{"title":"Identification and Distribution of the Petrophila fulicalis Species Group (Crambidae): Taking Advantage of Citizen Science Data","authors":"Chad L. Sexton","doi":"10.18473/lepi.75i2.a4","DOIUrl":null,"url":null,"abstract":"ABSTRACT. Six very similar species of Petrophila Guilding are reviewed and distinguished: P. fulicalis (Clements 1860), P. confusalis (Walker, [1866]), P. canadensis (Munroe, 1972), P. santafealis (Heppner, 1976), P. hodgesi (Munroe, 1972), and P. heppneri (Blanchard & Knudson, 1983). Large digital image sets derived from citizen science databases are used to supplement traditional data sources to elucidate suites of useful diagnostic characters. These expanded data sets allow for examination of phenotypic variation across ranges and for enhanced understanding of distributional patterns. The advantages and disadvantages of such data sets are discussed and existing data gaps are identified.","PeriodicalId":259893,"journal":{"name":"The Journal of the Lepidopterists’ Society","volume":"335 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of the Lepidopterists’ Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18473/lepi.75i2.a4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT. Six very similar species of Petrophila Guilding are reviewed and distinguished: P. fulicalis (Clements 1860), P. confusalis (Walker, [1866]), P. canadensis (Munroe, 1972), P. santafealis (Heppner, 1976), P. hodgesi (Munroe, 1972), and P. heppneri (Blanchard & Knudson, 1983). Large digital image sets derived from citizen science databases are used to supplement traditional data sources to elucidate suites of useful diagnostic characters. These expanded data sets allow for examination of phenotypic variation across ranges and for enhanced understanding of distributional patterns. The advantages and disadvantages of such data sets are discussed and existing data gaps are identified.