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2,390 results for “butterflies”
Data from: Divergence with gene flow across a speciation continuum of Heliconius butterflies
Background: A key to understanding the origins of species is determining the evolutionary processes that drive the patterns of genomic divergence during speciation. New genomic technologies enable the study of high-resolution genomic patterns of divergence across natural speciation continua, where taxa pairs with different levels of reproductive isolation can be used as proxies for different stages of speciation. Empirical studies of these speciation continua can provide valuable insights into how genomes diverge during speciation. Methods: We examine variation across a handful of genomic regions in parapatric and allopatric populations of Heliconius butterflies with varying levels of reproductive isolation. Genome sequences were mapped to 2.2-Mb of the H. erato genome, including 1-Mb across the red color pattern locus and multiple regions unlinked to color pattern variation. Results: Phylogenetic analyses reveal a speciation continuum of pairs of hybridizing races and incipient species in the Heliconius erato clade. Comparisons of hybridizing pairs of divergently colored races and incipient species reveal that genomic divergence increases with ecological and reproductive isolation, not only across the locus responsible for adaptive variation in red wing coloration, but also at genomic regions unlinked to color pattern. Discussion: We observe high levels of divergence between the incipient species H. erato and H. himera, suggesting that divergence may accumulate early in the speciation process. Comparisons of genomic divergence between the incipient species and allopatric races suggest that limited gene flow cannot account for the observed high levels of divergence between the incipient species. Conclusions: Our results provide a reconstruction of the speciation continuum across the H. erato clade and provide insights into the processes that drive genomic divergence during speciation, establishing the H. erato clade as a powerful framework for the study of speciation.
Data from: Plant defenses against ants provide a pathway to social parasitism in butterflies
Understanding the chemical cues and gene expressions that mediate herbivore–host-plant and parasite–host interactions can elucidate the ecological costs and benefits accruing to different partners in tight-knit community modules, and may reveal unexpected complexities. We investigated the exploitation of sequential hosts by the phytophagous–predaceous butterfly Maculinea arion, whose larvae initially feed on Origanum vulgare flowerheads before switching to parasitize Myrmica ant colonies for their main period of growth. Gravid female butterflies were attracted to Origanum plants that emitted high levels of the monoterpenoid volatile carvacrol, a condition that occurred when ants disturbed their roots: we also found that Origanum expressed four genes involved in monoterpene formation when ants were present, accompanied by a significant induction of jasmonates. When exposed to carvacrol, Myrmica workers upregulated five genes whose products bind and detoxify this biocide, and their colonies were more tolerant of it than other common ant genera, consistent with an observed ability to occupy the competitor-free spaces surrounding Origanum. A cost is potential colony destruction by Ma. arion, which in turn may benefit infested Origanum plants by relieving their roots of further damage. Our results suggest a new pathway, whereby social parasites can detect successive resources by employing plant volatiles to simultaneously select their initial plant food and a suitable sequential host.
Data from: Effect of winter cold duration on spring phenology of the orange tip butterfly, Anthocharis cardamines
The effect of spring temperature on spring phenology is well understood in a wide range of taxa. However, studies on how winter conditions may affect spring phenology are underrepresented. Previous work on Anthocharis cardamines (orange tip butterfly) has shown population-specific reaction norms of spring development in relation to spring temperature and a speeding up of post-winter development with longer winter durations. In this experiment, we examined the effects of a greater and ecologically relevant range of winter durations on post-winter pupal development of A. cardamines of two populations from the United Kingdom and two from Sweden. By analyzing pupal weight loss and metabolic rate, we were able to separate the overall post-winter pupal development into diapause duration and post-diapause development. We found differences in the duration of cold needed to break diapause among populations, with the southern UK population requiring a shorter duration than the other populations. We also found that the overall post-winter pupal development time, following removal from winter cold, was negatively related to cold duration, through a combined effect of cold duration on diapause duration and on post-diapause development time. Longer cold durations also lead to higher population synchrony in hatching. For current winter durations in the field, the A. cardamines population of southern UK could have a reduced development rate and lower synchrony in emergence because of short winters. With future climate change, this might become an issue also for other populations. Differences in winter conditions in the field among these four populations are large enough to have driven local adaptation of characteristics controlling spring phenology in response to winter duration. The observed phenology of these populations depends on a combination of winter and spring temperatures; thus, both must be taken into account for accurate predictions of phenology.
Data from: Dissecting the contributions of plasticity and local adaptation to the phenology of a butterfly and its host plants
Phenology affects the abiotic and biotic conditions that an organism encounters and consequently its fitness. For populations of high latitude species, spring phenology often occurs earlier in warmer years and regions. Here we apply a novel approach to decompose spatiotemporal covariation between spring temperature and the phenology of two flowering plants, Cardamine pratensis and Alliara petiolata, and a Lepidopteran herbivore, Anthocharis cardamines, across the UK, into the contributions of plasticity and local adaptation. All three species overlap in the time-window over which mean temperatures best predict variation in phenology and we find little evidence that the position of time-windows varies latitudinally, as expected if they were initiated by day-length. The focal species show pronounced temperature-mediated phenological plasticity of similar magnitude. While we find no evidence for local adaptation in the flowering times of the plants, geographic variation in the phenology of the butterfly reveals countergradient local adaptation. Geographic variation in the butterfly's phenology appears to be more sensitive to variation in temperature than the flowering times of the host plants and we find no evidence that coevolution has generated geographic variation in adaptive phenological plasticity.
Data from: Integrating three comprehensive datasets shows that mitochondrial DNA variation is linked to species traits and paleogeographic events in European butterflies.
Understanding the dynamics of biodiversity, including the spatial distribution of genetic diversity, is critical for predicting responses to environmental changes, as well as for effective conservation measures. This task requires tracking changes in biodiversity at large spatial scales and correlating with species functional traits. We provide three comprehensive resources to understand the determinants for mitochondrial DNA differentiation represented by i) 15,609 COI sequences and ii) 14 traits belonging to 307 butterfly species occurring in Western-Central Europe and iii) the first multi-locus phylogenetic tree of all European butterfly species. By applying phylogenetic regressions we show that mitochondrial DNA spatial differentiation (as measured with Gst, G'st, D and Dst) is negatively correlated with species traits determining dispersal capability and colonization ability. Thanks to the high spatial resolution of the COI data, we also provide the first zoogeographic regionalization maps based on intraspecific genetic variation. The overall pattern obtained by averaging the spatial differentiation of all Western-Central European butterflies shows that the paradigm of long-term glacial isolation followed by rapid pulses of post-glacial expansion has been a pervasive phenomenon in European butterflies. The results and the extensive datasets we provide here constitute the basis for genetically-informed conservation plans for a charismatic group in a continent where flying insects are under alarming decline.
FIGURE 19 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 19. Maximum Parsimony tree based on morphological characters. The left value is the Bremer support, and the right value is the Bootstrap support.
FIGURE 18 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 18. Bayesian Inference tree based on morphological characters with the posterior probability.
FIGURE 15 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 15. Female genitalia, in lateral view. A: Hypolimnas monteironis, Uganda, Mpanga, prep. genit. 1897; B: Hypolimnas deceptor, Kenya, Mrima, prep. genit. 1895; C: Hypolimnas usambara Kenya, Buda, prep. genit. 1893; D: Hypolimnas misippus, Kenya, Mrima, prep. genit. 1892.
FIGURE 17 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 17. Maximum Likelihood Cladogram based on COI sequences. Bootstrap support values higher than 0.6 indicated on the nodes.
FIGURE 14 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 14. Female genitalia, in lateral view. A: Precis antilope, Nigeria, Nsukka, prep. genit. 1941; B: Precis cuama, Zambia, prep. genit. 1943; C: Precis octavia, Nigeria, Nsukka, prep. genit. 1886; D: Precis ceryne, Uganda, Mpanga Forest, prep. genit. 1878.
FIGURE 16 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 16. Female genitalia, in lateral view. A: Yoma algina, New Guinea, Sogeri, prep. genit. 1891: B: Yoma sabina atomaria, Indonesia?, prep. genit. 1799; C: Rhinopalpa polynice, Thailand, Ranong, prep. genit. 1790.
FIGURE 13 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 13. Female genitalia, in lateral view. A: Junonia orithya, Rhodesia, prep. genit. 1932; B: Junonia hierta cebrene, Kenya, Bachuma, prep. genit. 1805; C: Junonia oenone, Kenya, Gongoni Forest, prep. genit. 1890; D: Junonia westermanni, Uganda, Kibale, prep. genit. 1888.
FIGURE 12 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 12. Female genitalia, in lateral view. A: Junonia artaxia, Angola, prep. genit. 1933; B: Junonia touhilimasa, Zambia, Kabwe, prep. genit. 1930; C: Junonia rhadama, Mauritius, prep. genit. 1889; D: Junonia sophia, Uganda, Mpanga, prep. genit. 1931.
FIGURE 10 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 10. Female genitalia, in lateral view. A: Salamis cacta, Uganda, Mubende, prep. genit. 1800; B: Salamis augustina, Reunion, prep. genit. 1881; C: Junonia (Kamilla) cymodoce, Principe, Terreiro Velho, prep. genit. 1803; D: Junonia (Kamilla) agnesberenyiae, Guinea, Nimba, prep. genit. 1898.
FIGURE 9 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 9. Female genitalia, in lateral view. A: Protogoniomorpha parhassus, Cameroun, Kienke, prep. genit. 1422; B: Protogoniomorpha nebulosa, Kenya, Mombasa, prep. genit. 1814; C: Junonia temora, Benin, prep. genit. 1815; D: Junonia cytora, Guinea, Conakry, prep. genit. 1970.
FIGURE 8 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 8. Male genitalia, lateral view, aedeagus extracted in dorsal view. A: Yoma algina netonia, X: massive gnathos, strongly adhered to tegumen, Y: stout, upcurved uncus; Z: sharp, basal process of the valva, New Guinea, prep. genit. 1420; B: Yoma algina pavonia, New Georgia, prep. genit. 1811; C: Yoma sabina nimbus, Celebes, prep. genit. 1806; D: Yoma sabina vasuki, Thailand, prep. genit. 1812; E: Yoma sabina sabina, New Caledonia, prep. genit. 1813; F: Rhinopalpa polynice, Indonesia, prep. genit. 1951.
FIGURE 11 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 11. Female genitalia, in lateral view. A: Junonia elgiva, Kenya, Gongoni Forest, prep. genit. 1802; B: Junonia chorimene, Nigeria, Nsukka, prep. genit. 1887; C: Junonia gregorii, Kenya, Kakamega, prep. genit. 1885; D: Junonia natalica, Kenya, Kwale, prep. genit. 1883
FIGURE 7 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 7. Male genitalia, lateral view, aedeagus extracted in dorsal view. A: Hypolimnas misippus, X: elongated, sinuate sacculus, Y: widened, apical part of the valva; Z: flattened uncus, Uganda, Mubende, prep. genit. 1864; B: Hypolimnas mechowi, Nigeria, Port Harcourt, prep. genit. 1869; C: Hypolimnas salmacis, Cameroun, Ebogo, prep. genit. 1865; D: Hypolimnas usambara, Kenya, Mrima, prep. genit. 1867; E: Hypolimnas deceptor, Kenya, Shimba, prep. genit. 1894; F: Hypolimnas antedon, Ghana, prep. genit. 1789.
FIGURE 4 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 4. Male genitalia, lateral view, aedeagus extracted in dorsal view. A: Junonia gregorii, X: harpe produced into a tip; Y: sacculus, Kenya, Kakamega Forest, prep. genit. 1427; B: Junonia natalica natalica, Kenya, Mombasa, prep. genit. 1779; C: Junonia elgiva stat. reinst., Kenya, Buda Forest, prep. genit. 1780; D: Junonia chorimene, Uganda, Mubende, prep. genit. 1792; E: Junonia terea terea Sao Tome and Principe, Principe Isl., prep. genit. 1858; F: Junonia rhadama, Mauritius, Trou d'Eau Douce, prep. genit. 1782.
FIGURE 6 in Alpha-taxonomy and phylogeny of African Junoniini butterflies based on morphological data, with an emphasis on genitalia, and COI barcode (Lepidoptera Nymphalidae)
FIGURE 6. Male genitalia, lateral view, aedeagus extracted in dorsal view. A: Precis octavia, X: flattened uncus; Y: downcurved, sharp tip of the valva, Nigeria, Nsukka, prep. genit. 1787; B: Precis sinuata, Ghana, Cape Three Points, prep. genit. 1862; C: Precis ceryne, Uganda, Mpanga Forest, prep. genit. 1863; D: Precis silvicola, Cameroun, Ebogo, prep. genit. 1978; E: Precis antilope, Nigeria, Nsukka, prep. genit. 1940; F: Precis rauana, Uganda, Kibale, prep. genit. 1950.
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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)
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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.