Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists
For species that are still widespread, obtaining accurate and precise measures of population change inevitably means gathering representative sample data rather than undertaking a complete census. In the UK, a system of raising 'alerts' utilises stochastic models for such data to identify...
Published in: | Biological Conservation |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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2008
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Online Access: | https://research-portal.st-andrews.ac.uk/en/researchoutput/quantifying-conservation-concern--bayesian-statistics-and-the-red-data-lists(1ab39ad2-ccb7-4eac-a861-3529e114a620).html https://doi.org/10.1016/j.biocon.2008.03.009 http://www.scopus.com/inward/record.url?scp=44149089270&partnerID=8YFLogxK |
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ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/1ab39ad2-ccb7-4eac-a861-3529e114a620 2024-06-23T07:57:23+00:00 Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists Brooks, SP Freeman, SN Greenwood, JJD King, Ruth Mazzetta, C 2008-05 https://research-portal.st-andrews.ac.uk/en/researchoutput/quantifying-conservation-concern--bayesian-statistics-and-the-red-data-lists(1ab39ad2-ccb7-4eac-a861-3529e114a620).html https://doi.org/10.1016/j.biocon.2008.03.009 http://www.scopus.com/inward/record.url?scp=44149089270&partnerID=8YFLogxK eng eng https://research-portal.st-andrews.ac.uk/en/researchoutput/quantifying-conservation-concern--bayesian-statistics-and-the-red-data-lists(1ab39ad2-ccb7-4eac-a861-3529e114a620).html info:eu-repo/semantics/restrictedAccess Brooks , SP , Freeman , SN , Greenwood , JJD , King , R & Mazzetta , C 2008 , ' Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists ' , Biological Conservation , vol. 141 , no. 5 , pp. 1436-1441 . https://doi.org/10.1016/j.biocon.2008.03.009 abundance demography management modelling LAPWINGS VANELLUS-VANELLUS RING-RECOVERY DATA SURVIVAL MODELS DYNAMICS POPULATIONS DECLINE CENSUS TRENDS article 2008 ftunstandrewcris https://doi.org/10.1016/j.biocon.2008.03.009 2024-06-13T00:12:23Z For species that are still widespread, obtaining accurate and precise measures of population change inevitably means gathering representative sample data rather than undertaking a complete census. In the UK, a system of raising 'alerts' utilises stochastic models for such data to identify species in rapid (>50%) or moderate (25-50%) decline across various temporal and spatial scales. Considerable improvements in interpretation can be made by explaining annual fluctuations in terms of explicit population models (rather than trends of an arbitrary mathematical form); through the simultaneous modelling of data from a complete or partial census with those providing information on the demographic rates employed in these models; and through adopting a Bayesian rather than a frequentist statistical approach. A Bayesian approach is natural for quantifying, in the form of a probability, the support provided by the data for assigning a species to each of the categories. Based on territory mapping and ringing data for the lapwing Vanellus vanellus, we describe such an approach. Trends are estimated more precisely than those under models previously employed in the alerts context. Some smoothing is induced, but realistic responses to years of severe weather are retained, and these are expressed also via model-averaged trends in key demographic parameters. We discuss the conservation implications for this declining species, and the wider potential arising from the ability to quantify confidence that population change has exceeded a threshold either generating conservation concern or justifying a subsequent programme of action for recovery. (C) 2008 Elsevier Ltd. All rights reserved. Article in Journal/Newspaper Vanellus vanellus University of St Andrews: Research Portal Biological Conservation 141 5 1436 1441 |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
topic |
abundance demography management modelling LAPWINGS VANELLUS-VANELLUS RING-RECOVERY DATA SURVIVAL MODELS DYNAMICS POPULATIONS DECLINE CENSUS TRENDS |
spellingShingle |
abundance demography management modelling LAPWINGS VANELLUS-VANELLUS RING-RECOVERY DATA SURVIVAL MODELS DYNAMICS POPULATIONS DECLINE CENSUS TRENDS Brooks, SP Freeman, SN Greenwood, JJD King, Ruth Mazzetta, C Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
topic_facet |
abundance demography management modelling LAPWINGS VANELLUS-VANELLUS RING-RECOVERY DATA SURVIVAL MODELS DYNAMICS POPULATIONS DECLINE CENSUS TRENDS |
description |
For species that are still widespread, obtaining accurate and precise measures of population change inevitably means gathering representative sample data rather than undertaking a complete census. In the UK, a system of raising 'alerts' utilises stochastic models for such data to identify species in rapid (>50%) or moderate (25-50%) decline across various temporal and spatial scales. Considerable improvements in interpretation can be made by explaining annual fluctuations in terms of explicit population models (rather than trends of an arbitrary mathematical form); through the simultaneous modelling of data from a complete or partial census with those providing information on the demographic rates employed in these models; and through adopting a Bayesian rather than a frequentist statistical approach. A Bayesian approach is natural for quantifying, in the form of a probability, the support provided by the data for assigning a species to each of the categories. Based on territory mapping and ringing data for the lapwing Vanellus vanellus, we describe such an approach. Trends are estimated more precisely than those under models previously employed in the alerts context. Some smoothing is induced, but realistic responses to years of severe weather are retained, and these are expressed also via model-averaged trends in key demographic parameters. We discuss the conservation implications for this declining species, and the wider potential arising from the ability to quantify confidence that population change has exceeded a threshold either generating conservation concern or justifying a subsequent programme of action for recovery. (C) 2008 Elsevier Ltd. All rights reserved. |
format |
Article in Journal/Newspaper |
author |
Brooks, SP Freeman, SN Greenwood, JJD King, Ruth Mazzetta, C |
author_facet |
Brooks, SP Freeman, SN Greenwood, JJD King, Ruth Mazzetta, C |
author_sort |
Brooks, SP |
title |
Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
title_short |
Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
title_full |
Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
title_fullStr |
Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
title_full_unstemmed |
Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists |
title_sort |
quantifying conservation concern - bayesian statistics and the red data lists |
publishDate |
2008 |
url |
https://research-portal.st-andrews.ac.uk/en/researchoutput/quantifying-conservation-concern--bayesian-statistics-and-the-red-data-lists(1ab39ad2-ccb7-4eac-a861-3529e114a620).html https://doi.org/10.1016/j.biocon.2008.03.009 http://www.scopus.com/inward/record.url?scp=44149089270&partnerID=8YFLogxK |
genre |
Vanellus vanellus |
genre_facet |
Vanellus vanellus |
op_source |
Brooks , SP , Freeman , SN , Greenwood , JJD , King , R & Mazzetta , C 2008 , ' Quantifying Conservation Concern - Bayesian Statistics and the Red Data Lists ' , Biological Conservation , vol. 141 , no. 5 , pp. 1436-1441 . https://doi.org/10.1016/j.biocon.2008.03.009 |
op_relation |
https://research-portal.st-andrews.ac.uk/en/researchoutput/quantifying-conservation-concern--bayesian-statistics-and-the-red-data-lists(1ab39ad2-ccb7-4eac-a861-3529e114a620).html |
op_rights |
info:eu-repo/semantics/restrictedAccess |
op_doi |
https://doi.org/10.1016/j.biocon.2008.03.009 |
container_title |
Biological Conservation |
container_volume |
141 |
container_issue |
5 |
container_start_page |
1436 |
op_container_end_page |
1441 |
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1802651002573160448 |