Lagged and dormant season climate better predict plant vital rates than climate during the growing season

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dc.citation.firstpage1927en_US
dc.citation.issueNumber9en_US
dc.citation.journalTitleGlobal Change Biologyen_US
dc.citation.lastpage1941en_US
dc.citation.volumeNumber27en_US
dc.contributor.authorEvers, Sanne M.en_US
dc.contributor.authorKnight, Tiffany M.en_US
dc.contributor.authorInouye, David W.en_US
dc.contributor.authorMiller, Tom E.X.en_US
dc.contributor.authorSalguero‐Gómez, Robertoen_US
dc.contributor.authorIler, Amy M.en_US
dc.contributor.authorCompagnoni, Aldoen_US
dc.contributor.orgProgram in Ecology and Evolutionary Biologyen_US
dc.date.accessioned2021-06-07T20:22:40Zen_US
dc.date.available2021-06-07T20:22:40Zen_US
dc.date.issued2021en_US
dc.description.abstractUnderstanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.en_US
dc.identifier.citationEvers, Sanne M., Knight, Tiffany M., Inouye, David W., et al.. "Lagged and dormant season climate better predict plant vital rates than climate during the growing season." <i>Global Change Biology,</i> 27, no. 9 (2021) Wiley: 1927-1941. https://doi.org/10.1111/gcb.15519.en_US
dc.identifier.digitalgcb-15519en_US
dc.identifier.doihttps://doi.org/10.1111/gcb.15519en_US
dc.identifier.urihttps://hdl.handle.net/1911/110688en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleLagged and dormant season climate better predict plant vital rates than climate during the growing seasonen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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