A Hierarchical Bayesian Approach to Ecological Count Data: A Flexible Tool for Ecologists
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{"title"=>"A hierarchical bayesian approach to ecological count data: A flexible tool for ecologists", "type"=>"journal", "authors"=>[{"first_name"=>"James A.", "last_name"=>"Fordyce", "scopus_author_id"=>"7004026957"}, {"first_name"=>"Zachariah", "last_name"=>"Gompert", "scopus_author_id"=>"13410566300"}, {"first_name"=>"Matthew L.", "last_name"=>"Forister", "scopus_author_id"=>"6602762348"}, {"first_name"=>"Chris C.", "last_name"=>"Nice", "scopus_author_id"=>"7004820482"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"22132077", "doi"=>"10.1371/journal.pone.0026785", "sgr"=>"81455144573", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-81455144573", "issn"=>"19326203", "pui"=>"362955837"}, "id"=>"7a48da73-0068-3ab0-b19b-62f815b80688", "abstract"=>"Many ecological studies use the analysis of count data to arrive at biologically meaningful inferences. Here, we introduce a hierarchical Bayesian approach to count data. This approach has the advantage over traditional approaches in that it directly estimates the parameters of interest at both the individual-level and population-level, appropriately models uncertainty, and allows for comparisons among models, including those that exceed the complexity of many traditional approaches, such as ANOVA or non-parametric analogs. As an example, we apply this method to oviposition preference data for butterflies in the genus Lycaeides. Using this method, we estimate the parameters that describe preference for each population, compare the preference hierarchies among populations, and explore various models that group populations that share the same preference hierarchy.", "link"=>"http://www.mendeley.com/research/hierarchical-bayesian-approach-ecological-count-data-flexible-tool-ecologists", "reader_count"=>112, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>29, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>6, "Other"=>6, "Student > Master"=>12, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>29, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>6, "Other"=>6, "Student > Master"=>12, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Environmental Science"=>17, "Biochemistry, Genetics and Molecular Biology"=>3, "Mathematics"=>2, "Agricultural and Biological Sciences"=>74, "Medicine and Dentistry"=>1, "Neuroscience"=>1, "Chemistry"=>1, "Social Sciences"=>3, "Computer Science"=>2, "Earth and Planetary Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Neuroscience"=>{"Neuroscience"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>3}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>74}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>17}}, "reader_count_by_country"=>{"Puerto Rico"=>1, "Hungary"=>1, "United States"=>7, "Japan"=>1, "United Kingdom"=>2, "Kenya"=>1, "Spain"=>2, "Canada"=>2, "Sweden"=>1, "Finland"=>1, "Poland"=>1, "Brazil"=>1, "Mexico"=>1, "Germany"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/710484"], "description"=>"<p>Colored curves indicate posterior density for population-level preference for four host plant species. Posterior densities estimated from 40000 MCMC steps following a burnin of 10000 generations.</p>", "links"=>[], "tags"=>["preferences", "focal"], "article_id"=>380851, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.g003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Host_plant_preferences_for_focal_populations_/380851", "title"=>"Host plant preferences for focal populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-21 00:14:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/360232"], "description"=>"<div><p>Many ecological studies use the analysis of count data to arrive at biologically meaningful inferences. Here, we introduce a hierarchical Bayesian approach to count data. This approach has the advantage over traditional approaches in that it directly estimates the parameters of interest at both the individual-level and population-level, appropriately models uncertainty, and allows for comparisons among models, including those that exceed the complexity of many traditional approaches, such as ANOVA or non-parametric analogs. As an example, we apply this method to oviposition preference data for butterflies in the genus <em>Lycaeides</em>. Using this method, we estimate the parameters that describe preference for each population, compare the preference hierarchies among populations, and explore various models that group populations that share the same preference hierarchy.</p> </div>", "links"=>[], "tags"=>["hierarchical", "bayesian", "ecologists"], "article_id"=>131194, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785", "stats"=>{"downloads"=>7, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Hierarchical_Bayesian_Approach_to_Ecological_Count_Data_A_Flexible_Tool_for_Ecologists/131194", "title"=>"A Hierarchical Bayesian Approach to Ecological Count Data: A Flexible Tool for Ecologists", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-11-21 00:19:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/710430"], "description"=>"<p>A) Performance of conventional methods for analyzing count/preference data. Red hatched line indicates the 0.05 quantile of p-values for 1000 data sets simulated under the null model of no preference. Numbers are the <i>p</i>-values of 0.05 quantile. Methods examined were the (i) Friedman test, (ii) the Quade test, and (iii) ANOVA on arcsin square root transformed proportions. B) Distribution of DIC values for models with equal preference versus models with different preferences for each item. Red hatched line indicates the 0.95 quantile of DIC values.</p>", "links"=>[], "tags"=>["examining"], "article_id"=>380794, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.g002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulations_examining_performance_/380794", "title"=>"Simulations examining performance.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-21 00:13:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/710348"], "description"=>"<p>Individual count data inform the parameters for each individual's multinomial parameters. The multinomial parameters for all individuals inform the population level preference modeled as a Dirichlet. This population-level preference is shown as a ternary diagram (a triangle plot). The population-level preference, in turn, informs the most likely individual multinomial parameters given the population preference. Thus, at each MCMC step information is passed from the individual preferences to the population preference, and <i>vice versa</i>. Note that the 's and are not fixed for the analysis. The role of the hyperpriors on <i>w</i> and <i>q</i> are not depicted in the figure.</p>", "links"=>[], "tags"=>["hierarchical", "bayesian"], "article_id"=>380711, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_of_hierarchical_Bayesian_model_for_count_data_/380711", "title"=>"Schematic of hierarchical Bayesian model for count data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-21 00:11:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/710615"], "description"=>"<p>Parenthetical groups constrained to have same preference parameters in the model. DIC values based on 40000 MCMC steps following a burnin of 10000 generations. Abbreviations are as follows: CP, Carson Pass; GV, Gardnerville; LS, Leek Springs; MR, Mt. Rose; TC, Trap Creek; VE, Verdi; YG, Yuba Gap.</p>", "links"=>[], "tags"=>["comparisons", "grouping", "schemes"], "article_id"=>380976, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.t002", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_DIC_comparisons_among_grouping_schemes_for_host_plant_preferences_/380976", "title"=>"DIC comparisons among grouping schemes for host plant preferences.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-11-21 00:16:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/710689"], "description"=>"<p>Constrained refers to models where preference for each plant is equal. Unconstrained refers to models where preferences are permitted to vary among host plants. N is the number of replicates for each population.</p>", "links"=>[], "tags"=>["dic", "constrained", "unconstrained"], "article_id"=>381049, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Populations_and_DIC_values_for_constrained_and_unconstrained_preference_/381049", "title"=>"Populations and DIC values for constrained and unconstrained preference.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-11-21 00:17:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/710558"], "description"=>"<p>Population-level preferences (solid lines) and individual-level preferences (dotted lines) for each of the four host plants. Colors for each plant as in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026785#pone-0026785-g003\" target=\"_blank\">figure 3</a>. Populations presented are A) Carson Pass and B) Gardnerville. Posterior densities estimated from 40000 MCMC steps following a burnin of 10000 generations.</p>", "links"=>[], "tags"=>["Computational biology", "ecology", "neuroscience", "Evolutionary biology", "mathematics"], "article_id"=>380915, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Population_and_individual_preferences_/380915", "title"=>"Population and individual preferences.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-21 00:15:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/710650"], "description"=>"<p>Host plant abbreviations are as follows: <i>A.l.</i>, <i>Astragalus letiginosus</i>; <i>A.w.</i>, <i>A. whitneyi</i>; <i>G.l.</i>, <i>Glycyrrhiza lepidota</i>; <i>M.s.</i>, <i>Medicago sativa</i>; <i>V.a.</i>,<i>Vicia americana</i>. Natal plant for Cave Lake population is not definitively known, however, it is not <i>A. whitneyi</i> and is most likely <i>L. polyphyllus</i>. Constrained model is one where preference for all plants is equal, whereas the unconstrained is one where preference is permitted to vary across host plants. DIC scores based on 40000 MCMC generations following a 10000 generation burnin.</p>", "links"=>[], "tags"=>["natal", "dic", "scores", "constrained", "non-constrained"], "article_id"=>381010, "categories"=>["Mathematics", "Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James A. Fordyce", "Zachariah Gompert", "Matthew L. Forister", "Chris C. Nice"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026785.t003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Non_focal_population_summary_of_preference_for_Astragalus_and_natal_host_plant_and_DIC_scores_for_constrained_and_non_constrained_models_/381010", "title"=>"Non-focal population summary of preference for <i>Astragalus</i> and natal host plant, and DIC scores for constrained and non-constrained models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-11-21 00:16:50"}

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Relative Metric

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