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dc.contributor.authorAntunes Lopes Da Silva Nicolau, Pedro Guilherme
dc.contributor.authorIms, Rolf Anker
dc.contributor.authorSørbye, Sigrunn Holbek
dc.contributor.authorYoccoz, Nigel
dc.date.accessioned2023-01-06T10:08:22Z
dc.date.available2023-01-06T10:08:22Z
dc.date.issued2022-12-15
dc.description.abstractStudies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.en_US
dc.identifier.citationAntunes Lopes Da Silva Nicolau, Ims, Sørbye, Yoccoz. Seasonality, density dependence, and spatial population synchrony. Proceedings of the National Academy of Sciences of the United States of America. 2022;119(51)en_US
dc.identifier.cristinIDFRIDAID 2099801
dc.identifier.doi10.1073/pnas.2210144119
dc.identifier.issn0027-8424
dc.identifier.issn1091-6490
dc.identifier.urihttps://hdl.handle.net/10037/28050
dc.language.isoengen_US
dc.publisherNational Academy of Sciencesen_US
dc.relation.journalProceedings of the National Academy of Sciences of the United States of America
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)en_US
dc.titleSeasonality, density dependence, and spatial population synchronyen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)