BackgroundThe 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.MethodsDuring 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.ResultsThe number of flagged nymphal tick densities range from zero (mountain site) to more than 1,000 nymphs/100 m2. Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m2 in 2013. Generally, nymphal densities (maximum 374 nymphs/100 m2), explained variance (46 %) and prediction error (61 nymphs/100 m2) were lower in 2014. The models were used to compile high-resolution maps with 0.5 km2 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 m2 for 2013 and 104 nymphs/100 m2 for 2014.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-015-0015-7) contains supplementary material, which is available to authorized users.
The castor bean tick Ixodes ricinus (L.) is the principal vector for a variety of viral, bacterial, and protozoan pathogens causing a growing public-health issue over the past decades. However, a national density map of I. ricinus is still missing. Here, I. ricinus nymphs in Germany were investigated by compiling a high-resolution map depicting the mean annually accumulated nymphal density, as observed by monthly flagging an area of 100 m Input data comprise ticks collected at 69 sampling sites. The model domain covers an area of about 357,000 km (regional scale). Two negative binomial regression models were fitted to the data to interpolate the tick densities to unsampled locations using bioclimatic variables and land cover, which were selected according to their significance by the Akaike information criterion (AIC). The default model was fitted to the complete dataset resulting in AIC = 842. An optimized model resulted in a significantly better value of AIC = 732. Tick densities are very low in urban (green) areas. Maximum annual densities up to 1,000 nymphs per 100 m are observed in broad-leaved forests. The tick maps were verified by leave-one-out cross-validation. Root mean square errors of RMSE = 137 and RMSE = 126 nymphs per 100 m were estimated for the two models, respectively. These errors are of the order of the interannual variation of the tick densities. The compilation of a high-resolution density map of unfed nymphal I. ricinus for Germany provides a novel, nationwide insight into the distribution of an important disease vector.
BackgroundEcological field research on the influence of meteorological parameters on a forest inhabiting species is confronted with the complex relations between measured data and the real conditions the species is exposed to. This study highlights this complexity for the example of Ixodes ricinus. This species lives mainly in forest habitats near the ground, but field research on impacts of meteorological conditions on population dynamics is often based on data from nearby official weather stations or occasional in situ measurements. In addition, studies use very different data approaches to analyze comparable research questions. This study is an extensive examination of the methodology used to analyze the impact of meteorological parameters on Ixodes ricinus and proposes a methodological approach that tackles the underlying complexity.MethodsOur specifically developed measurement concept was implemented at 25 forest study sites across Baden-Württemberg, Germany. Meteorological weather stations recorded data in situ and continuously between summer 2012 and autumn 2015, including relative humidity measures in the litter layer and different heights above it (50 cm, 2 m). Hourly averages of relative humidity were calculated and compared with data from the nearest official weather station.ResultsData measured directly in the forest can differ dramatically from conditions recorded at official weather stations. In general, data indicate a remarkable relative humidity decrease from inside to outside the forest and from ground to atmosphere. Relative humidity measured in the litter layer were, on average, 24% higher than the official data and were much more balanced, especially in summer.ConclusionsThe results illustrate the need for, and benefit of, continuous in situ measurements to grasp the complex relative humidity conditions in forests. Data from official weather stations do not accurately represent actual humidity conditions in forest stands and the explanatory power of short period and fragmentary in situ measurements is extremely limited. However, it is still an open question to what kind of meteorological data are necessary to answer specific questions in tick research. The comparison of research findings was hindered by the variety of information provided, which is why we propose details for future reporting.
Densely built-up areas are challenged by reduced biodiversity, high volumes of runoff water, reduced evaporation, and heat accumulation. Such phenomena are associated with imperviousness and low, unsustainable utilisation of land and exterior building surfaces. Local authorities have multiple objectives when (re-)developing future-proof districts. Hence, exploiting local potentials to mitigate adverse anthropogenic effects and managing the resource of urban land/surfaces have become key priorities. Accordingly, a five-level hierarchy for a land-sensitive urban development strategy was derived. To support the operationalisation of the hierarchy, we present the model Namares, a highly resolved GIS-based approach to enable spatially explicit identification and techno-economic and environmental assessment of intervention measures for advantageous utilisation of available surfaces per land parcel. It uses existing data and covers the management of economic, natural, and technical resources. Nine intervention measures are implemented to identify potentials, estimate investments and annual costs, and assess the appeal of existing subsidies. The approach was applied to a case study redevelopment area in a large city in Germany. The results provide spatially explicit information on greening potentials, estimated investments, subsidy demand, and other quantified benefits. The case study results show the limited potential for additional unsealing of impervious surfaces by transforming ca. 10% of sealed ground surface area into new urban gardens. At the same time, up to 47% of roof and 30% of facade surfaces could be utilised for greening and energy harvesting. The approach enables a comprehensive localisation and quantitative assessment of intervention potentials to enhance decision support in land-sensitive urban development strategies.
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