Extracting secondary data from citizen science images reveals host flower preferences of the Mexican grass‐carrying wasp Isodontia mexicana in its native and introduced ranges

Author:

Pernat Nadja12ORCID,Memedemin Daniyar3ORCID,August Tom4ORCID,Preda Cristina3ORCID,Reyserhove Lien5ORCID,Schirmel Jens6ORCID,Groom Quentin7ORCID

Affiliation:

1. Institute of Landscape Ecology University of Münster Münster Germany

2. Centre for Integrative Biodiversity Research and Applied Ecology University of Münster Münster Germany

3. Faculty of Natural and Agricultural Sciences Ovidius University of Constanta Constanţa Romania

4. UK Centre of Ecology and Hydrology Wallingford UK

5. Instituut voor Natuur‐ en Bosonderzoek, Team Oscibio Brussel Belgium

6. RPTU Kaiserslautern‐Landau, iES Landau Institute for Environmental Sciences Landau Germany

7. Meise Botanic Garden Meise Belgium

Abstract

AbstractWe investigated the plant‐pollinator interactions of the Mexican grass‐carrying wasp Isodontia mexicana—native to North America and introduced in Europe in the 1960sthrough the use of secondary data from citizen science observations. We applied a novel data exchange workflow from two global citizen science platforms, iNaturalist and Pl@ntNet. Images from iNaturalist of the wasp were used to query the Pl@ntNet application to identify possible plant species present in the pictures. Simultaneously, botanists manually identified the plants at family, genus and species levels and additionally documented flower color and biotic interactions. The goals were to calibrate Pl@ntNet's accuracy in relation to this workflow, update the list of plant species that I. mexicana visits as well as its flower color preferences in its native and introduced ranges. In addition, we investigated the types and corresponding frequencies of other biotic interactions incidentally captured on the citizen scientists' images. Although the list of known host plants could be expanded, identifying the flora from images that predominantly show an insect proved difficult for both experts and the Pl@ntNet app. The workflow performs with a 75% probability of correct identification of the plant at the species level from a score of 0.8, and with over 90% chance of correct family and genus identification from a score of 0.5. Although the number of images above these scores may be limited due to the flower parts present on the pictures, our approach can help to get an overview into species interactions and generate more specific research questions. It could be used as a triaging method to select images for further investigation. Additionally, the manual analysis of the images has shown that the information they contain offers great potential for learning more about the ecology of an introduced species in its new range.

Funder

European Cooperation in Science and Technology

Publisher

Wiley

Reference80 articles.

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3. August T.(2019).Plantnet: Automated plant identification with PlantNet. R package version 1.0.0[Software].https://github.com/BiologicalRecordsCentre/plantnet

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5. Bengus Y. U. V.(2022).Isodontia mexicana (Hymenoptera Sphecidae) a new invasive wasp species in the fauna of the Kharkiv region. (ISODONTIA MEXICANA (HYMENOPTERA SPHECIDAE) НОВИЙ ІНВАЗІЙНИЙ ВИД ОС У ФАУНІ ХАРКІВСЬКОЇ ОБЛАСТІ). International scientific and practical conference “Natural science and education: Current state and prospects for development” (September 22–23 2022) Abstract of abstracts 13–16.https://dspace.hnpu.edu.ua/bitstreams/472cff80‐21bc‐43aa‐98d3‐701c26337e2a/download

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