Dataset Information

A preliminary world checklist of fern-mining insects.

ABSTRACT: Compared to the leaf-miners and stem-miners on flowering plants, the miners on ferns (including both Lycopodiophyta and Polypodiophyta in the broad sense) are less known. Knowledge of miners and their host plants is essential to fully understand plant-insect interactions. Although there are many scattered records on fern miners, a worldwide checklist has not been reported. We provide a preliminary checklist of fern-mining insects and their host plants worldwide. Altogether, we found records for 128 species and 18 families of fern miners, mainly that feed on Dennstaedtiaceae, Equisetaceae, Polypodiaceae and Aspleniaceae. Fern miners belonged to four orders: Diptera (51 species; 39.8%), Coleoptera (33 species; 25.8%), Lepidoptera (28 species; 21.9%) and Hymenoptera (16 species; 12.5%). They are primarily known from the Palaearctic Region, Nearctic Region, Neotropical Region and Oriental Region.

SUBMITTER: Yang J

PROVIDER: S-EPMC8016819 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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A preliminary world checklist of fern-mining insects.

Yang Jie J Wang Xuexiong X Duffy Kevin Jan KJ Dai Xiaohua X

Biodiversity data journal 20210325

Compared to the leaf-miners and stem-miners on flowering plants, the miners on ferns (including both Lycopodiophyta and Polypodiophyta in the broad sense) are less known. Knowledge of miners and their host plants is essential to fully understand plant-insect interactions. Although there are many scattered records on fern miners, a worldwide checklist has not been reported. We provide a preliminary checklist of fern-mining insects and their host plants worldwide. Altogether, we found records for ...[more]

PMID: 33824618

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Project description:Observational studies are based on systematic observation, understood as an organized recording and quantification of behavior in its natural context. Applied to the specific area of sports, observational studies present advantages when comparing studies based on other designs, such as the flexibility for adapting to different contexts and the possibility of using non-standardized instruments as well as a high degree of development in specific software and data analysis. Although the importance and usefulness of sports-related observational studies have been widely shown, there is no checklist to report these studies. Consequently, authors do not have a guide to follow in order to include all of the important elements in an observational study in sports areas, and reviewers do not have a reference tool for assessing this type of work. To resolve these issues, this article aims to develop a checklist to measure the quality of sports-related observational studies based on a content validity study. The participants were 22 judges with at least 3 years of experience in observational studies, sports areas, and methodology. They evaluated a list of 60 items systematically selected and classified into 12 dimensions. They were asked to score four aspects of each item on 5-point Likert scales to measure the following dimensions: representativeness, relevance, utility, and feasibility. The judges also had an open-format section for comments. The Osterlind index was calculated for each item and for each of the four aspects. Items were considered appropriate when obtaining a score of at least 0.5 in the four assessed aspects. After considering these inclusion criteria and all of the open-format comments, the resultant checklist consisted of 54 items grouped into the same initial 12 dimensions. Finally, we highlight the strengths of this work. We also present its main limitation: the need to apply the resultant checklist to obtain data and, thus, increase quality indicators of its psychometric properties. For this reason, as relevant actions for further development, we encourage expert readers to use it and provide feedback; we plan to apply it to different sport areas.

Dataset Information

A preliminary world checklist of fern-mining insects.

Publications

A preliminary world checklist of fern-mining insects.

Similar Datasets

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