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Estimating Population Size of Eurasian Badgers (Meles meles) Using Mark-Recapture and Mark-Resight Data

Authors: F. A. M. Tuyttens; D. W. Macdonald; E. Swait; C. L. Cheeseman;

Estimating Population Size of Eurasian Badgers (Meles meles) Using Mark-Recapture and Mark-Resight Data

Abstract

Estimates of abundance of medium-to-large mammals by traditional mark-recapture models may be unreliable because quantity and quality of trapping data are low. The proposed closed-subpopulation model provides a flexible framework to increase the amount of data used for estimation of demographic parameters, by taking into account characteristics of the population and using ancillary non-trapping data. This model defines a subsection of the population that is known to be alive and within the study area during a certain period, regardless of which animals were actually caught. Population size is estimated from the proportion of animals in this closed subpopulation that were actually captured. We used this model to estimate size of a partly culled population of Eurasian badgers ( Meles meles ). Number of badgers included in the closed subpopulation was maximized by using data from trapping, road-traffic accidents, and radiotelemetry, and by assuming that no additions occurred to the population of young between trapping occasions. Probabilities of capture varied by season and age-class but not sex, trapping, or radio-tagging. Population estimates appeared reliable because estimated number of times individual badgers were trapped in a year corresponded with observed frequencies and estimated size of the young and adult populations corresponded favorably with estimates based on a mark-resight procedure.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Top 10%
Top 10%
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