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2,390 results for “butterflies”
Butterfly, Dragonfly and Damselfly Species at Harvard Forest 2015
I report on preliminary observations of butterflies in small meadows in the vicinity of “Harvard Farm” (formerly Petersham Country Club) in Petersham, MA, from 16-20 July 2015. I sampled butterflies at 10 locations over five days, visiting some areas twice. I documented (with digital photography) a total of 17 recognizable species/morpho-species, as well as 2-8 additional “grass skippers” which could not be identified to species. Initially I had planned to conduct a more organized survey, but most of the property had been grazed by the time I arrived in mid-July. This, combined with the late start date, meant that flowers – and nearly all butterflies – were absent at the Harvard Farm property during my visit. Instead, I opted to opportunistically sample several un-grazed meadows in the Petersham area, including North Common Meadow near the center of town and small meadows on Harvard Forest property, to develop a species list and photographic database of as many local butterflies as possible. From these surveys, the most numerous species were clouded/orange sulfur (Colias spp.; 34 individuals observed), followed by great spangled fritillary (Speyeria cybele; n = 32) and unidentified grass-skippers (various genera; n = 32). Moderately common species (n = 8-12) included Common wood-nymph (Cercyonis pegala), American copper (Lycaena phlaeas) and cabbage white (Pieris rapae); fewer than 4 individuals were recorded of: black/spicebush swallowtail (Papilio sp.), banded hairstreak (Satyrium calanus), gray hairstreak (Strymon melinus), azure (Celastrina ladon), eastern tailed-blue (Everes comyntas), pearl crescent (Phycioides tharos), eastern comma (Polygonia comma), Appalachian brown (Satyodes appalachia), northern pearly-eye (Enodia anthedon), and silver-spotted skipper (Epargyreus claras). These observations should be taken as preliminary, but may serve as a list of the most common and conspicuous butterfly taxa during mid-summer in the Petersham area, and could inform st
Genomics of extreme ecological specialists: multiple convergent evolution but no genetic divergence between ecotypes of Maculinea alcon butterflies
<p>Biotic interactions are often acknowledged as catalysers of genetic divergence and eventual explanation of processes driving species richness. We address the question, whether extreme ecological specialization is always associated with lineage sorting, by analysing polymorphisms in morphologically similar ecotypes of the myrmecophilous butterfly <em>Maculinea alcon</em>. The ecotypes occur in either hygric or xeric habitats, use different larval host plants and ant species, but no significant distinctive molecular traits have been revealed so far. We apply genome-wide RAD-sequencing to specimens originating from both habitats across Europe in order to get a view of the potential evolutionary processes at work. Our results confirm that genetic variation is mainly structured geographically but not ecologically — specimens from close localities are more related to each other than populations of each ecotype from distant localities. However, we found two loci for which the association with xeric versus hygric habitats is supported by segregating alleles, suggesting convergent evolution of habitat preference. Thus, ecological divergence between the forms probably does not represent an early stage of speciation, but may result from independent recurring adaptations involving few genes. We discuss the implications of these results for conservation and suggest preserving biotic interactions and main genetic clusters.</p>
Butterfly heavy metal content, wing size, egg count, and brain mass in the Minneapolis-St. Paul (MSP) Metropolitan Area
We collected 26 common species of butterflies across a gradient of lead pollution in the Twin Cities metropolitan area (Minneapolis and St. Paul, MN, USA). We measured their thorax lead concentrations and their body condition including wing area, number of eggs, and brain mass. We also quantified lead in the soil, host plant leaves, and air (through lichen bio-monitors) at sites where the butterflies were collected.
Cambridge butterfly collection - Loreto, Peru 2018
<p>Cambridge Butterfly Collection. Loreto, Peru Part 1</p> <p>EN: This upload contains photographs taken by Eva van der Heijden at the Butterfly Genetics Group at the University of Cambridge, from a butterfly wing collection from Loreto, Peru, in collaboration with Green Gold Forestry. Individual sample names can be found in the information sheet. Further Information on individual samples from the Butterfly Genetics Group Collection can be found on the public database Earthcape (<a href="https://heliconius.ecdb.io/">click here for the database</a>, and <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">here for FAQ</a>). Please contact Chris Jiggins (c.jiggins[at]zoo.cam.ac.uk) or Gabriela Montejo-Kovacevich (gmontejokovacevich[at]gmail.com) for further information.</p> <p> </p> <p>ES: Este repositorio contiene fotografías tomadas por Eva van der Heijden en el Butterfly Genetics Group de la Universidad de Cambridge, de mariposas de Loreto (Peru), en colaboración con la compañía Green Gold Forestry. Puede encontrar información sobre muestras individuales de Butterfly Genetics Group Collection en la base de datos pública Earthcape (<a href="https://heliconius.ecdb.io/">haga clic aquí para la base de datos</a>, y <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">aquí para preguntas frecuentes</a>) Por favor, póngase en contacto con Chris Jiggins (c.jiggins [arroba] zoo.cam.ac.uk) o Gabriela Montejo-Kovacevich (gmontejokovacevich[at]gmail.com) con sus preguntas o peticiones.</p>
Data: "Using butterfly survey data to model habitat associations in urban developments", JEJ Cooper et al., (2023)
<p>This data package has been used to examine the responses of UK butterfly species </p> <p>to different features of the urban environment. 'JC_WCBSmodel.Rdata' presents the</p> <p>butterfly abundance data, and supporting information about </p> <p>species and sites. This data can be fed through the script '04_model_builder.R', to </p> <p>produce the models reported in the research article. '00_functions.R' is a script </p> <p>containing functions which support the modelling process, which is loaded as part of </p> <p>the 04_model_builder script. </p> <p> </p> <p>Summaries of the resulting models are an output of that script - </p> <p>'Butterfly_GAM_Outputs.xlsx'. These are represented graphically in the manuscript, </p> <p>using scripts '06_01_Map'.R:'06_03_Cross_Validation'. '06_04_Model_Metric.R' </p> <p>is a further summary of the .xlsx file, found in the Supplementary Materials. </p> <p>'06_05_graphic_4_twitter.R' produces a condensed version of the figure resulting </p> <p>from the script '06_02_Metric_Summary.R'</p> <p> </p> <p>Dataset descriptions are found in the attached readme.txt</p> <p>........................................................................................</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Complex basis of hybrid female sterility and Haldane's rule in Heliconius butterflies: Z-linkage and epistasis - RADseq and RNAseq reads, sterility phenotypes and pedigree
<p>RADseq and RNAseq reads (.fastq files), and sterility phenotypes and pedigree (.xlsx) using for QTL mapping of Heliconius pardalinus sterility crosses in Rosser, N., Edelman, N.B., Queste, L.M., Nelson, M., Seixas, F., Dasmahapatra, K.K. and Mallet, J., 2021. Complex basis of hybrid female sterility and Haldane’s rule in Heliconius butterflies: Z-linkage and epistasis, accepted for publication in Molecular Ecology. Queries to Neil Rosser (neil.rosser@york.ac.uk). </p> <p> </p>
Cambridge butterfly wing collection - Ecuador, August 2019
<p>EN: This upload contains photographs taken by Annalie Barker and Joana Meier at the University of Cambridge, from a butterfly wing collection from Ecuador (August 2019), in collaboration with Caroline Bacquet (IKIAM). Individual sample names can be found in the information sheet. Further Information on individual samples from the Butterfly Genetics Group Collection can be found on the public database Earthcape (<a href="https://heliconius.ecdb.io/">click here for the database</a>, and <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">here for FAQ</a>). Please contact Joana Meier (jm2276[at]cam.ac.uk) or Chris Jiggins (c.jiggins[at]zoo.cam.ac.uk) for further information.</p> <p> </p> <p>ES: Este repositorio contiene fotografías tomadas por Annalie Barker y Joana Meier en la Universidad de Cambridge, de mariposas de Ecuador (Agosto 2019), en colaboración con Caroline Bacquet (IKIAM, Ecuador). Puede encontrar información sobre muestras individuales de Butterfly Genetics Group Collection en la base de datos pública Earthcape (<a href="https://heliconius.ecdb.io/">haga clic aquí para la base de datos</a>, y <a href="https://heliconius.zoo.cam.ac.uk/databases/earthcape-specimen-database/">aquí para preguntas frecuentes</a>) Por favor, póngase en contacto con Joana Meier (jm2276 [arroba] cam.ac.uk) or Chris Jiggins (c.jiggins [arroba] zoo.cam.ac.uk) con sus preguntas o peticiones.</p>
The genetic basis of structural colour variation in mimetic Heliconius butterflies
<p>Raw USAXS data from discal region of <em>Heliconius </em>butterflies (<em>H. erato </em>and<em> H. melpomene</em>). The data comes from wings of individuals of two intercross families, one from each species and was used to estimate scale structure variation and a QTL analysis.</p>
De novo genome assembly of the meadow brown butterfly, Maniola jurtina
<p>1. Whole-genome GFF file (raw and filtered for min. gene length) [<em>Maniola.jurtina.gff3</em>, <em>Maniola_jurtina_filtered.gff3</em>]</p> <p>2. List of <em>M. jurtina</em> proteins [<em>Mjurtina_proteins.fa</em>].</p> <p>3. Results of spot pattern genes BLAST against <em>M. jurtina</em> proteome [<em>Lepidoptera_MJ_protein_matches.xlsx</em>]. </p> <p>4. Annotations [blast2go_export.txt]</p>
Raw data of peacock butterflies
<p>We provide the raw peacock butterfly data. </p> <p>The id from waarnemingen.be, scientific name (always Aglais io), date, time (when available), number of individuals, lifestage, the coordinates x and y in Lambert 1972 (EPSG:<em>31370</em> Projected coordinate system for Belgium) and lon, lat in WGS84, the municipality in in Belgium (due to a mistake, this column is named community in the data file), the link to the original observation and the number of photo's included in this observation. </p> <p> </p>
Fruit-feeding butterfly community data analysed in "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration"
<p>Community data of fruit-feeding butterflies collected from Kibale National Park, Uganda, in the periods 2011-2012 and 2020-2021 analysed in our paper Korkiatupa et al. 2023: "Recovery patterns in community composition of fruit-feeding butterflies following 26 years of active forest restoration" (<em>Ecosphere</em> <span>14</span>(<span>5</span>): e4514. <a href="https://doi.org/10.1002/ecs2.4514">https://doi.org/10.1002/ecs2.4514</a>).</p> <p>The table consists of two parts. First part shows counts of individuals of butterfly species in each study site. Second part shows the metadata: code of studysite, census (2011-2012/2020-2021), planting year (planting year or "Primary forest"), and coordinates (WGS 84 coordinate system).</p>
BTO Garden BirdWatch: Weekly butterfly abundance data for modelling trends in UK gardens
<p>Dataset used to estimate annual abundance indices and trends for UK butterflies in gardens, covering the period 2007 to 2020.</p> <p>Data have been collected as part of the British Trust for Ornithology (BTO) Garden BirdWatch (GBW) survey. GBW is a structured, citizen science monitoring programme whereby volunteers record weekly abundances of various bird, invertebrate, mammal, reptile and amphibian species in (predominantly suburban and rural) gardens. See <a href="http://www.bto.org/gbw">www.bto.org/gbw</a> for further information about the survey. </p> <p>This dataset has been pre-filtered to meet criteria for inclusion in the modelling of butterfly species trends, as described by <a href="https://doi.org/10.1111/icad.12645">Plummer et al 2023</a>. Please refer to the 'readme' file for further details.</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Data from: Trends in butterfly populations in UK gardens – new evidence from citizen science monitoring
<p>This data package describes the annual abundance indices and trend estimates for 22 butterfly species in UK gardens for the period 2007-2020.</p> <p>These data form the basis of the results presented in: Plummer, K.E., Dadam, D., Brereton, T., Dennis, E.B., Massimino, D., Risely, K. et al. (2023) Trends in butterfly populations in UK gardens—New evidence from citizen science monitoring. <em>Insect Conservation and Diversity</em>, 1– 13. Available from: <a href="https://doi.org/10.1111/icad.12645">https://doi.org/10.1111/icad.12645</a></p> <p>Please refer to the paper for an explanation of the underlying BTO Garden BirdWatch (GBW) data and modelling protocols used to produce the datasets included here.</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Data from: Butterflies are not a robust bioindicator for assessing pollinator communities, but floral resources offer a promising way forward
<p>Monitoring pollinators is crucial for the evaluation of biodiversity and potential pollination services. Yet, efficiently monitoring multiple taxa over large areas can be costly. An alternative approach is using simple species bioindicators that represent the entire pollinator community. One of the requirements of a good bioindicator is that it can be easily identified to lower taxonomic levels and be sensitive to changes in habitat. This is the case for butterflies, a taxon for which many countries have a country-wide long-term monitoring scheme. We tested whether butterfly diversity can be used to predict diversity of bees and hoverflies both spatially and temporally. We surveyed 42 transects of the Dutch Butterfly Monitoring Scheme in 2020, to record species richness and abundance of butterflies, bees and hoverflies. We also recorded flower area and richness in the pollinator transects. To test whether pollinators with similar functional traits are more closely correlated than the entire pollinator community, we categorized bee and butterfly species according to their diet breadth (polyphagous vs. non-polyphagous), nitrogen-affinity (nitrophobous vs. nitrophilous larval resources) and body size. We used the same methods to test for temporal correlations over seven years for one site in Spain. Butterfly richness was not spatially correlated with bee richness (Pearson's r = 0.13), nor were the two taxa temporally correlated (Pearson's r = 0.02). Interestingly, hoverfly richness was spatially correlated with butterfly richness (Pearson's r = 0.43) and with bee richness (Pearson's r = 0.36) in the Netherlands and, hence, hoverflies might be slightly more suitable as a bioindicator of pollinator diversity in this area. Abundance of all three taxa showed no significant inter-correlation, except for correlations between diet specialist bees and butterflies (Pearson's r = 0.39). Importantly, all three taxa were strongly correlated with flower richness, but they varied in their preferences for host plant families. This is in line with 75% of the plant-pollinator studies finding significant positive relations. For monitoring schemes to be effective in informing better pollinator conservation, they should expand to include bees and hoverflies as well as simple indicators of habitat quality such as floral resources.</p>
Asynchronous life cycles contribute to reproductive isolation between two Alpine butterflies
<p>Data from: Asynchronous life cycles contribute to reproductive isolation between two Alpine butterflies</p> <p><strong>Abstract</strong></p> <p>Geographic isolation often leads to the emergence of distinct genetic lineages that are at least partially reproductively isolated. Zones of secondary contact between such lineages are natural experiments that allow investigating how reproductive isolation evolves and co-existence is maintained. While temporal isolation through allochrony has been suggested to promote reproductive isolation in sympatry, its potential for isolation upon secondary contact is far less understood. Sampling two contact zones of a pair of mainly allopatric Alpine butterflies over several years and taking advantage of museum samples, we show that the contact zones have remained geographically stable over several decades. Furthermore, they seem to be maintained by the asynchronous life cycles of the two butterflies, with one reaching adulthood primarily in even and the other primarily in odd years. Genomic inferences document that allochrony is leaky and that gene flow from allopatric sites scales with the degree of geographic isolation. Overall, we show that allochrony has the potential to contribute to the maintenance of secondary contact zones of lineages that diverged in allopatry.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>Morphology contains the following files:</p> <p>wing_morpho.R<br> R scripts for data transformation of wing shape</p> <p>genital_morpho.R<br> R scripts for data transformation of genital morphology</p> <p><br> Models_used.R:<br> R scripts used to produce the statistical analyses.</p> <p>genital_morpho_master_with_pca.txt<br> Phenotypic data for genital morphology</p> <p>wing_contemporary_morpho_master_with_pca.txt<br> Phenotypic data for contemporary wing patterns</p> <p>wing_historic_morpho_master_with_pca.txt<br> Phenotypic data for wing patterns from museum samples</p> <p>The text files contains the following information:</p> <p>ID = Individual ID<br> genotyped_allopatric = was the individual genotyped<br> latitude<br> longitude<br> DATE = Date of collection<br> DAY = Day of collection<br> MONTH = Month of collection<br> YEAR = Year of collection<br> SPOT = Collection site<br> boxplotID = ID to reproduce boxplot order as used in the paper<br> colory = color code to plot<br> cycle = year cycle (2018/19 or 2020/21)<br> yeartype = even or odd year<br> genital_x_LM1 = linear measure of genital landmark 1 along the x axis<br> genital_y_LM1 = linear measure of genital landmark 1 along the y axis<br> genital_x_LM2 = linear measure of genital landmark 2 along the x axis <br> genital_y_LM2 = linear measure of genital landmark 2 along the y axis <br> genital_x_LM3 = linear measure of genital landmark 3 along the x axis <br> genital_y_LM3 = linear measure of genital landmark 3 along the y axis <br> genital_x_LM4 = linear measure of genital landmark 4 along the x axis <br> genital_y_LM4 = linear measure of genital landmark 4 along the y axis <br> genital_x_LM5 = linear measure of genital landmark 5 along the x axis <br> genital_y_LM5 = linear measure of genital landmark 5 along the y axis <br> v_t1 = length relationship between v and t1<br> v_t2 = length relationship between v and t2 <br> v_t3 = length relationship between v and t3 <br> t3_t1 = length relationship between t3_t1 <br> t3_t2 = length relationship between t3_t2 <br> t2_t1 = length relationship between t2_t1 <br> v_tg = length relationship between v and tg <br> PC1.x = PC1 axis for unprojected morphospace<br> PC2.x = PC2 axis for unprojected morphospace <br> PC3.x = PC3 axis for unprojected morphospace <br> PC4.x = PC4 axis for unprojected morphospace <br> PC5.x = PC5 axis for unprojected morphospace <br> PC6.x = PC6 axis for unprojected morphospace <br> PC7.x = PC7 axis for unprojected morphospace <br> PC1.y = PC1 axis for projected morphospace <br> PC2.y = PC2 axis for projected morphospace <br> PC3.y = PC3 axis for projected morphospace <br> PC4.y = PC4 axis for projected morphospace <br> PC5.y = PC5 axis for projected morphospace <br> PC6.y = PC6 axis for projected morphospace <br> PC7.y = PC7 axis for projected morphospace</p> <p> </p> <p><br> wing_ProcCoord1 = Procrustes coordinate 1<br> wing_ProcCoord2 = Procrustes coordinate 2<br> wing_ProcCoord3 = Procrustes coordinate 3<br> wing_ProcCoord4 = Procrustes coordinate 4<br> wing_ProcCoord5 = Procrustes coordinate 5<br> wing_ProcCoord6 = Procrustes coordinate 6<br> wing_ProcCoord7 = Procrustes coordinate 7<br> wing_ProcCoord8 = Procrustes coordinate 8<br> wing_ProcCoord9 = Procrustes coordinate 9<br> wing_ProcCoord10 = Procrustes coordinate 10<br> wing_ProcCoord11 = Procrustes coordinate 11<br> wing_ProcCoord12 = Procrustes coordinate 12<br> wing_ProcCoord13 = Procrustes coordinate 13<br> wing_ProcCoord14 = Procrustes coordinate 14<br> wing_ProcCoord15 = Procrustes coordinate 15<br> wing_ProcCoord16 = Procrustes coordinate 16<br> wing_ProcCoord17 = Procrustes coordinate 17<br> wing_ProcCoord18 = Procrustes coordinate 18<br> wing_ProcCoord19 = Procrustes coordinate 19<br> wing_ProcCoord20 = Procrustes coordinate 20<br> wing_ProcCoord21 = Procrustes coordinate 21<br> wing_ProcCoord22 = Procrustes coordinate 22<br> wing_ProcCoord23 = Procrustes coordinate 23<br> wing_ProcCoord24 = Procrustes coordinate 24<br> wing_ProcCoord25 = Procrustes coordinate 25<br> wing_ProcCoord26 = Procrustes coordinate 26<br> wing_ProcCoord27 = Procrustes coordinate 27<br> wing_ProcCoord28 = Procrustes coordinate 28<br> wing_ProcCoord29 = Procrustes coordinate 29<br> wing_ProcCoord30 = Procrustes coordinate 30<br> wing_ProcCoord31 = Procrustes coordinate 31<br> wing_ProcCoord32 = Procrustes coordinate 32<br> wing_ProcCoord33 = Procrustes coordinate 33<br> wing_ProcCoord34 = Procrustes coordinate 34<br> wing_ProcCoord35 = Procrustes coordinate 35<br> wing_ProcCoord36 = Procrustes coordinate 36<br> wing_ProcCoord37 = Procrustes coordinate 37<br> wing_ProcCoord38 = Procrustes coordinate 38<br> wing_ProcCoord39 = Procrustes coordinate 39<br> wing_ProcCoord40 = Procrustes coordinate 40<br> wing_ProcCoord41 = Procrustes coordinate 41<br> wing_ProcCoord42 = Procrustes coordinate 42<br> wing_ProcCoord43 = Procrustes coordinate 43<br> wing_ProcCoord44 = Procrustes coordinate 44<br> wing_ProcCoord45 = Procrustes coordinate 45<br> wing_ProcCoord46 = Procrustes coordinate 46<br> wing_ProcCoord47 = Procrustes coordinate 47<br> wing_ProcCoord48 = Procrustes coordinate 48<br> wing_ProcCoord49 = Procrustes coordinate 49<br> wing_ProcCoord50 = Procrustes coordinate 50<br> wing_ProcCoord51 = Procrustes coordinate 51<br> wing_ProcCoord52 = Procrustes coordinate 52<br> wing_ProcCoord53 = Procrustes coordinate 53<br> wing_ProcCoord54 = Procrustes coordinate 54<br> PC1.x = PC1 unprojected<br> PC2.x = PC2 unprojected<br> PC3.x = PC3 unprojected<br> PC4.x = PC4 unprojected<br> PC5.x = PC5 unprojected<br> PC6.x = PC6 unprojected<br> PC7.x = PC7 unprojected<br> PC8.x = PC8 unprojected<br> PC9.x = PC9 unprojected<br> PC10.x = PC10 unprojected<br> PC11.x = PC11 unprojected<br> PC12.x = PC12 unprojected<br> PC13.x = PC13 unprojected<br> PC14.x = PC14 unprojected<br> PC15.x = PC15 unprojected<br> PC16.x = PC16 unprojected<br> PC17.x = PC17 unprojected<br> PC18.x = PC18 unprojected<br> PC19.x = PC19 unprojected<br> PC20.x = PC20 unprojected<br> PC21.x = PC21 unprojected<br> PC22.x = PC22 unprojected<br> PC23.x = PC23 unprojected<br> PC24.x = PC24 unprojected<br> PC25.x = PC25 unprojected<br> PC26.x = PC26 unprojected<br> PC27.x = PC27 unprojected<br> PC28.x = PC28 unprojected<br> PC29.x = PC29 unprojected<br> PC30.x = PC30 unprojected<br> PC31.x = PC31 unprojected<br> PC32.x = PC32 unprojected<br> PC33.x = PC33 unprojected<br> PC34.x = PC34 unprojected<br> PC35.x = PC35 unprojected<br> PC36 = PC36 unprojected<br> PC37 = PC37 unprojected<br> PC38 = PC38 unprojected<br> PC39 = PC39 unprojected<br> PC40 = PC40 unprojected<br> PC41 = PC41 unprojected<br> PC42 = PC42 unprojected<br> PC43 = PC43 unprojected<br> PC44 = PC44 unprojected<br> PC45 = PC45 unprojected<br> PC46 = PC46 unprojected<br> PC47 = PC47 unprojected<br> PC48 = PC48 unprojected<br> PC49 = PC49 unprojected<br> PC50 = PC50 unprojected<br> PC51 = PC51 unprojected<br> PC52 = PC52 unprojected<br> PC53 = PC53 unprojected<br> PC54 = PC54 unprojected<br> PC1.y = PC1 projected<br> PC2.y = PC2 projected<br> PC3.y = PC3 projected<br> PC4.y = PC4 projected<br> PC5.y = PC5 projected<br> PC6.y = PC6 projected<br> PC7.y = PC7 projected<br> PC8.y = PC8 projected<br> PC9.y = PC9 projected<br> PC10.y = PC10 projected<br> PC11.y = PC11 projected<br> PC12.y = PC12 projected<br> PC13.y = PC13 projected<br> PC14.y = PC14 projected<br> PC15.y = PC15 projected<br> PC16.y = PC16 projected<br> PC17.y = PC17 projected<br> PC18.y = PC18 projected<br> PC19.y = PC19 projected<br> PC20.y = PC20 projected<br> PC21.y = PC21 projected<br> PC22.y = PC22 projected<br> PC23.y = PC23 projected<br> PC24.y = PC24 projected<br> PC25.y = PC25 projected<br> PC26.y = PC26 projected<br> PC27.y = PC27 projected<br> PC28.y = PC28 projected<br> PC29.y = PC29 projected<br> PC30.y = PC30 projected<br> PC31.y = PC31 projected<br> PC32.y = PC32 projected<br> PC33.y = PC33 projected<br> PC34.y = PC34 projected<br> PC35.y = PC35 projected</p> <p> </p> <p> </p> <p> </p> <p>Genomics contains the following files (Genomic data is available from NCBI BioProject: PRJNA1019795):</p> <p>all_euryale_calls.vcf.gz<br> The unfiltered VCF file</p> <p>euryale_V2.sh<br> Shell script for the genomic data analysis</p> <p>introgress.R<br> R script for running Introgress</p> <p>introgress_all_east2.txt<br> Output of Introgress for the Eastern contact zone</p> <p>introgress_all_west2.txt<br> Output of Introgress for the Western contact zone</p> <p>Admixture_output.txt<br> Output of Admixture assuming either 2 or 3 genomic clusters (K) with the respective population and ID</p> <p>Outliers2BombyxMori.txt<br> BLAST summary of outlier regions against Bombyx Mori</p> <p>Outliers2ManjolaJurtina.txt<br> BLAST summary of outlier regions against Manjola jurtina</p> <p>Outliers2ParargeAegeria.txt<br> BLAST summary of outlier regions against Pararge aegeria</p> <p> </p>
Journey North - Monarch Butterfly and Milkweed observations by volunteer community scientists across Central and North America (1996-2020)
This data package contains monarch migration data (1996 - 2020) across North America collected by 42,518 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Monarch and Milkweed project is an ongoing study of monarch migration phenology conducted at broad spatial and temporal scales. Since 1996, community scientists have tracked first arrival dates and breeding and feeding behavior as well as the onset of fall migration, fall roosts, and peak migration events. Community scientists have also tracked the first emergence of milkweed in the spring and the presence of milkweed across the landscape during the summer, fall-winter months. The focal species is the Monarch Butterfly, Danaus plexippus. Community scientists indicate when known milkweed species in submitted comments. Journey North data is observational and often opportunistic in nature. Observers do provide estimates of the number of adult monarch butterflies sighted during an observation. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day; do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence, not abundance. Additional contextual information is provided as text in the comments field of the dataset. The Journey North Monarch and Milkweed project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
Spatial and temporal distribution and abundance of butterflies in the Andrews Experimental Forest, 1994-1996
This database contains information on species abundance according to date and location within the H.J. Andrews Experimental Forest Lookout Creek watershed. The database provides the information needed to assess patterns in the abundance of butterflies across time and space. The distribution and abundance of butterfly species on the Andrews Forest is strongly influenced by geographical scale, elevation, aspect, plant community, management regime, and time of year. Patterns of distribution and abundance are based on an historical total of 80 species, of which 73 are resident species and about 55 of which may be observed in any given year. Butterflies were surveyed at two- week intervals from late April through early October over a three-year period (1994-6). Approximately one-third of the watershed was covered during each visit, thus each area was sampled at about 6 week intervals within each sample season.
Fig. 15. Female sterigma. A in Revisiting the Andean butterfly Eryphanis zolvizora group (Lepidoptera, Nymphalidae): one or several species?
Fig. 15. Female sterigma. A. Eryphanis zolvizora zolvizora (Hewitson, 1877) (Bolivia; MNHN, CG). B-H. Eryphanis zolvizora chachapoya ssp. nov. B. PT from Cushi, Pasco, Peru (BMNH 8226). C. PT from Carpish, Huánuco, Peru (MNHN, PBB 2285). D. Specimen from Mallqui, Huánuco, Peru (MNHN, PBB 2327). E. PT from San José de Molinopampa, Amazonas, Peru (MNHN, PBGL 198). F. PT from Nieva, Amazonas, Peru (MNHN, PBGL 596). G. PT from Alto Nieva, Amazonas, Peru (MNHN, PBGL 519). H. Specimen from Alto Nieva, Amazonas, Peru (MNHN, PBGL 520). I. Eryphanis zolvizora greeneyi Penz & DeVries, 2008, stat. rev., specimen fromValladolid, Zamora-Chinchipe, Ecuador (MNHN, PBB 2288). J. Eryphanis zolvizora casagrande ssp. nov., PT from La Planada, Nariño, Colombia (IAvH; drawing by Jean-François Le Crom, JFL 337). K. E. zolvizora opimus (Staudinger, 1887), specimen from 'Colombie' (MNHN, CG). L. Eryphanis zolvizora reyi ssp. nov., PT from La Mina, Barinas, Venezuela (R, 116-JCSC). M-O. E. zolvizora isabelae ssp. nov. M. PT from Choroní, Aragua, Venezuela (R, 114-JCSC). N. PT from Rancho Grande, Aragua, Venezuela (MIZA, 118-JCSC). O. PT from La Llanada, Distrito Federal, Venezuela (MNHN, PBB 2322).
Fig. 13. A-C in Revisiting the Andean butterfly Eryphanis zolvizora group (Lepidoptera, Nymphalidae): one or several species?
Fig. 13. A-C. Male genitalia of Eryphanis zolvizora greeneyi Penz & DeVries, 2008, stat. rev. A. Specimen from Rio Blanco, Ecuador (MNHN, PBB 729). B. Specimen from Rio Blanco, Ecuador (MNHN, PBB 537). C. Specimen from Rio Blanco, Ecuador (MNHN, PBB 257). – D-F. Male genitalia of Eryphanis zolvizora casagrande ssp. nov. D. HT from Altaquer, Nariño, Colombia (ICNUN). E. PT from Ricaurte, Nariño, Colombia (IAvH; drawing by Jean-François Le Crom, JFL 336). F. Specimen from Las Gralarias, Pichincha, Ecuador (FLMNH). – G-I. Male genitalia of Eryphanis zolvizora opimus (Staudinger, 1887). G. Specimen from Manizales, Caldas, Colombia (BMNH 8228). H. Specimen from Arménia, Quindio, Colombia (MNHN, CG). I. Specimen from Pereira, Risaralda, Colombia (BMNH 8227).
Fig. 16 in Revisiting the Andean butterfly Eryphanis zolvizora group (Lepidoptera, Nymphalidae): one or several species?
Fig. 16. Geographical distribution of Eryphanis zolvizora subspecies. Unreliable localities are excluded. Male genitalia of specimens illustrating the different subspecies are represented.
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Allen Brain Atlas
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