Comparative assessment of soil quality parameters after implementing afforestation programme in forest areas of Hong Kong

Kim Yung FUNG, Ho Man LEUNG, Kin Lam Ken YUNG

Research output: Contribution to journalArticlespeer-review

1 Citation (Scopus)

Abstract

The objective of this research is to investigate and compare the alteration of soil parameters with and without afforestation programme in a Hong Kong forest, analysed by Principal Component Analysis (PCA). One hundred soil samples were collected from the following sites: Pak Ngau Shek (PNS), Shing Mun (SM), Tai Po Kau (TPK), Tai Tong (TT) (forest with afforestation programme) and Lantau Peak (LP) (control site). A significant difference was found in only two out of 16 parameters: pH (8.34–8.87) and PAHs (4.35–6.32 μg/kg) by comparing the soils taken in the forest with and without an afforestation programme implemented. Three principle components are responsible for soil quality variations in the studied sites. The first, second and third components included pH (0.167) and EC (0.176), PAHs (0.331) and PAHs (0.207), respectively. This framework provides information on the least disturbance of soil properties for the afforestation programme. To conclude, a rigorous monitoring of soil quality is necessary to assess forest health after an afforestation programme. Besides, in the long term, an appropriate forest preservation programme should be implemented to achieve rural area sustainability. Copyright © 2017 Springer-Verlag GmbH Germany.

Original languageEnglish
Pages (from-to)25051-25059
JournalEnvironmental Science and Pollution Research
Volume28
Early online dateJul 2017
DOIs
Publication statusPublished - May 2021

Citation

Fung, K. Y., Leung, H. M., & Yung, K. K. L. (2021). Comparative assessment of soil quality parameters after implementing afforestation programme in forest areas of Hong Kong. Environmental Science and Pollution Research, 28, 25051-25059. https://doi.org/10.1007/s11356-017-9550-z

Keywords

  • Afforestation program
  • Soil quality
  • Principal component analysis
  • Restoration
  • Forest health

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