Loading…
Bayesian shared frailty models for regional inference about wildlife survival
Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but inf...
Saved in:
Published in: | Animal conservation 2012-04, Vol.15 (2), p.117-124 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553 |
---|---|
cites | cdi_FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553 |
container_end_page | 124 |
container_issue | 2 |
container_start_page | 117 |
container_title | Animal conservation |
container_volume | 15 |
creator | Halstead, B. J. Wylie, G. D. Coates, P. S. Valcarcel, P. Casazza, M. L. |
description | Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates
Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology
The estimation of survival is an essential but difficult task important for developing rigorous conservation programs. Radio telemetry studies of wildlife survival are often characterized by small sample sizes and high rates of censoring. In cases where multiple radio telemetry studies of a species exist, shared frailty models of survival offer the ability to combine data from multiple studies and improve the precision of survival estimates. We used Bayesian analysis of shared frailty models to examine survival of adult females of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California, USA, and to examine the effects of individual and habitat characteristics on daily risk of mortality. Posterior mean annual survival probability of adult females was 0.61 [95% credible interval (CI) = 0.41–0.79]. The daily risk of mortality for adult female giant gartersnakes while in terrestrial habitats was 0.38 (0.09–0.89) times as great as when they inhabited aquatic habitats. Although 95% CIs for hazard ratios of other covariates included one, sites varied substantially in the effect of linear habitats, which appear to have context‐dependent effects on survival. Assessing survival with shared frailty models allows the prediction of survival probabilities at novel sites and identifies regional and context‐specific mortality risks that can be targeted for conservation action. |
doi_str_mv | 10.1111/j.1469-1795.2011.00495.x |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1008844541</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1008844541</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553</originalsourceid><addsrcrecordid>eNqNkMFPwjAUxhejiYj-D028eBm2rO22xAuigAliYhC9NWV71WLZsGXI_ns7MBw82Utf877v63u_IEAEd4g_14sOoTwNSZyyThcT0sGY-nJ7FLQOjWNfRzwOUxrh0-DMuQXGpJtEpBU83soanJYFch_SQo6Uldqsa7QsczAOqdIiC--6LKRBulBgocgAyXlZrdG3NrnRCpCr7EZvpDkPTpQ0Di5-73bwMrif9kfh-Gn40O-Nw4xywkKQfhxK5l2e4YilZE6AqiQnc8W7MeM551JFPMsZyNi_vSRNExUT4HHEGWNRO7ja565s-VWBW4uldhkYIwsoKycIxklCKaPESy__SBdlZf02XsUoTWiM0yYw2asyWzpnQYmV1Utpax8lGs5iIRqcosEpGs5ix1lsvfVmb_U0oP63T_T6M7r7OdzbtVvD9mCX9lP4bWMmXidD8TaaTgbP-E7Moh-sV5Gc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1544847095</pqid></control><display><type>article</type><title>Bayesian shared frailty models for regional inference about wildlife survival</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Halstead, B. J. ; Wylie, G. D. ; Coates, P. S. ; Valcarcel, P. ; Casazza, M. L.</creator><contributor>Altwegg, Res ; Schaub, Michael ; Schaub, Michael ; Altwegg, Res</contributor><creatorcontrib>Halstead, B. J. ; Wylie, G. D. ; Coates, P. S. ; Valcarcel, P. ; Casazza, M. L. ; Altwegg, Res ; Schaub, Michael ; Schaub, Michael ; Altwegg, Res</creatorcontrib><description>Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates
Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology
The estimation of survival is an essential but difficult task important for developing rigorous conservation programs. Radio telemetry studies of wildlife survival are often characterized by small sample sizes and high rates of censoring. In cases where multiple radio telemetry studies of a species exist, shared frailty models of survival offer the ability to combine data from multiple studies and improve the precision of survival estimates. We used Bayesian analysis of shared frailty models to examine survival of adult females of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California, USA, and to examine the effects of individual and habitat characteristics on daily risk of mortality. Posterior mean annual survival probability of adult females was 0.61 [95% credible interval (CI) = 0.41–0.79]. The daily risk of mortality for adult female giant gartersnakes while in terrestrial habitats was 0.38 (0.09–0.89) times as great as when they inhabited aquatic habitats. Although 95% CIs for hazard ratios of other covariates included one, sites varied substantially in the effect of linear habitats, which appear to have context‐dependent effects on survival. Assessing survival with shared frailty models allows the prediction of survival probabilities at novel sites and identifies regional and context‐specific mortality risks that can be targeted for conservation action.</description><identifier>ISSN: 1367-9430</identifier><identifier>EISSN: 1469-1795</identifier><identifier>DOI: 10.1111/j.1469-1795.2011.00495.x</identifier><language>eng</language><publisher>London: Blackwell Publishing Ltd</publisher><subject>Animal behavior ; Bayesian analysis ; Biotelemetry ; Conservation ; Data processing ; Frailty ; giant gartersnake ; Habitat ; hierarchical model ; Mathematical models ; Mortality ; proportional hazards ; random effects ; Survival ; Telemetry ; Thamnophis gigas ; valleys ; Wildlife</subject><ispartof>Animal conservation, 2012-04, Vol.15 (2), p.117-124</ispartof><rights>2011 The Authors. Animal Conservation © 2011 The Zoological Society of London</rights><rights>Animal Conservation © 2012 The Zoological Society of London</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553</citedby><cites>FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><contributor>Altwegg, Res</contributor><contributor>Schaub, Michael</contributor><contributor>Schaub, Michael</contributor><contributor>Altwegg, Res</contributor><creatorcontrib>Halstead, B. J.</creatorcontrib><creatorcontrib>Wylie, G. D.</creatorcontrib><creatorcontrib>Coates, P. S.</creatorcontrib><creatorcontrib>Valcarcel, P.</creatorcontrib><creatorcontrib>Casazza, M. L.</creatorcontrib><title>Bayesian shared frailty models for regional inference about wildlife survival</title><title>Animal conservation</title><addtitle>Anim Conserv</addtitle><description>Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates
Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology
The estimation of survival is an essential but difficult task important for developing rigorous conservation programs. Radio telemetry studies of wildlife survival are often characterized by small sample sizes and high rates of censoring. In cases where multiple radio telemetry studies of a species exist, shared frailty models of survival offer the ability to combine data from multiple studies and improve the precision of survival estimates. We used Bayesian analysis of shared frailty models to examine survival of adult females of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California, USA, and to examine the effects of individual and habitat characteristics on daily risk of mortality. Posterior mean annual survival probability of adult females was 0.61 [95% credible interval (CI) = 0.41–0.79]. The daily risk of mortality for adult female giant gartersnakes while in terrestrial habitats was 0.38 (0.09–0.89) times as great as when they inhabited aquatic habitats. Although 95% CIs for hazard ratios of other covariates included one, sites varied substantially in the effect of linear habitats, which appear to have context‐dependent effects on survival. Assessing survival with shared frailty models allows the prediction of survival probabilities at novel sites and identifies regional and context‐specific mortality risks that can be targeted for conservation action.</description><subject>Animal behavior</subject><subject>Bayesian analysis</subject><subject>Biotelemetry</subject><subject>Conservation</subject><subject>Data processing</subject><subject>Frailty</subject><subject>giant gartersnake</subject><subject>Habitat</subject><subject>hierarchical model</subject><subject>Mathematical models</subject><subject>Mortality</subject><subject>proportional hazards</subject><subject>random effects</subject><subject>Survival</subject><subject>Telemetry</subject><subject>Thamnophis gigas</subject><subject>valleys</subject><subject>Wildlife</subject><issn>1367-9430</issn><issn>1469-1795</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNqNkMFPwjAUxhejiYj-D028eBm2rO22xAuigAliYhC9NWV71WLZsGXI_ns7MBw82Utf877v63u_IEAEd4g_14sOoTwNSZyyThcT0sGY-nJ7FLQOjWNfRzwOUxrh0-DMuQXGpJtEpBU83soanJYFch_SQo6Uldqsa7QsczAOqdIiC--6LKRBulBgocgAyXlZrdG3NrnRCpCr7EZvpDkPTpQ0Di5-73bwMrif9kfh-Gn40O-Nw4xywkKQfhxK5l2e4YilZE6AqiQnc8W7MeM551JFPMsZyNi_vSRNExUT4HHEGWNRO7ja565s-VWBW4uldhkYIwsoKycIxklCKaPESy__SBdlZf02XsUoTWiM0yYw2asyWzpnQYmV1Utpax8lGs5iIRqcosEpGs5ix1lsvfVmb_U0oP63T_T6M7r7OdzbtVvD9mCX9lP4bWMmXidD8TaaTgbP-E7Moh-sV5Gc</recordid><startdate>201204</startdate><enddate>201204</enddate><creator>Halstead, B. J.</creator><creator>Wylie, G. D.</creator><creator>Coates, P. S.</creator><creator>Valcarcel, P.</creator><creator>Casazza, M. L.</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7U6</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H97</scope><scope>L.G</scope><scope>P64</scope><scope>RC3</scope></search><sort><creationdate>201204</creationdate><title>Bayesian shared frailty models for regional inference about wildlife survival</title><author>Halstead, B. J. ; Wylie, G. D. ; Coates, P. S. ; Valcarcel, P. ; Casazza, M. L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Animal behavior</topic><topic>Bayesian analysis</topic><topic>Biotelemetry</topic><topic>Conservation</topic><topic>Data processing</topic><topic>Frailty</topic><topic>giant gartersnake</topic><topic>Habitat</topic><topic>hierarchical model</topic><topic>Mathematical models</topic><topic>Mortality</topic><topic>proportional hazards</topic><topic>random effects</topic><topic>Survival</topic><topic>Telemetry</topic><topic>Thamnophis gigas</topic><topic>valleys</topic><topic>Wildlife</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Halstead, B. J.</creatorcontrib><creatorcontrib>Wylie, G. D.</creatorcontrib><creatorcontrib>Coates, P. S.</creatorcontrib><creatorcontrib>Valcarcel, P.</creatorcontrib><creatorcontrib>Casazza, M. L.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Animal conservation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Halstead, B. J.</au><au>Wylie, G. D.</au><au>Coates, P. S.</au><au>Valcarcel, P.</au><au>Casazza, M. L.</au><au>Altwegg, Res</au><au>Schaub, Michael</au><au>Schaub, Michael</au><au>Altwegg, Res</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bayesian shared frailty models for regional inference about wildlife survival</atitle><jtitle>Animal conservation</jtitle><addtitle>Anim Conserv</addtitle><date>2012-04</date><risdate>2012</risdate><volume>15</volume><issue>2</issue><spage>117</spage><epage>124</epage><pages>117-124</pages><issn>1367-9430</issn><eissn>1469-1795</eissn><abstract>Read the Commentaries on this Feature Paper: Combining information in hierarchical models improves inferences in population ecology and demographic population analyses; Bayesian shared frailty models for regional inference about wildlife survival; ‘Each site has its own survival probability, but information is borrowed across sites to tell us about survival in each site’: random effects models as means of borrowing strength in survival studies of wild vertebrates
Response from the authors: ‘Exciting statistics’: the rapid development and promising future of hierarchical models for population ecology
The estimation of survival is an essential but difficult task important for developing rigorous conservation programs. Radio telemetry studies of wildlife survival are often characterized by small sample sizes and high rates of censoring. In cases where multiple radio telemetry studies of a species exist, shared frailty models of survival offer the ability to combine data from multiple studies and improve the precision of survival estimates. We used Bayesian analysis of shared frailty models to examine survival of adult females of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California, USA, and to examine the effects of individual and habitat characteristics on daily risk of mortality. Posterior mean annual survival probability of adult females was 0.61 [95% credible interval (CI) = 0.41–0.79]. The daily risk of mortality for adult female giant gartersnakes while in terrestrial habitats was 0.38 (0.09–0.89) times as great as when they inhabited aquatic habitats. Although 95% CIs for hazard ratios of other covariates included one, sites varied substantially in the effect of linear habitats, which appear to have context‐dependent effects on survival. Assessing survival with shared frailty models allows the prediction of survival probabilities at novel sites and identifies regional and context‐specific mortality risks that can be targeted for conservation action.</abstract><cop>London</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/j.1469-1795.2011.00495.x</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1367-9430 |
ispartof | Animal conservation, 2012-04, Vol.15 (2), p.117-124 |
issn | 1367-9430 1469-1795 |
language | eng |
recordid | cdi_proquest_miscellaneous_1008844541 |
source | Wiley-Blackwell Read & Publish Collection |
subjects | Animal behavior Bayesian analysis Biotelemetry Conservation Data processing Frailty giant gartersnake Habitat hierarchical model Mathematical models Mortality proportional hazards random effects Survival Telemetry Thamnophis gigas valleys Wildlife |
title | Bayesian shared frailty models for regional inference about wildlife survival |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T23%3A59%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Bayesian%20shared%20frailty%20models%20for%20regional%20inference%20about%20wildlife%20survival&rft.jtitle=Animal%20conservation&rft.au=Halstead,%20B.%20J.&rft.date=2012-04&rft.volume=15&rft.issue=2&rft.spage=117&rft.epage=124&rft.pages=117-124&rft.issn=1367-9430&rft.eissn=1469-1795&rft_id=info:doi/10.1111/j.1469-1795.2011.00495.x&rft_dat=%3Cproquest_cross%3E1008844541%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4615-ea13641b26c03591b1e4f8d1bf62756d66af36cd5ea7756359998f71e67365553%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1544847095&rft_id=info:pmid/&rfr_iscdi=true |