Abundance and Seasonal Activity of Questing Ixodes ricinus Ticks in their Natural Habitats in Southern Germany in 2011 Author(s): Michaela Schulz, Monia Mahling and Kurt Pfister Source: Journal of Vector Ecology, 39(1):56-65. 2014. Published By: Society for Vector Ecology URL: http://www.bioone.org/doi/full/10.1111/j.1948-7134.2014.12070.x
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June 2014
Abundance and seasonal activity of questing Ixodes ricinus ticks in their natural habitats in southern Germany in 2011
Michaela Schulz¹, Monia Mahling², and Kurt Pfister1
¹Comparative Tropical Medicine and Parasitology, Ludwig-Maximilians-Universität München, Leopoldstr. 5, 80752 Munich, Germany, [email protected] ²Statistical Consulting Unit, Ludwig-Maximilians-Universität München, Akademiestraße 1, 80799 Munich, Germany Received 19 July 2013; Accepted 11 December 2013 ABSTRACT: Questing ticks were sampled monthly over a period of 11 months from February, 2011 to December, 2011 at 13 sites in southern Germany using the flagging method. The ticks were identified to species, gender, and stadium. Although both I. ricinus and D. reticulatus were sampled, this study concentrated on I. ricinus, since it was the most abundant tick to be found. Additional weather data (air and soil temperature, relative air humidity, precipitation, sunshine duration) were recorded on each sampling site and the local vegetation described. A total of 14, 394 ticks was collected (7,862 larvae, 5,568 nymphs, 964 adults) and their activity was recorded in order to determine the seasonal activity pattern over different periods of the year. In contrast to the widely accepted pattern of a bimodal seasonal activity in moderate areas with a dominant peak in spring and a minor peak in autumn, a unimodal activity pattern was found for all development stages on six of the 12 sampling sites. Tick abundance was compared to weather variables. Tick host-seeking activity was found to be significantly dependent on the temperature at ground level, precipitation, and sunshine duration as well as relative air humidity. Adult ticks showed a positive correlation with the duration of sunshine, whereas nymphs were mostly unaffected by this phenomenon. Journal of Vector Ecology 39 (1): 56-65. 2014. Keyword Index: Ixodes ricinus, seasonal activity, climate, Germany.
INTRODUCTION Changing environmental and climatic conditions in western Europe are believed to have led to changes not only in the geographic distribution of ticks but also in their seasonal questing activity throughout the year (Kupča 2009, Lindgren et al. 2000, Pérez et al. 2012). These changes are important for understanding the abundance and distribution of this important vector and hence the distribution of vector-borne diseases across Germany. So far there are only a few very fragmented and focally limited studies on the spectrum and the host-seeking activity of ticks in the southern parts of Germany (Immler 1973, Liebisch and Rahman 1976, Wilske et al. 1987, Zahler et al. 2000, Süss et al. 2004). They show that rising temperatures, especially in winter, provide benefits for ticks, providing them with a longer period in which they can quest and reproduce. To provide a better insight into the current situation, the following study was designed to evaluate the spectrum and seasonal activity of ticks in southern Germany and analyze the relationship between climatic factors and the abundance of I. ricinus, the predominant tick of the area (Schulz and Pfister 2012). MATERIALS AND METHODS Sampling sites A total of 13 different locations in three federal states covering southern Germany was sampled (Figure 1). The selection of the locations was based on the previous descriptions of tick occurrence (Immler 1973, Liebisch and Rahman 1976, Wilske et al. 1987,
Zahler et al. 2000, Süss et al. 2004). The 100 m2 sampling areas at these locations were selected after specifications provided by the EDEN-Project (http://www.eden-fp6project.net/), considering vegetation structures that were likely to harbor ticks, and testsamplings before the experimental sampling began. The locations and climatic conditions of sampling sites are shown in Table 1. Sampling of ticks All locations were sampled monthly from February, 2011 to December, 2011 on the same day each month. Although planned, no sampling took place in January because of the snow cover in all the locations. Although several other methods for collecting ticks have been described in the past (Ginsberg and Ewing 1989, Gherman et al. 2012), the flagging method according to Gray (1985) is an effective and economical way for gathering large numbers of ticks and determining their seasonal activity patterns. Furthermore it was also the method of choice of the EDEN project (http://www.eden-fp6project.net/) that our institute is integrated with. However the technique only collects ticks that are questing in the upper parts of the ground vegetation such as I. ricinus. Ticks caught this way represent only a small part of the total population, since ticks periodically return to lower vegetation levels in order to regulate their water balance (Needham and Teel 1991, Perret et al. 2000, Schulze et al. 2001). A standardized 1 m² flag consisting of a rough-structured cotton fabric was drawn across the lower vegetation over a surface of a 100 m²/sampling area and checked for ticks regularly in order to avoid a loss of ticks. The ticks were collected from the cloth and stored in 15 ml tubes filled with 70% ethanol. To obtain representative samples that could be compared to each other, certain parameters were defined as follows: Sampling
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Table 1. Number of ticks and climate dates according to the vegetation categories.
Vegetation category
Deciduous forest
Conifer forest
Mixed forest
Riparian forest
Clearing
Sampling location
Number of larvae
Number of nymphs
Number of adults
Total number of ticks
Average temperature (° C)
Average relative humidity (%)
Mooswald 47° 59’ 3.84” N 7° 46’ 15.96” E, 237 m above sea level
137
315
111
563
12.6
79.1
Neckarmuehlbach 49° 16’ 42.215” N 9° 7’ 39.799” E, 204 m a.s.l.
630
377
66
1,073
11.1
79.8
Unterfoehring 48° 12’ 12.496” N 11° 38’ 44.988” E, 508 m a.s.l.
2
67
9
78
13.1
64.8
Dambach 49° 0’ 18.994” N 10° 20’ 21.44” E, 463 m a.s.l.
403
273
62
738
13.1
65.6
Schalding 48° 36’ 34.254” N 13° 21’ 48.499” E, 379 m a.s.l.
125
325
87
537
11.9
67.2
Sinzing 48° 59’ 16.667” N 12° 1’ 9.977” E, 418 m a.s.l.
475
265
18
758
11.4
74.7
Ungelstetten 49° 24’ 34.758” N 11° 18’ 15.721” E, 400 m a.s.l.
38
107
43
188
11.6
76.6
Heiligenwald 49° 21’ 4.176” N 7° 5’ 31.027” E, 335 m a.s.l.
3,895
963
151
5,009
13.1
70.8
Moenchberg 48° 35’ 15.457” N 8° 55’ 4.93” E, 546 m a.s.l.
453
651
130
1,234
9.6
73.9
Elchingen 48° 26’ 23.622” N 10° 5’ 48.109” E, 461 m a.s.l.
309
641
89
1,039
11.3
71.6
Meissenheim 48° 24’ 29.16” N 7° 45’ 22.32” E, 147 m a.s.l.
1,014
844
138
1,996
14.2
70
Bostalsee 49° 33’ 23.098” N 7° 3’ 53.737” E, 404 m a.s.l.
64
318
33
415
15.1
66.7
Heidenheim 49° 1’ 50.956” N 10° 42’ 36.425” E, 527 m a.s.l.
444
295
27
766
8.5
74.1
was always performed at the same time of the day (in the course of the morning between 09:00 and 12:00), by the same person and took place independent of atmospheric conditions. To cover as many aspects of a sampling site as possible, both sunny and shady areas were sampled equally if they were accessible. Each location was sampled until the 100 m² were completed, independent from the time it took to collect the ticks. All persons who were involved in tick collections had the appropriate personal protection equipment to prevent them from exposure to tick bites. For technical and financial reasons, the study could only be performed over the period of one year, and consequently, no statement can be
made about long-term population dynamics. Tick identification Species, gender, and stadium were identified with taxonomic keys (Arthur 1963, Hillyard 1996). The ticks were preserved in 70% ethanol for further studies on tick-borne pathogens. Flora and fauna The sampling locations were chosen on the basis of suitable biotope structures. Particular attention was paid to benefitting vegetation for ticks, as for example, mixed forest with a distinctive
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foliage. Occasionally, locations with a less benefitting vegetation were also included in the study. The habitat types of all 13 sampling sites were categorized and the local flora was defined using a plant identification key (Licht 2011). The sampling locations could be divided into the following categories: deciduous forests (Mooswald, Nackarmuehlbach, Unterfoehring), conifer forests (Ungelstetten, Sinzing, Dambach, Schalding), mixed forests (Heiligenwald, Moenchberg), riparian forests (Meissenheim, Elchingen), and clearings (Bostalsee, Heidenheim) (Figure 1). The deciduous forests consisted mainly of European Beech (Fagus sylvaticus), European Hornbeam (Carpinus betulus), English Oak (Quercus robur), and Sycamore Maple (Acer pseudoplatanus). The conifer forests were composed of Norway Spruce (Picea abies) and Scots Pine (Pinus sylvestris). Mixed forests featured all of the above and, in addition, European Silver Fir (Abies alba). The riparian forests consisted of European Ash (Fraxinus excelsior), Field Elm (Ulmus minor), and miscellaneous plants native to wetlands. An overview of local wildlife and host animals was achieved by data from the local forestry commission offices and hunters. The main hosts in nearly all locations included large and mediumsized mammals such as roe deer (Capreolus capreolus), boars (Sus scrofa), and foxes (Vulpes vulpes). However, a lot of smaller mammals such as stoats (Mustela erminea), badgers (Meles meles), stone martens (Martes foina), brown hares (Lepus europaeus), and European rabbits (Oryctolagus cuniculus) were found, along with various rodents. No quantitative aspects regarding the population sizes are registered or available for the given areas.
June 2014
Weather variables In order to evaluate the potential influence of climatic conditions, weather variables were registered as follows: air temperature and relative air humidity were recorded during every sampling tour and at each location using a thermo-hygrometer (P330, Carl Roth GmbH Karlsruhe, Germany). Data were recorded before the start of each sampling at ground level as well as at 1 m height to cover the mean questing heights of ticks (Adams et al. 2003, Mejlon and Jaenson 1997, Oorebeek et al. 2009). Soil temperature was measured with an inserting thermometer. Additional weather data (daily values for sunshine duration, precipitation, relative air humidity, and air temperature) was provided from 12 nearby meteorological stations of Germany’s National Meteorological Service (Deutscher Wetterdienst, DWD) and included in the statistical evaluation. For statistical analysis, the mean values of these variables three days before sampling were also calculated. Weather data three days before sampling was also taken into account since it is believed to have a direct influence on the questing of ticks (Schulz and Pfister 2012). For example, if it rained for three days this would have a noticeable effect on the number of ticks found on the fourth day. Statistical analysis The total number of ticks for each location and each month was counted, as well as the number of the different developement stages. The ticks were divided into adults, nymphs and larvae. For statistical analysis these numbers were compared to the gathered weather variables with the help of scatterplots and a Poisson regression analysis.
Figure 1. Map of southern Germany displaying distribution of ticks on sampling sites and total tick numbers. Symbols indicate the sampling sites and their respective vegetational structure. Numbers outside of circle diagrams indicate the total number of ticks found at that location.
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For the analysis of the number of adults, nymphs, and larvae, a generalized additive mixed model with a Poisson distribution and log link were used. Z-tests were employed to test if the coefficents of the generalized additive mixed models were significantly different from 0. The model comprises a random intercept for the site and therefore addresses the effect of repeated measurements in the same site at different examinations. In order to obtain valid p-values, no model selection was performed (Hurvich and Tsai 1990). Instead, all collected variables were included in the evaluation. As the assumption of a linear effect of time (month) would have been too restrictive, smooth nonlinear terms which can be fitted by using penalized splines were added to allow for flexible modelling. In the models for the number of adult ticks and nymphs, smooth terms were also included for all other covariates. P-values < 0.05 were regarded as statistically significant. It was not possible to fit such a complex model to the data on the number of larvae, possibly due to several extreme observations. For statistical analysis, R version 2.13.0 (R Development Core Team: R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing) was used. Generalized additive mixed models were fitted by using the R package “amer” (CRAN-Package amer). RESULTS Tick numbers From February, 2011 to December, 2011 a total of 14,394 ticks (7,862 larvae, 5,568 nymphs, 455 female ticks, and 509 male ticks) was collected at 13 locations. Of these, 14,383 ticks were Ixodes ricinus, while 11 ticks were adult Dermacentor reticulatus. Among the different collection sites, considerable differences in the distribution of the developmental stages of the ticks were observed (Figure 1). The occurrence of larvae varied between sites from 15.4% to 77.8%, whereas the number of nymphs ranged from 19.2% to 76.6% and adults had a range from 2.4% up to 22.9% in relation to the total number of collected ticks. Furthermore considerable variances were present in the total number of ticks in relation to the different locations. For example, the most ticks were found in Heiligenwald (5,009), while the lowest number of ticks were present in Unterfoehring (78). The data from Unterfoehring, however, were excluded from the listings above and below, since the extreme low number of ticks made statistical evaluation impossible. Tick activity Tick activity was observed during the whole year, from February to December. However, in the latter month only one tick could be collected (Table 2). Questing ticks could repeatedly be caught at a locally measured air temperature of 1.1° C, but below that temperature ticks were not observed or collected. In contrast, a decrease in tick numbers in July and August, the hottest months of the year, with temperatures reaching up to 25.9° C, could only be observed at six locations. A unimodal activity pattern occurred more often than a bimodal pattern for all developmental stages at six out of 12 sampling sites. Larvae were mainly observed from May to August and showed an activity peak in July, nymphs were observed from March to August and had their peak in late April and early May, whereas adults were mainly found between March
59
and July and displayed an activity peak in May (Figure 2). Temperature Minimum air temperature during sampling was reached in December in seven out of 12 sampling locations, ranging from -3.3° to 4.1° C with an average air temperature of 0.6° C. The other four locations had an average minimum of 2.9° C in November with air temperatures ranging from 0.5° C to 6.2° C. One single location had a minimum air temperature of 8.1° C in November. Maximum air temperature was observed in August with an average of 21.8° C at seven out of 12 sampling locations, while the other five locations had their maximum temperatures in June with an average of 21.9° C. Statistical analyses The relative abundance of the collected ticks was compared to the gathered weather variables and statistically analyzed. For interpretation of the statistical data, the estimated Poisson regression coefficient and its exponential function were used. If the predictor variable changes for one unit and all other predictor variables are kept constant, the dependent variable (the expected tick count) changes multiplicatively by the exponential factor of the respective regression coefficient. These values therefore show the expected count of ticks in relation to all relevant weather variables. In the Poisson regression, tick host-seeking activity was found to be significantly dependent on average sunshine duration over the last three days before sampling (p=0.0434 for adults, p=0.040954 for nymphs, and p=0.0212 for larvae) and average precipitation over the last three days before sampling (p=0.027065 for nymphs), as well as average relative air humidity over the last Table 2. Total number of ticks and percentage distribution for each month. Month
Larvae
Nymphs
Adults
Total
February
3 (3.3 %)
69 (75.8 %)
19 (20.9 %)
91
March
1 (0.2 %)
464 (84.5 %)
84 (15.3 %)
549
April
101 (6 %)
1,412 (83.3 %)
183 (10.8 %)
1,696
May
1,606 (48.3 %)
1,424 (42.8 %)
296 (8.9 %)
3,326
June
1,987 (63.1 %)
1,013 (32.2 %)
150 (4.8 %)
3,150
July
1,915 (75 %)
543 (21.3 %)
94 (3.7 %)
2,552
1,805 (81.9 %)
341 (15.5 %)
59 (2.7 %)
2,205
September
389 (72.6 %)
115 (21.5 %)
32 (6 %)
536
October
46 (18.2 %)
173 (68.4 %)
34 (13.4 %)
253
November
9 (25.7 %)
13 (37.1 %)
13 (37.1 %)
35
December
0 (0 %)
1 (100 %)
0 (0 %)
1
7,862
5,568
964
14,394
August
Total
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June 2014
Figure 2. Boxplots of Ixodes ricinus adults (A), nymphs (B), and larvae (C) per month showing the statistical distribution of the different developmental stages each month. three days before sampling (p=0.017236 for nymphs) (Table 3). Additive Poisson regression models allow the modelling of the effects of continuous covariates as smooth functions, which have a more flexible form than the linear trend provided by a simple linear model. However, p-values can only be obtained for the linear part of the functions. The bigger the variance of the random effects in the model output, the further away is the fitted function from a straight line. The models are displayed in the following graphs (Figures 3 and 4). The model for average sunshine duration (Figure 3C) shows that the expected count of adult ticks decreases when sunshine duration increases. In contrast, the expected count of nymphs remains quite stable, forming a waved horizontal line with a variance of 4.02054 (Figure 4C), and showing that nymphs remain more or less unaffected by the average sunshine duration. As shown in Figure 3E (a model term that has a variance of only 0.00411 and therefore is relatively close to a straight line), the expected count of adult ticks increases with increasing average air humidity, forming a flat U-shape. Nymphs also have a relatively straight line sloping gently with a variance of 0.01028, but in contrast, their expected count drops with increasing average air humidity (Figure 4E). Figure 3F shows the model for precipitation for adults, and Figure 4F shows the model for precipitation for nymphs. Both tick numbers decrease with increasing precipitation, except for some isolated data scattered at the upper range, but only nymphs showed a significant dependency in the statistical results with a variance of 0.027065. The final Poisson regression model for the larvae, however, had to be interpreted cautiously, since there were some extreme outliers as well as many zero values in the data, making a final interpretation quite difficult. DISCUSSION The abundance of questing ixodid ticks varied considerably between the different sampling sites (Figure 1). Locations with fewer tick numbers, such as Unterfoehring and Ungelstetten, showed differences in their vegetational structure compared to the other sampling spots, as there were few or no leaves covering the ground and a very thin and monotone ground vegetation incapable of retaining much humidity, as well as a correspondingly low tick abundance, which is similar to previously published results (Daniel 1993). This illustrates the importance that the local
vegetation plays in maintaining a suitable climatic environment and shelter for ticks, which are very dependent on humidity in their microhabitat (Needham and Teel 1991, Perret et al. 2000). There were obvious differences between the abundance of different developmental stages at each sampling location. Heiligenwald had the highest number of larvae (3,895, 77.8% of the total number of collected ticks), while Bostalsee (64) and Elchingen (309) showed relatively low numbers of larvae (15.4% and 29.7% of the total number of collected ticks). Larvae are more likely to be overlooked especially in locations with high and/ or dense vegetation (Ginsberg and Ewing 1989, Randolph et al. 2000), as they tend to stay in lower vegetation which provides more humidity and shadow. This was confirmed in the two locations mentioned above (Bostalsee and Elchingen) and was also demonstrated by Oorebeek et al. (2009) with larvae of I. hirsti. However, the distribution of ticks in one location can vary due to fluctuations in the abundance of host animals or human utilization. An irregular, tesselated distribution is assumed for most areas, which results in unequally populated patches of land and the possibility of missing these spots (Daniel 1993). Questing ticks could be collected up to an air temperature at ground level as low as 1.1° C. Similar tick activity at low temperatures between -0.6 C and 5° C was observed in earlier studies (Sixl and Nosek 1971, Schulze et al. 2001). In this study a higher abundance of ticks was found at higher temperatures and longer sunshine duration. Precipitation correlated negatively with the abundance of all developmental stages. Humidity was less closely related to the abundance of ticks compared with the other parameters, yet it was significantly related to the appearance of nymphs and showed a positive correlation most of the time. It has been shown that humidity, although having a major influence on the activity of ticks, is not always directly related with tick numbers and varies according to the region and habitat as well as the developmental stage of the ticks (MacLeod 1936, Sixl and Nosek 1971, Gray et al. 1978, Daniels et al. 1989, Sonenshine 1993, Mejlon and Jaenson 1997, Schulze et al. 2001). Previous studies suggested that climate and vegetation are two extremely important factors in the seasonal questing activity of ticks, which are very susceptible to dehydration. When suffering from dehydration, questing ticks tend to move back towards ground level, where relative humidity is higher than at questing height (Lees 1946, Lees and Milne 1951, Randolph and
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Figure 3. Graphical depiction of Poisson regression showing the effect of the smoothly modelled covariates on the expected value for the number of adult ticks. X-axis: weather variable (black bars indicate observed values in the evaluated datasets), y-axis: function of weather variable as deviation from constant (on log scale).
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Figure 4. Graphical depiction of Poisson regression showing the effect of the smoothly modelled covariates on the expected value for the number of nymphs. X-axis: weather variable (black bars indicate observed values in the evaluated datasets), y-axis: function of weather variable as deviation from constant (log scale).
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Table 3. Poisson regression among variables of Ixodes ricinus adults, nymphs and larvae. P = p-value, Est. = estimated Poisson regression coefficient, Exp. = exponential function of Est., significance codes: ‘***’ (0 - 0.001) ‘**’ (0.001 - 0.01) ‘*’ (0.01 - 0.05) ‘.’ (0.05 - 0.1) ‘ ‘ (0.1 – 1). Variable Air temperature on ground level Average air temperature 3 days before sampling Average sunshine duration 3 days before sampling
Adults p
Est.
Nymphs Exp.
p
Est.
Larvae Exp.
p
Est.
Exp.
0.8238
-0.005039 0.9949737
0.6110
0.021243
1.0214703 < 2e-16 *** 0.086476
0.3267
0.039594
0.5268
0.025613
1.0259442 < 2e-16 *** -0.195034 0.8228068
1.1199163
1.0403878
0.0434 *
-0.115375 0.8910318 0.040954 *
0.113254
Relative air humidity on ground level
0.0958 .
-0.014068 0.9860308
-0.007813 0.9922170 < 2e-16 *** -0.050139 0.9510973
Relative air humidity 3 days before sampling
0.9818
0.002988
1.0029923 0.017236 * -0.251456 0.7776680 5.46e-08 *** -0.245856 0.7820352
Average precipitation 3 days before sampling
0.8447
0.006671
1.0066935 0.027065 * -0.120998 0.8860358 < 2e-16 *** 0.095533
0.3940
Storey 1999). Perret et al. (2000) showed a relationship between saturation deficit and tick density, as tick questing periods are shortened with high saturation deficits. It can be assumed that the vegetation in the immediate neighborhood of ticks plays a vital role in providing ideal conditions by retaining humidity, since ticks require at least 85% of relative air humidity to be able to survive their off-host-periods (Needham and Teel 1991). In accordance with this assumption, very low humidity was measured at Bostalsee, Schalding, and Unterfoehring, which stood out because of their low tick numbers. In the present study, six out of twelve sampling sites showed an unimodal activity pattern for all development stages, characterized by one single activity peak in early March, April, and May. The other six sampling locations showed a bimodal activity pattern with a second smaller activity peak for nymphs and larvae in autumn, while the adults didn’t have an apparent second peak. While generally a bimodal activity pattern with a dominant peak in spring and a minor peak in autumn is described for I. ricinus in Central Europe (Aeschlimann 1972, Belozerov 1982, Gray 1991, 2002), the activity peaks can differ from year to year. Decreased activity in late summer results in a bimodal pattern for subadult ticks with one peak in spring and a second peak in autumn the following year. Randolph et al. (2002) showed that an early onset of tick activity in spring can lead to an increased development speed and therefore to activity peaks in autumn, as could be seen in Mooswald and Elchingen. Unimodal activity patterns have repeatedly been described in the past, but mostly in countries in the Mediterranean area (Moreno and Estrada-Peña 1997). But lately there seems to be a change of this geographical border. Several studies from Germany and Switzerland also showed deviations from the formerly typical bimodal pattern (Kupča 2009, Pérez et al. 2012). It is assumed
0.0212 *
1.0903252
-0.029078 0.9713408
1.1002448
that changes in the climatic conditions (warmer temperatures in summer as well as in winter and an increasing humidity) support the living conditions of I. ricinus (Randolph et al. 2000). This extends the period in which ticks can quest and reproduce, which in turn is an important factor when evaluating the risk of vectorborne diseases throughout the year. All sampling locations with a unimodal activity pattern showed higher precipitation compared to the ones with a bimodal activity pattern. The total annual precipitation was >600 mm at all locations. The lowest precipitation was measured at Heidenheim with 618.9 mm, and the highest precipitation was found in Unterfoehring with 972.3 mm. The average precipitation of all locations was 733 mm, thus being lower than the nationwide annual average precipitation of 789 mm (DWD 2012). This corresponds with the fact that higher altitudes combined with moderate summers and an increased precipitation promote unimodal activity patterns (Moreno and Estrada- Peña 1997). Most locations that expressed an unimodal pattern had very dense vegetation. Mönchberg and Heiligenwald are both thick mixed forests covered with a variety of different trees and bushes. The location in Schalding consists of a little path that runs through the forest and is overgrown in many places. Sheltered habitats with dense vegetation and shady areas prevent a decrease in tick abundance especially in the hot summer months in contrast to sun-exposed areas in open terrain (Jensen and Kaufmann 2003). This results in no distinct separation between a spring and an autumn peak. Similar studies in Southern Germany over the last decade also showed unimodal patterns (Kupča 2009). This study emphasizes that climatic factors, especially ground temperature, relative humidity, and sunshine duration in the immediate habitat of ticks, play a vital role in the dynamics of tick populations and their activity. However, it was not easy to quantify
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which factors had the most dominant effect on the seasonal questing activity of ticks. It is most likely related to multiple biotic and abiotic parameters simultaneously. Of special interest is that a unimodal activity pattern was found at six of the 12 sampling sites, which corresponds to previous studies in Central Europe and appears to be an increasing trend. Acknowledgments We thank Merial Ltd. Lyon France and Merial GmbH Hallbergmoos for partially financing this study. We also thank Prof. Milan Daniel for sharing his opinion and remarks on this article. We are indebted to Prof. P. H. Holmes, University of Glasgow for his critical comments on the manuscript and the language corrections. This study was also partially funded by EU grant FP7-261504 EDENext and is catalogued by the EDENext Steering Committee as EDENext 200 (http://www.edenext.eu). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. REFERENCES CITED Adams, D.R., B.E. Anderson, C.T. Ammirati, and K.F. Helm. 2003. Identification and diseases of common U.S. ticks. Internet J. Dermatol. 2: DOI: 10.5580/1189. Aeschlimann, A. 1972. Ixodes ricinus, Linné, 1758 (Ixodoidea: Ixodidae). Essai préliminaire de synthèse sur la biologie de cette espèce en Suisse. Acta Trop. 29: 321–340. Arthur, D.R. 1963. British Ticks. Butterworths, London. Belozerov, V.N. 1982. Diapause and biological rhythms in ticks. In: F.D. Obenchain (ed.), Physiology of Ticks. pp. 469-500. Pergamon Press, Oxford. Daniel, M. 1993. Influence of the microclimate on the vertical distribution of the tick Ixodes ricinus (L.) in central Europe. Acarologia 34: 105–113. Daniels, T.J., D. Fish, and R.C. Falco. 1989. Seasonal activity and survival of adult Ixodes dammini (Acari: Ixodidae) in southern New York State. J. Med. Entomol. 26: 610-614. Gherman, C.M., A.D. Mihalca, M.O. Dumitrache, A. Gyorke, I. Oroian, M. Sandor, and V. Cozma. 2012. CO2 flagging - an improved method for the collection of questing ticks. Parasit. Vectors 5: 125. Ginsberg, H.S. and C.P. Ewing. 1989. Comparison of flagging, walking, trapping, and collecting from hosts as sampling methods for northern deer ticks, Ixodes dammini, and lonestar ticks, Amblyomma americanum (Acari: Ixodidae). Exp. Appl. Acarol. 7: 313–322. Gray, J.S. 1985. Studies on the larval activity of the tick Ixodes ricinus L. in Co. Wicklow, Ireland. Exp. Appl. Acarol. 1: 307316. Gray, J.S. 1991. The development and seasonal activity of the tick Ixodes ricinus: a vector of lyme borreliosis. Rev. Med. Vet. Entomol. 79: 323–333. Gray, J.S. 2002. Biology of Ixodes species ticks in relation to tickborne zoonoses. Wiener Klinische Wochenschrift. 114: 473– 478. Gray, J.S., T. Turley, and K.L. Strickland. 1978. Studies on the
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ecology of sheep tick, Ixodes ricinus, in Co. Wicklow, Ireland. Irish Vet. J. 32: 25-34. Hillyard, P.D. 1996. Ticks of North-West Europe. The Dorset Press, Dorchester. Hurvich, C.M. and C.L. Tsai. 1990. The impact of model selection on inference in linear regression. Am. Statist. 44: 214-217. Immler, R. 1973. Untersuchungen zur Biologie und Ökologie der Zecke Dermacentor reticulatus. Bull. Soc. Entomol. Suisse. 46. Jensen, P.M. and U. Kaufmann. 2003. Seasonal and diel activity of Ixodes ricinus (Acari: Ixodidae) subpopulations in Denmark. Aspects of size, physiological age, and malate dehydrogenase genotype in a forest site without any undergrowth. Exp. Appl. Acarol. 30: 289–303. Kupča, A.M. 2009. Ixodes ricinus (Ixodidae): Saisonale Aktivität und natürliche Infektionen mit dem FSME-Virus an ausgewählten Standorten in Bayern. DVM thesis. LudwigMaximilians-University Munich, Tierärztliche Fakultät. Lees, A.D. 1946. The water balance in Ixodes ricinus L. and certain other species of ticks. Parasitol. 37: 1–20. Lees, A.D. and A. Milne. 1951. The seasonal and diurnal activities of individual sheep ticks (Ixodes ricinus L.). Parasitology 41: 189–208. Licht, W. 2011. Einführung in die Pflanzenbestimmung nach vegetativen Merkmalen. Quelle and Meyer, Wiebelsheim. Liebisch, A. and M.S. Rahman. 1976. Zum Vorkommen und zur vektoriellen Bedeutung der Zecken Dermacentor marginatus (Sulzer, 1776) und Dermacentor reticulatus (Fabricius, 1794) in Deutschland. Tropenmed. Parasitol. 27: 393-404. Lindgren, E., L. Tälleklint, and T. Polfeldt. 2000. Impact of climatic change on the northern distribution limit and population density of the disease-transmitting European tick Ixodes ricinus. Envir. Hlth. Perspect. 108: 119-123. MacLeod, J. 1936. Ixodes ricinus in relation to its physical environment. IV. An analysis of the ecological complexes controlling distribution and activities. Parasitology 28: 295– 319. Mejlon, H.A. and T.G.T. Jaenson. 1997. Questing behaviour of Ixodes ricinus ticks (Acari: Ixodidae). Exp. Appl. Acarol. 21: 747–754. Moreno, J.A., and A. Estrada-Peña. 1997. Prevalence and seasonal activity of Ixodes ricinus (Acari: Ixodidae) on domestic ruminants of the Basque country, Spain. Exp. Appl. Acarol. 21: 41-48. Needham, G.R. and P.D. Teel. 1991. Off-host physiological ecology of Ixodid ticks. Annu. Rev. Entomol. 36: 659–681. Oorebeek, M., R. Sharrad, and S. Kleindorfer. 2009. What attracts larval Ixodes hirsti (Acari: Ixodidae) to their host? Parasitol. Res. 104: 623–628. Pérez, D., Y. Kneubühler, O. Rais, and L. Gern. 2012. Seasonality of Ixodes ricinus ticks on vegetation and on rodents and Borrelia burgdorferi sensu lato genospecies diversity in two Lyme borreliosis-endemic areas in switzerland. Vector Borne Zoonot. Dis. 12: 633-644. Perret, J.L., E. Guigoz, O. Rais, and L. Gern. 2000. Influence of saturation deficit and temperature on Ixodes ricinus tick questing activity in a Lyme borreliosis-endemic area (Switzerland). Parasitol. Res. 86: 554-557. Randolph, S.E. and K. Storey. 1999. Impact of microclimate on
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immature tick-rodent host interactions (Acari: Ixodidae): implications for parasite transmission. J. Med. Entomol. 36: 741-748. Randolph, S.E., R.M. Green, M.F. Peacey, and D.J. Rogers. 2000. Seasonal synchrony: the key to tick-borne encephalitis foci identified by satellite data. Parasitology 121: 15–23. Randolph, S.E., R.M. Green, A.N. Hoodless, and M.F. Peacey. 2002. An empirical quantitative framework for the seasonal population dynamics of the tick Ixodes ricinus. Int. J. Parasitol. 32: 979-989. Schulz, M. and K. Pfister. 2012. Untersuchungen zur saisonalen Populationsdynamik von Zecken in Süddeutschland. In: Tagung der Fachgruppe Parasitologie und parasitäre Krankheiten der DVG, 2.-4.Juli 2012 in Hannover. Tierärztliche Praxis Kleintiere. 4: 29-32. Schulze, T.L., R.A. Jordan, and R.W. Hung. 2001. Effects of selected meteorological factors on diurnal questing of Ixodes scapularis and Amblyomma americanum (Acari: Ixodidae). J. Med. Entomol. 38: 318-324.
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Sixl, W. and J. Nosek. 1971. Einfluss von Temperatur und Feuchtigkeit auf das Verhalten von Ixodes ricinus, Dermacentor marginatus und Haemaphysalis inermis. Arch. Sci. Genéve 24: 97-109. Sonenshine, D.E. 1993. Biology of Ticks Vol 2. Oxford University Press, New York. Süss, J., C. Schrader, U. Falk, and N. Wohanka. 2004. Tick-borne encephalitis (TBE) in Germany – epidemiological data, development of risk areas and virus prevalence in fieldcollected ticks and in ticks removed from humans. Int. J. Med. Microbiol. 293(Suppl. 37): 69–79. Wilske, B., R. Steinhuber, H. Bergmeister, V. Fingerle, G. Schierz, V. Preac-Mursic, E. Vanek, and B. Lorbeer. 1987. LymeBorreliose in Süddeutschland. Epidemiologische Daten zum Auftreten von Erkrankungsfällen sowie zur Durchseuchung von Zecken (Ixodes ricinus) mit Borrelia burgdorferi. Deutsche Medizin. Wochenschr. 112: 1730–1736. Zahler, M., F. Loster, C. Merkle, H. Rinder, and R. Gothe. 2000. Risk of infection for dogs in Regensburg - a new endemic focus of Babesia canis and Dermacentor reticulatus in Germany. Tierärztliche Praxis. 28(K): 395-398.
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Abundance and seasonal activity of questing Ixodes ricinus ticks in their natural habitats in southern Germany in 2011
Michaela Schulz¹, Monia Mahling², and Kurt Pfister1
¹Comparative Tropical Medicine and Parasitology, Ludwig-Maximilians-Universität München, Leopoldstr. 5, 80752 Munich, Germany, [email protected] ²Statistical Consulting Unit, Ludwig-Maximilians-Universität München, Akademiestraße 1, 80799 Munich, Germany Received 19 July 2013; Accepted 11 December 2013 ABSTRACT: Questing ticks were sampled monthly over a period of 11 months from February, 2011 to December, 2011 at 13 sites in southern Germany using the flagging method. The ticks were identified to species, gender, and stadium. Although both I. ricinus and D. reticulatus were sampled, this study concentrated on I. ricinus, since it was the most abundant tick to be found. Additional weather data (air and soil temperature, relative air humidity, precipitation, sunshine duration) were recorded on each sampling site and the local vegetation described. A total of 14, 394 ticks was collected (7,862 larvae, 5,568 nymphs, 964 adults) and their activity was recorded in order to determine the seasonal activity pattern over different periods of the year. In contrast to the widely accepted pattern of a bimodal seasonal activity in moderate areas with a dominant peak in spring and a minor peak in autumn, a unimodal activity pattern was found for all development stages on six of the 12 sampling sites. Tick abundance was compared to weather variables. Tick host-seeking activity was found to be significantly dependent on the temperature at ground level, precipitation, and sunshine duration as well as relative air humidity. Adult ticks showed a positive correlation with the duration of sunshine, whereas nymphs were mostly unaffected by this phenomenon. Journal of Vector Ecology 39 (1): 56-65. 2014. Keyword Index: Ixodes ricinus, seasonal activity, climate, Germany.
INTRODUCTION Changing environmental and climatic conditions in western Europe are believed to have led to changes not only in the geographic distribution of ticks but also in their seasonal questing activity throughout the year (Kupča 2009, Lindgren et al. 2000, Pérez et al. 2012). These changes are important for understanding the abundance and distribution of this important vector and hence the distribution of vector-borne diseases across Germany. So far there are only a few very fragmented and focally limited studies on the spectrum and the host-seeking activity of ticks in the southern parts of Germany (Immler 1973, Liebisch and Rahman 1976, Wilske et al. 1987, Zahler et al. 2000, Süss et al. 2004). They show that rising temperatures, especially in winter, provide benefits for ticks, providing them with a longer period in which they can quest and reproduce. To provide a better insight into the current situation, the following study was designed to evaluate the spectrum and seasonal activity of ticks in southern Germany and analyze the relationship between climatic factors and the abundance of I. ricinus, the predominant tick of the area (Schulz and Pfister 2012). MATERIALS AND METHODS Sampling sites A total of 13 different locations in three federal states covering southern Germany was sampled (Figure 1). The selection of the locations was based on the previous descriptions of tick occurrence (Immler 1973, Liebisch and Rahman 1976, Wilske et al. 1987,
Zahler et al. 2000, Süss et al. 2004). The 100 m2 sampling areas at these locations were selected after specifications provided by the EDEN-Project (http://www.eden-fp6project.net/), considering vegetation structures that were likely to harbor ticks, and testsamplings before the experimental sampling began. The locations and climatic conditions of sampling sites are shown in Table 1. Sampling of ticks All locations were sampled monthly from February, 2011 to December, 2011 on the same day each month. Although planned, no sampling took place in January because of the snow cover in all the locations. Although several other methods for collecting ticks have been described in the past (Ginsberg and Ewing 1989, Gherman et al. 2012), the flagging method according to Gray (1985) is an effective and economical way for gathering large numbers of ticks and determining their seasonal activity patterns. Furthermore it was also the method of choice of the EDEN project (http://www.eden-fp6project.net/) that our institute is integrated with. However the technique only collects ticks that are questing in the upper parts of the ground vegetation such as I. ricinus. Ticks caught this way represent only a small part of the total population, since ticks periodically return to lower vegetation levels in order to regulate their water balance (Needham and Teel 1991, Perret et al. 2000, Schulze et al. 2001). A standardized 1 m² flag consisting of a rough-structured cotton fabric was drawn across the lower vegetation over a surface of a 100 m²/sampling area and checked for ticks regularly in order to avoid a loss of ticks. The ticks were collected from the cloth and stored in 15 ml tubes filled with 70% ethanol. To obtain representative samples that could be compared to each other, certain parameters were defined as follows: Sampling
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Table 1. Number of ticks and climate dates according to the vegetation categories.
Vegetation category
Deciduous forest
Conifer forest
Mixed forest
Riparian forest
Clearing
Sampling location
Number of larvae
Number of nymphs
Number of adults
Total number of ticks
Average temperature (° C)
Average relative humidity (%)
Mooswald 47° 59’ 3.84” N 7° 46’ 15.96” E, 237 m above sea level
137
315
111
563
12.6
79.1
Neckarmuehlbach 49° 16’ 42.215” N 9° 7’ 39.799” E, 204 m a.s.l.
630
377
66
1,073
11.1
79.8
Unterfoehring 48° 12’ 12.496” N 11° 38’ 44.988” E, 508 m a.s.l.
2
67
9
78
13.1
64.8
Dambach 49° 0’ 18.994” N 10° 20’ 21.44” E, 463 m a.s.l.
403
273
62
738
13.1
65.6
Schalding 48° 36’ 34.254” N 13° 21’ 48.499” E, 379 m a.s.l.
125
325
87
537
11.9
67.2
Sinzing 48° 59’ 16.667” N 12° 1’ 9.977” E, 418 m a.s.l.
475
265
18
758
11.4
74.7
Ungelstetten 49° 24’ 34.758” N 11° 18’ 15.721” E, 400 m a.s.l.
38
107
43
188
11.6
76.6
Heiligenwald 49° 21’ 4.176” N 7° 5’ 31.027” E, 335 m a.s.l.
3,895
963
151
5,009
13.1
70.8
Moenchberg 48° 35’ 15.457” N 8° 55’ 4.93” E, 546 m a.s.l.
453
651
130
1,234
9.6
73.9
Elchingen 48° 26’ 23.622” N 10° 5’ 48.109” E, 461 m a.s.l.
309
641
89
1,039
11.3
71.6
Meissenheim 48° 24’ 29.16” N 7° 45’ 22.32” E, 147 m a.s.l.
1,014
844
138
1,996
14.2
70
Bostalsee 49° 33’ 23.098” N 7° 3’ 53.737” E, 404 m a.s.l.
64
318
33
415
15.1
66.7
Heidenheim 49° 1’ 50.956” N 10° 42’ 36.425” E, 527 m a.s.l.
444
295
27
766
8.5
74.1
was always performed at the same time of the day (in the course of the morning between 09:00 and 12:00), by the same person and took place independent of atmospheric conditions. To cover as many aspects of a sampling site as possible, both sunny and shady areas were sampled equally if they were accessible. Each location was sampled until the 100 m² were completed, independent from the time it took to collect the ticks. All persons who were involved in tick collections had the appropriate personal protection equipment to prevent them from exposure to tick bites. For technical and financial reasons, the study could only be performed over the period of one year, and consequently, no statement can be
made about long-term population dynamics. Tick identification Species, gender, and stadium were identified with taxonomic keys (Arthur 1963, Hillyard 1996). The ticks were preserved in 70% ethanol for further studies on tick-borne pathogens. Flora and fauna The sampling locations were chosen on the basis of suitable biotope structures. Particular attention was paid to benefitting vegetation for ticks, as for example, mixed forest with a distinctive
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Journal of Vector Ecology
foliage. Occasionally, locations with a less benefitting vegetation were also included in the study. The habitat types of all 13 sampling sites were categorized and the local flora was defined using a plant identification key (Licht 2011). The sampling locations could be divided into the following categories: deciduous forests (Mooswald, Nackarmuehlbach, Unterfoehring), conifer forests (Ungelstetten, Sinzing, Dambach, Schalding), mixed forests (Heiligenwald, Moenchberg), riparian forests (Meissenheim, Elchingen), and clearings (Bostalsee, Heidenheim) (Figure 1). The deciduous forests consisted mainly of European Beech (Fagus sylvaticus), European Hornbeam (Carpinus betulus), English Oak (Quercus robur), and Sycamore Maple (Acer pseudoplatanus). The conifer forests were composed of Norway Spruce (Picea abies) and Scots Pine (Pinus sylvestris). Mixed forests featured all of the above and, in addition, European Silver Fir (Abies alba). The riparian forests consisted of European Ash (Fraxinus excelsior), Field Elm (Ulmus minor), and miscellaneous plants native to wetlands. An overview of local wildlife and host animals was achieved by data from the local forestry commission offices and hunters. The main hosts in nearly all locations included large and mediumsized mammals such as roe deer (Capreolus capreolus), boars (Sus scrofa), and foxes (Vulpes vulpes). However, a lot of smaller mammals such as stoats (Mustela erminea), badgers (Meles meles), stone martens (Martes foina), brown hares (Lepus europaeus), and European rabbits (Oryctolagus cuniculus) were found, along with various rodents. No quantitative aspects regarding the population sizes are registered or available for the given areas.
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Weather variables In order to evaluate the potential influence of climatic conditions, weather variables were registered as follows: air temperature and relative air humidity were recorded during every sampling tour and at each location using a thermo-hygrometer (P330, Carl Roth GmbH Karlsruhe, Germany). Data were recorded before the start of each sampling at ground level as well as at 1 m height to cover the mean questing heights of ticks (Adams et al. 2003, Mejlon and Jaenson 1997, Oorebeek et al. 2009). Soil temperature was measured with an inserting thermometer. Additional weather data (daily values for sunshine duration, precipitation, relative air humidity, and air temperature) was provided from 12 nearby meteorological stations of Germany’s National Meteorological Service (Deutscher Wetterdienst, DWD) and included in the statistical evaluation. For statistical analysis, the mean values of these variables three days before sampling were also calculated. Weather data three days before sampling was also taken into account since it is believed to have a direct influence on the questing of ticks (Schulz and Pfister 2012). For example, if it rained for three days this would have a noticeable effect on the number of ticks found on the fourth day. Statistical analysis The total number of ticks for each location and each month was counted, as well as the number of the different developement stages. The ticks were divided into adults, nymphs and larvae. For statistical analysis these numbers were compared to the gathered weather variables with the help of scatterplots and a Poisson regression analysis.
Figure 1. Map of southern Germany displaying distribution of ticks on sampling sites and total tick numbers. Symbols indicate the sampling sites and their respective vegetational structure. Numbers outside of circle diagrams indicate the total number of ticks found at that location.
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For the analysis of the number of adults, nymphs, and larvae, a generalized additive mixed model with a Poisson distribution and log link were used. Z-tests were employed to test if the coefficents of the generalized additive mixed models were significantly different from 0. The model comprises a random intercept for the site and therefore addresses the effect of repeated measurements in the same site at different examinations. In order to obtain valid p-values, no model selection was performed (Hurvich and Tsai 1990). Instead, all collected variables were included in the evaluation. As the assumption of a linear effect of time (month) would have been too restrictive, smooth nonlinear terms which can be fitted by using penalized splines were added to allow for flexible modelling. In the models for the number of adult ticks and nymphs, smooth terms were also included for all other covariates. P-values < 0.05 were regarded as statistically significant. It was not possible to fit such a complex model to the data on the number of larvae, possibly due to several extreme observations. For statistical analysis, R version 2.13.0 (R Development Core Team: R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing) was used. Generalized additive mixed models were fitted by using the R package “amer” (CRAN-Package amer). RESULTS Tick numbers From February, 2011 to December, 2011 a total of 14,394 ticks (7,862 larvae, 5,568 nymphs, 455 female ticks, and 509 male ticks) was collected at 13 locations. Of these, 14,383 ticks were Ixodes ricinus, while 11 ticks were adult Dermacentor reticulatus. Among the different collection sites, considerable differences in the distribution of the developmental stages of the ticks were observed (Figure 1). The occurrence of larvae varied between sites from 15.4% to 77.8%, whereas the number of nymphs ranged from 19.2% to 76.6% and adults had a range from 2.4% up to 22.9% in relation to the total number of collected ticks. Furthermore considerable variances were present in the total number of ticks in relation to the different locations. For example, the most ticks were found in Heiligenwald (5,009), while the lowest number of ticks were present in Unterfoehring (78). The data from Unterfoehring, however, were excluded from the listings above and below, since the extreme low number of ticks made statistical evaluation impossible. Tick activity Tick activity was observed during the whole year, from February to December. However, in the latter month only one tick could be collected (Table 2). Questing ticks could repeatedly be caught at a locally measured air temperature of 1.1° C, but below that temperature ticks were not observed or collected. In contrast, a decrease in tick numbers in July and August, the hottest months of the year, with temperatures reaching up to 25.9° C, could only be observed at six locations. A unimodal activity pattern occurred more often than a bimodal pattern for all developmental stages at six out of 12 sampling sites. Larvae were mainly observed from May to August and showed an activity peak in July, nymphs were observed from March to August and had their peak in late April and early May, whereas adults were mainly found between March
59
and July and displayed an activity peak in May (Figure 2). Temperature Minimum air temperature during sampling was reached in December in seven out of 12 sampling locations, ranging from -3.3° to 4.1° C with an average air temperature of 0.6° C. The other four locations had an average minimum of 2.9° C in November with air temperatures ranging from 0.5° C to 6.2° C. One single location had a minimum air temperature of 8.1° C in November. Maximum air temperature was observed in August with an average of 21.8° C at seven out of 12 sampling locations, while the other five locations had their maximum temperatures in June with an average of 21.9° C. Statistical analyses The relative abundance of the collected ticks was compared to the gathered weather variables and statistically analyzed. For interpretation of the statistical data, the estimated Poisson regression coefficient and its exponential function were used. If the predictor variable changes for one unit and all other predictor variables are kept constant, the dependent variable (the expected tick count) changes multiplicatively by the exponential factor of the respective regression coefficient. These values therefore show the expected count of ticks in relation to all relevant weather variables. In the Poisson regression, tick host-seeking activity was found to be significantly dependent on average sunshine duration over the last three days before sampling (p=0.0434 for adults, p=0.040954 for nymphs, and p=0.0212 for larvae) and average precipitation over the last three days before sampling (p=0.027065 for nymphs), as well as average relative air humidity over the last Table 2. Total number of ticks and percentage distribution for each month. Month
Larvae
Nymphs
Adults
Total
February
3 (3.3 %)
69 (75.8 %)
19 (20.9 %)
91
March
1 (0.2 %)
464 (84.5 %)
84 (15.3 %)
549
April
101 (6 %)
1,412 (83.3 %)
183 (10.8 %)
1,696
May
1,606 (48.3 %)
1,424 (42.8 %)
296 (8.9 %)
3,326
June
1,987 (63.1 %)
1,013 (32.2 %)
150 (4.8 %)
3,150
July
1,915 (75 %)
543 (21.3 %)
94 (3.7 %)
2,552
1,805 (81.9 %)
341 (15.5 %)
59 (2.7 %)
2,205
September
389 (72.6 %)
115 (21.5 %)
32 (6 %)
536
October
46 (18.2 %)
173 (68.4 %)
34 (13.4 %)
253
November
9 (25.7 %)
13 (37.1 %)
13 (37.1 %)
35
December
0 (0 %)
1 (100 %)
0 (0 %)
1
7,862
5,568
964
14,394
August
Total
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Figure 2. Boxplots of Ixodes ricinus adults (A), nymphs (B), and larvae (C) per month showing the statistical distribution of the different developmental stages each month. three days before sampling (p=0.017236 for nymphs) (Table 3). Additive Poisson regression models allow the modelling of the effects of continuous covariates as smooth functions, which have a more flexible form than the linear trend provided by a simple linear model. However, p-values can only be obtained for the linear part of the functions. The bigger the variance of the random effects in the model output, the further away is the fitted function from a straight line. The models are displayed in the following graphs (Figures 3 and 4). The model for average sunshine duration (Figure 3C) shows that the expected count of adult ticks decreases when sunshine duration increases. In contrast, the expected count of nymphs remains quite stable, forming a waved horizontal line with a variance of 4.02054 (Figure 4C), and showing that nymphs remain more or less unaffected by the average sunshine duration. As shown in Figure 3E (a model term that has a variance of only 0.00411 and therefore is relatively close to a straight line), the expected count of adult ticks increases with increasing average air humidity, forming a flat U-shape. Nymphs also have a relatively straight line sloping gently with a variance of 0.01028, but in contrast, their expected count drops with increasing average air humidity (Figure 4E). Figure 3F shows the model for precipitation for adults, and Figure 4F shows the model for precipitation for nymphs. Both tick numbers decrease with increasing precipitation, except for some isolated data scattered at the upper range, but only nymphs showed a significant dependency in the statistical results with a variance of 0.027065. The final Poisson regression model for the larvae, however, had to be interpreted cautiously, since there were some extreme outliers as well as many zero values in the data, making a final interpretation quite difficult. DISCUSSION The abundance of questing ixodid ticks varied considerably between the different sampling sites (Figure 1). Locations with fewer tick numbers, such as Unterfoehring and Ungelstetten, showed differences in their vegetational structure compared to the other sampling spots, as there were few or no leaves covering the ground and a very thin and monotone ground vegetation incapable of retaining much humidity, as well as a correspondingly low tick abundance, which is similar to previously published results (Daniel 1993). This illustrates the importance that the local
vegetation plays in maintaining a suitable climatic environment and shelter for ticks, which are very dependent on humidity in their microhabitat (Needham and Teel 1991, Perret et al. 2000). There were obvious differences between the abundance of different developmental stages at each sampling location. Heiligenwald had the highest number of larvae (3,895, 77.8% of the total number of collected ticks), while Bostalsee (64) and Elchingen (309) showed relatively low numbers of larvae (15.4% and 29.7% of the total number of collected ticks). Larvae are more likely to be overlooked especially in locations with high and/ or dense vegetation (Ginsberg and Ewing 1989, Randolph et al. 2000), as they tend to stay in lower vegetation which provides more humidity and shadow. This was confirmed in the two locations mentioned above (Bostalsee and Elchingen) and was also demonstrated by Oorebeek et al. (2009) with larvae of I. hirsti. However, the distribution of ticks in one location can vary due to fluctuations in the abundance of host animals or human utilization. An irregular, tesselated distribution is assumed for most areas, which results in unequally populated patches of land and the possibility of missing these spots (Daniel 1993). Questing ticks could be collected up to an air temperature at ground level as low as 1.1° C. Similar tick activity at low temperatures between -0.6 C and 5° C was observed in earlier studies (Sixl and Nosek 1971, Schulze et al. 2001). In this study a higher abundance of ticks was found at higher temperatures and longer sunshine duration. Precipitation correlated negatively with the abundance of all developmental stages. Humidity was less closely related to the abundance of ticks compared with the other parameters, yet it was significantly related to the appearance of nymphs and showed a positive correlation most of the time. It has been shown that humidity, although having a major influence on the activity of ticks, is not always directly related with tick numbers and varies according to the region and habitat as well as the developmental stage of the ticks (MacLeod 1936, Sixl and Nosek 1971, Gray et al. 1978, Daniels et al. 1989, Sonenshine 1993, Mejlon and Jaenson 1997, Schulze et al. 2001). Previous studies suggested that climate and vegetation are two extremely important factors in the seasonal questing activity of ticks, which are very susceptible to dehydration. When suffering from dehydration, questing ticks tend to move back towards ground level, where relative humidity is higher than at questing height (Lees 1946, Lees and Milne 1951, Randolph and
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Figure 3. Graphical depiction of Poisson regression showing the effect of the smoothly modelled covariates on the expected value for the number of adult ticks. X-axis: weather variable (black bars indicate observed values in the evaluated datasets), y-axis: function of weather variable as deviation from constant (on log scale).
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Figure 4. Graphical depiction of Poisson regression showing the effect of the smoothly modelled covariates on the expected value for the number of nymphs. X-axis: weather variable (black bars indicate observed values in the evaluated datasets), y-axis: function of weather variable as deviation from constant (log scale).
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Table 3. Poisson regression among variables of Ixodes ricinus adults, nymphs and larvae. P = p-value, Est. = estimated Poisson regression coefficient, Exp. = exponential function of Est., significance codes: ‘***’ (0 - 0.001) ‘**’ (0.001 - 0.01) ‘*’ (0.01 - 0.05) ‘.’ (0.05 - 0.1) ‘ ‘ (0.1 – 1). Variable Air temperature on ground level Average air temperature 3 days before sampling Average sunshine duration 3 days before sampling
Adults p
Est.
Nymphs Exp.
p
Est.
Larvae Exp.
p
Est.
Exp.
0.8238
-0.005039 0.9949737
0.6110
0.021243
1.0214703 < 2e-16 *** 0.086476
0.3267
0.039594
0.5268
0.025613
1.0259442 < 2e-16 *** -0.195034 0.8228068
1.1199163
1.0403878
0.0434 *
-0.115375 0.8910318 0.040954 *
0.113254
Relative air humidity on ground level
0.0958 .
-0.014068 0.9860308
-0.007813 0.9922170 < 2e-16 *** -0.050139 0.9510973
Relative air humidity 3 days before sampling
0.9818
0.002988
1.0029923 0.017236 * -0.251456 0.7776680 5.46e-08 *** -0.245856 0.7820352
Average precipitation 3 days before sampling
0.8447
0.006671
1.0066935 0.027065 * -0.120998 0.8860358 < 2e-16 *** 0.095533
0.3940
Storey 1999). Perret et al. (2000) showed a relationship between saturation deficit and tick density, as tick questing periods are shortened with high saturation deficits. It can be assumed that the vegetation in the immediate neighborhood of ticks plays a vital role in providing ideal conditions by retaining humidity, since ticks require at least 85% of relative air humidity to be able to survive their off-host-periods (Needham and Teel 1991). In accordance with this assumption, very low humidity was measured at Bostalsee, Schalding, and Unterfoehring, which stood out because of their low tick numbers. In the present study, six out of twelve sampling sites showed an unimodal activity pattern for all development stages, characterized by one single activity peak in early March, April, and May. The other six sampling locations showed a bimodal activity pattern with a second smaller activity peak for nymphs and larvae in autumn, while the adults didn’t have an apparent second peak. While generally a bimodal activity pattern with a dominant peak in spring and a minor peak in autumn is described for I. ricinus in Central Europe (Aeschlimann 1972, Belozerov 1982, Gray 1991, 2002), the activity peaks can differ from year to year. Decreased activity in late summer results in a bimodal pattern for subadult ticks with one peak in spring and a second peak in autumn the following year. Randolph et al. (2002) showed that an early onset of tick activity in spring can lead to an increased development speed and therefore to activity peaks in autumn, as could be seen in Mooswald and Elchingen. Unimodal activity patterns have repeatedly been described in the past, but mostly in countries in the Mediterranean area (Moreno and Estrada-Peña 1997). But lately there seems to be a change of this geographical border. Several studies from Germany and Switzerland also showed deviations from the formerly typical bimodal pattern (Kupča 2009, Pérez et al. 2012). It is assumed
0.0212 *
1.0903252
-0.029078 0.9713408
1.1002448
that changes in the climatic conditions (warmer temperatures in summer as well as in winter and an increasing humidity) support the living conditions of I. ricinus (Randolph et al. 2000). This extends the period in which ticks can quest and reproduce, which in turn is an important factor when evaluating the risk of vectorborne diseases throughout the year. All sampling locations with a unimodal activity pattern showed higher precipitation compared to the ones with a bimodal activity pattern. The total annual precipitation was >600 mm at all locations. The lowest precipitation was measured at Heidenheim with 618.9 mm, and the highest precipitation was found in Unterfoehring with 972.3 mm. The average precipitation of all locations was 733 mm, thus being lower than the nationwide annual average precipitation of 789 mm (DWD 2012). This corresponds with the fact that higher altitudes combined with moderate summers and an increased precipitation promote unimodal activity patterns (Moreno and Estrada- Peña 1997). Most locations that expressed an unimodal pattern had very dense vegetation. Mönchberg and Heiligenwald are both thick mixed forests covered with a variety of different trees and bushes. The location in Schalding consists of a little path that runs through the forest and is overgrown in many places. Sheltered habitats with dense vegetation and shady areas prevent a decrease in tick abundance especially in the hot summer months in contrast to sun-exposed areas in open terrain (Jensen and Kaufmann 2003). This results in no distinct separation between a spring and an autumn peak. Similar studies in Southern Germany over the last decade also showed unimodal patterns (Kupča 2009). This study emphasizes that climatic factors, especially ground temperature, relative humidity, and sunshine duration in the immediate habitat of ticks, play a vital role in the dynamics of tick populations and their activity. However, it was not easy to quantify
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which factors had the most dominant effect on the seasonal questing activity of ticks. It is most likely related to multiple biotic and abiotic parameters simultaneously. Of special interest is that a unimodal activity pattern was found at six of the 12 sampling sites, which corresponds to previous studies in Central Europe and appears to be an increasing trend. Acknowledgments We thank Merial Ltd. Lyon France and Merial GmbH Hallbergmoos for partially financing this study. We also thank Prof. Milan Daniel for sharing his opinion and remarks on this article. We are indebted to Prof. P. H. Holmes, University of Glasgow for his critical comments on the manuscript and the language corrections. This study was also partially funded by EU grant FP7-261504 EDENext and is catalogued by the EDENext Steering Committee as EDENext 200 (http://www.edenext.eu). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. REFERENCES CITED Adams, D.R., B.E. Anderson, C.T. Ammirati, and K.F. Helm. 2003. Identification and diseases of common U.S. ticks. Internet J. Dermatol. 2: DOI: 10.5580/1189. Aeschlimann, A. 1972. Ixodes ricinus, Linné, 1758 (Ixodoidea: Ixodidae). Essai préliminaire de synthèse sur la biologie de cette espèce en Suisse. Acta Trop. 29: 321–340. Arthur, D.R. 1963. British Ticks. Butterworths, London. Belozerov, V.N. 1982. Diapause and biological rhythms in ticks. In: F.D. Obenchain (ed.), Physiology of Ticks. pp. 469-500. Pergamon Press, Oxford. Daniel, M. 1993. Influence of the microclimate on the vertical distribution of the tick Ixodes ricinus (L.) in central Europe. Acarologia 34: 105–113. Daniels, T.J., D. Fish, and R.C. Falco. 1989. Seasonal activity and survival of adult Ixodes dammini (Acari: Ixodidae) in southern New York State. J. Med. Entomol. 26: 610-614. Gherman, C.M., A.D. Mihalca, M.O. Dumitrache, A. Gyorke, I. Oroian, M. Sandor, and V. Cozma. 2012. CO2 flagging - an improved method for the collection of questing ticks. Parasit. Vectors 5: 125. Ginsberg, H.S. and C.P. Ewing. 1989. Comparison of flagging, walking, trapping, and collecting from hosts as sampling methods for northern deer ticks, Ixodes dammini, and lonestar ticks, Amblyomma americanum (Acari: Ixodidae). Exp. Appl. Acarol. 7: 313–322. Gray, J.S. 1985. Studies on the larval activity of the tick Ixodes ricinus L. in Co. Wicklow, Ireland. Exp. Appl. Acarol. 1: 307316. Gray, J.S. 1991. The development and seasonal activity of the tick Ixodes ricinus: a vector of lyme borreliosis. Rev. Med. Vet. Entomol. 79: 323–333. Gray, J.S. 2002. Biology of Ixodes species ticks in relation to tickborne zoonoses. Wiener Klinische Wochenschrift. 114: 473– 478. Gray, J.S., T. Turley, and K.L. Strickland. 1978. Studies on the
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ecology of sheep tick, Ixodes ricinus, in Co. Wicklow, Ireland. Irish Vet. J. 32: 25-34. Hillyard, P.D. 1996. Ticks of North-West Europe. The Dorset Press, Dorchester. Hurvich, C.M. and C.L. Tsai. 1990. The impact of model selection on inference in linear regression. Am. Statist. 44: 214-217. Immler, R. 1973. Untersuchungen zur Biologie und Ökologie der Zecke Dermacentor reticulatus. Bull. Soc. Entomol. Suisse. 46. Jensen, P.M. and U. Kaufmann. 2003. Seasonal and diel activity of Ixodes ricinus (Acari: Ixodidae) subpopulations in Denmark. Aspects of size, physiological age, and malate dehydrogenase genotype in a forest site without any undergrowth. Exp. Appl. Acarol. 30: 289–303. Kupča, A.M. 2009. Ixodes ricinus (Ixodidae): Saisonale Aktivität und natürliche Infektionen mit dem FSME-Virus an ausgewählten Standorten in Bayern. DVM thesis. LudwigMaximilians-University Munich, Tierärztliche Fakultät. Lees, A.D. 1946. The water balance in Ixodes ricinus L. and certain other species of ticks. Parasitol. 37: 1–20. Lees, A.D. and A. Milne. 1951. The seasonal and diurnal activities of individual sheep ticks (Ixodes ricinus L.). Parasitology 41: 189–208. Licht, W. 2011. Einführung in die Pflanzenbestimmung nach vegetativen Merkmalen. Quelle and Meyer, Wiebelsheim. Liebisch, A. and M.S. Rahman. 1976. Zum Vorkommen und zur vektoriellen Bedeutung der Zecken Dermacentor marginatus (Sulzer, 1776) und Dermacentor reticulatus (Fabricius, 1794) in Deutschland. Tropenmed. Parasitol. 27: 393-404. Lindgren, E., L. Tälleklint, and T. Polfeldt. 2000. Impact of climatic change on the northern distribution limit and population density of the disease-transmitting European tick Ixodes ricinus. Envir. Hlth. Perspect. 108: 119-123. MacLeod, J. 1936. Ixodes ricinus in relation to its physical environment. IV. An analysis of the ecological complexes controlling distribution and activities. Parasitology 28: 295– 319. Mejlon, H.A. and T.G.T. Jaenson. 1997. Questing behaviour of Ixodes ricinus ticks (Acari: Ixodidae). Exp. Appl. Acarol. 21: 747–754. Moreno, J.A., and A. Estrada-Peña. 1997. Prevalence and seasonal activity of Ixodes ricinus (Acari: Ixodidae) on domestic ruminants of the Basque country, Spain. Exp. Appl. Acarol. 21: 41-48. Needham, G.R. and P.D. Teel. 1991. Off-host physiological ecology of Ixodid ticks. Annu. Rev. Entomol. 36: 659–681. Oorebeek, M., R. Sharrad, and S. Kleindorfer. 2009. What attracts larval Ixodes hirsti (Acari: Ixodidae) to their host? Parasitol. Res. 104: 623–628. Pérez, D., Y. Kneubühler, O. Rais, and L. Gern. 2012. Seasonality of Ixodes ricinus ticks on vegetation and on rodents and Borrelia burgdorferi sensu lato genospecies diversity in two Lyme borreliosis-endemic areas in switzerland. Vector Borne Zoonot. Dis. 12: 633-644. Perret, J.L., E. Guigoz, O. Rais, and L. Gern. 2000. Influence of saturation deficit and temperature on Ixodes ricinus tick questing activity in a Lyme borreliosis-endemic area (Switzerland). Parasitol. Res. 86: 554-557. Randolph, S.E. and K. Storey. 1999. Impact of microclimate on
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immature tick-rodent host interactions (Acari: Ixodidae): implications for parasite transmission. J. Med. Entomol. 36: 741-748. Randolph, S.E., R.M. Green, M.F. Peacey, and D.J. Rogers. 2000. Seasonal synchrony: the key to tick-borne encephalitis foci identified by satellite data. Parasitology 121: 15–23. Randolph, S.E., R.M. Green, A.N. Hoodless, and M.F. Peacey. 2002. An empirical quantitative framework for the seasonal population dynamics of the tick Ixodes ricinus. Int. J. Parasitol. 32: 979-989. Schulz, M. and K. Pfister. 2012. Untersuchungen zur saisonalen Populationsdynamik von Zecken in Süddeutschland. In: Tagung der Fachgruppe Parasitologie und parasitäre Krankheiten der DVG, 2.-4.Juli 2012 in Hannover. Tierärztliche Praxis Kleintiere. 4: 29-32. Schulze, T.L., R.A. Jordan, and R.W. Hung. 2001. Effects of selected meteorological factors on diurnal questing of Ixodes scapularis and Amblyomma americanum (Acari: Ixodidae). J. Med. Entomol. 38: 318-324.
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Sixl, W. and J. Nosek. 1971. Einfluss von Temperatur und Feuchtigkeit auf das Verhalten von Ixodes ricinus, Dermacentor marginatus und Haemaphysalis inermis. Arch. Sci. Genéve 24: 97-109. Sonenshine, D.E. 1993. Biology of Ticks Vol 2. Oxford University Press, New York. Süss, J., C. Schrader, U. Falk, and N. Wohanka. 2004. Tick-borne encephalitis (TBE) in Germany – epidemiological data, development of risk areas and virus prevalence in fieldcollected ticks and in ticks removed from humans. Int. J. Med. Microbiol. 293(Suppl. 37): 69–79. Wilske, B., R. Steinhuber, H. Bergmeister, V. Fingerle, G. Schierz, V. Preac-Mursic, E. Vanek, and B. Lorbeer. 1987. LymeBorreliose in Süddeutschland. Epidemiologische Daten zum Auftreten von Erkrankungsfällen sowie zur Durchseuchung von Zecken (Ixodes ricinus) mit Borrelia burgdorferi. Deutsche Medizin. Wochenschr. 112: 1730–1736. Zahler, M., F. Loster, C. Merkle, H. Rinder, and R. Gothe. 2000. Risk of infection for dogs in Regensburg - a new endemic focus of Babesia canis and Dermacentor reticulatus in Germany. Tierärztliche Praxis. 28(K): 395-398.
