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Fig. 1 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 1. Map of sampling localities in California, Oregon, and Washington, United States.Bombus vancouverensis is indicated by circles,B. vosnesenskii by triangles, and additional B. vosnesenskii from 2013 used to improve elevational coverage at middle latitudes for some traits by open triangles. Grayscale shading reflects a digital elevation model for the region.
Fig. 5 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 5. Relationships among space, population structure (FST), and average mass and wing loading (pw) differences among pair of populations for (A) B. vancouverensis and (B) B. vosnesenskii. Panels include plots of isolation by distance (FST by geographic distance), effects of population structure on mass, and the effects of elevation on mass and pw residuals from models including FST and geographic distance.The latter panels are included to illustrate the remaining positive effect of elevational separation on wing loading differences among B. vancouverensis populations after accounting for space and population structure, but not for B. vosnesenskii populations and not for mass in either species (seeTable 3 and Supp Fig. S6 [online only]).
Fig. 4 in Phylogenomic Variation at the Population-Species Interface and Assessment of Gigantism in a Model Wolf Spider Genus (Lycosidae, Schizocosa)
Fig. 4. Cluster analysis of unlinked SNPs using VAE for "Western group" individuals. Individuals are assigned to clades from the concatenated analysis (see Fig. 1).
Fig. 8 in Phylogenomic Variation at the Population-Species Interface and Assessment of Gigantism in a Model Wolf Spider Genus (Lycosidae, Schizocosa)
Fig. 8. Waveforms from substrate-borne vibrations produced by males in response to female pheromone cues. Phylogeny is based on maximum likelihood analysis of the concatenated dataset generated with IQ-TREE (see Fig. 2).
Fig. 2 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 2. Boxplots (shown for site means) and tests of differences between species in overall field mass (A), empty mass (B), ITS (C), forewing area (D), pw-Field (E), and pw-Empty (F). Statistical tests are summaries taken from linear mixed models (full report and parameter estimates in Supp Table S1 [online only]), showing marginal (R 2) and conditional (R 2) R2 values and with df for the species effect t statistic and P-values (***P <0.001; N.S. = not significant) associated with the M C relevant fixed effect estimated using lmertest. Mass, ITS, and pw values were log-transformed for statistical tests but plotted untransformed. Panels G–L show scatterplots of correlations among several traits for each bee and are presented with Pearson's correlation coefficients (r) and 95% CIs (see SuppTables 2 and 3 [online only] and Supp Figs. S2–S4 [online only] for additional trait correlation statistical details).
Molecular and quantitative genetic variation within and between populations of the declining grassland species Saxifraga granulata
<p class="MsoNormal"><span>Formerly common plant species are expected to be particularly susceptible to recent habitat fragmentation. We studied the population genetics of 19 recently fragmented <em>Saxifraga granulata</em> populations (max. distance 61 km) in Luxembourg and neighbouring Germany using RAPD markers and a common garden experiment. We assessed (1) the relationships between plant fitness, quantitative genetic variation, molecular genetic variation and population size, and (2) the relative importance of genetic drift and selection in shaping genetic variation. Molecular genetic diversity was high but did not correlate with population size, habitat conditions or with plant performance. Genetic differentiation was low (<em>F</em><sub>ST</sub> = 0.079 ± 0.135) and there was no isolation by distance. Longevity, clonality and the long-lived seed bank of <em>S. granulata</em> may have prevented strong genetic erosion and genetic differentiation among populations. H</span><span>owever, genetic distinctness increased with decreasing genetic diversity indicating that random genetic drift occurred in the studied populations. Quantitative and molecular gen</span><span>etic variation were correlated and their differentiation (<em>Q</em><sub>ST </sub>vs. <em>F</em><sub>ST</sub>) among <em>S. granulata</em> populations was similar, suggesting that mainly random processes have shaped the quantitative genetic differentiation among populations. However, pairwise quantitative genetic distances increased with geographic and climatic distances, even when adjusted for molecular genetic distances, indicating diversifying selection. Our results indicate that long-lived clonal species may be buffered at least temporarily against the negative effects of fragmentation. The relationship between quantitative genetic and geographic distance may be a more sensitive indicator of selection than <em>Q</em><sub>ST</sub> - <em>F</em><sub>ST</sub> differences.</span></p>
FIGURE 4 in Geographic variation in quantitative skull traits and systematic of southern populations of the leaf-eared mice of the Phyllotis xanthopygus complex (Cricetidae, Phyllotini) in southern South America
FIGURE 4. Dice-Leraas diagrams elaborated with the geometric mean (a) and individual scores of the first principal component (b) over selected localities of the geographical groups busw, rnsc, chnc, chew, chce, chse, scnw, scne, and scwc in a NE-SW transect. The black spots represent the means; the gray area represent the 95% confidence intervals and the bars the range. For the acronyms, see Materials and Methods section.
FIGURE 3 in Geographic variation in quantitative skull traits and systematic of southern populations of the leaf-eared mice of the Phyllotis xanthopygus complex (Cricetidae, Phyllotini) in southern South America
FIGURE 3. Specimen scores of adult individuals (ages 3–5) of Phyllotis (N = 336) for: a) Shape variable principal components 1 and 2 (light green = busw; dark green = coce and slno; orange = menw, mewe and nqne; blue = mesw, nqnw, nqso; red = chce, chnc, chse, chsw, chew, rnsc, scne, scnw, scwc); b) Shape variable canonical variates 1 and 2 extracted from 18-group discriminant function analysis based on samples grouped by its geographical origin (colors as in A); c) Shape variable principal components 1 and 2 (light green = bona; dark green = cent; yellow = nort; blue = west; red = sout); and ds) Shape variable canonical variates 1 and 2 extracted from 5-group discriminant function analysis based on samples grouped by its membership to mitochondrial lineages (colors as in C). For the acronyms, see Materials and Methods section.
FIGURE 2 in Geographic variation in quantitative skull traits and systematic of southern populations of the leaf-eared mice of the Phyllotis xanthopygus complex (Cricetidae, Phyllotini) in southern South America
FIGURE 2. Specimen scores of adult individuals (ages 3–5) of Phyllotis (N = 336) for: a) Size dependent principal components 1 and 2 (light green = busw; dark green = coce and slno; orange = menw, mewe and nqne; blue = mesw, nqnw, nqso; red = chce, chnc, chsc, chse, chsw, chew, rnsc, scne, scnw, scwc); b) Size dependent canonical variates 1 and 2 extracted from 18-group discriminant function analysis based on samples grouped by its geographical origin (colors as in A); c) Size dependent principal components 1 and 2 (light green = bona; dark green = cent; yellow = nort; blue = west; red = sout); and d) Size dependent canonical variates 1 and 2 extracted from 5-group discriminant function analysis based on samples grouped by its membership to mitochondrial lineages (colors as in C). For the acronyms, see Materials and Methods section.
FIGURE 1. a in Geographic variation in quantitative skull traits and systematic of southern populations of the leaf-eared mice of the Phyllotis xanthopygus complex (Cricetidae, Phyllotini) in southern South America
FIGURE 1. a) Map of southern South America indicating the placement of the collection localities of the specimens of Phyllotis studied in this work (see Appendix 1 for a detail); type localities of nominal forms discussed in the text were indicated by red stars. b) Geographical groups recognized in this study; different colors correspond to the mitochondrial lineages documented by Riverón (2011) as follow: light green = bona (P. bonariensis); dark green = central Argentina; orange = northcentral Argentina; blue = west-central Argentina; red = southern Argentina and Chile. For the acronyms, see Materials and Methods section. Specimens from busw correspond to P. bonariensis, while the remaining samples could be referred to the current concept of P. xanthopygus; individuals from coce, menw, mese, meso, mesw, nqne, nqnw and slno are usually included under P. x. vaccarum, while those of chnc, chwe, chce, chse, chsw, chsc, nqso, rnce, rnsc, scne, scwc, and scnw are traditionally assigned to P. x. xanthopygus.
Seasonal variation of mortality, detectability and body condition in a population of the adder (Vipera berus)
<p>Raw data used in paper by Dirk Bauwens & Katja Claus. 2019. Seasonal variation of mortality, detectability and body condition in a population of the adder (<em>Vipera berus</em>). Ecology and Evolution 9:5821–5834. DOI: 10.1002/ece3.5166 </p> <p>CH_data_Season_males.INP</p> <p>A text file with extension .INP for input in the program MARK (White & Burnham, 1999; Cooch & White, 2015), containing the capture-recapture histories of individual adult male adders (n = 1146). Each 52-digit string contains a 1-digit score (1/0 ; captured / not captured) per season (1-4) and year of study (2005 – 2017).</p> <p>CH_data_Season_females.INP</p> <p>A text file with extension .INP for input in the program MARK (White & Burnham, 1999; Cooch & White, 2015), containing the capture-recapture histories, including breeding status of individual adult female adders (n = 832). Each 39-digit string contains a 1-digit score (B/N/0 ; Breeding / Non-breeding / not captured) per season (1-3) and year of study (2005 – 2017).</p>
FIGURE 5 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 5. Cluster analysis of 11 populations of J. heuffelii from open grassland communities based on (A) 34 morphological characters, and (B) 19 bioclimatic parameters (C1 and C2 climate type, for details see Table 5.). The asterisk indicates the position of the morphologically most specific populations on both cluster diagrams, while the triangle indicates the position of the bioclimatically most specific populations on both cluster diagrams.
FIGURE 2 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 2. Results of the principal component analysis (PCA) for 34 quantitative morphological characters.
FIGURE 3 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 3. Results of the canonical discriminant analysis (CDA) based on 34 quantitative morphological characters of 299 individuals of J. heuffelii analyzed: (A) Canonical scores for each individual on the first and second DA axis; (B) Cluster analysis (UPGMA) for populations of J. heuffelii based on Mahalanobis distances. Full triangle, 8-SR: Radan; full square, 2-SR: Gradac; full circle, 5-SR: Nebeske stolice; full rhombus, 3-SR: Suvaja; gray triangle, 4-SR: Studenica; gray square, 6- SR: Treska; black-white circle, 11-SR: Stara planina; gray rhombus, 13-MA: Treskavec; empty triangle, 14-MA: Mavrovo; empty square, 12-BU: Trojanski prolaz; empty rhombus, 7-SR: Basarski kamik; plus, 9-SR: Pljačkovica; star, 10-SR: Besna Kobila; empty circle, 1-RO: Domogled.
FIGURE 4 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 4. Results of multiple correspondence analysis (MCA) of qualitative characters based on Mahalanobis distance between the populations of J. heuffelii analyzed.
FIGURE 1 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 1. Distribution of the population of J. heuffelii in Serbia, Macedonia, Bulgaria and Romania studied here. (see Table 1 for details.).
FIGURE 6 in Morphological variation of Jovibarba heuffelii (Crassulaceae) in the central Balkan Peninsula-The impact of geological, orographical and bioclimatic factors on the differentiation of populations
FIGURE 6. Results of canonical discriminant analysis (CDA) based on 34 quantitative morphological characters where the type of substrate was used as a categorical variable.
FIGURE 5 in Morphological variations among populations of Monochoria vaginalis s.l. (Pontederiaceae) in Thailand
FIGURE 5. Ordination plot of 244 specimens from 10 populations of M. vaginalis s.l. in Thailand based on 22 quantitative characters: MV1 = populations from Chiang Mai, Nan, Kanchanaburi, Ratchaburi, Suphan Buri and Ang Thong; MV2 = populations from Prachin Buri, Chachoengsao, Chumphon and Phatthalung.
FIGURE 4 in Morphological variations among populations of Monochoria vaginalis s.l. (Pontederiaceae) in Thailand
FIGURE 4. UPGMA clustering of each population (number of OTUs) based on Gower General Similarity Coefficient calculated between means of 22 quantitative characters of the M. vaginalis s.l. in Thailand. MV 1 and MV 2 represent the morphological forms of each population.
FIGURE 2 in Morphological variations among populations of Monochoria vaginalis s.l. (Pontederiaceae) in Thailand
FIGURE 2. Comparison of quantitative characters between 10 populations of M. vaginalis s.l. in Thailand, superscript a, b, c, d, e. f, g or h on bar graphs is significant difference at P <0.05 when compared with the other populations in each characters, analyzing by Duncan's multiple range test. (a): Leaf width, (b): Floral leaf - petiole length, (c): Rachis length, (d): Peduncle length, (e): Outer perianth width, (f): Number of flowers per inflorescence and (g): Seed length.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.