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Supplementary material 1 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure S1. Geographic distribution of voucher specimens used in this analysis
Figure 2 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure 2 Parts A and B. Phylogeny of Hipposideridae based on Bayesian analysis of 303 cyt-b sequences. Colored lines denote well supported clades and symbols denote nodal support: red circles, BS ≥ 70%, PP ≥ 0.95; black circles BS ≥ 70%, PP ≤ 0.95; open circles BS ≤ 70%, PP ≥ 0.95.
Figure 1 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure 1 Type localities for Afrotropical hipposiderids: Doryrhina, blue symbols; Hipposideros, white symbols; Macronycteris, black symbols. Stars denote valid species, whereas circles indicate taxa considered as subspecies or synonyms. Localities are projected onto the biome map of Olson et al. (2001). Taxa depicted are: Hipposideros abae J. A. Allen,1917; †Hipposideros (Pseudorhinolophus) amenhotepos Gunnell, Winkler, Miller, Head, El-Barkooky, Gawad, Sanders & Gingerich, 2015; Phyllorhina angolensis Seabra, 1898; Hipposideros caffer var. aurantiaca De Beaux, 1924; Hipposideros beatus K. Andersen, 1906; †Hipposideros besaoka Samonds, 2007; Phyllorrhina bicornis Heuglin, 1861; Hipposideros braima Monard, 1939; Hipposideros caffer Sundevall, 1846; Phyllorhina caffra Peters, 1852; Hipposideros camerunensis Eisentraut, 1956; Hipposideros caffer centralis K. Andersen, 1906; Rhinolophus Commersonii É. Geoffroy, 1813; Hipposideros cryptovalorona Goodman, Schoeman, Rakotoarivelo & Willows-Munro, 2016; Hipposideros curtus G. M. Allen, 1921; Phyllorrhina cyclops Temminck, 1853; Phyllorrhina fuliginosa Temminck, 1853; Hipposideros gigas gambiensis K. Andersen, 1906; Rhinolophus gigas Wagner, 1845; Phyllorrhina gracilis Peters, 1852; Hipposideros caffer guineensis K. Andersen, 1906; Hipposideros jonesi Hayman, 1947; †Hipposideros kaumbului Wesselman, 1984; Hipposideros lamottei Brosset, 1985; Hipposideros langi J. A. Allen, 1917; Hipposideros marisae Aellen, 1954; Phyllorhina Commersoni, var. marungensis Noack, 1887; Hipposideros beatus maximus Verschuren, 1957; Phyllorrhina megalotis Heuglin, 1861; Rhinolophus micaceus de Winton, 1897; HipposiderosCommersoni mostellum Thomas, 1904; Hipposideros nanus J. A. Allen, 1917; Hipposideros gigas niangarae J. A. Allen, 1917; Hipposideros caffer niapu J. A. Allen, 1917; Phyllorrhina rubra Noack, 1893; Hipposideros sandersoni Sanderson, 1937; Hipposideros tephrus Cabrera, 1906; Phyllorhina Commersoni, var. thomensis Bocage, 1891; Hipposideros gigas viegasi Monard, 1939; Phyllorhina vittata Peters, 1852.
Figure 7 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 7 Classification of Pontoscolex corethrurus individuals according to a Bayesian assignment algorithm implemented in NEWHYBRIDS (Anderson and Thompson 2002) to detect gene flow. Each unit represents an individual corresponding to parental lineages (Lineage A and Lineage B), F1 generation, F2 (F1 x F1) and later generation or introgressive hybrids B1 (Lineage A x F1) and B2 (e.g., Lineage B x F1).
Figure 6 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 6 Genetic structure using ISSR data for 35 Pontoscolex corethrurus individuals based on discriminant analysis of principal components (DAPC). Proportion of eigenvalues in discriminant analysis (bottom left plot) and PCA eigenvalues (bottom right), with the first 12 significant principal components highlighted in black.
Figure 4 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 4 UPGMA dendrogram of genetic distance between MGLs (A) and between populations (B) observed in the distinct populations of Pontoscolex corethrurus collected in central Veracruz State, Mexico. Only bootstrap values higher than or equal to 70% are shown.
Figure 2 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 2 Rarefaction curve of expected number of MLGs captured per earthworm of Pontoscolex corethrurus sampled (A), and a MLG accumulation curve according to the number of loci sampled (B).
Figure 3 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 3 A Principal Components Analysis, where colors indicate specimens of the population (A) and a Minimum Spanning Network where each node denotes a different MLG, with size matching the number of individuals. Edge thickness and color are proportional to absolute genetic distance. Edge lengths are arbitrary (B). Both analyses show the relationship between multilocus genotypes (MLGs) for four different earthworm populations of Pontoscolex corethrurus living in central Veracruz State, Mexico.
Figure 1 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 1 Pastures sampled in the central region of Veracruz State, Mexico. LV, Laguna verde; AC, Actopan; LC, La Concepción; NA, Naolinco. The digital elevation model was created using data provided by Instituto Nacional de Estadística y Geografía, México.
Figure 5 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure 5 Estimated population genetic structure with a summary plot of Q estimates based on the ISSR data observed for four populations of Pontoscolex corethrurus in central Veracruz State, Mexico. Each individual is shown by a vertical line, which is partitioned into colored segments representing the fraction of the number of members in cluster K (%).
Supplementary material 1 from: Ortíz-Gamino D, Gregorio J, Cunha L, Martínez-Romero E, Fragoso C, Ortíz-Ceballos ÁI (2020) Population genetics and diversity structure of an invasive earthworm in tropical and temperate pastures from Veracruz, Mexico. ZooKeys 941: 49-69. https://doi.org/10.3897/zookeys.941.49319
Figure S1
Global patterns of population genetic differentiation in seed plants
<p>Evaluating the factors that drive patterns of population differentiation in plants is critical for understanding several biological processes such as local adaptation and incipient speciation. Previous studies have given conflicting results regarding the significance of pollination mode, seed dispersal mode, mating system, growth form, and latitudinal region in shaping patterns of genetic structure, as estimated by F<sub>ST</sub> values, and no study to date has tested their relative importance together across a broad scale. Here we assembled a 337-species dataset for seed plants from publications with data on F<sub>ST</sub> from nuclear markers and species traits, including variables pertaining to the sampling scheme of each study. We used species traits, while accounting for sampling variables, to perform phylogenetic multiple regressions. Results demonstrated that F<sub>ST</sub> values were higher for tropical, mixed-mating, non-woody species pollinated by small insects, indicating greater population differentiation, and lower for temperate, outcrossing trees pollinated by wind. Among the factors we tested, latitudinal region explained the largest portion of variance, followed by pollination mode, mating system and growth form, while seed dispersal mode did not significantly relate to F<sub>ST</sub>. Our analyses provide the most robust and comprehensive evaluation to date of the main ecological factors predicted to drive population differentiation in seed plants, with important implications for understanding the basis of their genetic divergence. Our study supports previous findings showing greater population differentiation in tropical regions and is the first that we are aware of to robustly demonstrate greater population differentiation in species pollinated by small insects.</p>
Figure 2 in Non-invasive genetic study and population monitoring of the brown bear (Ursus arctos) (Mammalia: Ursidae) in Kastoria region - Greece
Figure 2. (A) Means of estimated LnP (Data) and standard deviations for K = 1 to K = 5. (B) Factorial correspondence analysis plot of multilocus genotypes for 82 brown bear individuals identified in the present study.
Figure 8 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 8 The intensity of purifying selection of 12 mitochondrial genes of Lateolabrax maculatus. The different colors represent different geographical populations.
Figure 7 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 7 The changed trend of effective population numbers with the time based on Bayesian skyline plot method. X-axis is the timescale before present, and Y-axis is the estimated effective population size. Solid curves indicate median effective population size; the shaded range indicates 95% highest posterior density intervals.
Figure 5 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 5 Bayesian tree constructed based on 86 whole-mitochondrial sequences of Lateolabrax maculatus. Each line represents one individual in the population. The reseda area and orange area represent north population and south population, respectively. Lateolabrax japonicus was used as outgroup.
Figure 6 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 6 The median-joining network constructed based on 78 haplotypes of Lateolabrax maculatus. Each cycle represents a haplotype, the area of the circle is proportional to the frequency of haplotype. Different geographical populations were shown in different colors.
Figure 3 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 3 Plot of pairwise estimates of genetic (FST) and geographical distance between populations of Lateolabrax maculatus.
Figure 4 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 4 Admixture analysis among all populations derived from 85 whole-mitochondrial sequences. The K value was set 2 and 3.
Figure 2 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 2 The structure of Lateolabrax maculatus mitochondrial genome. The total length of mitochondrial genome of L. maculatus was 16,601 bp comprising 13 protein-coding genes (PCGs), 2 rRNA genes and 22 tRNA genes. 249 high-confidence single nucleotide polymorphism (SNP) sites and 24 indels was identified in 85 individuals.
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