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Title: Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity

Abstract

Abstract Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO 2 fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO 2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived frommore » first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [4];  [5];  [6]; ORCiD logo [7]
  1. School of Biological Sciences University of Utah Salt Lake City Utah, Department of Geography University of California, Santa Santa Barbara California
  2. Department of Global Ecology Carnegie Institution for Science Stanford California, Department of Integrative Biology University of California, Berkeley Berkeley California
  3. Smithsonian Tropical Research Institute Balboa Panama
  4. Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK‐IFU) Karlsruhe Institute of Technology (KIT) Garmisch‐Partenkirchen Germany
  5. Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey
  6. Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey, Department of Viticulture and Enology University of California Davis California
  7. School of Biological Sciences University of Utah Salt Lake City Utah
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1525898
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Name: Global Change Biology Journal Volume: 25 Journal Issue: 10; Journal ID: ISSN 1354-1013
Publisher:
Wiley-Blackwell
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Trugman, Anna T., Anderegg, Leander D. L., Wolfe, Brett T., Birami, Benjamin, Ruehr, Nadine K., Detto, Matteo, Bartlett, Megan K., and Anderegg, William R. L. Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity. United Kingdom: N. p., 2019. Web. doi:10.1111/gcb.14680.
Trugman, Anna T., Anderegg, Leander D. L., Wolfe, Brett T., Birami, Benjamin, Ruehr, Nadine K., Detto, Matteo, Bartlett, Megan K., & Anderegg, William R. L. Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity. United Kingdom. https://doi.org/10.1111/gcb.14680
Trugman, Anna T., Anderegg, Leander D. L., Wolfe, Brett T., Birami, Benjamin, Ruehr, Nadine K., Detto, Matteo, Bartlett, Megan K., and Anderegg, William R. L. Wed . "Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity". United Kingdom. https://doi.org/10.1111/gcb.14680.
@article{osti_1525898,
title = {Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity},
author = {Trugman, Anna T. and Anderegg, Leander D. L. and Wolfe, Brett T. and Birami, Benjamin and Ruehr, Nadine K. and Detto, Matteo and Bartlett, Megan K. and Anderegg, William R. L.},
abstractNote = {Abstract Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO 2 fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO 2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.},
doi = {10.1111/gcb.14680},
journal = {Global Change Biology},
number = 10,
volume = 25,
place = {United Kingdom},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1111/gcb.14680

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Cited by: 40 works
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