Published February 10, 2021 | Version v1
Dataset Open

Leaf size of woody dicots predicts ecosystem primary productivity

  • 1. Peking University
  • 2. University of Minnesota
  • 3. University of Zurich
  • 4. Lanzhou University
  • 5. University of Arizona
  • 6. Sichuan University
  • 7. Peking University Third Hospital
  • 8. Hainan University
  • 9. Chinese Academy of Sciences

Description

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10,480 woody dicots in China and 2,374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice-versa. In addition to advancing understanding of the relationship between a climate-driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in paleoecology for scaling from fossil leaves to paleo-primary productivity of woody ecosystems.

Notes

The definitions for all columns (i.e. variables) within each sheet have been listed in the metadata sheet in each Excel file.

Funding provided by: the National Key Research Development Program of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100012166
Award Number: #2017YFA0605101

Funding provided by: the National Key Research Development Program of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100012166
Award Number: #2018YFA0606104

Funding provided by: National Natural Science Foundation of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809
Award Number: #31988102

Funding provided by: National Natural Science Foundation of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809
Award Number: #31911530102

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