Bait effectiveness in camera trap studies in the Iberian Peninsula View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Noé Ferreira-Rodríguez, Manuel A. Pombal

ABSTRACT

A wide variety of baits is used in camera trap studies, but few have been validated to obtain optimal and comparable results. The present study aimed to analyze the effectiveness of different baits commonly used in camera trap studies in the Iberian Peninsula. First, a bibliographic review was performed in order to identify the most common baits. Then, an intensive camera trap monitoring program was carried out with the identified baits. Finally, we estimate the effect of bait type on the average detection of several target and nontarget mammal species. Results show that chicken- and fish-baited cameras produced satisfactory results for targeted species. Chicken meat showed higher detection for badgers, stone martens, and common genets. Canned sardines in vegetable oil resulted an attractive bait for red foxes and feral dogs. Unbaited cameras, vegetable-based baits, or scats and urine as operational attractants resulted ineffective baits for mesocarnivores, with the exception of feral cats. A variety of baits has been used for mesocarnivore inventories or single-species studies in the Iberian Peninsula. In consequence, most of these inventories and studies cannot be fully compared. Moreover, as baits are not equally effective, diversity and abundance data could be underestimated and compromise the quality of the survey data. The present results highlight the need for standardized methods in camera trap studies to follow a replicable methodology in order to obtain feasible and comparable results among studies. More... »

PAGES

155-164

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  • Journal

    TITLE

    Mammal Research

    ISSUE

    2

    VOLUME

    64

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s13364-018-00414-1

    DOI

    http://dx.doi.org/10.1007/s13364-018-00414-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111250033


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