Pest occurrence of <i>Aedes rossicus</i>
 close to the Arctic Circle in northern Sweden

Blomgren, Eric; Hesson, Jenny C.; Schäfer, Martina L.; Lundström, Jan O.

doi:10.1111/jvec.12280

Cited by 11 publications

(10 citation statements)

References 12 publications

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“…When comparing the Finnish and Swedish fauna, it was expected that Ae. rossicus would also be present in Finland, based on its occurrence around the Swedish Arctic Circle (Lundström et al ., 2013, Blomgren et al ., 2018). It was only after fieldwork for this study ended that Ae.…”

Section: Discussionmentioning

confidence: 99%

The mosquitoes of Finland: updated distributions and bionomics

Culverwell

Uusitalo

Korhonen

et al. 2020

Medical Vet Entomology

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Mosquitoes (Diptera: Culicidae) were collected in Finland between 2012 and 2018 to determine the species present and their distributions. In total, 52 466 specimens from 1031 collections formed the basis for the preparation of distribution maps for each of the 40 species that were collected. Anopheles maculipennis s.s., An. claviger, Aedes geminus and Ochlerotatus sticticus are confirmed on mainland Finland after previous records were uncertain or absent. Coquillettidia richiardii, Culiseta morsitans, Cs. ochroptera, Culex territans, Cx. torrentium, Oc. leucomelas, Oc. nigrinus, Oc. pullatus and Oc. punctodes occur more widely than previously reported. Three species, Ae. rossicus, Cs. subochrea and Oc. cyprius were not collected, although Ae. rossicus was subsequently found in Lapland by another researcher. No invasive species were collected. Ochlerotatus communis, an aggressive biter, was the most commonly encountered species. Larval collection data suggest that several species may have up to three generations per year in Finland, with Cx. torrentium and Cx. pipiens having at least two, and Oc. communis and Oc. punctor regularly found as larvae across the summer. These data, especially when coupled with historical records, are vital for monitoring species which have significant vector potential, particularly when faced with a warming climate.

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Section: Discussionmentioning

confidence: 99%

The mosquitoes of Finland: updated distributions and bionomics

Culverwell

Uusitalo

Korhonen

et al. 2020

Medical Vet Entomology

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“…Climate change is driving the spread of a range of CSI disease vectors (Zuliani et al, 2015;Andersen and Davis, 2017;Blomgren et al, 2018), so understanding the spatio-temporal distribution and evolution of characteristics, such as habitat suitability of these vectors or reservoirs, is essential. These characteristics can then be used in an ecological model that could be coupled with epidemiological models to estimate future risks of disease incidence, e.g.…”

Section: Lsm and Ecological Modelling Aspects Relevant To Csi Predictionmentioning

confidence: 99%

“…Variables simulated by combined climate and land surface models, such as surface temperature, soil moisture, precipitation and land cover, can be used in ecological models or as part of an epidemiological model, e.g. for a species distribution model (Booth et al, 2014). However, the predictive uncertainty in these variables may lead to significant uncertainty in the predictions from CSI modelling (Asghar et al, 2016).…”

Section: Lsm and Ecological Modelling Aspects Relevant To Csi Predictionmentioning

confidence: 99%

“…In the Arctic, climate change is likely to cause enhanced CSI risk in terms of increased incidence, more frequent outbreaks, geographic spread of existing affected zones, and occurrence of newly affected zones (Pauchard et al, 2016;Sajanti et al, 2017;Waits et al, 2018) The complex ecology of CSI organisms presents a challenge to modelling and predicting their epidemiology (Ostfeld, 2010;Carvalho et al, 2014;Ruscio et al, 2015;Sormunen et al, 2016;Li et al, 2016;White et al, 2018). However, such modelling is needed as disease vectors, such as ticks, mosquitoes, badgers and roe deer, which are associated, for example, with Lyme disease (borreliosis) and tularemia, are expanding their ranges northwards (Jaenson et al, 2012;Jore et al, 2014;Andersen and Davis, 2017;Laaksonen et al, 2017;Blomgren et al, 2018). Under climate change and human-induced land use changes, fragmentation of the landscape was found to affect Lyme disease (Simon et al, 2014), whilst mosquito abundance was associated with outbreaks of tularemia in boreal forest (Rydén et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Spatio-temporal variations and uncertainty in land surface modelling for high latitudes: univariate response analysis

et al. 2020

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Abstract. A range of applications analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, make use of land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from that account for land processes in different ways and this may introduce predictive uncertainty when LSM outputs are used as inputs to inform a given application. For useful predictions for a specific application, one must therefore understand the inherent uncertainties in the LSMs and the variations between them, as well as uncertainties arising from variation in the climate data driving the LSMs. This requires methods to analyse multivariate spatio-temporal variations and differences. A methodology is proposed based on multiway data analysis, which extends singular value decomposition (SVD) to multidimensional tables and provides spatio-temporal descriptions of agreements and disagreements between LSMs for both historical simulations and future predictions. The application underlying this paper is prediction of how climate change will affect the spread of CSIs in the Fennoscandian and north-west Russian regions, and the approach is explored by comparing net primary production (NPP) estimates over the period 1998–2013 from versions of leading LSMs (JULES, CLM5 and two versions of ORCHIDEE) that are adapted to high-latitude processes, as well as variations in JULES up to 2100 when driven by 34 global circulation models (GCMs). A single optimal spatio-temporal pattern, with slightly different weights for the four LSMs (up to 14 % maximum difference), provides a good approximation to all their estimates of NPP, capturing between 87 % and 93 % of the variability in the individual models, as well as around 90 % of the variability in the combined LSM dataset. The next best adjustment to this pattern, capturing an extra 4 % of the overall variability, is essentially a spatial correction applied to ORCHIDEE-HLveg that significantly improves the fit to this LSM, with only small improvements for the other LSMs. Subsequent correction terms gradually improve the overall and individual LSM fits but capture at most 1.7 % of the overall variability. Analysis of differences between LSMs provides information on the times and places where the LSMs differ and by how much, but in this case no single spatio-temporal pattern strongly dominates the variability. Hence interpretation of the analysis requires the summation of several such patterns. Nonetheless, the three best principal tensors capture around 76 % of the variability in the LSM differences and to a first approximation successively indicate the times and places where ORCHIDEE-HLveg, CLM5 and ORCHIDEE-MICT differ from the other LSMs. Differences between the climate forcing GCMs had a marginal effect up to 6 % on NPP predictions out to 2100 without specific spatio-temporal GCM interaction.

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“…Ae. rossicus was found close to the Arctic circle in northern Sweden [20]. Therefore, prediction of the epidemiological threat and its control requires knowledge about the species composition of the corresponding mosquito vectors.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Metaphase Chromosome Karyotypes in Imaginal Discs of Aedes communis, Ae. punctor, Ae. intrudens, and Ae. rossicus (Diptera: Culicidae) Mosquitoes

Alekseeva

Andreeva

Wasserlauf

et al. 2020

Insects

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In this study, cytogenetic analysis of the metaphase chromosomes from imaginal discs of Aedes (Diptera: Culicidae) mosquitoes—Aedes communis, Ae. punctor, Ae. intrudens, and Ae. rossicus—was performed. The patterns of C-banding and DAPI staining of the heteroсhromatin and the length of the chromosomes demonstrate species specificity. In particular, the Ae. punctor chromosomes are the shortest compared with Ae. communis, Ae. intrudens, and Ae. rossicus, and they also carry additional C and DAPI bands in intercalary regions. The Ae. intrudens chromosomes are the longest, they have pericentromeric C bands, and they almost lack any DAPI bands near the centromere of chromosome 3 versus Ae. communis, which has the largest pericentromeric DAPI blocks in all three chromosome pairs. Ae. rossicus also possesses DAPI bands in the centromeric regions of all chromosomes, but their staining is weaker compared with those of Ae. communis. Therefore, the analysis of karyotypes is a tool for species-level identification of these mosquitoes.

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Pest occurrence of Aedes rossicus close to the Arctic Circle in northern Sweden

Cited by 11 publications

References 12 publications

The mosquitoes of Finland: updated distributions and bionomics

The mosquitoes of Finland: updated distributions and bionomics

Spatio-temporal variations and uncertainty in land surface modelling for high latitudes: univariate response analysis

Analysis of the Metaphase Chromosome Karyotypes in Imaginal Discs of Aedes communis, Ae. punctor, Ae. intrudens, and Ae. rossicus (Diptera: Culicidae) Mosquitoes

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