Incorporating Detection Probability to Estimate Pheasant Density
Indices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants (Phasi...
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Veröffentlicht in: | The Journal of wildlife management 2018-11, Vol.82 (8), p.1680-1688 |
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description | Indices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants (Phasianus colchicus) were translocated to 10 study areas in Pennsylvania from 2007 to 2014 with the goal of establishing female densities of 3.86 pheasants/km². We developed a population density estimator that used 3-minute crowing counts adjusted for probability of detection to estimate male pheasant density and flushing surveys to estimate the female:male ratio. To account for detection probability, we estimated the probability a pheasant was available to be detected by monitoring crowing frequency of male pheasants fitted with radio-transmitters and the probability an observer was able to detect a crowing pheasant at distances from 0 to 0.93 km. We found the probability a pheasant crowed during 3 minutes decreased linearly over our survey period from 0.66 in mid-April to 0.46 by the end of May. At the farthest distance we were able to accurately detect a crowing pheasant. We estimated the probability of detecting a pheasant at 0.80 km to be 0.019 ± 0.005 (SE), which means that we could not assume any fixed distance beyond which crowing birds could not be detected. Therefore, we replaced the probability of detection in the standard distance sampling estimator with the effective area of detection. The estimation of the effective area of detection is robust to choice of radius of the point and did not require observers to estimate the distance to crowing pheasants. We estimated the female:male ratio to be 1.02:1, despite the ratio of released pheasants being 4.46:1. Only 1 study area achieved the female density goal (D̂ = 4.16); the maximum density at all other study areas was |
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DAVID ; KLINGER, SCOTT R. ; DIEFENBACH, DUANE R.</creator><creatorcontrib>WILLIAMSON, LACEY T. ; WALTER, W. DAVID ; KLINGER, SCOTT R. ; DIEFENBACH, DUANE R.</creatorcontrib><description>Indices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants (Phasianus colchicus) were translocated to 10 study areas in Pennsylvania from 2007 to 2014 with the goal of establishing female densities of 3.86 pheasants/km². We developed a population density estimator that used 3-minute crowing counts adjusted for probability of detection to estimate male pheasant density and flushing surveys to estimate the female:male ratio. To account for detection probability, we estimated the probability a pheasant was available to be detected by monitoring crowing frequency of male pheasants fitted with radio-transmitters and the probability an observer was able to detect a crowing pheasant at distances from 0 to 0.93 km. We found the probability a pheasant crowed during 3 minutes decreased linearly over our survey period from 0.66 in mid-April to 0.46 by the end of May. At the farthest distance we were able to accurately detect a crowing pheasant. We estimated the probability of detecting a pheasant at 0.80 km to be 0.019 ± 0.005 (SE), which means that we could not assume any fixed distance beyond which crowing birds could not be detected. Therefore, we replaced the probability of detection in the standard distance sampling estimator with the effective area of detection. The estimation of the effective area of detection is robust to choice of radius of the point and did not require observers to estimate the distance to crowing pheasants. We estimated the female:male ratio to be 1.02:1, despite the ratio of released pheasants being 4.46:1. Only 1 study area achieved the female density goal (D̂ = 4.16); the maximum density at all other study areas was <2 females/km². The estimator we developed incorporated multiple detection probabilities to provide density estimates and simplified the crowing count protocol by eliminating the need for observers to estimate their distance from a detected bird, which makes the estimator useful for estimation of population abundance when explicit population density objectives must be evaluated.</description><identifier>ISSN: 0022-541X</identifier><identifier>EISSN: 1937-2817</identifier><identifier>DOI: 10.1002/jwmg.21545</identifier><language>eng</language><publisher>Bethesda: Wiley</publisher><subject>Abundance ; Bird populations ; Birds ; density estimation ; detection probability ; Females ; Information management ; Observers ; Pennsylvania ; Phasianus colchicus ; Polls & surveys ; Population density ; Population Ecology ; Population statistics ; Probability ; restoration ; ring‐necked pheasant ; Transmitters ; Wildlife ; Wildlife management</subject><ispartof>The Journal of wildlife management, 2018-11, Vol.82 (8), p.1680-1688</ispartof><rights>2018 The Wildlife Society</rights><rights>The Wildlife Society, 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2825-67e5f58eddef31d9b58d86ee341e6e925393de927029c5b1645cc2c568a922433</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26609495$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26609495$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,1411,27901,27902,45550,45551,57992,58225</link.rule.ids></links><search><creatorcontrib>WILLIAMSON, LACEY T.</creatorcontrib><creatorcontrib>WALTER, W. DAVID</creatorcontrib><creatorcontrib>KLINGER, SCOTT R.</creatorcontrib><creatorcontrib>DIEFENBACH, DUANE R.</creatorcontrib><title>Incorporating Detection Probability to Estimate Pheasant Density</title><title>The Journal of wildlife management</title><description>Indices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants (Phasianus colchicus) were translocated to 10 study areas in Pennsylvania from 2007 to 2014 with the goal of establishing female densities of 3.86 pheasants/km². We developed a population density estimator that used 3-minute crowing counts adjusted for probability of detection to estimate male pheasant density and flushing surveys to estimate the female:male ratio. To account for detection probability, we estimated the probability a pheasant was available to be detected by monitoring crowing frequency of male pheasants fitted with radio-transmitters and the probability an observer was able to detect a crowing pheasant at distances from 0 to 0.93 km. We found the probability a pheasant crowed during 3 minutes decreased linearly over our survey period from 0.66 in mid-April to 0.46 by the end of May. At the farthest distance we were able to accurately detect a crowing pheasant. We estimated the probability of detecting a pheasant at 0.80 km to be 0.019 ± 0.005 (SE), which means that we could not assume any fixed distance beyond which crowing birds could not be detected. Therefore, we replaced the probability of detection in the standard distance sampling estimator with the effective area of detection. The estimation of the effective area of detection is robust to choice of radius of the point and did not require observers to estimate the distance to crowing pheasants. We estimated the female:male ratio to be 1.02:1, despite the ratio of released pheasants being 4.46:1. Only 1 study area achieved the female density goal (D̂ = 4.16); the maximum density at all other study areas was <2 females/km². The estimator we developed incorporated multiple detection probabilities to provide density estimates and simplified the crowing count protocol by eliminating the need for observers to estimate their distance from a detected bird, which makes the estimator useful for estimation of population abundance when explicit population density objectives must be evaluated.</description><subject>Abundance</subject><subject>Bird populations</subject><subject>Birds</subject><subject>density estimation</subject><subject>detection probability</subject><subject>Females</subject><subject>Information management</subject><subject>Observers</subject><subject>Pennsylvania</subject><subject>Phasianus colchicus</subject><subject>Polls & surveys</subject><subject>Population density</subject><subject>Population Ecology</subject><subject>Population statistics</subject><subject>Probability</subject><subject>restoration</subject><subject>ring‐necked pheasant</subject><subject>Transmitters</subject><subject>Wildlife</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><recordid>eNp9kDFPwzAUhC0EEqWwsCNFYkNK8bNjJ95ApZSiIjqAYLMSxymJ0rjYrqr-e1wCjEw33Hf3ng6hc8AjwJhcN9vVckSAJewADUDQNCYZpIdoEEwSswTej9GJcw3GFCDjA3Qz65Sxa2NzX3fL6E57rXxtumhhTZEXdVv7XeRNNHG-XuVeR4sPnbu88wHtXDBP0VGVt06f_egQvd5PXsYP8fx5OhvfzmNFMsJinmpWsUyXpa4olKJgWZlxrWkCmmtBGBW0DJpiIhQrgCdMKaIYz3JBSELpEF32vWtrPjfaedmYje3CSUmAJEBTIDxQVz2lrHHO6kqubfjb7iRguV9I7heS3wsFGHp4W7d69w8pH9-epr-Ziz7TOG_sX4ZwjkUiGP0CYZdxyg</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>WILLIAMSON, LACEY T.</creator><creator>WALTER, W. DAVID</creator><creator>KLINGER, SCOTT R.</creator><creator>DIEFENBACH, DUANE R.</creator><general>Wiley</general><general>Blackwell Publishing Ltd</general><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></search><sort><creationdate>20181101</creationdate><title>Incorporating Detection Probability to Estimate Pheasant Density</title><author>WILLIAMSON, LACEY T. ; WALTER, W. DAVID ; KLINGER, SCOTT R. ; DIEFENBACH, DUANE R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2825-67e5f58eddef31d9b58d86ee341e6e925393de927029c5b1645cc2c568a922433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abundance</topic><topic>Bird populations</topic><topic>Birds</topic><topic>density estimation</topic><topic>detection probability</topic><topic>Females</topic><topic>Information management</topic><topic>Observers</topic><topic>Pennsylvania</topic><topic>Phasianus colchicus</topic><topic>Polls & surveys</topic><topic>Population density</topic><topic>Population Ecology</topic><topic>Population statistics</topic><topic>Probability</topic><topic>restoration</topic><topic>ring‐necked pheasant</topic><topic>Transmitters</topic><topic>Wildlife</topic><topic>Wildlife management</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>WILLIAMSON, LACEY T.</creatorcontrib><creatorcontrib>WALTER, W. DAVID</creatorcontrib><creatorcontrib>KLINGER, SCOTT R.</creatorcontrib><creatorcontrib>DIEFENBACH, DUANE R.</creatorcontrib><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>WILLIAMSON, LACEY T.</au><au>WALTER, W. DAVID</au><au>KLINGER, SCOTT R.</au><au>DIEFENBACH, DUANE R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Incorporating Detection Probability to Estimate Pheasant Density</atitle><jtitle>The Journal of wildlife management</jtitle><date>2018-11-01</date><risdate>2018</risdate><volume>82</volume><issue>8</issue><spage>1680</spage><epage>1688</epage><pages>1680-1688</pages><issn>0022-541X</issn><eissn>1937-2817</eissn><abstract>Indices of abundance, such as point counts, commonly are used to monitor trends in bird populations. In some circumstances, however, an index of abundance provides insufficient information for making management decisions and accurate density estimates are necessary. Wild ring-necked pheasants (Phasianus colchicus) were translocated to 10 study areas in Pennsylvania from 2007 to 2014 with the goal of establishing female densities of 3.86 pheasants/km². We developed a population density estimator that used 3-minute crowing counts adjusted for probability of detection to estimate male pheasant density and flushing surveys to estimate the female:male ratio. To account for detection probability, we estimated the probability a pheasant was available to be detected by monitoring crowing frequency of male pheasants fitted with radio-transmitters and the probability an observer was able to detect a crowing pheasant at distances from 0 to 0.93 km. We found the probability a pheasant crowed during 3 minutes decreased linearly over our survey period from 0.66 in mid-April to 0.46 by the end of May. At the farthest distance we were able to accurately detect a crowing pheasant. We estimated the probability of detecting a pheasant at 0.80 km to be 0.019 ± 0.005 (SE), which means that we could not assume any fixed distance beyond which crowing birds could not be detected. Therefore, we replaced the probability of detection in the standard distance sampling estimator with the effective area of detection. The estimation of the effective area of detection is robust to choice of radius of the point and did not require observers to estimate the distance to crowing pheasants. We estimated the female:male ratio to be 1.02:1, despite the ratio of released pheasants being 4.46:1. Only 1 study area achieved the female density goal (D̂ = 4.16); the maximum density at all other study areas was <2 females/km². The estimator we developed incorporated multiple detection probabilities to provide density estimates and simplified the crowing count protocol by eliminating the need for observers to estimate their distance from a detected bird, which makes the estimator useful for estimation of population abundance when explicit population density objectives must be evaluated.</abstract><cop>Bethesda</cop><pub>Wiley</pub><doi>10.1002/jwmg.21545</doi><tpages>9</tpages></addata></record> |
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subjects | Abundance Bird populations Birds density estimation detection probability Females Information management Observers Pennsylvania Phasianus colchicus Polls & surveys Population density Population Ecology Population statistics Probability restoration ring‐necked pheasant Transmitters Wildlife Wildlife management |
title | Incorporating Detection Probability to Estimate Pheasant Density |
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