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

Autor: Evers SM; Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany., Knight TM; Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.; Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Halle (Saale), Germany., Inouye DW; Department of Biology, University of Maryland, College Park, MD, USA.; Rocky Mountain Biological Laboratory, Crested Butte, CO, USA., Miller TEX; Program in Ecology and Evolutionary Biology, Department of BioSciences, Rice University, Houston, TX, USA., Salguero-Gómez R; Department of Zoology, University of Oxford, Oxford, UK., Iler AM; Rocky Mountain Biological Laboratory, Crested Butte, CO, USA.; The Negaunee Institute for Plant Conservation Science and Action, Chicago Botanic Garden, Glencoe, IL, USA., Compagnoni A; Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Jazyk: angličtina
Zdroj: Global change biology [Glob Chang Biol] 2021 May; Vol. 27 (9), pp. 1927-1941. Date of Electronic Publication: 2021 Feb 15.
DOI: 10.1111/gcb.15519
Abstrakt: Understanding 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.
(© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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