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Processed data supporting the manuscript "Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution"
<div><strong>Processed data supporting the manuscript: </strong>Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution</div> <div> </div> <div><strong>By:</strong> Diego de S. Souza 1, 2, Rowan L. K. French 3, José O. Silva Júnior 4, Eugenio H. Nearns 5, Luciane Marinoni 4, Ian P. Swift 6, Kelly B. Miller 7, Felix A. H. Sperling 2 & Marcela L. Monné 1</div> <div> </div> <div>1 Department of Entomology, National Museum, Federal University of Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.</div> <div>2 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.</div> <div>3 Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.</div> <div>4 Department of Zoology, Federal University of Paraná, Curitiba, Paraná, Brazil.</div> <div>5 National Museum of Natural History, Smithsonian Institution, Washington, DC, USA.</div> <div>6 California State Collection of Arthropods, Sacramento, California, USA.</div> <div>7 Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, USA.</div> <div> </div> <div>Corresponding author: Diego de S. Souza, dsouza@fieldmuseum.org. Current affiliation: Field Museum of Natural History, Chicago, Illinois, USA.</div> <div> </div> <div> </div> <div><strong>List of Contents: </strong></div> <div> </div> <div><strong>Onciderini_concat_matrix.phy</strong></div> <div>Concatenated matrix (cox1, Wg and CPS) used for the phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini). </div> <div> </div> <div><strong>PartitionFinder_AICc_best_scheme.txt</strong></div> <div>Results from PartitionFinder v2.1.1, containing the best partitioning scheme for the concatenated matrix of Onciderini, identified using the corrected Akaike Information Criterion (AICc), with model definitions for use in the phylogenetic analyses.</div> <div> </div> <div><strong>RAxML_Onciderini_concat_matrix (zip file)</strong></div> <div>- Onciderini_concat_matrix.phy: concatenated matrix (cox1, Wg and CPS) used in the RAxML phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini).</div> <div>- Partitions_AICc_RAxML.txt: partitioning scheme used in the RAxML analysis as predefined by PartitionFinder v2.1.1 using the corrected Akaike Information Criterion (AICc).</div> <div>- RAxML_bestTree.Onciderini_concat_matrix_ML: best-scoring maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini.</div> <div>- RAxML_bipartitions.Onciderini_concat_matrix_final: bipartitions (clades) of the maximum likelihood tree inferred by RAxML with support values estimated from 1,000 pseudoreplicates.</div> <div>- RAxML_bipartitionsBranchLabels.Onciderini_concat_matrix_final: final maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini, with labeled branches showing bootstrap support values.</div> <div>- RAxML_bootstrap.Onciderini_concat_matrix_bootstrap: bootstrap trees generated from a non-parametric bootstrap analysis in RAxML based on 1,000 pseudoreplicates.</div> <div>- RAxML_info.Onciderini_concat_matrix_bootstrap: log file containing details of the bootstrap analysis, including the settings and parameters used in the non-parametric bootstrap runs in RAxML.</div> <div>- RAxML_info.Onciderini_concat_matrix_final: log file summarizing the RAxML analysis, including settings and convergence statistics for the final maximum likelihood tree.</div> <div>- RAxML_info.Onciderini_concat_matrix_ML: log file containing details of the maximum likelihood tree search, including the parameters and models applied during the maximum likelihood analysis conducted by RAxML.</div> <div>- RAxML_log.Onciderini_concat_matrix_ML: log file of the maximum likelihood tree search for the concatenated matrix of Onciderini.</div> <div>- RAxML_parsimonyTree.Onciderini_concat_matrix_ML: parsimony starting tree used by RAxML during the maximum likelihood analysis for the concatenated matrix of Onciderini.</div> <div>- RAxML_result.Onciderini_concat_matrix_ML: maximum likelihood tree inferred by RAxML from the concatenated matrix of Onciderini, summarizing the tree topology and likelihood score for the best tree obtained.</div> <div> </div> <div><strong>BI_AICc_Onciderini_concat_matrix (zip file)</strong></div> <div>- BI_AICc_Onciderini_concat_matrix.nex: nexus file containing the concatenated matrix of Onciderini used for Bayesian Inference (BI), including the best-fit model scheme identified by PartitionFinder and MCMC parameters for running the analysis in MrBayes.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex_r1_r2_combined_consensus.tree: consensus tree from two combined independent Bayesian Inference (BI) runs based on the concatenated matrix of Onciderini, after discarding the first 25% of initial generations as burn-in.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run1.p: log file containing parameter values and likelihood scores from the first run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run2.p: log file containing parameter values and likelihood scores from the second run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_lognormal (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_lognormal.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- BEAST2_Onciderini_BD_lognormal_run[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_exponential (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_exponential.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- BEAST2_Onciderini_BD_exponential_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_uniform (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_uniform.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- BEAST2_Onciderini_BD_uniform_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>Comparative_analyses (zip file)</strong></div> <div><strong>RawData (folder):</strong> raw morphometric and girdling data, plus tree that was later pruned for downstream comparative analyses; these data were used as input for the OncidHeadDimorphism-DatasetPREP-FINAL.R data cleaning script. </div> <div>- Onciderini_BD_lognormal_run1-run8_consensus.nwk: newick version of TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre (outputted as a newick file by importing the .tre file into FigTree and exporting in newick format).</div> <div>- Measurements_Onciderini_Raw_Final.csv: individual-level raw morphometric data for Onciderini.</div> <div>- Behav_Matrix_2_states_trimmed_2022-12-15.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as girdlers (2 behavioral states across Onciderini species). </div> <div>- Matrix_3_states_trimmed_final.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as facultative girdlers (3 behavioral states across Onciderini species). </div> <div>- Matrix_2_states_trimmed_1LochGirdler_Final.csv: species-level data on girdling status for Onciderini species, with only one Lochmaeocles species (L. tessellatus) classified as a girdler (2 behavioral states across Onciderini species). </div> <div> </div> <div><strong>ProcessedData (folder): </strong>filtered data and pruned trees outputted by the OncidHeadDimorphism-DatasetPREP-FINAL.R script</div> <div>- oncid_f_36spp_clean.csv: dataset of species means and log-ratios for morphometric traits in females, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_m_42spp_clean.csv: dataset of species means and log-ratios for morphometric traits in males, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_sd_35spp_clean.csv: dataset of species means for sexual dimorphism in morphometric traits, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_girdlingbehav_allingroupspp_clean.csv: full dataset of girdling behavior for 56 Onciderini species that are in the phylogenetic tree; includes separate columns for the three alternative girdling classification schemes</div> <div>- oncid_tree_behavfull_56spp.nwk: pruned phylogenetic tree for the full girdling dataset (56 species)</div> <div>- oncid_tree_f_36spp.nwk: pruned phylogenetic tree for the female morphometric dataset (36 species)</div> <div>- oncid_tree_m_42spp.nwk: pruned phylogenetic tree for the male morphometric dataset (42 species)</div> <div>- oncid_tree_mf_43spp.nwk: pruned phylogenetic tree for all species with morphometric data for males or females; used for the stochastic character map next to the heatmap plot (Fig 4)</div> <div>- oncid_tree_sd_35spp.nwk: pruned phylogenetic tree for the sexual dimorphism dataset (35 species)</div> <div> </div> <div><strong>FittedModels (folder): </strong>fitted models (mvgls, model comparison analyses, OUM models, simmaps) outputted by the OncidHeadDimorphism-Analysis-FINAL.R script </div> <div>- MacroModelFits_logRtraits_f_36spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to female morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits_logRtraits_m_42spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to male morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits-SDDI-35spp_2024-10-11.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to sexual dimorphism data across 100 stochastic character maps of girdling behavior</div> <div>- mvgls-results-headsize-mf-2024-10-12.Rdata: fitted mvgls regression models for male and female traits (analyzed separately)</div> <div>- mvgls-results-sddi-2024-10-12.Rdata: fitted mvgls regression models for sexual dimorphism</div> <div>- OUM_headtraits_f_36spp-2024-10-12.Rdata: fitted OUM models and summary statistics for female head traits</div> <div>- OUM_headtraits_m_42spp-2024-10-12.Rdata: fitted OUM models and summary statistics for male head traits</div> <div>- OUM-SDDI-35spp-2024-10-12.Rdata: fitted OUM models and summary statistics for sexual dimorphism in head traits</div> <div>- simmaps_ard_full_2state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - all Lochmaeocles species are classified as girdlers</div> <div>- simmaps_ard_full_3state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with three behavioral states (girdling, non-girdling, or facultative girdling)</div> <div>- simmaps_ard_full_1Loch.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - only one Lochmaeocles species (L. tessellatus) is classified as a girdler</div> <div>- simmaps_ard_m.RDS: stochastic character map for the 42 species used in the analyses of male morphometric traits</div> <div>- simmaps_ard_f.RDS: stochastic character map for the 36 species used in the analyses of female morphometric traits</div> <div>- simmaps_ard.RDS: stochastic character map for the 35 species used in the sexual dimorphism analyses; 2 behavioral states.</div> <div> </div> <div><strong>Rscripts (folder): </strong>R scripts used to process data and run phylogenetic comparative analyses of head size and girdling behavior.</div> <div>- OncidHeadDimorphism-DatasetPREP-FINAL.R: R script used to filter data and prune trees from the RawData folder for downstream phylogenetic comparative analyses; outputs of this script are in the ProcessedData folder.</div> <div>- OncidHeadDimorphism-Analysis-FINAL.R: R script used to analyze data in the ProcessedData folder to answer questions about the origin and evolution of girdling behavior and the relationship between girdling and head size or head size sexual dimorphism; fitted models outputted by this script are in the FittedModels folder</div> <div>- OncidHeadDimorphism-Plots-FINAL.R: R script used to generate plots for the manuscript<br><br></div>
Host phylogeny and elevation predict infection by avian haemosporidians in a diverse New Guinean bird community (R script for analyses, figures, and supplemental figures )
<p>This script performs the glmm analysis of the elevation and infection prevalence data as well as the script required to generate the figures in the article.</p>
Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals
<p>Differences in the bacteria inhabiting mammalian gut microbiomes tend to reflect the phylogenetic relatedness of their hosts, a pattern dubbed phylosymbiosis. Although most research on this pattern has compared the gut microbiomes of host species across biomes, understanding the evolutionary and ecological processes that generate phylosymbiosis requires comparisons across phylogenetic scales and under similar ecological conditions. We analyzed the gut microbiomes of 14 sympatric small-mammal species in a semi-arid African savanna, hypothesizing that there would be a strong phylosymbiosis pattern associated with the different body sizes and diets of the mammalian lineages present. Consistent with phylosymbiosis, microbiome dissimilarity increased with phylogenetic distance among hosts, ranging from congeneric sets of mice and hares that did not differ significantly in microbiome composition to species from different taxonomic orders that had almost no gut bacteria in common. While phylosymbiosis was detected among just the 11 species of rodents, it was substantially weaker than comparisons involving all 14 species together. In contrast, microbiome diversity and composition were generally more strongly correlated with body size, dietary breadth, and dietary overlap in comparisons restricted to rodents than in those including all lineages. The starkest divides in microbiome composition thus reflected the broad evolutionary divergence of hosts, regardless of body size or dietary composition, while subtler microbiome differences reflected variation in ecologically important traits between closely related hosts. Strong phylosymbiotic patterns arose deep in the phylogeny, and ecological filters that promote functional differentiation of cooccurring host species may disrupt or obscure this pattern near the tips.</p>
Data from: Tracking of host defenses and phylogeny during the radiation of Neotropical Inga-Feeding sawflies (Hymenoptera; Argidae)
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Data from: New species of closely related endosymbiotic dinoflagellates in the Greater Caribbean have niches corresponding to host coral phylogeny
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Data and code from: Pest host expansion as a scale-free stepwise process across the host phylogeny
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Foliar endophyte diversity in eastern Asia-eastern North America disjunct tree species – Influences of host identity, environment, phylogeny, and geographic isolation
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Phylogeny of Rhus gall aphids (Hemiptera: Aphididae) reveals an earlier origin than their primary host plant
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Data from: Detecting ancient co-dispersals and host shifts by double dating of host and parasite phylogenies: application in proctophyllodid feather mites associated with passerine birds
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Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals
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Community composition of arctic root-associated fungi mirrors host plant phylogeny
<p></p><p>The number of plant species regarded as non-mycorrhizal increases at higher latitudes, and several plant species in the High-Arctic Archipelago Svalbard have been reported as non-mycorrhizal. We used the rRNA ITS2 and 18S gene markers to survey which fungi, as well as other micro-eukaryotes, were associated with roots of 31 arctic plant species not usually regarded as mycorrhizal in Svalbard. We assessed to what degree the root-associated fungi showed any host preference and whether the phylogeny of the plant hosts may mirror the composition of root-associated fungi. Fungal communities were largely structured according to host plant identity and to a less extent by environmental factors. We observed a positive relationship between the phylogenetic distance of host plants and the distance of fungal community composition between samples, indicating that the evolutionary history of the host plants plays a major role for which fungi colonize the plant roots. In contrast to the ITS2 marker, the 18S rRNA gene marker showed that chytrid fungi were prevalently associated with plant roots, together with a wide spectrum of amoeba-like protists and nematodes. Our study confirms that arbuscular mycorrhizal (AM) fungi are present also in arctic environments in low abundance.</p><p></p>
Data from: A non-parametric analytic framework for within-host viral phylogenies and a test for HIV-1 founder multiplicity
Phylogenetics is a powerful tool for understanding the diversification dynamics of viral pathogens. Here we present an extension of the spectral density profile of the modified graph Laplacian, which facilitates the characterization of within-host molecular evolution of viruses and the direct comparison of diversification dynamics between hosts. This approach is non-parametric and therefore fast and model-free. We used simulations of within-host evolutionary scenarios to evaluate the efficiency of our approach and to demonstrate the significance of interpreting a viral phylogeny by its spectral density profile in terms of diversification dynamics. The key features that are captured by the profile are positive selection on the viral gene (or genome), temporal changes in substitution rates, mutational fitness, and time between sampling. Using sequences from individuals infected with HIV-1, we showed the utility of this approach for characterizing within-host diversification dynamics, for comparing dynamics between hosts, and for charting disease progression in infected individuals sampled over multiple years. We furthermore propose a heuristic test for assessing founder heterogeneity, which allows us to classify infections with single and multiple HIV-1 founder viruses. This non-parametric approach can be a valuable complement to existing parametric approaches.
Data from: Tracing horizontal Wolbachia movements among bees (Anthophila): a combined approach using multilocus sequence typing data and host phylogeny
The endosymbiotic bacterium Wolbachia enhances its spread via vertical transmission by generating reproductive effects in its hosts, most notably cytoplasmic incompatibility (CI). Additionally, frequent interspecific horizontal transfer is evident from a lack of phylogenetic congruence between Wolbachia and its hosts. The mechanisms of this lateral transfer are largely unclear. To identify potential pathways of Wolbachia movements, we performed multilocus sequence typing of Wolbachia strains from bees (Anthophila). Using a host phylogeny and ecological data, we tested various models of horizontal endosymbiont transmission. In general, Wolbachia strains seem to be randomly distributed among bee hosts. Kleptoparasite-host associations among bees as well as other ecological links could not be supported as sole basis for the spread of Wolbachia. However, cophylogenetic analyses and divergence time estimations suggest that Wolbachia may persist within a host lineage over considerable timescales and that strictly vertical transmission and subsequent random loss of infections across lineages may have had a greater impact on Wolbachia strain distribution than previously estimated. Although general conclusions about Wolbachia movements among arthropod hosts cannot be made, we present a framework by which precise assumptions about shared evolutionary histories of Wolbachia and a host taxon can be modelled and tested.
Data from: A molecular phylogeny and revised higher-level classification for the leaf-mining moth family Gracillariidae and its implications for larval host-use evolution
Gracillariidae are one of the most diverse families of internally feeding insects, and many species are economically important. Study of this family has been hampered by lack of a robust and comprehensive phylogeny. In the present paper, we sequenced up to 22 genes in 96 gracillariid species, representing all previously recognized subfamilies and genus groups, plus 20 outgroups representing other families and superfamilies. Following objective identification and removal of two rogue taxa, two datasets were constructed: dataset 1, which included 12 loci totalling 9927 bp for 94 taxa, and dataset 2, which supplemented dataset 1 with 10 additional loci for 10 taxa, for a total of 22 loci and 16 167 bp. Maximum likelihood analyses strongly supported the monophyly of Gracillariidae and most previously recognized subfamilies and genus groups. On this basis, we propose a new classification consisting of eight subfamilies, four of which are newly recognized or resurrected: Acrocercopinae Kawahara & Ohshima subfam. n.; Gracillariinae Stainton; Lithocolletinae Stainton; Marmarinae Kawahara & Ohshima subfam. n.; Oecophyllembiinae Réal & Balachowsky; Parornichinae Kawahara & Ohshima subfam. n.; Ornixolinae Kuznetzov & Baryshnikova stat. rev.; and Phyllocnistinae Zeller. The subfamily Gracillariinae is restricted to the monophyletic group comprising Gracillaria Haworth and closely related genera. We also formally transfer Acrocercops scriptulata Meyrick to Ornixolinae and use the name Diphtheroptila Vári, creating Diphtheroptila scriptulata comb. n. An exploratory mapping of larval host-use traits on the phylogeny shows strong conservation of modes of leaf mining but much higher lability of associations with host plant orders and families, suggesting that host shifts could play a significant role in gracillariid diversification.
FIGURES 10–11 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURES 10–11. Conicobruchus strangulatus: 10—median lobe; 11—basal strut and lateral lobes (specimen 14495, Senegal).
FIGURE 2 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURE 2. Conicobruchus atrosuturalis: 2—median lobe (Paratype, Ethiopia); arrows were used to show the following structures: 2A—minute spinules; 2B—ctenoid scales; 2C—small sclerotized teethes; 2D—strong ventro-lateral dented rods; 2E—teethes; 2F—dented sticks or masses; 2G—apical ampoule.
FIGURES 3–4 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURES 3–4. Conicobruchus cicatricosus: 3—median lobe; 4—basal strut and lateral lobes (specimen 02212, Kenya).
FIGURE 18 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURE 18. Best tree (L= -25368.23) from the partitioned maximum likelihood analyses of the dataset. Bootstrap values> 50% are figured on nodes.
FIGURES 12–17 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURES 12–17. Conicobruchus strangulatus: Ornamentation of saccus, ventral view: 12—specimen 00714, Burkina Faso; 13—specimen 02699, Senegal, Dakar; 14—specimen 14395, Dakar (Joal); 15—specimen 00614, Mali; 16—specimen 14495, Senegal (Missira); 17—specimen 19207, Senegal (Nianing).
FIGURES 8–9 in Taxonomy, host-plant associations and phylogeny of African Crotalaria - feeding seed beetles (Coleoptera, Chrysomelidae, Bruchinae): the Conicobruchus strangulatus (Fåhraeus) species group
FIGURES 8–9. Conicobruchus rubricollis: 7—median lobe; 8—basal strut and lateral lobes (specimen 18907, Zimbabwe).
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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
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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
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