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2021-04-23Zeitschriftenartikel DOI: 10.18452/23517
Dynamic multistate occupancy modeling to evaluate population dynamics under a scenario of preferential sampling
dc.contributor.authorFandos, Guillermo
dc.contributor.authorKéry, Marc
dc.contributor.authorCano-Alonso, Luis Santiago
dc.contributor.authorCarbonell, Isidoro
dc.contributor.authorTellería, José Luis
dc.date.accessioned2021-10-13T09:37:16Z
dc.date.available2021-10-13T09:37:16Z
dc.date.issued2021-04-23none
dc.identifier.urihttp://edoc.hu-berlin.de/18452/24171
dc.descriptionThis article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.none
dc.description.abstractEffective conservation of animal populations depends on the availability of reliable data derived from rigorous monitoring protocols, which allows us to assess trends and understand the processes they are governed by. Nevertheless, population monitoring schemes are hampered by multiple sources of errors resulting from specific logistical and survey constraints. Two common complications are the non-visitation of some sites in certain years and preferential sampling (PS), that is, the tendency to survey “better” sites disproportionately more often. Both factors can lead to serious biases unless accommodated into models. We used 22 yr of nest-monitoring data to develop a dynamic multistate occupancy model, including a PS component to investigate occupancy and reproduction dynamics in a peripheral Black Stork (Ciconia nigra) population in Spain. We analyzed the effects of climate and nesting substrate (tree vs. cliff) on population dynamics and accounted for PS and non-visitation biases using a model that distinguished three territorial states: unoccupied, occupied without, or occupied with successful reproduction. We found strong evidence for positive PS, and when accounting for this bias, lower population size estimates were generated. Black stork nests had a high probability of remaining in the same state from one year to the next, with successful nests more likely to be occupied again and to be successful the following year than occupied but unsuccessful or unoccupied nests. Nesting substrate and spring precipitation did not influence state transition probabilities or the probability of reproductive success; nevertheless, cliff nest occupancy was overall higher than tree nest occupancy. Our results highlight the importance of correcting for non-visitation and PS in habitat occupancy models. If these potential biasing effects are not accounted for, inferences of population size may be overestimate. Multistate occupancy models with correction for PS offer a powerful analytical framework for data collected as part of population studies of unmarked animals. These models compensate for common methodological biases in biological surveys and can help implement efficient conservation strategies based on robust population dynamics estimates.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectBayesian inferenceeng
dc.subjectbias samplingeng
dc.subjectBlack Storkeng
dc.subjectoccupancy modelseng
dc.subjectpopulation dynamicseng
dc.subjectpopulation surveyeng
dc.subjectspecies distributioneng
dc.subject.ddc000 Informatik, Informationswissenschaft, allgemeine Werkenone
dc.titleDynamic multistate occupancy modeling to evaluate population dynamics under a scenario of preferential samplingnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/24171-4
dc.identifier.doihttp://dx.doi.org/10.18452/23517
dc.type.versionpublishedVersionnone
local.edoc.pages12none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
dc.description.versionPeer Reviewednone
dc.identifier.eissn2150-8925
dcterms.bibliographicCitation.doi10.1002/ecs2.3469
dcterms.bibliographicCitation.journaltitleEcospherenone
dcterms.bibliographicCitation.volume12none
dcterms.bibliographicCitation.issue4
dcterms.bibliographicCitation.articlenumbere03469none
dcterms.bibliographicCitation.originalpublishernameESAnone
dcterms.bibliographicCitation.originalpublisherplaceIthaca, NYnone
bua.departmentMathematisch-Naturwissenschaftliche Fakultätnone

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