Integrated Modeling to Estimate Population Size and Composition of Mule Deer
Estimating population size, age composition, and sex ratio of mule deer (Odocoileus hemionus) is important to conservation and managed hunting of this species in the western United States. Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested...
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Veröffentlicht in: | The Journal of wildlife management 2018-09, Vol.82 (7), p.1429-1441 |
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creator | FURNAS, BRETT J. LANDERS, RUSS H. HILL, SCOTT ITOGA, STUART S. SACKS, BENJAMIN N. |
description | Estimating population size, age composition, and sex ratio of mule deer (Odocoileus hemionus) is important to conservation and managed hunting of this species in the western United States. Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested habitats where aerial surveys are not feasible. These same data can be used to estimate overall sex ratio but require additional data on age structure to quantify adult- and fawn-specific sex ratios, which are expected to differ substantially. We demonstrate an integrated modeling approach to estimating population sizes of adult females, adult males, and fawns from 3 sources of data: fDNA, camera stations, and global positioning system (GPS) telemetry. We conducted the study on an 11,500-km² forested region in northern California, USA, corresponding to 3 hunt management zones. Within a Bayesian framework, we used spatial capture–recapture (SCR) modeling of fDNA samples and prior information on home range sizes from telemetry to estimate sex-specific densities, and N-mixture modeling of camera detections to separate adult and fawn densities. We estimated 29,317 adult females (90% CI = 24,550–34,592), 10,845 adult males (90% CI = 7,778–14,858), and 19,587 fawns (90% CI = 15,340–24,430) within the study area. The inclusion of telemetry increased precision of our results, and cameras provided comparable estimates of density when we calibrated them on the SCR results. Based on these results, we recommend a monitoring program of fDNA transects repeated once every 5 years, camera stations repeated at half of transects every year, and telemetry data from 1 deer for every 2 transects on average. We estimated an average annual cost of $1,316 (U.S.) per transect to sustain this endeavor. The integration of cameras with fDNA to combine age structure data with sex-specific abundance data represents a novel and significant step forward in the capacity to estimate deer population parameters. |
doi_str_mv | 10.1002/jwmg.21507 |
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Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested habitats where aerial surveys are not feasible. These same data can be used to estimate overall sex ratio but require additional data on age structure to quantify adult- and fawn-specific sex ratios, which are expected to differ substantially. We demonstrate an integrated modeling approach to estimating population sizes of adult females, adult males, and fawns from 3 sources of data: fDNA, camera stations, and global positioning system (GPS) telemetry. We conducted the study on an 11,500-km² forested region in northern California, USA, corresponding to 3 hunt management zones. Within a Bayesian framework, we used spatial capture–recapture (SCR) modeling of fDNA samples and prior information on home range sizes from telemetry to estimate sex-specific densities, and N-mixture modeling of camera detections to separate adult and fawn densities. We estimated 29,317 adult females (90% CI = 24,550–34,592), 10,845 adult males (90% CI = 7,778–14,858), and 19,587 fawns (90% CI = 15,340–24,430) within the study area. The inclusion of telemetry increased precision of our results, and cameras provided comparable estimates of density when we calibrated them on the SCR results. Based on these results, we recommend a monitoring program of fDNA transects repeated once every 5 years, camera stations repeated at half of transects every year, and telemetry data from 1 deer for every 2 transects on average. We estimated an average annual cost of $1,316 (U.S.) per transect to sustain this endeavor. The integration of cameras with fDNA to combine age structure data with sex-specific abundance data represents a novel and significant step forward in the capacity to estimate deer population parameters.</description><identifier>ISSN: 0022-541X</identifier><identifier>EISSN: 1937-2817</identifier><identifier>DOI: 10.1002/jwmg.21507</identifier><language>eng</language><publisher>Bethesda: Wiley</publisher><subject>Abundance ; Aerial surveys ; Age ; Age composition ; Animal populations ; Bayesian analysis ; Cameras ; Capture-recapture studies ; Composition ; costs ; Deer ; density ; Deoxyribonucleic acid ; DNA ; Estimation ; fecal DNA ; Females ; Global positioning systems ; GPS ; Home range ; Hunting ; Males ; Modelling ; monitoring ; N‐mixture model ; Odocoileus ; Parameter estimation ; Population Ecology ; Population number ; Population statistics ; Satellite navigation systems ; Sex ; Sex ratio ; spatial capture–recapture ; Stations ; Telemetry ; Wildlife conservation ; Wildlife habitats ; Wildlife management</subject><ispartof>The Journal of wildlife management, 2018-09, Vol.82 (7), p.1429-1441</ispartof><rights>2018 The Authors</rights><rights>2018 The Authors. 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Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested habitats where aerial surveys are not feasible. These same data can be used to estimate overall sex ratio but require additional data on age structure to quantify adult- and fawn-specific sex ratios, which are expected to differ substantially. We demonstrate an integrated modeling approach to estimating population sizes of adult females, adult males, and fawns from 3 sources of data: fDNA, camera stations, and global positioning system (GPS) telemetry. We conducted the study on an 11,500-km² forested region in northern California, USA, corresponding to 3 hunt management zones. Within a Bayesian framework, we used spatial capture–recapture (SCR) modeling of fDNA samples and prior information on home range sizes from telemetry to estimate sex-specific densities, and N-mixture modeling of camera detections to separate adult and fawn densities. We estimated 29,317 adult females (90% CI = 24,550–34,592), 10,845 adult males (90% CI = 7,778–14,858), and 19,587 fawns (90% CI = 15,340–24,430) within the study area. The inclusion of telemetry increased precision of our results, and cameras provided comparable estimates of density when we calibrated them on the SCR results. Based on these results, we recommend a monitoring program of fDNA transects repeated once every 5 years, camera stations repeated at half of transects every year, and telemetry data from 1 deer for every 2 transects on average. We estimated an average annual cost of $1,316 (U.S.) per transect to sustain this endeavor. The integration of cameras with fDNA to combine age structure data with sex-specific abundance data represents a novel and significant step forward in the capacity to estimate deer population parameters.</description><subject>Abundance</subject><subject>Aerial surveys</subject><subject>Age</subject><subject>Age composition</subject><subject>Animal populations</subject><subject>Bayesian analysis</subject><subject>Cameras</subject><subject>Capture-recapture studies</subject><subject>Composition</subject><subject>costs</subject><subject>Deer</subject><subject>density</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>Estimation</subject><subject>fecal DNA</subject><subject>Females</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Home range</subject><subject>Hunting</subject><subject>Males</subject><subject>Modelling</subject><subject>monitoring</subject><subject>N‐mixture model</subject><subject>Odocoileus</subject><subject>Parameter estimation</subject><subject>Population Ecology</subject><subject>Population number</subject><subject>Population statistics</subject><subject>Satellite navigation systems</subject><subject>Sex</subject><subject>Sex ratio</subject><subject>spatial capture–recapture</subject><subject>Stations</subject><subject>Telemetry</subject><subject>Wildlife conservation</subject><subject>Wildlife habitats</subject><subject>Wildlife management</subject><issn>0022-541X</issn><issn>1937-2817</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kN1LwzAUxYMoOKcvvgsB34TO3KRpmkeZUycbCir6FvqRjJauqUnLmH-93ao--nTh3N-5HwehcyATIIRel5v1akKBE3GARiCZCGgM4hCN-iYNeAgfx-jE-5IQBhBHI7SY161euaTVOV7aXFdFvcKtxTPfFutexc-26aqkLWyNX4ovjZM6x1O7bqwv9qI1eNlVGt9q7U7RkUkqr89-6hi93c1epw_B4ul-Pr1ZBFlIuQhSFlNGUwoylkmeSy2lkAZklposSfvLMslkFKU55zzloE0aJSHLQBrJjADDxuhymNs4-9lp36rSdq7uVypKJMRChJL11NVAZc5677RRjet_clsFRO3SUru01D6tHoYB3hSV3v5Dqsf35f2v52LwlL617s9DowgI44x9A0CHdfU</recordid><startdate>201809</startdate><enddate>201809</enddate><creator>FURNAS, BRETT J.</creator><creator>LANDERS, RUSS H.</creator><creator>HILL, SCOTT</creator><creator>ITOGA, STUART S.</creator><creator>SACKS, BENJAMIN N.</creator><general>Wiley</general><general>Blackwell Publishing Ltd</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7QL</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7U6</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>M7N</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0003-0143-6589</orcidid></search><sort><creationdate>201809</creationdate><title>Integrated Modeling to Estimate Population Size and Composition of Mule Deer</title><author>FURNAS, BRETT J. ; LANDERS, RUSS H. ; HILL, SCOTT ; ITOGA, STUART S. ; SACKS, BENJAMIN N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4257-b38232b21989add9e9979f19cbfcab031c93966bd555b51efb6a43c19f93f71f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abundance</topic><topic>Aerial surveys</topic><topic>Age</topic><topic>Age composition</topic><topic>Animal populations</topic><topic>Bayesian analysis</topic><topic>Cameras</topic><topic>Capture-recapture studies</topic><topic>Composition</topic><topic>costs</topic><topic>Deer</topic><topic>density</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>Estimation</topic><topic>fecal DNA</topic><topic>Females</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Home range</topic><topic>Hunting</topic><topic>Males</topic><topic>Modelling</topic><topic>monitoring</topic><topic>N‐mixture model</topic><topic>Odocoileus</topic><topic>Parameter estimation</topic><topic>Population Ecology</topic><topic>Population number</topic><topic>Population statistics</topic><topic>Satellite navigation systems</topic><topic>Sex</topic><topic>Sex ratio</topic><topic>spatial capture–recapture</topic><topic>Stations</topic><topic>Telemetry</topic><topic>Wildlife conservation</topic><topic>Wildlife habitats</topic><topic>Wildlife management</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>FURNAS, BRETT J.</creatorcontrib><creatorcontrib>LANDERS, RUSS H.</creatorcontrib><creatorcontrib>HILL, SCOTT</creatorcontrib><creatorcontrib>ITOGA, STUART S.</creatorcontrib><creatorcontrib>SACKS, BENJAMIN N.</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Online Library Free Content</collection><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Sustainability Science Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>The Journal of wildlife management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>FURNAS, BRETT J.</au><au>LANDERS, RUSS H.</au><au>HILL, SCOTT</au><au>ITOGA, STUART S.</au><au>SACKS, BENJAMIN N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrated Modeling to Estimate Population Size and Composition of Mule Deer</atitle><jtitle>The Journal of wildlife management</jtitle><date>2018-09</date><risdate>2018</risdate><volume>82</volume><issue>7</issue><spage>1429</spage><epage>1441</epage><pages>1429-1441</pages><issn>0022-541X</issn><eissn>1937-2817</eissn><abstract>Estimating population size, age composition, and sex ratio of mule deer (Odocoileus hemionus) is important to conservation and managed hunting of this species in the western United States. Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested habitats where aerial surveys are not feasible. These same data can be used to estimate overall sex ratio but require additional data on age structure to quantify adult- and fawn-specific sex ratios, which are expected to differ substantially. We demonstrate an integrated modeling approach to estimating population sizes of adult females, adult males, and fawns from 3 sources of data: fDNA, camera stations, and global positioning system (GPS) telemetry. We conducted the study on an 11,500-km² forested region in northern California, USA, corresponding to 3 hunt management zones. Within a Bayesian framework, we used spatial capture–recapture (SCR) modeling of fDNA samples and prior information on home range sizes from telemetry to estimate sex-specific densities, and N-mixture modeling of camera detections to separate adult and fawn densities. We estimated 29,317 adult females (90% CI = 24,550–34,592), 10,845 adult males (90% CI = 7,778–14,858), and 19,587 fawns (90% CI = 15,340–24,430) within the study area. The inclusion of telemetry increased precision of our results, and cameras provided comparable estimates of density when we calibrated them on the SCR results. Based on these results, we recommend a monitoring program of fDNA transects repeated once every 5 years, camera stations repeated at half of transects every year, and telemetry data from 1 deer for every 2 transects on average. We estimated an average annual cost of $1,316 (U.S.) per transect to sustain this endeavor. The integration of cameras with fDNA to combine age structure data with sex-specific abundance data represents a novel and significant step forward in the capacity to estimate deer population parameters.</abstract><cop>Bethesda</cop><pub>Wiley</pub><doi>10.1002/jwmg.21507</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-0143-6589</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abundance Aerial surveys Age Age composition Animal populations Bayesian analysis Cameras Capture-recapture studies Composition costs Deer density Deoxyribonucleic acid DNA Estimation fecal DNA Females Global positioning systems GPS Home range Hunting Males Modelling monitoring N‐mixture model Odocoileus Parameter estimation Population Ecology Population number Population statistics Satellite navigation systems Sex Sex ratio spatial capture–recapture Stations Telemetry Wildlife conservation Wildlife habitats Wildlife management |
title | Integrated Modeling to Estimate Population Size and Composition of Mule Deer |
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