Abstract

Context. In studies of population dynamics, disease ecology and prevalence, point-sampling of data is a widely used sampling technique and capture–mark–recapture (CMR) is the most popular method of point sampling. Population estimates based on CMR are sensitive to deviations from the assumptions of the models such as equal catchability of all animals. Although consistent deviations from these assumptions can be accounted for in a robust statistical framework (e.g. identification of trap-shy animals), transient effects cannot be adequately incorporated in the statistical models and thus are expected to affect the accuracy of model predictions. In natural animal populations, parasitism is often transient but inevitable and studies showing behavioural changes, e.g. foraging strategies, as a result of infection are numerous. Thus, parasitism may represent a transient source of heterogeneity of trapping probability in small mammal populations and may affect accuracy of wildlife sampling techniques. Aims. The aim of the present study was to quantify the effect of parasitic status on capture rates of wood mice (Apodemus sylvaticus), and thus the potential for parasitism to act as a source of bias in wildlife sampling techniques such as CMR. Methods. In total, 41 wood mice were successfully captured, marked and released from two study sites in two different years, with weight, sex and faecal egg counts (FEC; used as a measure of the level of parasitism) recorded at every capture. Key results. In both studies, FEC was positively correlated with the capture rate of mice and the number of different traps in which an individual was caught. Conclusions. We conclude that parasitism affects the rate of capture of wood mice and has the potential to represent a significant source of heterogeneity in trapping probability. Implications. The consistent results of these two small studies suggest that wildlife point-sampling techniques may be biased by the parasitic status of the animals, which has potentially significant and far-reaching implications for wildlife population studies and disease-prevalence studies.

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