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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

Study area and explanatory variables used to calculate nymphal densities. Study area Baden-Württemberg located in the southwest of Germany (a), height above sea level in meters (b), CORINE land cover classification (c), temperature in °C (d), relative humidity in % (e) and saturation deficit in hPa (f).
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Fig2: Study area and explanatory variables used to calculate nymphal densities. Study area Baden-Württemberg located in the southwest of Germany (a), height above sea level in meters (b), CORINE land cover classification (c), temperature in °C (d), relative humidity in % (e) and saturation deficit in hPa (f).

Mentions: The model domain covers the entire region of the German federal state Baden-Württemberg with an area of 35,750 km2. It is located in the southwest of Germany (Fig. 2a) and has a wide ecological variability with low lands and mountains up to 1,500 m height above sea level (Fig. 2b). The historical natural coverage was woodland with European beech (Fagus sylvatica) as the main tree species. Today the natural landscape has been widely replaced by areas of anthropogenic utilization. The main tree species is the economically important European spruce (Picea abies) with 38 % followed by European beech with 21 % of the total forest area. Following the well-known Köppen-Geiger climate classification [18], the climate conditions in Baden-Württemberg as well as in the entire region of Germany were characterized by Cfb climate (C = warm temperate climate, f = fully humid, b = warm summers). Even under climate change conditions the Cfb climate in Baden-Württemberg will be preserved [19]. Total annual precipitation varies between 600 and 2,000 mm.Fig. 2


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)

Study area and explanatory variables used to calculate nymphal densities. Study area Baden-Württemberg located in the southwest of Germany (a), height above sea level in meters (b), CORINE land cover classification (c), temperature in °C (d), relative humidity in % (e) and saturation deficit in hPa (f).
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig2: Study area and explanatory variables used to calculate nymphal densities. Study area Baden-Württemberg located in the southwest of Germany (a), height above sea level in meters (b), CORINE land cover classification (c), temperature in °C (d), relative humidity in % (e) and saturation deficit in hPa (f).
Mentions: The model domain covers the entire region of the German federal state Baden-Württemberg with an area of 35,750 km2. It is located in the southwest of Germany (Fig. 2a) and has a wide ecological variability with low lands and mountains up to 1,500 m height above sea level (Fig. 2b). The historical natural coverage was woodland with European beech (Fagus sylvatica) as the main tree species. Today the natural landscape has been widely replaced by areas of anthropogenic utilization. The main tree species is the economically important European spruce (Picea abies) with 38 % followed by European beech with 21 % of the total forest area. Following the well-known Köppen-Geiger climate classification [18], the climate conditions in Baden-Württemberg as well as in the entire region of Germany were characterized by Cfb climate (C = warm temperate climate, f = fully humid, b = warm summers). Even under climate change conditions the Cfb climate in Baden-Württemberg will be preserved [19]. Total annual precipitation varies between 600 and 2,000 mm.Fig. 2

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