Climate and hydraulic traits interact to set thresholds for liana viability

Alyssa M. Willson, Anna T. Trugman, Jennifer S. Powers, Chris M. Smith-Martin, David Medvigy

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

Original languageEnglish (US)
Article number3332
JournalNature communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022

Bibliographical note

Funding Information:
We thank Helena Kleiner, Megan Vahsen, Jason McLachlan, Jody Peters, and Haley Kodak for suggestions on an early drafts of the manuscript. We are grateful for meteorological data obtained from Copernicus Climate Change Service information 2019. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office Biological and Environmental Research, under Award Numbers DESC0014363 and DESC0020344. A.M.W. received support from an NSF Graduate Research Fellowship, an Arthur J. Schmitt Fellowship, University of Notre Dame Environmental Research Center Graduate Fellowship and NSF Grant 1241874. A.T.T. acknowledges funding from the NSF Grants 2003205 and 2017949, the USDA National Institute of Food and Agriculture, Agricultural and Food Research Initiative Competitive Programme Grant No. 2018-67012-31496 and the University of California Laboratory Fees Research Program Award No. LFR-20-652467.

Publisher Copyright:
© 2022, The Author(s).

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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