Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

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dc.identifier.uri http://dx.doi.org/10.15488/573
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/597
dc.contributor.author Lühken, Renke
dc.contributor.author Gethmann, Jörn Martin
dc.contributor.author Kranz, Petra
dc.contributor.author Steffenhagen, Pia
dc.contributor.author Staubach, Christoph
dc.contributor.author Conraths, Franz J.
dc.contributor.author Kiel, Ellen
dc.date.accessioned 2016-10-31T07:59:00Z
dc.date.available 2016-10-31T07:59:00Z
dc.date.issued 2016
dc.identifier.citation Lühken, R.; Gethmann, J.M.; Kranz, P.; Steffenhagen, Pia; Staubach, C. et al.: Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany. In: Geospatial Health 11 (2016), Nr. 2, S. 119-129. DOI: http://dx.doi.org/10.4081/gh.2016.405
dc.description.abstract This study analysed Culicoides presence-absence data from 46 sampling sites in Germany, where monitoring was carried out from April 2007 until May 2008. Culicoides presence-absence data were analysed in relation to land cover data, in order to study whether the prevalence of biting midges is correlated to land cover data with respect to the trapping sites. We differentiated eight scales, i.e. buffer zones with radii of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 km, around each site, and chose several land cover variables. For each species, we built eight single-scale models (i.e. predictor variables from one of the eight scales for each model) based on averaged, generalised linear models and two multiscale models (i.e. predictor variables from all of the eight scales) based on averaged, generalised linear models and generalised linear models with random forest variable selection. There were no significant differences between performance indicators of models built with land cover data from different buffer zones around the trapping sites. However, the overall performance of multi-scale models was higher than the alternatives. Furthermore, these models mostly achieved the best performance for the different species using the index area under the receiver operating characteristic curve. However, as also presented in this study, the relevance of the different variables could significantly differ between various scales, including the number of species affected and the positive or negative direction. This is an even more severe problem if multi-scale models are concerned, in which one model can have the same variable at different scales but with different directions, i.e. negative and positive direction of the same variable at different scales. However, multi-scale modelling is a promising approach to model the distribution of Culicoides species, accounting much more for the ecology of biting midges, which uses different resources (breeding sites, hosts, etc.) at different scales. eng
dc.language.iso eng
dc.publisher Pavia : Page Press Publications
dc.relation.ispartofseries Geospatial Health 11 (2016), Nr. 2
dc.rights CC BY-NC 4.0
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
dc.subject Ceratopogonidae eng
dc.subject Culicoides eng
dc.subject Multiscale model eng
dc.subject Species distribution model eng
dc.subject.ddc 610 | Medizin, Gesundheit ger
dc.subject.ddc 630 | Landwirtschaft, Veterinärmedizin
dc.title Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany
dc.type article
dc.type Text
dc.relation.issn 1827-1987
dc.relation.doi http://dx.doi.org/10.4081/gh.2016.405
dc.bibliographicCitation.issue 2
dc.bibliographicCitation.volume 11
dc.bibliographicCitation.firstPage 119
dc.bibliographicCitation.lastPage 129
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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