Dogs can detect scat samples more efficiently than humans: an experiment in a continuous Atlantic Forest remnant


Autoria(s): Oliveira, Márcio L. de; Norris, Darren; Ramírez, José F. M.; Peres, Pedro H. de F.; Galetti, Mauro; Duarte, José M. B.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/04/2012

Resumo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Scat-detection dogs have been used to locate feces of rare and elusive species across tropical biomes. However their detection efficiency in relation to human observers has rarely been evaluated. In this study, we evaluated the ability of a scat detection dog to locate feces in comparison with human researchers. Human researchers and a scat detection dog surveyed for deer (Mazama spp.) feces in dense ombrofilous Atlantic forest in the Paranapiacaba continuum, SP, Brazil. A controlled experiment was used to assess the maximum effective perpendicular distance from a transect search line that the dog could detect a Mazama spp fecal sample. Results from a linear regression model revealed that the maximum effective perpendicular distance from a transect search line that the dog could detect a scat was 7.2 m. The detection success from our surveys in the Atlantic forest was zero for humans and 0.15 samples/ha or 0.20 samples/km walked for the dog team. Our results demonstrated the importance of scat-detection dogs for non invasive sampling and provide data relevant for the design of future studies.

Formato

183-186

Identificador

http://dx.doi.org/10.1590/S1984-46702012000200012

Zoologia (Curitiba). Sociedade Brasileira de Zoologia, v. 29, n. 2, p. 183-186, 2012.

1984-4670

http://hdl.handle.net/11449/4398

10.1590/S1984-46702012000200012

S1984-46702012000200012

WOS:000303976100012

S1984-46702012000200012.pdf

Idioma(s)

eng

Publicador

Sociedade Brasileira de Zoologia

Relação

Zoologia (Curitiba)

Direitos

openAccess

Palavras-Chave #Deer #fecal samples #Mazama #sampling
Tipo

info:eu-repo/semantics/article