Detecting target species : With how many samples?
Delgado de la Torre, Rosario (Universitat Autònoma de Barcelona. Departament de Matemàtiques)

Fecha:	2022
Resumen:	The detection of target species is of paramount importance in ecological studies, with implications for environmental management and natural resource conservation planning. This is usually done by sampling the area: The species is detected if the presence of at least one individual is detected in the samples. Green & Young (Green & Young 1993 Sampling to detectrare species. Ecol. Appl. 3, 351-356. (doi:10. 2307/1941837) introduce two models to determine the minimum number of samples n to ensure that the probability of failing to detect the species from them, if the species is actually present in the area, does not exceed a fixed threshold: based on the Poisson and the Negative Binomial distributions. We generalize them to two scenarios, one considering the area size N to be finite, and the other allowing detectability errors, with probability δ. The results in Green & Young are recovered by taking N → ∞ and δ= 0. Not taking into consideration the finite size of the area, if known, leads to an overestimation of n, which is vital to avoid if sampling is expensive or difficult, while assuming that there are no detectability errors, if they really exist, produces an undesirable bias. Our approximation manages to skirt both problems, for the Poisson and the Negative Binomial.
Ayudas:	Agencia Estatal de Investigación PGC2018-097848-B-I0
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Detection error ; Negative Binomial ; Poisson ; Sampling ; Target species
Publicado en:	Royal Society Open Science, Vol. 9 Núm. 8 (october 2022) , p. 220046, ISSN 2054-5703

DOI: 10.1098/rsos.220046
PMID: 35958088

18 p, 753.6 KB

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