Publication Abstracts

Weng et al. 2017

Weng, E., C.E. Farrior, R. Dybzinski, and S.W. Pacala, 2017: Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework. Glob. Change Biol., 23, no. 6, 2482-2498, doi:10.1111/gcb.13542.

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade?offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual?based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen?use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade?offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones.

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BibTeX Citation

@article{we07100r,
  author={Weng, E. and Farrior, C. E. and Dybzinski, R. and Pacala, S. W.},
  title={Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework},
  year={2017},
  journal={Glob. Change Biol.},
  volume={23},
  number={6},
  pages={2482--2498},
  doi={10.1111/gcb.13542},
}

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RIS Citation

TY  - JOUR
ID  - we07100r
AU  - Weng, E.
AU  - Farrior, C. E.
AU  - Dybzinski, R.
AU  - Pacala, S. W.
PY  - 2017
TI  - Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework
JA  - Glob. Change Biol.
VL  - 23
IS  - 6
SP  - 2482
EP  - 2498
DO  - 10.1111/gcb.13542
ER  -

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