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1、AnalysisofN-mixtureabundanceandsite-occupancyspeciesdistributionmodelsusingWinBUGS,JAGSandunmarkedAnillustrationoftheeffectsofimperfectdetectioninspeciesdistributionmodels:Speciesdistributionmapproducedwithaconventionalspeciesdistributionwhichignoresimperfectdetection,suchasaGLM,aGAM,boostedre
2、gressiontreesorMaxEnt(top),amapproducedwithasite-occupancymodelwhichdoesnotignoreimperfectdetection(middle)andthedifferencebetweenthetwo,representingthebiasincurredbyignoringimperfectdetection,forthedragonflyAeshnacyeaneainSwitzerland(fromKéryetal.,2010a)MarcKéry&MichaelSchaubUSGSPatuxentWildl
3、ifeResearchCenterLaurel,MD207088–12July2013101Allmaterialintheremainderofthisdocumentistakendirectlyfromanewbook:BayesianPopulationAnalysisusingWinBUGS-ahierarchicalperspectivebyMarcKéry&MichaelSchaub;AcademicPress,2012;seewww.vogelwarte.ch/bpaSpecifically,thefollowingmaterialistakenfromtheBPA
4、bookchapters12and13onNmixandonsite-occupancymodeling,andcontainsanappendixwithWinBUGStipsandapartiallistofBPAbookreferences.Twoslightchangesweremadetochapters12and13astheyappearintheBPAbook:1.RcodeisaddedtofittheNmixandsite-occmodelsusingfunctionsinthehighlyuseful(non-Bayesian)Rpackageunmarked
5、(Fiske&Chandler,2011).2.Inchapter13,BUGScodeisaddedforfittingdynamicoccupancymodelstodatainthe‘vertical’format.Thiscansavemuchtimewhenanalysinglargeandunbalanceddatasets,astheyoftenoccurwhenfittingsite-occupancymodelstoopportunisticdata(Tingley&Beissinger,2009;Kéryetal.2010a,b;vanStrienetal.,2
6、011).3.Plus,thereareacoupleotherssneakingin101Tableofcontentsinfinaltwochapters12.Estimationofabundancefromcountsinmetapopulationdesignsusingthebinomial-mixturemodel412.1.Introduction412.2.Generationandanalysisofsimulateddata912.2.1.Thesimplestcasewithconstantparameters9Interlude:GettingMLesti
7、mateswithunmarked1112.2.2.Introducingcovariates14Interlude:GettingMLestimateswithunmarked1912.3.Analysisofrealdata:Open-populationbinomial-mixturemodel2312.3.1.SimplePoissonmodel2512.3.2.Zero-inflatedPoissonbinomial-mixturemodel(ZIPbino
