Reliability of Different Mark-Recapture Methods for Population Size Estimation Tested against Reference Population Sizes Constructed from Field Data
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{"title"=>"Reliability of different mark-recapture methods for population size estimation tested against reference population sizes constructed from field data", "type"=>"journal", "authors"=>[{"first_name"=>"Annegret", "last_name"=>"Grimm", "scopus_author_id"=>"56206149200"}, {"first_name"=>"Bernd", "last_name"=>"Gruber", "scopus_author_id"=>"7006623335"}, {"first_name"=>"Klaus", "last_name"=>"Henle", "scopus_author_id"=>"7005254240"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84902531902", "doi"=>"10.1371/journal.pone.0098840", "pui"=>"373324013", "pmid"=>"24896260", "scopus"=>"2-s2.0-84902531902", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"5a56bcbd-508c-3719-b5ce-230e237f62a0", "abstract"=>"Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko Gehyra variegata to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the performance of mark-recapture population size estimators under field conditions, which is essential for selecting an appropriate method and obtaining reliable results in ecology and conservation biology, and thus for sound management.", "link"=>"http://www.mendeley.com/research/reliability-different-markrecapture-methods-population-size-estimation-tested-against-reference-popu", "reader_count"=>102, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>2, "Researcher"=>16, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>8, "Student > Master"=>16, "Other"=>4, "Student > Bachelor"=>24, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>2, "Researcher"=>16, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>8, "Student > Master"=>16, "Other"=>4, "Student > Bachelor"=>24, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Environmental Science"=>22, "Nursing and Health Professions"=>1, "Agricultural and Biological Sciences"=>71, "Medicine and Dentistry"=>1, "Business, Management and Accounting"=>1, "Social Sciences"=>1, "Computer Science"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>71}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>22}}, "reader_count_by_country"=>{"Canada"=>1, "Colombia"=>1, "Czech Republic"=>1, "United States"=>1, "Uruguay"=>1, "Finland"=>1, "Brazil"=>2, "United Kingdom"=>1, "Australia"=>1, "France"=>1, "Portugal"=>1, "Spain"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1520895"], "description"=>"<p>Comparison of different methods for population size estimates with the partly independent reference population sizes (connected by a line). LP: Lincoln-Petersen; MLP: Multiple Lincoln-Petersen; MPE: Mean Petersen estimate; IntJK: Interpolated jackknife; ME: Moment estimator; SC1: Sample coverage 1; SC2: Sample coverage 2; EE: Estimating equation.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimates"], "article_id"=>1045937, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Population_size_estimates_of_partly_independent_entities_/1045937", "title"=>"Population size estimates of partly independent entities.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520896"], "description"=>"<p>Comparison of different methods for population size estimates with the fully independent reference population sizes (connected by a line). LP: Lincoln-Petersen; MLP: Multiple Lincoln-Petersen; MPE: Mean Petersen estimate; IntJK: Interpolated jackknife; ME: Moment estimator; SC1: Sample coverage 1; SC2: Sample coverage 2; EE: Estimating equation.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimates"], "article_id"=>1045938, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.g002", "stats"=>{"downloads"=>1, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Population_size_estimates_of_fully_independent_entities_/1045938", "title"=>"Population size estimates of fully independent entities.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520897"], "description"=>"<p>LP: Lincoln-Petersen. MLP: Multiple Lincoln-Petersen. MPE: Mean Petersen estimate. Int. JK: Interpolated jackknife. ME: Moment estimator. SC1: Sample coverage 1. SC2: Sample coverage 2. EE: Estimating equation. Tr. geom. distribution: Truncated geometric distribution.</p><p>Ranking positions with difference <50% of the best model are shown in bold.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimators"], "article_id"=>1045939, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.t005", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ranking_of_estimators_for_the_fully_independent_data_/1045939", "title"=>"Ranking of estimators for the fully independent data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520898"], "description"=>"<p><i>f<sub>k</sub></i>: number of individuals captured <i>k</i> times. <i>S</i>: number of distinct individuals captured. <i>p<sub>tr</sub></i>: daily threshold capture probability for which 95% of individuals are expected to be included in the reference population. <i>CV</i>: coefficient of variation (degree of heterogeneity). LP: Lincoln-Petersen; MLP: Multiple Lincoln-Petersen; MPE: Mean Petersen estimate; IntJK: Interpolated jackknife; ME: Moment estimator; SC1: Sample coverage 1; SC2: Sample coverage 2; EE: Estimating equation.</p><p>The 95%-confidence interval is shown in brackets. Estimations that cover the reference population size are highlighted in bold.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimation"], "article_id"=>1045940, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.t004", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_for_population_size_estimation_with_fully_independent_data_/1045940", "title"=>"Results for population size estimation with fully independent data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520899"], "description"=>"<p>LP: Lincoln-Petersen. MLP: Multiple Lincoln-Petersen. MPE: Mean Petersen estimate. Int. JK: Interpolated jackknife. ME: Moment estimator. SC1: Sample coverage 1. SC2: Sample coverage 2. EE: Estimating equation. Tr. geom. distribution: Truncated geometric distribution.</p><p><b>Ranking positions with difference <50% of the best model are shown in bold.</b></p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimators"], "article_id"=>1045941, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.t003", "stats"=>{"downloads"=>6, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ranking_of_estimators_for_the_partly_independent_data_/1045941", "title"=>"Ranking of estimators for the partly independent data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520900"], "description"=>"<p><i>f<sub>k</sub></i>: Number of individuals captured <i>k</i> times. <i>S</i>: number of distinct individuals captured. <i>p<sub>tr</sub></i>: daily threshold capture probability for which 95% of individuals are expected to be included in the reference population. <i>CV</i>: coefficient of variation (degree of heterogeneity). LP: Lincoln-Petersen; MLP: Multiple Lincoln-Petersen; MPE: Mean Petersen estimate; IntJK: Interpolated jackknife; ME: Moment estimator; SC1: Sample coverage 1; SC2: Sample coverage 2; EE: Estimating equation.</p><p>The 95%-confidence interval is shown in brackets. Estimations that cover the reference population size are highlighted in bold.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "estimation"], "article_id"=>1045942, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.t002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_for_population_size_estimation_with_partly_independent_data_/1045942", "title"=>"Results for population size estimation with partly independent data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520901"], "description"=>"<p>Overview on all tested population size estimators including their references, basics, and model selection procedures.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "tested", "estimators"], "article_id"=>1045943, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_on_all_tested_population_size_estimators_including_their_references_basics_and_model_selection_procedures_/1045943", "title"=>"Overview on all tested population size estimators including their references, basics, and model selection procedures.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/1520902"], "description"=>"<div><p>Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko <i>Gehyra variegata</i> to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the performance of mark-recapture population size estimators under field conditions, which is essential for selecting an appropriate method and obtaining reliable results in ecology and conservation biology, and thus for sound management.</p></div>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "ecology", "Ecological metrics", "Population growth", "Population ecology", "Population biology", "Population metrics", "Conservation science", "mark-recapture", "methods", "estimation", "tested", "sizes", "constructed"], "article_id"=>1045944, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Annegret Grimm", "Bernd Gruber", "Klaus Henle"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098840", "stats"=>{"downloads"=>9, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reliability_of_Different_Mark_Recapture_Methods_for_Population_Size_Estimation_Tested_against_Reference_Population_Sizes_Constructed_from_Field_Data_/1045944", "title"=>"Reliability of Different Mark-Recapture Methods for Population Size Estimation Tested against Reference Population Sizes Constructed from Field Data", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-04 03:24:54"}

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  • {"unique-ip"=>"155", "full-text"=>"171", "pdf"=>"17", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"150", "full-text"=>"171", "pdf"=>"18", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"1", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"135", "full-text"=>"168", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"104", "full-text"=>"118", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"63", "full-text"=>"68", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Ecology", "average_usage"=>[331]}, {"subject_area"=>"/Ecology and environmental sciences", "average_usage"=>[320]}, {"subject_area"=>"/Ecology and environmental sciences/Conservation science", "average_usage"=>[419, 667]}, {"subject_area"=>"/Ecology and environmental sciences/Ecology", "average_usage"=>[313]}]}
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