Details
| Original language | English |
|---|---|
| Article number | 405 |
| Pages (from-to) | 119-129 |
| Number of pages | 11 |
| Journal | Geospatial health |
| Volume | 11 |
| Issue number | 2 |
| Publication status | Published - 2016 |
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.
Keywords
- Ceratopogonidae, Culicoides, Multiscale model, Species distribution model
ASJC Scopus subject areas
- Social Sciences(all)
- Health(social science)
- Social Sciences(all)
- Geography, Planning and Development
- Medicine(all)
- Health Policy
- Medicine(all)
- Medicine (miscellaneous)
Sustainable Development Goals
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In: Geospatial health, Vol. 11, No. 2, 405, 2016, p. 119-129.
Research output: Contribution to journal › Article › Research
}
TY - JOUR
T1 - Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany.
AU - Lühken, Renke
AU - Gethmann, Jörn Martin
AU - Kranz, Petra
AU - Steffenhagen-Koch, Pia
AU - Staubach, Cristoph
AU - Conraths, Franz J.
AU - Kiel, Ellen
N1 - Publisher Copyright: © R. Lühken et al., 2016.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Ceratopogonidae
KW - Culicoides
KW - Multiscale model
KW - Species distribution model
UR - http://www.scopus.com/inward/record.url?scp=84973131370&partnerID=8YFLogxK
U2 - 10.4081/gh.2016.405
DO - 10.4081/gh.2016.405
M3 - Article
VL - 11
SP - 119
EP - 129
JO - Geospatial health
JF - Geospatial health
SN - 1827-1987
IS - 2
M1 - 405
ER -