Frontiers in Plant Science (Jun 2021)

Functional Traits Are Good Predictors of Tree Species Abundance Across 101 Subtropical Forest Species in China

  • Ronghua Li,
  • Ronghua Li,
  • Ronghua Li,
  • Shidan Zhu,
  • Juyu Lian,
  • Juyu Lian,
  • Hui Zhang,
  • Hui Liu,
  • Hui Liu,
  • Wanhui Ye,
  • Wanhui Ye,
  • Qing Ye,
  • Qing Ye

DOI
https://doi.org/10.3389/fpls.2021.541577
Journal volume & issue
Vol. 12

Abstract

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What causes variation in species abundance for a given site remains a central question in community ecology. Foundational to trait-based ecology is the expectation that functional traits determine species abundance. However, the relative success of using functional traits to predict relative abundance is questionable. One reason is that the diversity in plant function is greater than that characterized by the few most commonly and easily measurable traits. Here, we measured 10 functional traits and the stem density of 101 woody plant species in a 200,000 m2 permanent, mature, subtropical forest plot (high precipitation and high nitrogen, but generally light- and phosphorus-limited) in southern China to determine how well relative species abundance could be predicted by functional traits. We found that: (1) leaf phosphorus content, specific leaf area, maximum CO2 assimilation rate, maximum stomata conductance, and stem hydraulic conductivity were significantly and negatively associated with species abundance, (2) the ratio of leaf nitrogen content to leaf phosphorus content (N:P) and wood density were significantly positively correlated with species abundance; (3) neither leaf nitrogen content nor leaf turgor loss point were related to species abundance; (4) a combination of N:P and maximum stomata conductance accounted for 44% of the variation in species’ abundances. Taken together, our findings suggested that the combination of these functional traits are powerful predictors of species abundance. Species with a resource-conservative strategy that invest more in their tissues are dominant in the mature, subtropical, evergreen forest.

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