distance (IBD)  and isolation by resistance (IBR) . The principal component analysis found clear climatic differentiation among two genetic clusters (N and S) in the first two principal components   analysis revealed significant effects of isolation by environment (IBE) on population genetic divergence (3%) Fig. . FrequenM. thunbergii clusters to predict their current potential distributions and the model was then projected to past scenarios . Observed measures of niche similarity (D and I) were higher than null distributions for N vs. S, suggesting high niche differentiation between N and S , Schima superba (Theaceae), Lindera aggregata (Lauraceae), Oreocharis auricula (Gesneriaceae))  of each scenario using logistic regression of 1% of simulated data sets closest to the observed data.The genetic divergence time between genetic clusters was also tested using ABC approach implemented in Dbc 2.1.0 . In addi changes . The perus study . DIYABC east 2.5.1 [Ne) changes of the Structure clusters. We used the default substitution model and the substitution rate of 3.4 × 10− 9 per site per year [Furthermore, we used extended Bayesian skyline plots (EBSP) analysis in Bst 2.5.1  to inferper year . We set FST) among each pair of populations were calculated using Arlequin 3.01 [essistance And Habitat Calculator tool in Arcmap 10.8.1 to calculate resistance values from raster layers of elevation, roads, water bodies and rivers. Then the pairwise resistance distance matrix were generated using Circuitscape 4.0 [http://www.worldclim.org) and used as proxies of environmental gradients. A climatic distance matrix was constructed using population pairwise Euclidean distances across all 19 bioclimatic variables. Then, after standardizing the four distance matrices by Z scores, we quantified the contributions of geographical distance, resistance distance and environmental distance to genetic distance using the ‘Multiple Matrix Regression with Randomization (MMRR)’ function in R 3.6.3 [Isolation by distance (IBD), isolation by environment (IBE) and isolation by resistance (IBR) has been considered as the main forces for driving the population structure across a species’ range . Isolatiuin 3.01 ; A geogrcape 4.0 . Ninetee R 3.6.3 .http://www.worldclim.org) located within the sampling areas of the two groups. In addition, we used nonparametric Kruskal–Wallis multiple-range test [In this study, we detected significant isolation-by-environment (see Results). To further detect which climatic variable is associated with the genetic differentiation between the two clusters, we conducted a principal component analysis (PCA) on climate data (19 climate variables) obtained from Worldclim (nge test  to examiaxent 3.3.4 [r) among the bioclimatic variables were examined to avoid multicollinearity, and we excluded one of the variables in each pair with r > 0.7. The AUC (area under the receiver operating characteristic curve) values were used to measure model accuracy, and the model with values above 0.9 was considered better discrimination. We also conducted the Jackknife tests to identify the contribution of each climatic variable. The niche differences between the two groups were measured by niche overlap and identity tests in Enmtools 1.4.4 using statistics of Schoener’s D and standardized Hellinger distance (I) [Current potential distributions for northern and southern clusters were predicted using ecological niche modeling (ENM) in Mnt 3.3.4  with theance (I) .Additional file 1.


Ovis aries). However, their genetic diversity and population structure have been less studied, especially at the genome-wide level. In the present study, we employed the specific-locus amplified fragment sequencing for identifying genome-wide single nucleotide polymorphisms (SNPs) among five breeds of sheep distributed in Sichuan, including three local pure breeds, one composite breed, and one exotic breed of White Suffolk. From 494 million clean paired-end reads, we obtained a total of 327,845 high-quality SNPs that were evenly distributed among all 27 chromosomes, with a transition/transversion ratio of 2.56. Based on this SNP panel, we found that the overall nucleotide diversity was 0.2284 for all five breeds, with the highest and lowest diversity observed in Mage sheep (0.2125) and Butuo Black (0.1963) sheep, respectively. Both Wright’s fixation index and Identity-by-State distance revealed that all individuals of Liangshan Semifine-wool, White Suffolk, and Butuo Black sheep were respectively clustered together, and the breeds could be separated from each other, whereas Jialuo and Mage sheep had the closest genetic relationship and could not be distinguished from each other. In conclusion, we provide a reference panel of genome-wide and high-quality SNPs in five sheep breeds in Sichuan, by which their genetic diversity and population structures were investigated.Sichuan, China, has abundant genetic resources of sheep ( Ovis aries) were domesticated in the Fertile Crescent region of the Near East approximately 8,000–9,000 years ago [Modern sheep , T4 DNA ligase (NEB), ATP (NEB), and adapter. After heat-inactivating ligation reactions at 65°C, the samples were digested with AluI at 37°C. Polymerase chain reaction was performed using diluted restriction-ligation samples, dNTP, Taq DNA polymerase (NEB), and EcoRI-primer containing barcode1. The purified samples were subjected to the fragment selection for ~450 bp using a Gel Extraction Kit . These fragment products were then subjected to polymerase chain reaction using Phusion Master Mix (NEB) and Solexa Amplification primer mix to add barcode2. The sequencing libraries were obtained using the Illumina HiSeq platform, and 100 bp paired-end reads were generated .Genomic DNA was extracted from the blood samples using Axy-Prep Genomic DNA Miniprep Kit  and evaluated for quality using agarose gel electrophoresis. According to the recommended pipeline, ~1 μg genomic DNA was incubated at 37°C with phred value-based error rate and GC content were analyzed. Using the fastp tool [http://broadinstitute.github.io/picard/) were employed to remove duplicate reads and sort the Sequence Alignment/Map files. Subsequently, SNPs were called and genotyped using GATK software (v3.7) according to GATK Best Practices recommendations [For the raw sequencing reads, the Qstp tool , low-quastp tool . Picard ndations –12.π), observed heterozygosity (Ho), and expected heterozygosity (He), Hardy–Weinberg equilibrium, and pairwise Identity-by-State (IBS) distance using the VCF tools and Plink . The polymorphism information content (PIC) and Wright’s fixation index (FST) of the breeds were computed using the PopSc toolkit [All clean SNPs were individually annotated using the genome annotation file in GTF format and analysis of variance tool . We anal toolkit .We obtained 507 million raw paired-end reads in total and 494 million clean reads after quality filtering . The aveHo lower than He, and the largest and smallest differences were observed in Jialuo (0.1507 vs. 0.2212) and Liangshan Semifine-wool (0.1918 vs. 0.2132) sheep, respectively. The PIC ranged from 0.1395 in Jialuo sheep to 0.2492 in Liangshan Semifine-wool sheep, with the average value of 0.2217 among the five breeds.Based on all the clean SNPs, we calculated the genetic diversity for individual and pooled breeds . The oveP-value < 0.05. The pairwise FST values among the five breeds are shown in ST = 0.0789), whereas the lowest FST was 0.0474 . Among the three local pure breeds of Butuo Black, Jialuo, and Mage sheep, the pairwise genetic divergences slightly ranged from 0.0656 to 0.0774 in terms of FST value. PCA-based clustering was performed based on the pairwise IBS distances  used 12 microsatellite markers and investigated the genetic diversity of six sheep breeds in Sichuan , which r9 for Ho . In the 9 for Ho . We alsoST values also supported this overall population structure for the five sheep breeds studied.Among the five sheep breeds included in the present study, Liangshan Semifine-wool, White Suffolk, and Butuo Black sheep had obvious genetic divergences, according to pairwise IBS distance. However, we could not differentiate Jialuo and Mage sheep because all the individuals were mostly clustered together. This is inconsistent with the former microsatellite marker-based report showing that Butuo Black and Jialuo sheep have a close genetic relationship ; this diIn the present study, we successfully employed SLAF-seq and constructed a reference panel of genome-wide and high-quality SNPs in five sheep breeds in Sichuan, China. Their genetic diversity and population structures were subsequently revealed, which would be helpful to facilitate our understanding and conservation of these genetic resources.S1 Table(PDF)Click here for additional data file.


Lynx rufus), a highly mobile, generalist felid that exhibits ecological and behavioral plasticity, high abundance, and broad connectivity across much of their range. However, bobcats also show genetic differentiation along habitat breaks, a pattern typically observed in cases of isolation-by-ecology (IBE). The IBE observed in bobcats is hypothesized to occur due to habitat-biased dispersal, but it is unknown if this occurs at other habitat breaks across their range or at what spatial scale IBE becomes most apparent. Thus, we used a multiscale approach to examine isolation by ecology (IBE) patterns in bobcats (Lynx rufus) at both fine and broad spatial scales in western Texas. We genotyped 102 individuals at nine microsatellite loci and used partial redundancy analysis (pRDA) to test if a suite of landscape variables influenced genetic variation in bobcats. Bobcats exhibited a latitudinal cline in population structure with a spatial signature of male-biased dispersal, and no clear barriers to gene flow. Our pRDA tests revealed high genetic similarity in similar habitats, and results differed by spatial scale. At the fine spatial scale, herbaceous rangeland was an important influence on gene flow whereas mixed rangeland and agriculture were significant at the broad spatial scale. Taken together, our results suggests that complex interactions between spatial-use behavior and landscape heterogeneity can create non-random gene flow in highly mobile species like bobcats. Furthermore, our results add to the growing body of data highlighting the importance of multiscale study designs when assessing spatial genetic structure.Patterns of spatial genetic variation can be generated by a variety of ecological processes, including individual preferences based on habitat. These ecological processes act at multiple spatial and temporal scales, generating scale-dependent effects on gene flow. In this study, we focused on bobcats ( Landscape heterogeneity has a powerful influence on genetic structure in nature, owing to the complex interaction between habitat preferences, resource distribution, movement capabilities, and underlying landscapes. Habitats are important for determining where organisms prefer to establish their home ranges and where they disperse; ultimately, shaping how landscape patterns influence gene flow. Much research has focused on how landscape heterogeneity influences genetic differentiation between populations or individuals, culminating in the field of landscape genetics . LandscaIn the absence of IBD or obvious barriers, habitat preferences can result in cryptic genetic structure in even the most mobile, generalist species. Several studies have described the various effects of habitat heterogeneity on neutral genetic structure when space is not the dominant driving force of spatial genetic patterns e.g., . For exaGenetic variation in vagile species often is a function of spatial scale where habitat preferences and local adaptation influence gene flow at small spatial scales and high dispersal abilities impact broadscale population structure. Because the landscape variables impacting gene flow are not consistent across spatial scales e.g., , single-Lynx rufus), a vagile, generalist felid found throughout North America  or a more complex association between genetic differentiation and site-specific environmental differences (IBE). Because the scale of landscape sampling can introduce varying features that may affect gene flow, we conducted multiscale analyses to test if IBE patterns differed based on spatial scale. Overall, bobcats’ high movement capability and generalist ecology could result in little genetic structure as expected in a relatively contiguous landscape. However, phylogenetic lineages of bobcats meet in the southern Great Plains along habitat gradients, a similar scenario to where bobcats exhibit habitat-based differentiation in the Midwestern United States . In the Our study area comprised five level III ecoregions across western Texas: High Plains, Rolling Plains, Edward’s Plateau, Trans-Pecos, and South Texas Plains . Brieflyn = 2) and fur-harvested animals (n = 98). Two additional samples were obtained from live animals, which were live-trapped with approval obtained from the West Texas A&M University Institutional Animal Care and Use Committee (IACUC # 04-12-12). Individuals were sexed  and classified as adult (n = 93), juvenile (n = 2), or unknown age (n = 7). DNA extractions on all samples were conducted using a modified Gentra Puregene tissue kit protocol . The primary modification concerned tailoring the amount of elution buffer based upon the quantity of DNA after the final EtOH wash, as revealed by visualization in a 1% agarose gel following electrophoresis. We genotyped all samples at 9 microsatellite loci shown to be variable in other bobcat genetic studies , 10 uM forward primer, 10 uM reverse primer, and 20–325 ng DNA template. PCR reaction thermal cycling conditions for all 9 microsatellites included an initial denaturing step of 94 °C for 1 min, 10 cycles of 94 °C for 15 s, 53 °C for 15 s and 72 °C for 45 s, followed by 50 cycles of 89 °C for 15 s, 53 °C for 15 s and 72 °C for 45 s and a final extension of 72 °C for 30 min (Polymerase chain reactions (PCR) were conducted in 12.5 ul volume reactions containing GeneMate Taq 2X Mastermix (GeneMate) with 2.5 mM MgClr 30 min . The denr 30 min . All ampA), observed and expected heterozygosity , FST and FIS estimates  with GenAlEx 6.5.03  and quantifies levels of admixture between putative clusters  steps and 300,000 burn-in steps under the admixture, correlated allele frequency model. The optimal K among the tested values was determined by visual examination of the likelihood scores in structure harvester (K statistic (K are above the optimum (q), a value that represents the proportion of an individual’s genome that belongs to each cluster structure bar plots were created in structure plot , using adegenet, version 2.1.1 (K) de novo, retaining all principal components (PCs) to infer a range of possible clusters. We selected the optimal K as that with the lowest BIC value. The optimal number of PCs to use in the DAPC was determined using the xval method.To complement our on 2.1.1  in R, veIn addition to identifying the number of genetic clusters across our study area, we also tested for the presence of IBD via a simple Mantel test. Simple Mantel tests quantify the correlation between matrices of pairwise genetic and Euclidean distances. We used GenAlEx to calculate Euclidean and pairwise genetic distance (default genetic distance in GenAlEx). Statistical significance was assessed with 10,000 permutations.r) using matrices of pairwise geographic and squared genetic distances between genotypes across all microsatellite loci to detect departures from random mating , then performs both a permutation and bootstrap test to assess significance of r-values within pre-defined distance intervals . Like many mammals e.g., , bobcatsntervals , 2012. Pntervals . SignifiDefining relevant spatial scales in highly mobile species often relies on either expert opinion or is an artifact of opportunistic sampling, so we calculated landscape variables at two biologically relevant spatial scales: a fine spatial scale based on bobcat home range sizes, and a broad spatial scale based on reported dispersal distances. For the fine spatial scale, we calculated landscape variables within a 2.69 km radius buffer around each point. The distance was based on the mean of published home range sizes in the southern Great Plains . For theIn total, both spatial scales were examined using nine environmental variable classes . Geospatial data for each environmental variable class was pulled from the Texas Natural Resources Information System (TNRIS). We selected variables from literature that found correlations between bobcat behavior and ecology and a particular landscape variable, or were previously shown to influence gene flow in other meso-carnivore species e.g., . Each enr > 0.7. For both spatial scales, we also removed variables with 50% 0 s or more .At both spatial scales, we used Patch Analyst 3.1  to calcuOrdination techniques are especially useful in landscape studies due to their ability to identify the combination of landscape variables that influence genetic variation, and can overcome assumptions of linearity that characterize distance-based methods . We usedadegenet , which was high compared to another study that used the same loci , and the spatial arrangement of the highest q-values suggested a weak latitudinal cline of the three clusters (structureq-plots at K = 2–5 and structure Harvester outputs). Pairwise FST values between the three putative clusters from structure were low, but significant . Visual examination of individual assignments to each cluster showed a random pattern, with no correlation to geographic location. structure may provide false certainty regarding K when FST is low (FST < 0.05). Taken together, K = 3 may not reflect true population structure. For DAPC analysis, the optimal number of clusters was found to be 3, and the optimal number of PCs retained for analysis was 20 . However, we observed support for fine-scale spatial autocorrelations among all bobcats. For all 102 cats, autocorrelation coefficients between proximate individuals were significantly larger than by chance , whereas males were random  was retained after model selection, and was associated with spatially lagged scores for sPCA Axis 1, suggesting individuals living in herbaceous rangeland are more genetically similar. The land use categories labeled urban, agriculture, mixed rangeland, and stream density were insignificant variables and not retained at the fine scale. The adjusted R-squared value, which represents the proportion of variation explained after removing variability due to the conditional terms , was low (0.096).Spatial PCA axes  revealedF1, 101 = 24.9527, P < 0.001) and agriculture  were significant and retained as variables after model selection. Mixed rangeland was associated with spatially lagged sPCA scores for Axis 1, and agriculture was also detected as a potential influence on spatially lagged sPCA scores for Axis 1. No variables were significantly associated with Axis 2. The variables included in the broad spatial scale pRDA were the same as in the fine spatial scale pRDA with the addition of the vegetation type mesquite juniper bush. The adjusted R-squared value at the broad scale explained a higher proportion of the genetic variation than the fine scale (0.236).In contrast, at the broad spatial scale, the land use categories of mixed rangeland  cline, differentiating bobcats in the northern portion of western Texas from cats in the southern half. This cline was similar to that detected by Bobcats exhibited clinal population genetic structure. Spatial examination of the As predicted, we found support for fine-scale genetic structure consistent with sex-biased dispersal in bobcats , which mOur ordination analysis found that patterns of landscape effects on genetic variation differed by spatial scale, which highlights the importance of multiscale designs to gain a more holistic view of landscape effects on genetic variation. At the fine scale, our analysis detected herbaceous rangeland as a potential influence on patterns in the sPCA Axis 1. Herbaceous rangeland is dominated by naturally occurring and modified areas that include tall and short grasses and forbs as their principal cover . The assMixed rangeland and agriculture were dominant influences on genetic variation at the broad spatial scale. This contrast with the fine scale emphasizes how spatial scale can impact the relationship between gene flow and landscape structure . Mixed rAgriculture had a weak influence on genetic variation at the broad scale. Bobcats tend to avoid large homogenous agricultural patches , and oneOverall, landscape effects on bobcat genetic variation were relatively weak in our study area, which argues against strong habitat-biased dispersal and IBE in our study area. Certainly, other environmental factors could influence genetic variation like prey preference and abundance, which has also been shown to influence genetic structure  and habiBobcats exhibit considerable behavioral plasticity, making it difficult to predict if landscape heterogeneity predicts genetic variation  and what scale is most relevant to examine such effects. Our study underscores how fine-scale analyses across an environmental gradient at multiple scales can identify unique landscape factors important for spatial genetic structure. In particular, site-specific habitat differences based on habitat are more likely to reveal important environmental variables that generate habitat-based genetic breaks as predicted by habitat-biased dispersal or local adaptation. Despite being a highly vagile species, the ecological and social determinants of bobcat gene flow in Texas appear to be scale-dependent, and the processes resulting in the IBE patterns are complex. These results likely reflect linkages among different scales of landscape composition and configuration, which is relevant to bobcat management in Texas. When combined with multiscale analyses, IBE methods can address the challenges of using landscape and genetic data to identify meaningful ecological patterns for management .10.7717/peerj.11498/supp-1Supplemental Information 1(A) Eigenvalues of sPCA  according their variance and Moran’s I A B components. (B) Positive eigenvalues (on the left) correspond to global structures, while negative eigenvalues (on the right) indicate local patterns.Click here for additional data file.10.7717/peerj.11498/supp-2Supplemental Information 2Structure of bobcat clusters (K) in western Texas revealed by Bayesian analysis implemented in STRUCTURE. Each individual is represented by a vertical bar broken into different colored genetic clusters and arranged by latitude, with length proportional to the assignment probability to each cluster. Analysis of 102 individuals, with possible numbers of clusters ranging from 2–10, indicated that the most likely number of clusters was 3. Bar plots created in STRUCTURE PLOT .Click here for additional data file.10.7717/peerj.11498/supp-3Supplemental Information 3Statistical output from Structure Harvester suggesting [A] optimal K with ΔK and [B] LnP(D).Click here for additional data file.10.7717/peerj.11498/supp-4Supplemental Information 4Bayesian information criterion (BIC) plot for DAPC between 1 and 10 showing an elbow with an arrow at K = 3.Click here for additional data file.10.7717/peerj.11498/supp-5Supplemental Information 5adegenet. Dots represent individuals, with colors denoting cluster assignment. [B] A plot of the individual densities against the first discriminant function retained show that the greatest proportion of variation lies with it. Colors correspond to cluster assignments, with significant overlap between clusters 1 and 3, suggesting two groups instead of 3.[A] Discriminant Analysis of Principal Components (DAPC) scatterplot drawn using nine microsatellites across 102 individual bobcats in the R package Click here for additional data file.10.7717/peerj.11498/supp-6Supplemental Information 6r > 0.7.We intersected GIS layers for each variable with a buffer polygon at both spatial scales and calculated the proportion of each variable within each buffer polygon. For the linear variables , we divided total variable lengths by the total hectares of the buffer polygons and converted to km/km2. For stream density, we included streams above an order of magnitude of 5 given the likelihood that anything below this cutoff would not be a significant barrier to bobcat movement. Maximum and minimum temperature reflected the weighted average of maximum minimum temperatures within each polygon. We calculated annual precipitation to a weighted average by intersecting this layer with buffer polygons and adding the products of the number of hectares at each rain average value (in) and divided by the total hectares of each buffer polygon. To determine which variables to use in the partial redundancy analysis (RDA), variables were selected from among nine environmental classes following Pearson’s correlation, and selected if Click here for additional data file.10.7717/peerj.11498/supp-7Supplemental Information 7R code for sPCA, DAPC, RDA analyses of raw data.Click here for additional data file.10.7717/peerj.11498/supp-8Supplemental Information 8Raw data for genetic analyses, including genotypes, geographic data, and output for descriptive statistics using GenAlEx.Click here for additional data file.10.7717/peerj.11498/supp-9Supplemental Information 9Raw data for 102 bobcat genotypes using .gen extension for genepop.Click here for additional data file.10.7717/peerj.11498/supp-10Supplemental Information 10Raw data of XY coordinates for 102 bobcat samples.Click here for additional data file.10.7717/peerj.11498/supp-11Supplemental Information 11Proportions of each environmental variable within sample location buffer polygons at the home range spatial scale. For the linear variables , we divided total variable lengths by the total hectares of the buffer polygons and converted to km/km2. For stream density, we included streams above an order of magnitude of 5 given the likelihood that anything below this cutoff would not be a significant barrier to bobcat movement. Maximum and minimum temperature reflected the weighted average of maximum minimum temperatures within each polygon. We calculated annual precipitation to a weighted average by intersecting this layer with buffer polygons and adding the products of the number of hectares at each rain average value (in) and divided by the total hectares of each buffer polygon.Click here for additional data file.10.7717/peerj.11498/supp-12Supplemental Information 12Proportions of each environmental variable within sample location buffer polygons at the dispersal range spatial scale. For the linear variables , we divided total variable lengths by the total hectares of the buffer polygons and converted to km/km2. For stream density, we included streams above an order of magnitude of 5 given the likelihood that anything below this cutoff would not be a significant barrier to bobcat movement. Maximum and minimum temperature reflected the weighted average of maximum minimum temperatures within each polygon. We calculated annual precipitation to a weighted average by intersecting this layer with buffer polygons and adding the products of the number of hectares at each rain average value (in) and divided by the total hectares of each buffer polygon.Click here for additional data file.


Bombax ceiba (B. ceiba)  in Hainan Island, South China, using simple sequence repeat (SSR) markers. A low genetic diversity  and bottleneck effects were observed. Genetic kinship was significant within 400 m or in 1,800–3,800 m. Both the mating pattern and paternity analysis confirmed obligate xenogamy and a low multiple paternity in B. ceiba. There was a strongly negative relationship between the frequency of matings and the distance between mating pairs. The average pollen dispersal distance was 202.89 ± 41.01 m (mean ± SE) and the farthest distance of > 1 km was recorded. Realized mating events showed an extremely leptokurtic distribution within 1,200 m, suggesting that the pollen dispersal distance was consistent with the optimal foraging theory of generalist birds such as Zosterops spp. and Pycnonotus spp. Paternity per tree ranged from two to six and the average effective number of pollen donors per maternal plant was 3.773, suggesting a low level of paternity diversity as compared to other bird-pollinated plants. We concluded that optimal foraging behavior by generalist birds could explain the leptokurtic pollen dispersal distribution and predominantly near-neighbor matings in B. ceiba. The limited pollen dispersal distance and low multiple paternity were consistent with low fruit setting rate (3.27 ± 0.93%) in this self-incompatible tree, which was caused mainly by the restricted flight distance of birds and human disturbances. Low genetic diversity and significant spatial genetic structure might have largely resulted from logging and human collection of fruits.Bird pollination in Asia is regarded as an uncommon phenomenon and, therefore, only a few investigations on mating pattern and paternity in fruits of Asian bird-pollinated plants have been conducted. Here, we examined spatial genetic structure, pollen dispersal, and multiple paternity in a natural population of  Birds are one of the most diverse group of ecosystem service providers. More than 900 bird species pollinate members of ca. 500 of the 13,500 vascular plant genera, making bird pollination an essential component of the ecosystem . This poFritillaria imperialis  L.  is an umbrella species in dry and hot forest areas of Asia because they can provide food, shelter, roosting, and breeding sites to a large number of birds as well as insects and form the major structural and functional basis of forest ecosystems .1 At this time, there are only limited number of plants that are flowering in southern China and the copious dilute nectar of B. ceiba acts as the main food and a safe water resource for generalist birds. B. ceiba during the peak flowering in China, especially in Hainan Island and dry-hot valleys of Yunnan  What is the mating system and pollen dispersal of B. ceiba? and (ii) How do generalist birds affect genetic diversity and mating patterns? We hypothesize that: (i) limited-distance pollen dispersal and low paternal diversity may be due to high density of B. ceiba individuals and bird habits such as the restricted flight distance of birds and optimum foraging behavior of birds and (ii) pollination by generalist birds may result in high outcrossing rate, but low genetic diversity in B. ceiba due to human disturbances.In this study, we analyzed genetic diversity, mating system, gene flow, and multiple paternity of B. ceiba trees that were located at the forest margins near the Bawangling National Nature Reserve, west Hainan Island  and a dry season (November to next April), and witnesses the lowest annual precipitation  on Hainan Island. The annual average temperature is about 24.3°C .2This study was conducted on a wild population of hectares  and the B. ceiba is from early February to late March and the life span of one single flower is 7–12 days. At midnight, hundreds of the mature buds begin to open. B. ceiba is a protandry plant and the anthers dehisce almost immediately after the flowers open and pollen activity was about 80%. After anther dehiscence, the stigma becomes receptive and the function between the sexes overlapped. The staminate phase can last for about 30 h, while the pistillate phase of B. ceiba can last around 3–4 days.The flowering season of B. ceiba in Hainan Island is between March and May. Capsules are ellipsoid and dehisce after the ripening. Many seeds are produced (about 200), which are obovate, smooth, and fibrous from outside and form fluffy spheres of seed coats. The seeds are located in the center of the sphere and are dispersed far away by the wind.The capsule maturation period of On around 10 consecutive sunny days, between 06:00 and 18:00 h in February 2018, the number and type of bird visits per day in the 10 blooming individuals were recorded and photographed everyday in studied population.B. ceiba. Five pollination treatments were applied on different branches on four trees (n = 20 flowers), bagging mature buds without any hand pollination; (2) emasculation (n = 20 flowers), bagging mature buds and all the anthers were cutoff; (3) autogamy (n = 20 flowers), bagging mature buds and pollinated with pollen from the same flower; (4) geitonogamy (n = 20 flowers), bagging emasculated mature buds and pollinated with pollen from the same plant; and (5) xenogamy (n = 20 flowers), bagging emasculated mature buds and pollinated with pollen from different B. ceiba trees. Fruit set of open pollination was observed from all the flowers on 17 individuals as control.Hand-pollination experiments were conducted in the wild population to estimate mating systems of ur trees : (1) Bag3 was used to obtain the global positioning system (GPS) coordinates of each plant and all the adults were mapped on this study site in 2018  protocol . A total2O. Forward primers were labeled with a fluorescent dye . PCR amplifications were performed as following: an initial denaturation step at 94°C for 5 min, 35 cycles comprising of: (i) denaturation at 94°C for 30 s, (ii) 45 s annealing at temperatures specified below, and (iii) extension at 72°C for 1 min. This was followed by a final extension step at 72°C for 10 min. The annealing temperature was 57°C for BC1, BC3, BC4, BC8, BC9, and BC13 and 60°C for BC2, BC5, BC6, BC7, BC10, BC11, and BC12. To test the utility of the primers, PCR products were detected on 1% agarose gels. Next, the PCR products were resolved on the ABI3730xl Genetic Analyzer  with an internal lane standards (LIZ) (500) size standard. Fragment data were analyzed by using GeneMarker version 2.4.0 .Polymerase chain reaction amplification of primer pairs was performed with the Veriti 96-Well Thermal Cycler  by using a 25-μl reaction mixture containing 1 μl of genomic DNA (50 μg/ml stock), 1 μl each of forward and reverse primers (10 μM stock), 12.5 μl of PCR Master Mix, and 9.5 μl of ddHNa), number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and inbreeding coefficient (Fis). The total paternity exclusion probability of the first [Pr(Ex1)] and second parent [Pr(Ex2)] was also estimated. These analyses were performed by using the Cervus version 3.0.7 program  between individuals  and single locus (ts) outcrossing rates, correlation of tm within progeny arrays (rt), and multilocus paternity correlation (rp) were calculated with the help of multilocus t and r (MLTR) win 3.4 (Nep) that participated in cross-pollination was estimated from the within-sibship correlated paternity (rp), which is defined as Nep = 1/rp. The program was run by using default parameters for the outcrossing rate (t = 0.9), parental inbreeding (F = 0.1), and paternity correlation (rp = 0.1). The estimation of mating system indices was made by the expectation-maximization method to ensure convergence; 1,000 bootstraps were used to calculate SE.Estimates of mean multilocus  by using the kurtosis function in R , Pycnonotus xanthorrhous (P. xanthorrhous), Pycnonotus jocosus (P. jocosus), Acridotheres cristatellus, Sturnus sinensis, Lanius spp., and Parus spp. , while P. xanthorrhous, P. jocosus, and Parus spp. are resident birds  for the adults and –0.224  for the offspring, which indicated “heterozygote excess,” but there was no significant difference between them (P = 0.638). In addition, Fis in adults and seedlings significantly differed from 0 . Eight loci in the adults and ten loci in the offspring showed significant deviation from HWE , Ne (P = 0.499), Ho (P = 0.271), and He (P = 0.494). Across all the 13 loci, the cumulative expected exclusion probability of the first Pr(Ex1) and second Pr(Ex2) parents, estimated from adults, was 0.9935 and 0.9999, respectively  and the offspring  of B. ceiba were found not at mutation-drift equilibrium under the SMM. Under the TPM, the program detected a bottleneck signature for adults ; however, the program did not find this signature for the offspring cohort . However, the allele frequency distribution test showed a mode-shift shape for the adults as well as the offspring of B. ceiba in Hainan population , 0.03270 (P = 0.031), 0.2370 (P = 0.033), and 0.01813 (P = 0.017), respectively , but not significantly different from the expected value (P > 0.05).Spatial genetic structure analysis, by using pairwise differentiation measures, showed significance in the first (0–200 m), second (200–400 m), and eighth distance classes , with a ectively . In the tm) for 17 mother plants were equal to 1.000 (tm-ts) ranged from –0.196 to 0.123, with a mean (± SE) value of –0.063 ± 0.017 among F1 seedlings from 79 capsules . The estimated correlation of paternity (rp) was 0.265 ± 0.024, indicating that individuals in the family have the opportunity to share the same father (Nep) was 3.773. This showed that there was more than one male parent in F1 seedlings derived from a single capsule  and 605 (50.8%) seedlings were assigned to a single pollen parent in the population at the 95 and 80% confidence levels, respectively. The remaining 585 seedlings (49.2%), which were not assigned to a pollen parent within the study population at < 80% confidence levels, were assumed to have been sired by an individual in the population that had not been sampled or to be a product of immigrant pollen grains from outside Bawangling population.Paternity analysis revealed high outcrossing rates (1.000) and multiple paternity, as 36 different sires were identified for 376 seeds in 12 families. The mean number of different sires per fruit ranged from 1.0 to 2.0, whereas the number of different sires assigned for paternity per tree ranged from 2 to 6 .P-values < 0.05), where their proportions (observed/random mating events) were 0.351/0.010 at 0–100 m and 0.410/0.022 at 100–200 m, respectively. Realized mating events were more frequent than events expected for random mating for the plants < 500 m apart, indicating a leptokurtic dispersal at this scale  between the frequency of the outcross mating and the distance between mating pairs (K = 0.495).There was a significant negative correlation  in a small isolated population (about 80 m)  , but sig reduced . Our res reduced  because  reduced , unlike  reduced . FurtherB. ceiba and disturbances by human activities such as tourism and farming facilitated short-distance flight of birds, resulting in many near random matings in Baoshan village (rp = 0.265) and may also be the main reason of the SGS of B. ceiba at this study site.Our paternity analysis indicates that pollen dispersal follows an extremely leptokurtic distribution within 1,200 m , which w village . In addi village . This reB. ceiba is observed in this study  accumulate more pollen on the stigma  was markedly lower than those reported in generalist-pollinated E. caesia (4.6 ± 0.3) (Banksia hookeriana (29.8 ± 1.96) (B. ceiba could be explained by following reasons: (1) Low multiple paternity probably resulted mainly from low fruit setting rate (3.27 ± 0.93%) in B. ceiba and restricted flight distance of birds  A massive number of flowers on one tree allows birds to meet their nectar needs without moving frequently between trees, which was proved by the restricted pollen dispersal distance   and Bank ± 1.96)  in Austrof birds , which mdistance . The higdistance  also maddistance ; and (3)distance  and someB. ceiba is extremely strict and has been documented in the present and previous studies (B. ceiba might be related to flower traits and the behavior of visiting birds. B. ceiba flowers are large, erect, and bowl shaped, with numerous stamens surrounding the five-branched stigmas (B. ceiba evolved to ensure outcrossing. This is confirmed by the significant number of aborted fruits observed in the field as well as the withered developing fruits observed in artificial self-pollination treatments.The self-incompatibility in  studies ; Table 2 stigmas  and, thuB. ceiba. Normally, nectar-feeding birds assist frequent outcrossing and facilitate pollen dispersal over long distances, which are predicted to result in high genetic diversity and weak genetic structure for bird-pollinated plants (Banksia attenuata in Australia (Camellia japonica in Japan (Penstemon scariosus (B. ceiba, the low genetic diversity and considerable SGS may be an outcome of the genetic bottlenecks (B. ceiba is widely used in engineering, construction, and composite manufacturing, as it is easily available in form of a fast-growing plant species (B. ceiba trees were cut down for economic development and fruits were collected by local people for silk making to make cloth at the beginning of the twentieth century (B. ceiba.Our results found a low genetic diversity and obvious SGS in d plants  such as ustralia , Camelliin Japan , and Pencariosus . In B. ctlenecks  caused b species . A large century , resulti century . These hThe original contributions presented in the study are included in the article/W-QX assembled and analyzed the data and wrote the initial draft of the manuscript. PM and LT helped with data analyses, reviewed, and revised the draft. M-XR conceived the idea, designed this study, and critically reviewed the manuscript. All the authors contributed to the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Network control makes the software stack more robust, allows multiple microscopes to be controlled by one computer, and facilitates sharing of equipment. Graphical and script-based clients can run simultaneously, making it easier to monitor ongoing experiments. We have included an extension mechanism to add functionality, for example controlling additional hardware components or adding automation routines. Using a Web of Things approach has resulted in a user-friendly and extremely versatile software control solution for the OpenFlexure Microscope, and we believe this approach could be generalized in the future to make automated experiments involving several instruments much easier to implement.We present the OpenFlexure Microscope software stack which provides computer control of our open source motorised microscope. Our diverse community of users needs both graphical and script-based interfaces. We split the control code into client and server applications interfaced via a web API conforming to the W3C Web of Things standard. A graphical interface is viewed either in a web browser or in our cross-platform Electron application, and gives basic interactive control including common operations such as Z stack acquisition and tiled scanning. Automated control is possible from Python and M These nAligning our software stack with the W3C WoT Architecture  means th. 1.2pyro library [Splitting microscope control software into client and server applications is also done by Microscope Cockpit ,12, thou library  for comm library –17, wher library .The software stack as described in this manuscript is specific to the OpenFlexure Microscope, but has the potential to be generalized. Generalizing this WoT approach adds another competing solution to the previous paragraph, though we do not propose an all-in-one solution requiring the adoption of our server code and user interface. Instead, our hope is that the approach of splitting up instrument control with a documented, standards-compliant API can enable intercompatibility. For example, it would be possible to write a server to act as a bridge, allowing μ Manager device adapters to be controlled through an HTTP API. Similarly, a set of device adapters could enable WoT devices to be controlled by the existing MMCore system, and hence the wide variety of applications that use it. Crucially, the ‘semantic typing’ mechanism that allows WoT devices to declare their capabilities and their compatibility with particular protocols enables this intercompatibility to be added gradually. Semantic types are not exclusive, so a particular device could be used from μ Manager or Cockpit or its own bespoke software, all through the same HTTP interface. We suggest that the taxonomy and object model provided by μ Manager could be an ideal basis for a set of semantic types for microscope components due to its wide adoption. In the long term, we hope that both open projects and proprietary hardware and software developers will adopt the WoT protocol as a common language, enabling more direct interoperability and eliminating the requirement to use any particular control system for a given experiment.. 2. 2.1A microscope’s software stack generally includes low-level device control code, logic to integrate the hardware components into a useful instrument, automation for common tasks, a graphical interface for interactive control, and a way to script automated experiments. Treating the microscope as a WoT device naturally splits these functions into client applications  and a server handling the bulk of the logic and hardware control as depicted in This split between the server application and clients has several important advantages. First, it enables multiple client applications to connect to a microscope simultaneously. This allows a graphical interface to display a real-time camera feed, while a script controls sample manipulation, data acquisition, and analysis. The server also provides continuity, so devices need not be reinitialized every time an experiment script is started. Conversely, a single client can manage multiple microscopes simultaneously. This has allowed clinicians to image sample slides from several microscopes concurrently, dramatically increasing data acquisition throughput.Separating the more complex server application from comparatively simple client applications makes it significantly easier to write client libraries in a broad set of languages. This means that microscope users can script experiments without having to re-implement the hardware control code in their language of choice, interface with a binary library, or learn a new language. It also ensures consistency between different languages and avoids duplicated effort, as most of the complexity is in the server application. Indeed, using the OpenAPI description, it is in principle possible to automatically generate clients in a wide range of languages, though these may not be as user-friendly as our current clients, which are written by hand.. 2.2Our server runs on a Raspberry Pi computer embedded in the microscope . The serClient applications can run on the embedded Raspberry Pi computer, making the microscope a stand-alone system to which keyboard, monitor, and mouse may be attached. More usually, client applications will run on other devices connected via a wired or wireless IP network, using the Raspberry Pi’s ethernet and WiFi interfaces. By using IP networking, we enable control of multiple instruments with any external router or switch. Replacing different (often proprietary and expensive) connectors and adaptors  with comThe IP itself allows for high-speed, low-latency plug-and play communication. Fully remote control can be enabled using existing, well-established secure protocols such as SSH forwarding and VPN connections. Clients can automatically detect the server’s IP address and capabilities via mDNS (multicast Domain Name System) , which i. 2.3The server application is written in Python, with much of the back-end code released as a separate library (Python-LabThings) . This liClient–server interactions take place over HTTP. Our HTTP API follows the W3C Web of Things interaction model  that repThe widespread existing use of REST APIs means that users can interact with the OpenFlexure Microscope using existing standard libraries. We make use of the OpenAPI standard  to provitype of operation to be handled. For example, an HTTP GET request will read the value of a property, whereas an HTTP PUT request will write a new value to the property . Each request and action is therefore handled by its own thread to allow concurrency. Access to physical hardware is carefully managed to avoid conflicting instructions by use of re-entrant locks. For example, if the translation stage is currently in the middle of a long movement, a request to move elsewhere will be denied until the initial move has completed, releasing the stage’s lock. Clients can continue to interact with the microscope while an action is running, as long as they do not require a locked piece of hardware. This, for example, allows the live camera stream to be monitored during long-running experiments without users having to manually manage multiple threads.push updates to clients without polling, for example using Server-Sent Events [Background tasks are handled automatically by the server. Whenever an ‘action’ is requested, the server will start the function in a new thread and immediately send a ‘created’ response back to the client, including the URL of an ‘action resource’ the client can poll to check its progress or final return value. In the future, we can improve efficiency by allowing the server to asynchronously t Events .. 2.3.2Most automation and integration can be achieved using client-side code, which is simple to write and easy to debug. When the server code must be added to, for example to allow control of additional hardware components, Python code can be added to the server through our ‘extension’ mechanism. This also provides a way to make routines that are initially developed using client code to be made conveniently available to clients in any language, simplifying experiment scripts by providing higher-level actions. The main server application handles only the most basic microscope functionality: capturing images, moving the stage and managing device settings. A set of default extensions is included in the server package, providing higher-level capabilities including autofocus, scanning the stage to produce mosaics of images, and calibrating the camera and stage. Default extensions may be removed or replaced, allowing functionality to be customized on each microscope. Extensions are written as Python scripts that have direct access to Python objects that manage physical components comprising the microscope (e.g. camera and translation stage). Extensions can provide HTTP API endpoints and HTML interfaces that are displayed as part of the microscope’s web app, and their capabilities are included in the microscope’s built-in API documentation.. 2.3.3The OpenFlexure Microscope software does not yet implement access control, and relies on network topology for security . Secure remote access is already possible by using tools such as SSH to ‘tunnel’ connections, but in the future access control could be provided using standard security protocols that are provided for in the WoT standard, making the microscope more suitable for use on an insecure network.. 2.4Our primary client for the OpenFlexure Microscope is a web application included in the microscope’s internal API server. This application provides a comprehensive graphical interface for the microscope, including a live stream of the camera, capture functionality, basic data management and full extension support. By developing the client as a browser-accessible web application, we are able to support many different operating systems without any additional code, while simultaneously drawing on the expertise brought by a large community of existing libraries.The web application is accompanied by a desktop application (OpenFlexure Connect) handling device discovery and connection. The application finds and displays discovered microscopes using mDNS, as well as allowing manual connections and saving a list of commonly accessed microscopes. Upon connecting, the application loads the microscope’s graphical user interface . The intUsing a modular interface served by the microscope allows the client to only render user interface elements for enabled functionality. Server extensions are able to define new graphical interface components to be rendered within the main client application. For example, the interface to manage where images are stored is defined in the relevant extension. This mechanism is specific to our web application, rather than a general feature of the WoT standard. Interfaces are served through the HTTP API as HTML or JSON documents, linked to from the automatically generated description of the extensions.For experiment scripting, we have created a Python client for the microscope ,37 that The flexibility of the client–server architecture allows task or experiment specific interfaces to be created quickly. For example, a client for controlling the microscope with a USB game pad was developed . This cl. 3. 3.1Central to the microscope interface is the integrated live video display. The Raspberry Pi camera is supported by GPU firmware that provides accelerated JPEG compression of each video frame, allowing us to serve a real-time Motion JPEG (MJPEG) live stream of the camera. The server starts a background thread on startup that records JPEG frames from the camera into a buffer. When clients connect to the stream, the server will begin sending a multi-part stream of frames taken from that buffer. A synchronization event is created for each client thread ensuring that clients never receive the same frame twice. As a new frame is read from the camera, the event for each client is set, at which point the response handler for each client will pass the frame onto the client, unset the event, and then wait for the event to be set again, dropping frames if necessary to ensure latency is minimized for clients not able to receive frames at the full rate. This system is based on the work of Miguel Grinberg , and is . 3.2The Raspberry Pi camera can capture JPEG images and the raw 8 megapixel Bayer data from the camera sensor ,43. ThisAs previously mentioned, multiple microscopes can be run in parallel to increase data throughput for a single operator. The greatest time saving can be achieved by setting microscopes to automatically scan over a large area, building a composite image of hundreds of overlapping fields of view (FOVs). The server has the option to perform such scans with movements, paths and capture types chosen by the user. Capture options and metadata are the same as individual captures, and individual images are saved, with metadata, as the scan runs . Scans r. 3.3x-y position move the sample over a sphere cap relative to the optics rather than a plane [x − y location in an automatic scan. As a typical diagnostic scan may require over 100 x − y sites to be imaged, the software must focus rapidly while still being sufficiently reliable to not invalidate a large scan with any out-of-focus images.Due to the parallelogram-based mechanisms controlling the motion of the OFM translation stage, changes to the  a plane . This nez-stack of images regularly spaced between points expected to be far above and below the focal point. At each height, an image is captured and converted to grey-scale. A Laplacian convolution is applied to the whole image, assigning higher values to areas of greater spatial brightness variance. These values are raised to the fourth power and summed over the image to provide a sharpness value. The translation stage is then returned to the z-position with the highest sharpness. This procedure is based on methods used previously to detect focused areas in an out-of-focus image [A basic autofocus procedure captures a us image , and whiz-position as the objective moves through the focal point without stopping, the position of peak sharpness can be identified and returned to. On a sparse sample, blur in out-of-focus images can introduce information into blocks which would otherwise be empty. If this increase in the number of blocks containing some non-zero information outweighs the reduction of blocks containing a large amount of information, the JPEG size may maximize away from focus. However, for feature-dense samples the size of a JPEG image can generally be used as a reliable measure of focus. This autofocus method has a greater positional resolution than the discrete steps of the simpler autofocus as MJPEG frame size can be tracked on-the-fly, reducing the time taken to less than 5 s. As autofocus is a rate-limiting step for scanning large samples, we have continued to refine the method in application-specific estensions, for example adding error correction to improve reliability when using oil immersion objectives [A fast autofocus procedure uses the MJPEG preview stream as a metric of focus. By disabling bit rate control, the stream becomes a simple series of independent JPEG images each with identical compression settings. This JPEG compression uses the discrete cosine transform to describe blocks of the image , where ejectives .. 3.4. 3.4.1Due to chief ray angle compensation on the Raspberry Pi camera module’s Sony IMX219 image sensor, the raw images captured by the microscope suffer from vignetting even when the sample is uniformly illuminated. However, flat-field correction allows us to recover uniform images in software . We use . 3.4.2x- and y-axes in turn, analysing the resulting displacement in the image from the camera [It is often convenient to move the microscope stage by a given displacement in pixels on the camera, but the axes and step size of the translation stage rarely align perfectly. We calibrate this relationship by moving back and forth along the stage’s e camera . We combe camera , but treThe same image analysis used for stage calibration is used as a two-dimensional displacement encoder, allowing for closed-loop sample translation and closed-loop scanning. This significantly reduces the error in each individual move, as well as ensuring that errors do not accumulate over the course of a large scan. Going forward, we will extend this functionality to include simultaneous location and mapping (SLAM) . This wi. 4The OpenFlexure Microscope software stack provides both graphical and scripted interfaces to the microscope’s hardware capabilities, meeting the needs of users with a very wide range of technical abilities. Splitting the code into a server and multiple clients allows the microscope to be controlled as a stand-alone device or over a network, via an interactive application or through a script. Multiple clients can connect to the microscope at once, which reduces the need to duplicate the functions of the graphical interface in scripts that run particular experimental protocols. Using IP networks allows for multiple devices to access a microscope simultaneously, or for one computer to control multiple microscopes. Our standards-compliant HTTP API allows experiments to be scripted in almost any modern language on any operating system, using only standard libraries.atlab clients, which can run alongside the graphical interface and integrate well with notebook-based programming.We have created a desktop application that makes it easy to find devices on a network, and display a graphical interface for the OpenFlexure microscope suitable for scientific, educational and clinical use. Extensions can add to or modify the graphical interface, to expose new capabilities or make it more suited to a particular purpose. We enable remote scripting of experiments with our Python and MThe core architecture of our software is written as stand-alone libraries which are not specific to the microscope . This maClick here for additional data file.