Publications

When you submit a checklist to eButterfly, you make your observations available to the global community of citizen scientists, researchers, educators, conservationists, and butterfly enthusiasts. The publications listed below highlight the various ways in which all these contributions are being used.

We want this list of publications to be as inclusive as possible. If you know of other publications not listed that used eButterfly data, please let us know.

2024

  • MacDonald, Z. G., Shaffer, H. B., & Sperling, F. A. Impacts of land use and climate change on natural populations: The butterfly perspective.
  • Schlesinger, M. D., Hardy, S. P., McFarland, K. P., Saucier, L., White, E. L., Zarrillo, T. A., & Young, B. E. (2024). Insect pollinators: The time is now for identifying species of greatest conservation need. Wildlife Society Bulletin, e1537. https://doi.org/10.1002/wsb.1537
  • Goldstein, M. I., Tallamy, D. W., Espindola, A., Lemoine, N. P., & Kharouba, H. M. (2024). Logistical and preference bias in participatory science butterfly data. Frontiers in Ecology and the Environment. https://doi.org/10.1002/fee.2783
  • Larsen, E. A., Belitz, M. W., Di Cecco, G. J., Glassberg, J., Hurlbert, A. H., Ries, L., & Guralnick, R. P. (2024). Overwintering strategy regulates phenological sensitivity and consequences for ecological services in a clade of temperate North American insects. Functional Ecology, 38(5), 1075-1088. https://doi.org/10.1111/1365-2435.14543
  • Boxler, B.M., Loftin, C.S. & Sutton, W.B. Monarch Butterfly (Danaus plexippus) Roost Site-Selection Criteria and Locations East of the Appalachian Mountains, U.S.A.. J Insect Behav 37, 22–48 (2024). https://doi.org/10.1007/s10905-023-09844-5
  • Larsen, E. A., Belitz, M. W., Di Cecco, G. J., Glassberg, J., Hurlbert, A. H., Ries, L., & Guralnick, R. P. (2024). Overwintering strategy regulates phenological sensitivity and consequences for ecological services in a clade of temperate North American insects. Functional Ecology. https://doi.org/10.1111/1365-2435.14543
  • Carvalho, A. P. S., Owens, H. L., St Laurent, R. A., Pierce, N. E., Kawahara, A. Y., & Lohman, D. J. (2024). Comprehensive phylogeny of Pieridae butterflies reveals strong correlation between diversification and temperature. iScience, 27(4), 109336. https://doi.org/10.1016/j.isci.2024.109336

2023

  • Shirey, V., Neupane, N., Guralnick, R., & Ries, L. (2024). Rising minimum temperatures contribute to 50 years of occupancy decline among cold-adapted Arctic and boreal butterflies in North America. Global Change Biology, 30(2), e17205. https://doi.org/10.1111/gcb.17205
  • Drapeau Picard, A.-P., Dieni, A., Moreau, A., Moczula, D., Casajus, N., Charest, S., Girault, C., Bennett, J. R., & Larrivée, M. (2023). Mission Monarch: engaging the Canadian public for the conservation of a species at risk. Journal of Insect Conservation. https://doi.org/10.1007/s10841-023-00540-5
  • Pinkert, S., Sica, Y.V., Winner, K. and Jetz, W. (2023), The potential of ecoregional range maps for boosting taxonomic coverage in ecology and conservation. Ecography, 2023: e06794. https://doi.org/10.1111/ecog.06794
  • Eckert, I., Brown, A., Caron, D., Riva, F., & Pollock, L. J. (2023). 30×30 biodiversity gains rely on national coordination. Nature Communications, 14(1), 7113.
  • Butterflies of Maine and the Canadian Maritime Provinces. (n.d.). Cornell University Press. Retrieved November 30, 2023, from https://www.cornellpress.cornell.edu/book/9781501768941/butterflies-of-maine-and-the-canadian-maritime-provinces/
  • Skvarla, M. J., & Fisher, J. R. (2023). Online community photo-sharing in entomology: a large-scale review with suggestions on best practices. Annals of the Entomological Society of America, 116(5), 276-304. https://doi.org/10.1093/aesa/saad021
  • Bolton, G. (2023). Growing utility of online photo-sharing in entomology research. Entomology Today. https://entomologytoday.org/2023/10/31/growing-utility-online-photo-sharing-entomology-research/

2022

  • Pinkert, S., Sica, Y., Winner, K., & Jetz, W. (2022). The potential of ecoregional range maps for boosting taxonomic coverage in large-scale ecology and conservation. Authorea Preprints. https://www.authorea.com/doi/pdf/10.22541/au.167156303.39224288
  • Calhoun, John V. (2022).A local irruption of Chlosyne nycteis (Nymphalidae) in Maine, with an important new food plant record. News of The Lepidopterists’ Society 64(1): 26-33. https://images.peabody.yale.edu/lepsoc/nls/2020s/2022/2022_v64_n1.pdf
  • David, K. T. (2022). Global gradients in the distribution of animal polyploids. Proceedings of the National Academy of Sciences, 119(48), e2214070119. https://doi.org/10.1073/pnas.2214070119
  • Ednie, G., & Kerr, J. T. (2022). High resolution thermal remote sensing and the limits of species’ tolerance. PeerJ, 10, e13911.
  • Erin Toffelmier, Joscha Beninde, H Bradley Shaffer, The phylogeny of California, and how it informs setting multi-species conservation priorities, Journal of Heredity, 2022;, esac045, https://doi.org/10.1093/jhered/esac045
  • Forister, Matthew L.; Eliza M. Grames, Christopher A. Halsch, Kevin J. Burls, Cas F. Carroll, Katherine L. Bell, Joshua P. Jahner, Taylor Bradford, Jing Zhang, Qian Cong, Nick V. Grishin, Jeffrey Glassberg, Arthur M. Shapiro, Thomas V. Riecke (2022). Assessing risk for butterflies in the context of climate change, demographic uncertainty, and heterogenous data sources. bioRxiv 2022.05.22.492972; https://doi.org/10.1101/2022.05.22.492972.
  • Larsen, E. A., Belitz, M. W., Guralnick, R. P., & Ries, L. (2022). Consistent trait-temperature interactions drive butterfly phenology in both incidental and survey data. Scientific Reports, 12(1), 1-10. https://doi.org/10.1038/s41598-022-16104-7
  • Pinkert, S., Barve, V., Guralnick, R., & Jetz, W. (2022). Global geographical and latitudinal variation in butterfly species richness captured through a comprehensive country‐level occurrence database. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13475.
  • Prudic, K. L., Cruz, T. M. P., Winzer, J. I., Oliver, J. C., Melkonoff, N. A., Verbais, H., & Hogan, A. (2022). Botanical Gardens Are Local Hotspots for Urban Butterflies in Arid Environments. Insects, 13(10), 865.https://doi.org/10.3390/insects13100865
  • Valho, A. P. S., Owens, H. L., St Laurent, R. A., Earl, C., Dexter, K. M., Messcher, R. L., … & Lohman, D. J. (2022). Diversification is correlated with temperature in white and sulfur butterflies. bioRxiv. https://doi.org/10.1101/2022.09.22.509088
  • Wilson Rankin, E.E. and Rankin, D.T. (2022), Secondary nectar robbing by Lycaenidae and Riodinidae: Opportunistic but not infrequent. Ecology. Accepted Author Manuscript e3892. https://doi.org/10.1002/ecy.3892

2021

  • Wilson J. Keaton, Casajus Nicolas, Hutchinson Rebecca A., McFarland Kent P., Kerr Jeremy T., Berteaux Dominique, Larrivée Maxim, Prudic Kathleen L. (2021). Climate Change and Local Host Availability Drive the Northern Range Boundary in the Rapid Expansion of a Specialist Insect Herbivore, Papilio cresphontes. Frontiers in Ecology and Evolution 9:85. https://doi.org/10.3389/fevo.2021.579230
  • Davidson, S. C., & Ruhs, E. C. (2021). Understanding the dynamics of Arctic animal migrations in a changing world. Animal Migration, 8(1), 56-64. https://doi.org/10.1515/ami-2020-0114
  • Lewthwaite, J. M., & Mooers, A. Ø. Geographical homogenization but little net change in the local richness of Canadian butterflies. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13426
  • Rivest, S. A., & Kharouba, H. M. (2021). Anthropogenic disturbance promotes the abundance of a newly introduced butterfly, the European common blue (Polyommatus icarus; Lepidoptera: Lycaenidae), in Canada. Canadian Journal of Zoology, 99(8), 642-652. https://doi.org/10.1139/cjz-2021-0009
  • Dargent, F., Gilmour, S. M., Brown, E. A., Kassen, R., & Kharouba, H. M. (2021). Low prevalence of the parasite Ophryocystis elektroscirrha at the range edge of the eastern North American monarch (Danaus plexippus) butterfly population. Canadian Journal of Zoology, 99(5), 409-413. https://doi.org/10.1139/cjz-2020-0175
  • Bates, A. E., Primack, R. B., Duarte, C. M., & PAN-Environment Working Group. (2021). Global COVID-19 lockdown highlights humans as both threats and custodians of the environment. Biological Conservation, 109175. https://doi.org/10.1016/j.biocon.2021.109175
  • Crimmins, T. M., Posthumus, E., Schaffer, S., & Prudic, K. L. (2021). COVID-19 impacts on participation in large scale biodiversity-themed community science projects in the United States. Biological Conservation, 256, 109017. https://doi.org/10.1016/j.biocon.2021.109017
  • Shirey, V., Belitz, M. W., Barve, V., & Guralnick, R. (2021). A complete inventory of North American butterfly occurrence data: narrowing data gaps, but increasing bias. Ecography, 44(4), 537-547. https://doi.org/10.1111/ecog.05396
  • Dexheimer, E., de Araújo, H. N., & Despland, E. (2021). Novel mutualistic interaction in introduced Polyommatus icarus larvae in Quebec. The Journal of the Entomological Society of Ontario, 152, 29-38. https://journal.lib.uoguelph.ca/index.php/eso/article/view/6370
  • Kantor, C. A., Skreta, M., Rauby, B., Boussioux, L., Jehanno, E., Luccioni, A., … & Talbot, H. (2021). Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification. arXiv preprint arXiv:2103.11285. https://arxiv.org/pdf/2103.11285.pdf
  • Kantor, C. A., Boussioux, L., Rauby, B., & Talbot, H. (2021). Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15807-15808. https://ojs.aaai.org/index.php/AAAI/article/view/17900
  • Kantor, C. A., Skreta, M., Rauby, B., Boussioux, L., Jehanno, E., Luccioni, A., … & Talbot, H. (2021). Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification. arXiv preprint arXiv:2103.11285. https://arxiv.org/pdf/2103.11285
  • Kantor, C. A., Boussioux, L., Rauby, B., & Talbot, H. (2021). Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15316-15322. https://ojs.aaai.org/index.php/AAAI/article/view/17798

2020

  • Skreta, M., Luccioni, A., & Rolnick, D. (2020). Spatiotemporal Features Improve Fine-Grained Butterfly Image Classification. Tackling Climate Change with Machine Learning workshop at NeurIPS 2020. https://www.climatechange.ai/papers/neurips2020/63/paper.pdf
  • Tremblay, P., MacMillan, H. A., & Kharouba, H. M. (2020). Autumn larval cold tolerance does not predict the northern range limit of a widespread butterfly species. bioRxiv. https://doi.org/10.1101/2020.06.14.151266
  • Weiser, E. L., Diffendorfer, J. E., Lopez-Hoffman, L., Semmens, D., & Thogmartin, W. E. (2020). Challenges for leveraging citizen science to support statistically robust monitoring programs. Biological Conservation, 242, 108411. https://doi.org/10.1016/j.biocon.2020.108411

2019

  • Crewe, Tara L., Mitchell, Greg W., Larrivée, Maxim. (2019). Size of the Canadian Breeding Population of Monarch Butterflies Is Driven by Factors Acting During Spring Migration and Recolonization. Frontiers in Ecology and Evolution 7: 308. https://doi.org/10.3389/fevo.2019.00308
  • Calhoun, John. (2019). Watch for Erynnis funeralis (Hesperiidae) in the East. SOUTHERN LEPIDOPTERISTS’ NEWS 41 (4):285-287. (PDF)
  • Weiser, E. L., Diffendorfer, J. E., Grundel, R., López‐Hoffman, L., Pecoraro, S., Semmens, D., & Thogmartin, W. E. (2019). Balancing sampling intensity against spatial coverage for a community science monitoring programme. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.13491
  • Wilson, J. Keaton, Nicolas Casajus, Rebecca A. Hutchinson, Kent P. McFarland, Jeremy T. Kerr, Dominique Berteaux, Maxim Larrivée, Kathleen L. Prudic (2019) Climate change and local host availability drive the northern range boundary in the rapid northward expansion of the eastern giant swallowtail butterfly
    bioRxiv 868125; doi: https://doi.org/10.1101/868125

2015-2018

  • Soroye, P., Ahmed, N., Kerr, J.T. (2018). Opportunistic citizen science data transform understanding of species distributions, phenology, and diversity gradients for global change research. Global Change Biology 24, 5281–5291. https://doi.org/10.1111/gcb.14358
  • Prudic, K. L., Oliver, J. C., Brown, B. V., & Long, E. C. (2018). Comparisons of citizen science data-gathering approaches to evaluate urban butterfly diversity. Insects, 9(4), 186.
  • Prudic, K. L., McFarland, K. P., Oliver, J. C., Hutchinson, R. A., Long, E. C., Kerr, J. T., & Larrivée, M. (2017). eButterfly: leveraging massive online citizen science for butterfly conservation. Insects, 8(2), 53. https://doi.org/10.3390/insects8020053
  • Schmidt BC, Layberry RA (2016) What Azure blues occur in Canada? A re-assessment of Celastrina Tutt species (Lepidoptera, Lycaenidae). ZooKeys 584: 135-164. https://doi.org/10.3897/zookeys.584.7882
  • Ries, L., & Oberhauser, K. (2015). A citizen army for science: quantifying the contributions of citizen scientists to our understanding of monarch butterfly biology. BioScience, 65(4), 419-430. https://doi.org/10.1093/biosci/biv011+

Other Publications and reports listed on GBIF: 

  • https://www.gbif.org/resource/search?contentType=literature&gbifDatasetKey=cf3bdc30-370c-48d3-8fff-b587a39d72d6

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