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    Rights statement: © 2014 The Authors. Journal of Applied Ecology © 2014 British Ecological Society This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science

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Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science. / Banks-leite, Cristina; Pardini, Renata; Boscolo, Danilo; Cassano, Camila Righetto; Püttker, Thomas; Barros, Camila Santos; Barlow, Jos.

In: Journal of Applied Ecology, Vol. 51, No. 4, 08.2014, p. 849-859.

Research output: Contribution to journalJournal article

Harvard

Banks-leite, C, Pardini, R, Boscolo, D, Cassano, CR, Püttker, T, Barros, CS & Barlow, J 2014, 'Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science', Journal of Applied Ecology, vol. 51, no. 4, pp. 849-859. https://doi.org/10.1111/1365-2664.12272

APA

Banks-leite, C., Pardini, R., Boscolo, D., Cassano, C. R., Püttker, T., Barros, C. S., & Barlow, J. (2014). Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science. Journal of Applied Ecology, 51(4), 849-859. https://doi.org/10.1111/1365-2664.12272

Vancouver

Banks-leite C, Pardini R, Boscolo D, Cassano CR, Püttker T, Barros CS et al. Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science. Journal of Applied Ecology. 2014 Aug;51(4):849-859. https://doi.org/10.1111/1365-2664.12272

Author

Banks-leite, Cristina ; Pardini, Renata ; Boscolo, Danilo ; Cassano, Camila Righetto ; Püttker, Thomas ; Barros, Camila Santos ; Barlow, Jos. / Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science. In: Journal of Applied Ecology. 2014 ; Vol. 51, No. 4. pp. 849-859.

Bibtex

@article{34b3373a315d4fe5bccbe8db5320e2ae,
title = "Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science",
abstract = "1. In recent years, there has been a fast development of models that adjust for imperfect detection. These models have revolutionised the analysis of field data, and their use has repeatedly demonstrated the importance of sampling design and data quality. There are, however, several practical limitations associated with the use of detectability models which restrict their relevance to tropical conservation science.2. We outline the main advantages of detectability models, before examining their limitations associated with their applicability to the analysis of tropical communities, rare species and large-scale datasets. Finally, we discuss whether detection probability needs to be controlled before and/or after data collection.3. Models that adjust for imperfect detection allow ecologists to assess data quality by estimating uncertainty, and to obtain adjusted ecological estimates of populations and communities. Importantly, these models have allowed informed decisions to be made about the conservation and management of target species.4. Data requirements for obtaining unadjusted estimates are substantially lower than for detectability-adjusted estimates, which require relatively high detection/recapture probabilities and a number of repeated surveys at each location. These requirements can be difficult to meet in large-scale environmental studies where high levels of spatial replication are needed, or in the tropics where communities are composed of many naturally rare species. However, while imperfect detection can only be adjusted statistically, covariates of detection probability can also be controlled through study design. Using three study cases where we controlled for covariates of detection probability through sampling design, we show that the variation in unadjusted ecological estimates from nearly 100 species was qualitatively the same as that obtained from adjusted estimates. Finally, we discuss that the decision as to whether one should control for covariates of detection probability through study design or statistical analyses should be dependent on study objectives.5. Synthesis and applications. Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost-effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.",
keywords = "biodiversity conservation, capture-recapture models, detectability, detection probability, imperfect detection, monitoring, occupancy models, species richness",
author = "Cristina Banks-leite and Renata Pardini and Danilo Boscolo and Cassano, {Camila Righetto} and Thomas P{\"u}ttker and Barros, {Camila Santos} and Jos Barlow",
note = "{\textcopyright} 2014 The Authors. Journal of Applied Ecology {\textcopyright} 2014 British Ecological Society This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.",
year = "2014",
month = aug
doi = "10.1111/1365-2664.12272",
language = "English",
volume = "51",
pages = "849--859",
journal = "Journal of Applied Ecology",
issn = "0021-8901",
publisher = "Blackwell Publishing Ltd",
number = "4",

}

RIS

TY - JOUR

T1 - Assessing the utility of statistical adjustments for imperfect detection in tropical conservation science

AU - Banks-leite, Cristina

AU - Pardini, Renata

AU - Boscolo, Danilo

AU - Cassano, Camila Righetto

AU - Püttker, Thomas

AU - Barros, Camila Santos

AU - Barlow, Jos

N1 - © 2014 The Authors. Journal of Applied Ecology © 2014 British Ecological Society This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

PY - 2014/8

Y1 - 2014/8

N2 - 1. In recent years, there has been a fast development of models that adjust for imperfect detection. These models have revolutionised the analysis of field data, and their use has repeatedly demonstrated the importance of sampling design and data quality. There are, however, several practical limitations associated with the use of detectability models which restrict their relevance to tropical conservation science.2. We outline the main advantages of detectability models, before examining their limitations associated with their applicability to the analysis of tropical communities, rare species and large-scale datasets. Finally, we discuss whether detection probability needs to be controlled before and/or after data collection.3. Models that adjust for imperfect detection allow ecologists to assess data quality by estimating uncertainty, and to obtain adjusted ecological estimates of populations and communities. Importantly, these models have allowed informed decisions to be made about the conservation and management of target species.4. Data requirements for obtaining unadjusted estimates are substantially lower than for detectability-adjusted estimates, which require relatively high detection/recapture probabilities and a number of repeated surveys at each location. These requirements can be difficult to meet in large-scale environmental studies where high levels of spatial replication are needed, or in the tropics where communities are composed of many naturally rare species. However, while imperfect detection can only be adjusted statistically, covariates of detection probability can also be controlled through study design. Using three study cases where we controlled for covariates of detection probability through sampling design, we show that the variation in unadjusted ecological estimates from nearly 100 species was qualitatively the same as that obtained from adjusted estimates. Finally, we discuss that the decision as to whether one should control for covariates of detection probability through study design or statistical analyses should be dependent on study objectives.5. Synthesis and applications. Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost-effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.

AB - 1. In recent years, there has been a fast development of models that adjust for imperfect detection. These models have revolutionised the analysis of field data, and their use has repeatedly demonstrated the importance of sampling design and data quality. There are, however, several practical limitations associated with the use of detectability models which restrict their relevance to tropical conservation science.2. We outline the main advantages of detectability models, before examining their limitations associated with their applicability to the analysis of tropical communities, rare species and large-scale datasets. Finally, we discuss whether detection probability needs to be controlled before and/or after data collection.3. Models that adjust for imperfect detection allow ecologists to assess data quality by estimating uncertainty, and to obtain adjusted ecological estimates of populations and communities. Importantly, these models have allowed informed decisions to be made about the conservation and management of target species.4. Data requirements for obtaining unadjusted estimates are substantially lower than for detectability-adjusted estimates, which require relatively high detection/recapture probabilities and a number of repeated surveys at each location. These requirements can be difficult to meet in large-scale environmental studies where high levels of spatial replication are needed, or in the tropics where communities are composed of many naturally rare species. However, while imperfect detection can only be adjusted statistically, covariates of detection probability can also be controlled through study design. Using three study cases where we controlled for covariates of detection probability through sampling design, we show that the variation in unadjusted ecological estimates from nearly 100 species was qualitatively the same as that obtained from adjusted estimates. Finally, we discuss that the decision as to whether one should control for covariates of detection probability through study design or statistical analyses should be dependent on study objectives.5. Synthesis and applications. Models that adjust for imperfect detection are an important part of an ecologist's toolkit, but they should not be uniformly adopted in all studies. Ecologists should never let the constraints of models dictate which questions should be pursued or how the data should be analysed, and detectability models are no exception. We argue for pluralism in scientific methods, particularly where cost-effective applied ecological science is needed to inform conservation policy at a range of different scales and in many different systems.

KW - biodiversity conservation

KW - capture-recapture models

KW - detectability

KW - detection probability

KW - imperfect detection

KW - monitoring

KW - occupancy models

KW - species richness

U2 - 10.1111/1365-2664.12272

DO - 10.1111/1365-2664.12272

M3 - Journal article

VL - 51

SP - 849

EP - 859

JO - Journal of Applied Ecology

JF - Journal of Applied Ecology

SN - 0021-8901

IS - 4

ER -