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Removal modelling in ecology: A systematic review

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Removal modelling in ecology: A systematic review. / McCrea, Rachel; Rodriguez de Rivera, Oscar.
In: PLoS One, Vol. 16, No. 3, 04.03.2021, p. e0229965.

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McCrea, R & Rodriguez de Rivera, O 2021, 'Removal modelling in ecology: A systematic review', PLoS One, vol. 16, no. 3, pp. e0229965. https://doi.org/10.1371/journal.pone.0229965

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McCrea R, Rodriguez de Rivera O. Removal modelling in ecology: A systematic review. PLoS One. 2021 Mar 4;16(3):e0229965. doi: 10.1371/journal.pone.0229965

Author

McCrea, Rachel ; Rodriguez de Rivera, Oscar. / Removal modelling in ecology : A systematic review. In: PLoS One. 2021 ; Vol. 16, No. 3. pp. e0229965.

Bibtex

@article{af80ca8c13904523ab614ca6e2e52cc9,
title = "Removal modelling in ecology: A systematic review",
abstract = "Removal models were proposed over 80 years ago as a tool to estimate unknown population size. More recently, they are used as an effective tool for management actions for the control of non desirable species, or for the evaluation of translocation management actions. Although the models have evolved over time, in essence, the protocol for data collection has remained similar: at each sampling occasion attempts are made to capture and remove individuals from the study area. Within this paper we review the literature of removal modelling and highlight the methodological developments for the analysis of removal data, in order to provide a unified resource for ecologists wishing to implement these approaches. Models for removal data have developed to better accommodate important features of the data and we discuss the shift in the required assumptions for the implementation of the models. The relative simplicity of this type of data and associated models mean that the method remains attractive and we discuss the potential future role of this technique.",
author = "Rachel McCrea and {Rodriguez de Rivera}, Oscar",
year = "2021",
month = mar,
day = "4",
doi = "10.1371/journal.pone.0229965",
language = "English",
volume = "16",
pages = "e0229965",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "3",

}

RIS

TY - JOUR

T1 - Removal modelling in ecology

T2 - A systematic review

AU - McCrea, Rachel

AU - Rodriguez de Rivera, Oscar

PY - 2021/3/4

Y1 - 2021/3/4

N2 - Removal models were proposed over 80 years ago as a tool to estimate unknown population size. More recently, they are used as an effective tool for management actions for the control of non desirable species, or for the evaluation of translocation management actions. Although the models have evolved over time, in essence, the protocol for data collection has remained similar: at each sampling occasion attempts are made to capture and remove individuals from the study area. Within this paper we review the literature of removal modelling and highlight the methodological developments for the analysis of removal data, in order to provide a unified resource for ecologists wishing to implement these approaches. Models for removal data have developed to better accommodate important features of the data and we discuss the shift in the required assumptions for the implementation of the models. The relative simplicity of this type of data and associated models mean that the method remains attractive and we discuss the potential future role of this technique.

AB - Removal models were proposed over 80 years ago as a tool to estimate unknown population size. More recently, they are used as an effective tool for management actions for the control of non desirable species, or for the evaluation of translocation management actions. Although the models have evolved over time, in essence, the protocol for data collection has remained similar: at each sampling occasion attempts are made to capture and remove individuals from the study area. Within this paper we review the literature of removal modelling and highlight the methodological developments for the analysis of removal data, in order to provide a unified resource for ecologists wishing to implement these approaches. Models for removal data have developed to better accommodate important features of the data and we discuss the shift in the required assumptions for the implementation of the models. The relative simplicity of this type of data and associated models mean that the method remains attractive and we discuss the potential future role of this technique.

U2 - 10.1371/journal.pone.0229965

DO - 10.1371/journal.pone.0229965

M3 - Journal article

C2 - 33661897

VL - 16

SP - e0229965

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 3

ER -