{"refrec":{"BRefID":350416,"RR":"<b>Rakhimberdiev, E.; Karagicheva, J.; Saveliev, A.; Loonstra, A.H.J.; Verhoeven, M.A.; Hooijmeijer, J.C.E.W. ; Schaub, M.; Piersma, T.</b> (2022). Misidentification errors in reencounters result in biased estimates of survival probability from CJS models: Evidence and a solution using the robust design. <i>Methods Ecol. Evol. 13(5)</i>: 1106-1118. <a href=\"https://dx.doi.org/10.1111/2041-210x.13825\" target=\"_blank\">https://dx.doi.org/10.1111/2041-210x.13825</a>","BEntID":348112,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Methods Ecol. Evol. 13(5)</i>: 1106-1118. <a href=\"https://dx.doi.org/10.1111/2041-210x.13825\" target=\"_blank\">https://dx.doi.org/10.1111/2041-210x.13825</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Rakhimberdiev, E.; Karagicheva, J.; Saveliev, A.; Loonstra, A.H.J.; Verhoeven, M.A.; Hooijmeijer, J.C.E.W. ; Schaub, M.; Piersma, T.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Rakhimberdiev, E. <i>et al.</i>","Englishabstract":"<ol start=\"1\" type=\"1\">    <li>        Misidentification of marked individuals is unavoidable in most studies        of wild animal populations. Models commonly used for the estimation of        survival from such capture–recaapture data ignore misidentification        errors potentially resulting in biased parameter estimates. With a        simulation study, we show that ignoring misidentification in        Cormack–Jolly–Seber (CJS) models results in systematic positive biases        in the estimates of survival and in spurious declines of survival over        time.    </li>    <li>        We developed an extended robust design capture mark–resight (RDM) model        that includes correct identification parameters to get unbiased        survival estimates when resighting histories are prone to        misidentification. The model assumes that resightings occur repeatedly        within a season, which in practice is often the case when resightings        of colour-marked individuals are collected. We implemented the RDM        model in a state-space formulation and also an approximate, but        computationally faster, model (RDMa) in JAGS and evaluated their        performances using simulated and empirical capture–resight data on        black-tailed godwits <em>Limosa limosa</em>.    </li>    <li>        The CJS models applied to simulated data under an imperfect        identification scenario data produced strongly positively biased        estimates of survival. For a range of degrees of correct identification        probabilities, the RDM model provided unbiased and accurate estimates        of survival, reencounter and correct-identification probabilities. The        RDMa model performed well for large datasets (>25 individuals), with        high resighting (>0.3) and high correct identification (>0.7)        probabilities. For the empirical data, the CJS model estimated average        juvenile survival at 0.997% and adult survival at 0.939% and also        detected a strong decline in adult survival over time at a rate of        −0.14 ± 0.029. In contrast, the RDMa model estimated a probability of        correct identification of 0.94, annual juvenile survival at 0.234%,        adult at 0.834% and less strong decline over time (−0.046 ± 0.016).    </li>    <li>        We conclude that estimates of survival probabilities obtained from data        that include misidentification errors and analysed with standard CJS        model are unlikely to be correct. The bias in survival increases with        the magnitude of misidentification errors, which is inevitable as        datasets become longer. Since misidentification due to tag misreads is        common in empirical data, we recommend the use of the here presented        RDM model to provide unbiased parameter estimates.    </li></ol>","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Misidentification errors in reencounters result in biased estimates of survival probability from CJS models: Evidence and a solution using the robust design","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2026-06-03 01:31:58.663929","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"Bayesian analysis; black-tailed godwit; capture-recapture; CJS; misidentification; misreading; survival","OtherDescriptors":null,"Notes":null,"AnaPub":2022,"MonPub":null,"DateUpdate":"2022-10-06","DateCreate":"2022-03-16","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000767119800001","VABBcode":null,"OpenAcc":1,"DOI":"10.1111/2041-210x.13825"},"refs":null,"anarec":{"AnaID":350416,"PubliDate":2022,"Pagination":"1106-1118","XtraPublOfAnaID":null,"ISBN":null,"Volume":"13","Issue":"5","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":205126,"SerRR":"Methods in Ecology and Evolution. 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