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N-mixture models reliably estimate the abundance of small vertebrates
by
Muraro, Martina
, Scali, Stefano
, Silva-Rocha, Iolanda
, Barzaghi, Benedetta
, Urso, Arianna
, Andreone, Franco
, Lunghi, Enrico
, Carretero, Miguel Angel
, Lo Parrino, Elia
, Scarì, Giorgio
, Melotto, Andrea
, Canedoli, Claudia
, Ficetola, Gentile Francesco
, Nanni, Veronica
, Salvi, Daniele
, Manenti, Raoul
, Pennati, Roberta
in
631/158/1144
/ 631/158/670
/ 631/158/672
/ Abundance
/ Amphibians
/ Animal diseases
/ Capture-recapture studies
/ Conservation
/ Endangered & extinct species
/ Endemic species
/ Estimates
/ Heterogeneity
/ Humanities and Social Sciences
/ Hydromantes ambrosii
/ Lizards
/ multidisciplinary
/ Podarcis raffonei
/ Reptiles
/ Reptiles & amphibians
/ Salamandra lanzai
/ Sampling
/ Science
/ Science (multidisciplinary)
/ Threatened species
2018
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N-mixture models reliably estimate the abundance of small vertebrates
by
Muraro, Martina
, Scali, Stefano
, Silva-Rocha, Iolanda
, Barzaghi, Benedetta
, Urso, Arianna
, Andreone, Franco
, Lunghi, Enrico
, Carretero, Miguel Angel
, Lo Parrino, Elia
, Scarì, Giorgio
, Melotto, Andrea
, Canedoli, Claudia
, Ficetola, Gentile Francesco
, Nanni, Veronica
, Salvi, Daniele
, Manenti, Raoul
, Pennati, Roberta
in
631/158/1144
/ 631/158/670
/ 631/158/672
/ Abundance
/ Amphibians
/ Animal diseases
/ Capture-recapture studies
/ Conservation
/ Endangered & extinct species
/ Endemic species
/ Estimates
/ Heterogeneity
/ Humanities and Social Sciences
/ Hydromantes ambrosii
/ Lizards
/ multidisciplinary
/ Podarcis raffonei
/ Reptiles
/ Reptiles & amphibians
/ Salamandra lanzai
/ Sampling
/ Science
/ Science (multidisciplinary)
/ Threatened species
2018
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N-mixture models reliably estimate the abundance of small vertebrates
by
Muraro, Martina
, Scali, Stefano
, Silva-Rocha, Iolanda
, Barzaghi, Benedetta
, Urso, Arianna
, Andreone, Franco
, Lunghi, Enrico
, Carretero, Miguel Angel
, Lo Parrino, Elia
, Scarì, Giorgio
, Melotto, Andrea
, Canedoli, Claudia
, Ficetola, Gentile Francesco
, Nanni, Veronica
, Salvi, Daniele
, Manenti, Raoul
, Pennati, Roberta
in
631/158/1144
/ 631/158/670
/ 631/158/672
/ Abundance
/ Amphibians
/ Animal diseases
/ Capture-recapture studies
/ Conservation
/ Endangered & extinct species
/ Endemic species
/ Estimates
/ Heterogeneity
/ Humanities and Social Sciences
/ Hydromantes ambrosii
/ Lizards
/ multidisciplinary
/ Podarcis raffonei
/ Reptiles
/ Reptiles & amphibians
/ Salamandra lanzai
/ Sampling
/ Science
/ Science (multidisciplinary)
/ Threatened species
2018
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N-mixture models reliably estimate the abundance of small vertebrates
Journal Article
N-mixture models reliably estimate the abundance of small vertebrates
2018
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Overview
Accurate measures of species abundance are essential to identify conservation strategies.
N
-mixture models are increasingly used to estimate abundance on the basis of species counts. In this study we tested whether abundance estimates obtained using
N-
mixture models provide consistent results with more traditional approaches requiring capture (capture-mark recapture and removal sampling). We focused on endemic, threatened species of amphibians and reptiles in Italy, for which accurate abundance data are needed for conservation assessments: the Lanza’s Alpine salamander
Salamandra lanzai
, the Ambrosi’s cave salamander
Hydromantes ambrosii
and the Aeolian wall lizard
Podarcis raffonei
. In visual counts, detection probability was variable among species, ranging between 0.14 (Alpine salamanders) and 0.60 (cave salamanders). For all the species, abundance estimates obtained using
N
-mixture models showed limited differences with the ones obtained through capture-mark-recapture or removal sampling. The match was particularly accurate for cave salamanders in sites with limited abundance and for lizards, nevertheless non-incorporating heterogeneity of detection probability increased bias.
N-
mixture models provide reliable abundance estimates that are comparable with the ones of more traditional approaches, and offer additional advantages such as a smaller sampling effort and no need of manipulating individuals, which in turn reduces the risk of harming animals and spreading diseases.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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