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Research article - Peer-reviewed, 2014

Using citizen-reported data to predict distributions of two non-native insect species in Sweden

Widenfalk, Lina; Ahrné, Karin; Berggren, Åsa; Ahlbäck, Lina

Abstract

Information on exotic species' current and potential distribution is vital for decisions on management. Species distribution models can predict where colorizations are likely; however, the collection of species' distribution data over large areas in order to parameterize the models is costly. Therefore, modelling methods that are able to use low-cost information such as citizen-reported data are potentially very useful. In this study, we used the species habitat modelling program Maxent to predict the potential geographical distribution of two non-native insect species in Sweden, the butterfly Araschnia levana and the shield bug Graphosoma lineatum. For this we used citizen-reported presence-only open-access data in combination with climate and land cover data from national databases. Our models showed that presence of A. levana was best predicted by winter temperature and habitats related to open grasslands. For G. lineatum, summer temperature and open green areas, in both urban and rural areas were the best predictors for species presence. These models show that large areas of non-colonized potential habitats exist within Sweden. For A. levana these yet-to-be-colonized habitats are mainly in the south, while for G. lineatum these habitats occur in the south and along the Baltic Sea coast. Comparisons of temporal patterns in species reporting for A. levana and G. lineatum to similar insects with known stable populations revealed large 'willingness to report' effects that could potentially bias range expansion rates. Once corrected for, current distribution expansion rates were estimated as 1.9 km/yr and 1.07 km/yr respectively. The study shows the use of public reports in conservation science as a way of gathering species information over large areas. This increases the data sources available for researchers to predict the distribution of species and have the additional value of the involvement of the public in conservation efforts.

Published in

Ecosphere
2014, volume: 5, number: 12, article number: 156

Authors' information

Widenfalk, Lina (Ahlbäck Widenfalk, Lina)
Swedish University of Agricultural Sciences, Department of Ecology
Swedish University of Agricultural Sciences, Swedish Species Information Centre
Swedish University of Agricultural Sciences, Department of Ecology
Ahlbäck, Lina (Ahlbäck Widenfalk, Lina)
Swedish University of Agricultural Sciences, Department of Ecology

Sustainable Development Goals

SDG13 Climate action
SDG9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

UKÄ Subject classification

Ecology

Publication Identifiers

DOI: https://doi.org/10.1890/ES14-00212.1

URI (permanent link to this page)

https://res.slu.se/id/publ/63730