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Abundance estimation of Ixodes ticks (Acari: Ixodidae) on roe deer (Capreolus capreolus).

Kiffner C, Lödige C, Alings M, Vor T, Rühe F - Exp. Appl. Acarol. (2010)

Bottom Line: In order to estimate the combined tick burden, tick counts on the head can be used for extrapolation.The presented linear models are highly significant and explain 84.1, 77.3, 90.5, 91.3, and 65.3% (adjusted R (2)) of the observed variance, respectively.Thus, these models offer a robust basis for rapid tick abundance assessment.

View Article: PubMed Central - PubMed

Affiliation: Department of Forest Zoology and Forest Conservation incl. Wildlife Biology and Game Management, Büsgen-Institute, Georg-August-University Göttingen, Büsgenweg 3, Göttingen, Germany. ckiffne@gwdg.de

ABSTRACT
Despite the importance of roe deer as a host for Ixodes ticks in central Europe, estimates of total tick burden on roe deer are not available to date. We aimed at providing (1) estimates of life stage and sex specific (larvae, nymphs, males and females, hereafter referred to as tick life stages) total Ixodes burden and (2) equations which can be used to predict the total life stage burden by counting the life stage on a selected body area. Within a period of 1(1/2) years, we conducted whole body counts of ticks from 80 hunter-killed roe deer originating from a beech dominated forest area in central Germany. Averaged over the entire study period (winter 2007-summer 2009), the mean tick burden per roe deer was 64.5 (SE +/- 10.6). Nymphs were the most numerous tick life stage per roe deer (23.9 +/- 3.2), followed by females (21.4 +/- 3.5), larvae (10.8 +/- 4.2) and males (8.4 +/- 1.5). The individual tick burden was highly aggregated (k = 0.46); levels of aggregation were highest in larvae (k = 0.08), followed by males (k = 0.40), females (k = 0.49) and nymphs (k = 0.71). To predict total life stage specific burdens based on counts on selected body parts, we provide linear equations. For estimating larvae abundance on the entire roe deer, counts can be restricted to the front legs. Tick counts restricted to the head are sufficient to estimate total nymph burden and counts on the neck are appropriate for estimating adult ticks (females and males). In order to estimate the combined tick burden, tick counts on the head can be used for extrapolation. The presented linear models are highly significant and explain 84.1, 77.3, 90.5, 91.3, and 65.3% (adjusted R (2)) of the observed variance, respectively. Thus, these models offer a robust basis for rapid tick abundance assessment. This can be useful for studies aiming at estimating effects of abiotic and biotic factors on tick abundance, modelling tick population dynamics, modelling tick-borne pathogen transmission dynamics or assessing the efficacy of acaricides.

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Linear regression plots showing the relationship between number of larvae (a), nymphs (b), females (c) and males (d) on one body part and predicted number of each tick life stage on the entire roe deer body
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Fig2: Linear regression plots showing the relationship between number of larvae (a), nymphs (b), females (c) and males (d) on one body part and predicted number of each tick life stage on the entire roe deer body

Mentions: For Ixodes larvae, the counts on the front legs correlated most strongly with the entire larvae burden (Table 2). Fitting a linear regression to these data (Fig. 2a) resulted in a significant predictive model (F = 419, DF = 1, 78, P ≪ 0.001) which explains a considerable amount of the observed variance (adjusted R2 = 0.841). Figures in brackets indicate the standard error of each regression coefficient.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Larvae on entire roe deer}} = 3. 3 8\left( { \pm 1. 7 1} \right) + 1. 4 1\left( { \pm 0.0 7} \right) \times {\text{larvae on front legs}} $$\end{document}For Ixodes nymphs, the tick count on the head was chosen as predictor for the entire nymph burden (Table 2). The fitted linear relationship for these data (Fig. 2b) was highly significant (F = 270.7, DF = 1, 78, P ≪ 0.001) and explained ca. 77% of the variance (adjusted R2 = 0.773).\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Nymphs on entire roe}}\,{\text{deer}} = 2. 2 7\left( { \pm 2.0 2} \right) + 1. 2 8\left( { \pm 0.0 8} \right) \times {\text{nymphs on head}} $$\end{document}For the adult ticks, the tick counts on the neck were selected to predict the total female and male tick abundance (Table 2). For female ticks (Fig. 2c), a linear model (F = 752.8, DF = 1, 78, P ≪ 0.001) explained ca. 90% of the variance (adjusted R2 = 0.905):\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Females on entire roe}}\,{\text{deer}} = 5. 8 7\left( { \pm 1. 2 1} \right) + 1. 6 1\left( { \pm 0.0 6} \right) \times {\text{females on neck}} $$\end{document}Fig. 2


Abundance estimation of Ixodes ticks (Acari: Ixodidae) on roe deer (Capreolus capreolus).

Kiffner C, Lödige C, Alings M, Vor T, Rühe F - Exp. Appl. Acarol. (2010)

Linear regression plots showing the relationship between number of larvae (a), nymphs (b), females (c) and males (d) on one body part and predicted number of each tick life stage on the entire roe deer body
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2914293&req=5

Fig2: Linear regression plots showing the relationship between number of larvae (a), nymphs (b), females (c) and males (d) on one body part and predicted number of each tick life stage on the entire roe deer body
Mentions: For Ixodes larvae, the counts on the front legs correlated most strongly with the entire larvae burden (Table 2). Fitting a linear regression to these data (Fig. 2a) resulted in a significant predictive model (F = 419, DF = 1, 78, P ≪ 0.001) which explains a considerable amount of the observed variance (adjusted R2 = 0.841). Figures in brackets indicate the standard error of each regression coefficient.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Larvae on entire roe deer}} = 3. 3 8\left( { \pm 1. 7 1} \right) + 1. 4 1\left( { \pm 0.0 7} \right) \times {\text{larvae on front legs}} $$\end{document}For Ixodes nymphs, the tick count on the head was chosen as predictor for the entire nymph burden (Table 2). The fitted linear relationship for these data (Fig. 2b) was highly significant (F = 270.7, DF = 1, 78, P ≪ 0.001) and explained ca. 77% of the variance (adjusted R2 = 0.773).\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Nymphs on entire roe}}\,{\text{deer}} = 2. 2 7\left( { \pm 2.0 2} \right) + 1. 2 8\left( { \pm 0.0 8} \right) \times {\text{nymphs on head}} $$\end{document}For the adult ticks, the tick counts on the neck were selected to predict the total female and male tick abundance (Table 2). For female ticks (Fig. 2c), a linear model (F = 752.8, DF = 1, 78, P ≪ 0.001) explained ca. 90% of the variance (adjusted R2 = 0.905):\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Females on entire roe}}\,{\text{deer}} = 5. 8 7\left( { \pm 1. 2 1} \right) + 1. 6 1\left( { \pm 0.0 6} \right) \times {\text{females on neck}} $$\end{document}Fig. 2

Bottom Line: In order to estimate the combined tick burden, tick counts on the head can be used for extrapolation.The presented linear models are highly significant and explain 84.1, 77.3, 90.5, 91.3, and 65.3% (adjusted R (2)) of the observed variance, respectively.Thus, these models offer a robust basis for rapid tick abundance assessment.

View Article: PubMed Central - PubMed

Affiliation: Department of Forest Zoology and Forest Conservation incl. Wildlife Biology and Game Management, Büsgen-Institute, Georg-August-University Göttingen, Büsgenweg 3, Göttingen, Germany. ckiffne@gwdg.de

ABSTRACT
Despite the importance of roe deer as a host for Ixodes ticks in central Europe, estimates of total tick burden on roe deer are not available to date. We aimed at providing (1) estimates of life stage and sex specific (larvae, nymphs, males and females, hereafter referred to as tick life stages) total Ixodes burden and (2) equations which can be used to predict the total life stage burden by counting the life stage on a selected body area. Within a period of 1(1/2) years, we conducted whole body counts of ticks from 80 hunter-killed roe deer originating from a beech dominated forest area in central Germany. Averaged over the entire study period (winter 2007-summer 2009), the mean tick burden per roe deer was 64.5 (SE +/- 10.6). Nymphs were the most numerous tick life stage per roe deer (23.9 +/- 3.2), followed by females (21.4 +/- 3.5), larvae (10.8 +/- 4.2) and males (8.4 +/- 1.5). The individual tick burden was highly aggregated (k = 0.46); levels of aggregation were highest in larvae (k = 0.08), followed by males (k = 0.40), females (k = 0.49) and nymphs (k = 0.71). To predict total life stage specific burdens based on counts on selected body parts, we provide linear equations. For estimating larvae abundance on the entire roe deer, counts can be restricted to the front legs. Tick counts restricted to the head are sufficient to estimate total nymph burden and counts on the neck are appropriate for estimating adult ticks (females and males). In order to estimate the combined tick burden, tick counts on the head can be used for extrapolation. The presented linear models are highly significant and explain 84.1, 77.3, 90.5, 91.3, and 65.3% (adjusted R (2)) of the observed variance, respectively. Thus, these models offer a robust basis for rapid tick abundance assessment. This can be useful for studies aiming at estimating effects of abiotic and biotic factors on tick abundance, modelling tick population dynamics, modelling tick-borne pathogen transmission dynamics or assessing the efficacy of acaricides.

Show MeSH
Related in: MedlinePlus