Herbaceous perennial plants with short generation time have stronger responses to climate anomalies than those with longer generation time

Aldo Compagnoni*, Sam Levin, Dylan Z. Childs, Stan Harpole, Maria Paniw, Gesa Römer, Jean H. Burns, Judy Che-Castaldo, Nadja Rüger, Georges Kunstler, Joanne M. Bennett, C. Ruth Archer, Owen R. Jones, Roberto Salguero-Gómez, Tiffany M. Knight

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There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.

TidsskriftNature Communications
Antal sider8
StatusUdgivet - 23. mar. 2021

Bibliografisk note

Funding Information:
This article is the result of working group sAPROPOS (Analyses of PROjectionS of POpulations) supported by sDiv, the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (funded by the German Research Foundation, FZT 118—202548816), led by R.S.-G. and T.M.K. T.M.K., A.C., and S.L. were supported by the Alexander von Humboldt foundation; R.S.-G. was supported by NERC IRF (NE/M018458/1); J.C.-C., R.S.-G., and O.R.J. were also supported by an NSF Advances in Biological Informatics grant (DBI-1661342000), N.R. was funded by a research grant from Deutsche Forschungsgemeinschaft DFG (RU 1536/3-1). We acknowledge the efforts of the Max Planck Institute for Demographic Research in curating and making the COMPADRE Plant Matrix Database open-access, as well as the numerous authors who have kindly shared their demographic data and population models.

Publisher Copyright:
© 2021, The Author(s).

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