Limits...
Estimating Ixodes ricinus densities on the landscape scale.

Boehnke D, Brugger K, Pfäffle M, Sebastian P, Norra S, Petney T, Oehme R, Littwin N, Lebl K, Raith J, Walter M, Gebhardt R, Rubel F - Int J Health Geogr (2015)

Bottom Line: Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m(2) in 2013.The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m(2) for 2013 and 104 nymphs/100 m(2) for 2014.The methodology introduced here may be applied to further tick species or extended to other study regions.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Reinhard-Baumeister-Platz 1, 76131, Karlsruhe, Germany. denise.boehnke@kit.edu.

ABSTRACT

Background: The study describes the estimation of the spatial distribution of questing nymphal tick densities by investigating Ixodes ricinus in Southwest Germany as an example. The production of high-resolution maps of questing tick densities is an important key to quantify the risk of tick-borne diseases. Previous I. ricinus maps were based on quantitative as well as semi-quantitative categorisations of the tick density observed at study sites with different vegetation types or indices, all compiled on local scales. Here, a quantitative approach on the landscape scale is introduced.

Methods: During 2 years, 2013 and 2014, host-seeking ticks were collected each month at 25 sampling sites by flagging an area of 100 square meters. All tick stages were identified to species level to select nymphal ticks of I. ricinus, which were used to develop and calibrate Poisson regression models. The environmental variables height above sea level, temperature, relative humidity, saturation deficit and land cover classification were used as explanatory variables.

Results: The number of flagged nymphal tick densities range from zero (mountain site) to more than 1,000 nymphs/100 m(2). Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m(2) in 2013. Generally, nymphal densities (maximum 374 nymphs/100 m(2)), explained variance (46 %) and prediction error (61 nymphs/100 m(2)) were lower in 2014. The models were used to compile high-resolution maps with 0.5 km(2) grid size for the study region of the German federal state Baden-Württemberg. The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m(2) for 2013 and 104 nymphs/100 m(2) for 2014.

Conclusions: The methodology introduced here may be applied to further tick species or extended to other study regions. Finally, the study is a first step towards the spatial estimation of tick-borne diseases in Central Europe.

No MeSH data available.


Related in: MedlinePlus

Ixodes ricinus nymphal ticks per 100 m2 for 2013. Map of the total number of nymphal ticks monthly flagged during 2013 and interpolated to the entire region of Baden-Württemberg, Germany. Sampling locations are marked by a circle showing both the observed (left half) and the modelled (right half) tick density.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4536605&req=5

Fig4: Ixodes ricinus nymphal ticks per 100 m2 for 2013. Map of the total number of nymphal ticks monthly flagged during 2013 and interpolated to the entire region of Baden-Württemberg, Germany. Sampling locations are marked by a circle showing both the observed (left half) and the modelled (right half) tick density.

Mentions: Poisson regression models with the parameters depicted in Table 2 were used to construct nymphal density maps of Baden-Württemberg for 2013 (Fig. 4) and 2014 (Additional file 1). Each map depicts the spatial distribution of the density of nymphs and should be interpreted as the amount of I. ricinus nymphs that may be collected by monthly flagging an area of 100 m2. Green grids represent regions with low nymphal densities (N = 0–50 nymphs/100 m2), while red gradations indicate regions with high nymphal densities (N = 50–1,000 nymphs/100 m2). Low densities of I. ricinus are restricted to higher altitudes in the Black Forest characterised by slightly fragmented coniferous forest habitats (Fig. 2c, class C). Moderate densities were estimated for all other hilly countryside with heights around 300–800 m characterised by shorter growing periods and/or forested areas with high proportions of coniferous forest. Very high densities were estimated for the warmest parts at altitudes below 400 m. This includes, in particular, the regions along the river Rhine and Neckar with surrounding areas, as well as the ambience of Lake Constance. The estimates for all other parts with warm to moderate climatic conditions tend to high nymphal densities. Urban areas and water bodies were excluded from the analysis (Fig. 4, yellow and blue areas). Comparing the maps for 2013 and 2014 depicts a similar distribution of the nymphal density, which is generally lower in 2014 (Fig. 5). These lower densities are caused by extraordinary high temperatures in 2014. The difference of the mean temperatures listed in Table 2 is 1.6 °C, which is of the same order as the temperature increase predicted by climatologists for the next 100 years. It seems that higher temperatures at lower altitudes are responsible for the observed decrease of the I. ricinus nymphal densities, while an increase of the generally lower temperatures at higher altitudes, e.g. in the black forest, cause an increase of the nymphal densities (Fig. 5). The frequency distribution of the difference between the nymphal densities mapped for 2013 and 2014 are depicted in Fig. 6. According to this frequency distribution about 50 % of the study region depicts only minor changes in the nymphal density (below ± 25 nymphs/100 m2). For the other 50 % of the area of Baden-Württemberg considerably lower nymphal densities were estimated for 2014.Fig. 4


Estimating Ixodes ricinus densities on the landscape scale.

Boehnke D, Brugger K, Pfäffle M, Sebastian P, Norra S, Petney T, Oehme R, Littwin N, Lebl K, Raith J, Walter M, Gebhardt R, Rubel F - Int J Health Geogr (2015)

Ixodes ricinus nymphal ticks per 100 m2 for 2013. Map of the total number of nymphal ticks monthly flagged during 2013 and interpolated to the entire region of Baden-Württemberg, Germany. Sampling locations are marked by a circle showing both the observed (left half) and the modelled (right half) tick density.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4536605&req=5

Fig4: Ixodes ricinus nymphal ticks per 100 m2 for 2013. Map of the total number of nymphal ticks monthly flagged during 2013 and interpolated to the entire region of Baden-Württemberg, Germany. Sampling locations are marked by a circle showing both the observed (left half) and the modelled (right half) tick density.
Mentions: Poisson regression models with the parameters depicted in Table 2 were used to construct nymphal density maps of Baden-Württemberg for 2013 (Fig. 4) and 2014 (Additional file 1). Each map depicts the spatial distribution of the density of nymphs and should be interpreted as the amount of I. ricinus nymphs that may be collected by monthly flagging an area of 100 m2. Green grids represent regions with low nymphal densities (N = 0–50 nymphs/100 m2), while red gradations indicate regions with high nymphal densities (N = 50–1,000 nymphs/100 m2). Low densities of I. ricinus are restricted to higher altitudes in the Black Forest characterised by slightly fragmented coniferous forest habitats (Fig. 2c, class C). Moderate densities were estimated for all other hilly countryside with heights around 300–800 m characterised by shorter growing periods and/or forested areas with high proportions of coniferous forest. Very high densities were estimated for the warmest parts at altitudes below 400 m. This includes, in particular, the regions along the river Rhine and Neckar with surrounding areas, as well as the ambience of Lake Constance. The estimates for all other parts with warm to moderate climatic conditions tend to high nymphal densities. Urban areas and water bodies were excluded from the analysis (Fig. 4, yellow and blue areas). Comparing the maps for 2013 and 2014 depicts a similar distribution of the nymphal density, which is generally lower in 2014 (Fig. 5). These lower densities are caused by extraordinary high temperatures in 2014. The difference of the mean temperatures listed in Table 2 is 1.6 °C, which is of the same order as the temperature increase predicted by climatologists for the next 100 years. It seems that higher temperatures at lower altitudes are responsible for the observed decrease of the I. ricinus nymphal densities, while an increase of the generally lower temperatures at higher altitudes, e.g. in the black forest, cause an increase of the nymphal densities (Fig. 5). The frequency distribution of the difference between the nymphal densities mapped for 2013 and 2014 are depicted in Fig. 6. According to this frequency distribution about 50 % of the study region depicts only minor changes in the nymphal density (below ± 25 nymphs/100 m2). For the other 50 % of the area of Baden-Württemberg considerably lower nymphal densities were estimated for 2014.Fig. 4

Bottom Line: Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m(2) in 2013.The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m(2) for 2013 and 104 nymphs/100 m(2) for 2014.The methodology introduced here may be applied to further tick species or extended to other study regions.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Reinhard-Baumeister-Platz 1, 76131, Karlsruhe, Germany. denise.boehnke@kit.edu.

ABSTRACT

Background: The study describes the estimation of the spatial distribution of questing nymphal tick densities by investigating Ixodes ricinus in Southwest Germany as an example. The production of high-resolution maps of questing tick densities is an important key to quantify the risk of tick-borne diseases. Previous I. ricinus maps were based on quantitative as well as semi-quantitative categorisations of the tick density observed at study sites with different vegetation types or indices, all compiled on local scales. Here, a quantitative approach on the landscape scale is introduced.

Methods: During 2 years, 2013 and 2014, host-seeking ticks were collected each month at 25 sampling sites by flagging an area of 100 square meters. All tick stages were identified to species level to select nymphal ticks of I. ricinus, which were used to develop and calibrate Poisson regression models. The environmental variables height above sea level, temperature, relative humidity, saturation deficit and land cover classification were used as explanatory variables.

Results: The number of flagged nymphal tick densities range from zero (mountain site) to more than 1,000 nymphs/100 m(2). Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m(2) in 2013. Generally, nymphal densities (maximum 374 nymphs/100 m(2)), explained variance (46 %) and prediction error (61 nymphs/100 m(2)) were lower in 2014. The models were used to compile high-resolution maps with 0.5 km(2) grid size for the study region of the German federal state Baden-Württemberg. The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m(2) for 2013 and 104 nymphs/100 m(2) for 2014.

Conclusions: The methodology introduced here may be applied to further tick species or extended to other study regions. Finally, the study is a first step towards the spatial estimation of tick-borne diseases in Central Europe.

No MeSH data available.


Related in: MedlinePlus