Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation

Abstract N-mixture models usually rely on a meta-population design, in which repeated counts of individuals in multiple sampling locations are obtained over time. The time-for-space substitution (TSS) in N-mixture models allows to estimate population abundance and trend of a single population, witho...

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Autores principales:	Andrea Costa, Sebastiano Salvidio, Johannes Penner, Marco Basile
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a087e8aec87548c28d334f936dd8b211
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spelling	oai:doaj.org-article:a087e8aec87548c28d334f936dd8b2112021-12-02T15:53:03ZTime-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation10.1038/s41598-021-84010-52045-2322https://doaj.org/article/a087e8aec87548c28d334f936dd8b2112021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84010-5https://doaj.org/toc/2045-2322Abstract N-mixture models usually rely on a meta-population design, in which repeated counts of individuals in multiple sampling locations are obtained over time. The time-for-space substitution (TSS) in N-mixture models allows to estimate population abundance and trend of a single population, without spatial replication. This application could be of great interest in ecological studies and conservation programs; however, its reliability has only been evaluated on a single case study. Here we perform a simulation-based evaluation of this particular application of N-mixture modelling. We generated count data, under 144 simulated scenarios, from a single population surveyed several times per year and subject to different dynamics. We compared simulated abundance and trend values with TSS estimates. TSS estimates are overall in good agreement with real abundance. Trend and abundance estimation is mainly affected by detection probability and population size. After evaluating the reliability of TSS, both against real world data, and simulations, we suggest that this particular application of N-mixture model could be reliable for monitoring abundance in single populations of rare or difficult to study species, in particular in cases of species with very narrow geographic ranges, or known only for few localities.Andrea CostaSebastiano SalvidioJohannes PennerMarco BasileNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Andrea Costa Sebastiano Salvidio Johannes Penner Marco Basile Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
description	Abstract N-mixture models usually rely on a meta-population design, in which repeated counts of individuals in multiple sampling locations are obtained over time. The time-for-space substitution (TSS) in N-mixture models allows to estimate population abundance and trend of a single population, without spatial replication. This application could be of great interest in ecological studies and conservation programs; however, its reliability has only been evaluated on a single case study. Here we perform a simulation-based evaluation of this particular application of N-mixture modelling. We generated count data, under 144 simulated scenarios, from a single population surveyed several times per year and subject to different dynamics. We compared simulated abundance and trend values with TSS estimates. TSS estimates are overall in good agreement with real abundance. Trend and abundance estimation is mainly affected by detection probability and population size. After evaluating the reliability of TSS, both against real world data, and simulations, we suggest that this particular application of N-mixture model could be reliable for monitoring abundance in single populations of rare or difficult to study species, in particular in cases of species with very narrow geographic ranges, or known only for few localities.
format	article
author	Andrea Costa Sebastiano Salvidio Johannes Penner Marco Basile
author_facet	Andrea Costa Sebastiano Salvidio Johannes Penner Marco Basile
author_sort	Andrea Costa
title	Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
title_short	Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
title_full	Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
title_fullStr	Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
title_full_unstemmed	Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
title_sort	time-for-space substitution in n-mixture models for estimating population trends: a simulation-based evaluation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a087e8aec87548c28d334f936dd8b211
work_keys_str_mv	AT andreacosta timeforspacesubstitutioninnmixturemodelsforestimatingpopulationtrendsasimulationbasedevaluation AT sebastianosalvidio timeforspacesubstitutioninnmixturemodelsforestimatingpopulationtrendsasimulationbasedevaluation AT johannespenner timeforspacesubstitutioninnmixturemodelsforestimatingpopulationtrendsasimulationbasedevaluation AT marcobasile timeforspacesubstitutioninnmixturemodelsforestimatingpopulationtrendsasimulationbasedevaluation
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Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation

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