Shifting Importance of Abiotic versus Biotic Filtering from Intact Mature Forests to Post-Clearcut Secondary Forests

  • Junkang Ouyang
  • , Shekhar R. Biswas*
  • , Chaoqin Yin
  • , Yanxia Qing
  • , Prity L. Biswas
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Although ecologists often emphasize the roles of environmental-versus biotic-filtering in structuring forest communities, the relative importance of these processes could vary among undisturbed versus disturbed forests. To test this assumption, we gathered leaf traits and site conditions data from intact mature forests (control), moderately disturbed shrublands, and severely disturbed plantations from subtropical China. We found that plantations had higher leaf area, specific leaf area, leaf nitrogen and phosphorus concentrations but lower leaf thickness, dry matter content, and C:N than the shrubland or mature forest, suggesting the dominance of resource acquisition strategy in plantations versus conservation strategy in the mature forests. Plantations also had significantly lower trait ranges than mature forest or shrubland, suggesting the play of stringent environmental filtering in the plantation. However, intraspecific trait variations in leaf dry matter content and C:N were substantial in plantation, while interspecific variation in leaf thickness was high in mature forests, suggesting the importance of intra-versus inter-specific competition in plantation versus mature forests. Results from our species-level analysis were consistent with the community-level results mentioned above. Overall, our study demonstrates the shifting importance of environmental and biotic filtering from disturbed to undisturbed forests.

Original languageEnglish
Article number672
JournalForests
Volume13
Issue number5
DOIs
StatePublished - May 2022

Keywords

  • environmental filtering
  • habitat disturbance
  • intraspecific trait variation
  • leaf economic spectrum
  • trait gradient analyses

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