On the road: Anthropogenic factors drive the invasion risk of a wild solitary bee species

Lanner, Julia; Dubos, Nicolas; Geslin, Benoît; Leroy, Boris; Hernández-Castellano, Carlos; Dubaić, Jovana Bila; Bortolotti, Laura; Calafat, Joan Díaz; Ćetković, Aleksandar; Flaminio, Simone; Féon, Violette Le; Margalef-Marrase, Jordi; Orr, Michael C.; Pachinger, Bärbel; Ruzzier, Enrico; Smagghe, Guy; Tuerlings, Tina; Vereecken, Nicolas; Meimberg, Harald

doi:10.1016/j.scitotenv.2022.154246

Cited by 21 publications

(17 citation statements)

References 103 publications

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“…We used a null geographic model (i.e., a map of the geographic distance to presence points) generated with the dismo R package (Hijmans 2012) and used it as a probability weight for pseudo-absence selection. This technique was deemed appropriate for IAS that are still expanding (i.e., not at equilibrium), because it reduces the generation of pseudo-absences in regions that are suitable but not yet invaded (e.g., Lanner et al 2022). Since no independent data are available to assess the effect of sample bias correction, we used the Relative Overlap Index (ROI) based on Schoener's D overlap (Dubos et al 2021b).…”

Section: Distribution Modellingmentioning

confidence: 99%

“…Early detection is a key determinant to prevent invasions, suggesting the urgent need to identify priority areas for surveillance efforts. In this regard, a widely advocated management tool in conservation biology is Species Distribution Modelling (SDM; Gallien et al 2012; Lanner et al 2022). This approach consists of identifying the environmental factors explaining the distribution of a species and predicting areas of high environmental suitability.…”

Section: Introductionmentioning

confidence: 99%

“…maritime traffic). The distribution of IAS may be explained and predicted by a combination of environmental and socio-economic predictors (Bellard et al 2016; Lanner et al 2022). Environmental predictors (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Choice of climate data influences current and future global invasion risks for twoPhelsumageckos

Dubos

Fieldsend

Roesch

et al. 2022

Preprint

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Invasion risks may be influenced either negatively or positively by climate change, depending on the species. These can be predicted with species distribution models, but projections can be strongly affected by input environmental data (climate data source, Global Circulation Models and Shared Socio-economic Pathways SSP). We modelled the distribution of Phelsuma grandis and P. laticauda, two Malagasy reptiles that are spreading globally. We accounted for drivers of spread and establishment using socio-economic factors (e.g., distance from ports) and two climate data sources, i.e., Climatologies at High Resolution for the Earth's and Land Surface Areas (CHELSA) and Worldclim. We further quantified the degree of agreement in invasion risk models that utilised CHELSA and Worldclim data for current and future conditions. Most areas identified as highly exposed to invasion risks were consistently identified (e.g. in Caribbean and Pacific Islands). However, projected risks differed locally. We also found notable differences in quantitative invasion risk (3% difference in suitability scores for P. laticauda and up to 14% for P. grandis) under current conditions. Despite both species native distributions overlap substantially, climate change will drive opposite responses on invasion risks by 2070 (decrease for P. grandis, increase for P. laticauda). Overall, projections of future invasion risks were the most affected by climate data source, followed by SSP. Our results highlight that assessments of current and future invasion risks are sensitive to the climate data source, especially in Islands. We stress the need to account for multiple climatologies when assessing invasion risks.

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Section: Distribution Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Choice of climate data influences current and future global invasion risks for twoPhelsumageckos

Dubos

Fieldsend

Roesch

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…maritime traffic). The distribution of IAS may be explained and predicted by a combination of environmental and socio-economic predictors (Bellard et al 2016;Lanner et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Choice of climate data influences current and future global invasion risks for two Phelsuma geckos

Dubos

Fieldsend

Roesch

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Invasion risks may be influenced either negatively or positively by climate change, depending on the species. These can be predicted with species distribution models, but projections can be strongly affected by input environmental data (climate data source, Global Circulation Models and Shared Socio-economic Pathways SSP). We modelled the distribution of Phelsuma grandis and P. laticauda , two Malagasy reptiles that are spreading globally. We accounted for drivers of spread and establishment using socio-economic factors (e.g., distance from ports) and two climate data sources, i.e., Climatologies at High Resolution for the Earth’s and Land Surface Areas (CHELSA) and Worldclim. We further quantified the degree of agreement in invasion risk models that utilised CHELSA and Worldclim data for current and future conditions. Most areas identified as highly exposed to invasion risks were consistently identified (e.g. in Caribbean and Pacific Islands). However, projected risks differed locally. We also found notable differences in quantitative invasion risk (3% difference in suitability scores for P. laticauda and up to 14% for P. grandis ) under current conditions. Despite both species native distributions overlap substantially, climate change will drive opposite responses on invasion risks by 2070 (decrease for P. grandis, increase for P. laticauda ). Overall, projections of future invasion risks were the most affected by climate data source, followed by SSP. Our results highlight that assessments of current and future invasion risks are sensitive to the climate data source, especially in Islands. We stress the need to account for multiple climatologies when assessing invasion risks.

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“…Since exotic ornamental plants are currently documented as dominant food sources throughout the species' non-native range, many European records are associated with various human settlements, urban and rural. Megachile sculpturalis seems to thrive in urban areas [67], following the concentration of s foraging resources [42,43], and abundant nesting opportunities [68]. The complicated interplay of these factors may also vary over time through the effects of temporal food variability and the early dynamics of local bee population build-up (cf [42,43]).…”

Section: Introductionmentioning

confidence: 99%

Towards a real-time tracking of an expanding alien bee species in Southeast Europe through citizen science and floral host monitoring

Dubaić¹,

Lanner²,

Rohrbach³

et al. 2022

Environ. Res. Commun.

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Citizen science, a practice of public participation in scientific projects, is popular in Western countries, however, it is still a relatively novel approach in Southeast Europe. In this region, citizen science can be a useful tool for increasing the understanding of alien species. One such species is the sculptured resin bee, Megachile sculpturalis, a putatively invasive alien pollinator native to East Asia. It was introduced to France in 2008, from where it quickly spread across West and Central Europe. However, our knowledge of its eastern distribution is scarce since it is based mostly on isolated findings. We combined citizen science and data extraction from online sources (e.g., naturalist’s databases and social media) covering 6 years, and 3 years of targeted floral resource monitoring in the search for M. sculpturalis across regions of southeastern Europe. We collected presence data and information on M. sculpturalis abundances across an urban-rural gradient from eight countries: Hungary, Slovenia, Croatia, Serbia, Bosnia and Herzegovina, Montenegro, Romania, Bulgaria, and the region of the Crimean Peninsula. We present the first country records for Romania, Bulgaria, and Montenegro, identify the dynamic expansion front in southern Serbia and provide new southernmost occurrences in Southeast Europe. We also collected data on species ecology (e.g., phenology, pollen/nectar sources, nest characteristics) and gathered evidence of reproducing populations of this species across the studied region. Citizen science data provided a five times larger spatial coverage, including recordings from remote locations, than the data collected by expert field surveys and provided critical additional data about the species biology, thanks to exceptionally engaged participants. We emphasize the importance of close collaboration between regional scientist teams and citizen participants and the benefits of this approach for monitoring a species with a continent-wide spread potential.

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On the road: Anthropogenic factors drive the invasion risk of a wild solitary bee species

Cited by 21 publications

References 103 publications

Choice of climate data influences current and future global invasion risks for twoPhelsumageckos

Choice of climate data influences current and future global invasion risks for twoPhelsumageckos

Choice of climate data influences current and future global invasion risks for two Phelsuma geckos

Towards a real-time tracking of an expanding alien bee species in Southeast Europe through citizen science and floral host monitoring

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