ArticleParasites & vectors2019
What makes the Asian bush mosquito Aedes japonicus japonicus feel comfortable in Germany? A fuzzy modelling approach.
Article in Parasites & vectors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Trends in mosquito species distribution modeling: insights for vector surveillance and disease control.Parasites & vectors · 2023Pooled it
- From a long-distance threat to the invasion front: a review of the invasive Aedes mosquito species in Belgium between 2007 and 2020.Parasites & vectors · 2022Review
- Laboratory Evaluation of Flight Capacities of Aedes japonicus (Diptera: Culicidae) Using a Flight Mill Device.Journal of insect science (Online) · 2021Article
- Drivers of spatio-temporal variation in mosquito submissions to the citizen science project 'Mückenatlas'.Scientific reports · 2021Article
- Article
- Oviposition of Aedes japonicus japonicus (Diptera: Culicidae) and associated native species in relation to season, temperature and land use in western Germany.Parasites & vectors · 2020Article
- Identification of Aedes mosquitoes by MALDI-TOF MS biotyping using protein signatures from larval and pupal exuviae.Parasites & vectors · 2020Article
- Can data from native mosquitoes support determining invasive species habitats? Modelling the climatic niche of Aedes japonicus japonicus (Diptera, Culicidae) in Germany.Parasitology research · 2020Article
- The Asian bush mosquito Aedes japonicus japonicus (Diptera: Culicidae) in Europe, 17 years after its first detection, with a focus on monitoring methods.Parasites & vectors · 2019Review
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Authors and funding
7 authors.
Funding
Abstract
backgroundThe Asian bush mosquito Aedes japonicus japonicus is an invasive species native to East Asia and has become established in North America and Europe. On both continents, the species has spread over wide areas. Since it is a potential vector of human and livestock pathogens, distribution and dissemination maps are urgently needed to implement targeted surveillance and control in case of disease outbreaks. Previous distribution models for Europe and Germany in particular focused on climate data. Until now, effects of other environmental variables such as land use and wind remained unconsidered.
resultsIn order to better explain the distribution pattern of Ae. j. japonicus in Germany at a regional level, we have developed a nested approach that allows for the combination of data derived from (i) a climate model based on a machine-learning approach; (ii) a landscape model developed by means of ecological expert knowledge; and (iii) wind speed data. The approach is based on the fuzzy modelling technique that enables to precisely define the interactions between the three factors and additionally considers uncertainties with regard to the acceptance of certain environmental conditions. The model combines different spatial resolutions of data for Germany and achieves a much higher degree of accuracy than previous published distribution models. Our results reveal that a well-suited landscape structure can even facilitate the occurrence of Ae. j. japonicus in a climatically unsuitable region. Vice versa, unsuitable land use types such as agricultural landscapes and coniferous forests reduce the occurrence probability in climatically suitable regions.
conclusionsThe approach has significantly improved existing distribution models of Ae. j. japonicus for the area of Germany. We generated distribution maps with a resolution of 100 × 100 m that can serve as a basis for the design of control measures. All model input data and scripts are open source and freely available, so that the model can easily be applied to other countries or, more generally, to other species.
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