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Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods

Understanding where species occur and how difficult they are to detect during surveys is crucial for designing and evaluating monitoring programs, and has broader applications for conservation planning and management. In this study, we modelled occupancy and the effectiveness of six sampling methods...

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Autores principales: Einoder, Luke D., Southwell, Darren M., Lahoz-Monfort, José J., Gillespie, Graeme R., Fisher, Alaric, Wintle, Brendan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152866/
https://www.ncbi.nlm.nih.gov/pubmed/30248104
http://dx.doi.org/10.1371/journal.pone.0203304
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author Einoder, Luke D.
Southwell, Darren M.
Lahoz-Monfort, José J.
Gillespie, Graeme R.
Fisher, Alaric
Wintle, Brendan A.
author_facet Einoder, Luke D.
Southwell, Darren M.
Lahoz-Monfort, José J.
Gillespie, Graeme R.
Fisher, Alaric
Wintle, Brendan A.
author_sort Einoder, Luke D.
collection PubMed
description Understanding where species occur and how difficult they are to detect during surveys is crucial for designing and evaluating monitoring programs, and has broader applications for conservation planning and management. In this study, we modelled occupancy and the effectiveness of six sampling methods at detecting vertebrates across the Top End of northern Australia. We fitted occupancy-detection models to 136 species (83 birds, 33 reptiles, 20 mammals) of 242 recorded during surveys of 333 sites in eight conservation reserves between 2011 and 2016. For modelled species, mean occupancy was highly variable: birds and reptiles ranged from 0.01–0.81 and 0.01–0.49, respectively, whereas mammal occupancy was lower, ranging from 0.02–0.30. Of the 11 environmental covariates considered as potential predictors of occupancy, topographic ruggedness, elevation, maximum temperature, and fire frequency were retained more readily in the top models. Using these models, we predicted species occupancy across the Top End of northern Australia (293,017 km(2)) and generated species richness maps for each species group. For mammals and reptiles, high richness was associated with rugged terrain, while bird richness was highest in coastal lowland woodlands. On average, detectability of diurnal birds was higher per day of surveys (0.33 ± 0.09) compared with nocturnal birds per night of spotlighting (0.13 ± 0.06). Detectability of reptiles was similar per day/night of pit trapping (0.30 ± 0.09) as per night of spotlighting (0.29 ± 0.11). On average, mammals were highly detectable using motion-sensor cameras for a week (0.36 ± 0.06), with exception of smaller-bodied species. One night of Elliott trapping (0.20 ± 0.06) and spotlighting (0.19 ± 0.06) was more effective at detecting mammals than cage (0.08 ± 0.03) and pit trapping (0.05 ± 0.04). Our estimates of species occupancy and detectability will help inform decisions about how best to redesign a long-running vertebrate monitoring program in the Top End of northern Australia.
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spelling pubmed-61528662018-10-19 Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods Einoder, Luke D. Southwell, Darren M. Lahoz-Monfort, José J. Gillespie, Graeme R. Fisher, Alaric Wintle, Brendan A. PLoS One Research Article Understanding where species occur and how difficult they are to detect during surveys is crucial for designing and evaluating monitoring programs, and has broader applications for conservation planning and management. In this study, we modelled occupancy and the effectiveness of six sampling methods at detecting vertebrates across the Top End of northern Australia. We fitted occupancy-detection models to 136 species (83 birds, 33 reptiles, 20 mammals) of 242 recorded during surveys of 333 sites in eight conservation reserves between 2011 and 2016. For modelled species, mean occupancy was highly variable: birds and reptiles ranged from 0.01–0.81 and 0.01–0.49, respectively, whereas mammal occupancy was lower, ranging from 0.02–0.30. Of the 11 environmental covariates considered as potential predictors of occupancy, topographic ruggedness, elevation, maximum temperature, and fire frequency were retained more readily in the top models. Using these models, we predicted species occupancy across the Top End of northern Australia (293,017 km(2)) and generated species richness maps for each species group. For mammals and reptiles, high richness was associated with rugged terrain, while bird richness was highest in coastal lowland woodlands. On average, detectability of diurnal birds was higher per day of surveys (0.33 ± 0.09) compared with nocturnal birds per night of spotlighting (0.13 ± 0.06). Detectability of reptiles was similar per day/night of pit trapping (0.30 ± 0.09) as per night of spotlighting (0.29 ± 0.11). On average, mammals were highly detectable using motion-sensor cameras for a week (0.36 ± 0.06), with exception of smaller-bodied species. One night of Elliott trapping (0.20 ± 0.06) and spotlighting (0.19 ± 0.06) was more effective at detecting mammals than cage (0.08 ± 0.03) and pit trapping (0.05 ± 0.04). Our estimates of species occupancy and detectability will help inform decisions about how best to redesign a long-running vertebrate monitoring program in the Top End of northern Australia. Public Library of Science 2018-09-24 /pmc/articles/PMC6152866/ /pubmed/30248104 http://dx.doi.org/10.1371/journal.pone.0203304 Text en © 2018 Einoder et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Einoder, Luke D.
Southwell, Darren M.
Lahoz-Monfort, José J.
Gillespie, Graeme R.
Fisher, Alaric
Wintle, Brendan A.
Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title_full Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title_fullStr Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title_full_unstemmed Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title_short Occupancy and detectability modelling of vertebrates in northern Australia using multiple sampling methods
title_sort occupancy and detectability modelling of vertebrates in northern australia using multiple sampling methods
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152866/
https://www.ncbi.nlm.nih.gov/pubmed/30248104
http://dx.doi.org/10.1371/journal.pone.0203304
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