Determining the effects of the forest stand age on the soil quality index in afforested areas: A case study in the Palandoken mountains

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ÇOMAKLI E., TURGUT B.

SOIL AND WATER RESEARCH, cilt.16, sa.4, ss.237-249, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 4
  • Basım Tarihi: 2021
  • Doi Numarası: 10.17221/179/2020-swr
  • Dergi Adı: SOIL AND WATER RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Directory of Open Access Journals
  • Sayfa Sayıları: ss.237-249
  • Anahtar Kelimeler: analytic hierarchy process (AHP), principal component analysis (PCA), degradation, ecosystem, forest, ORGANIC-CARBON, BACTERIAL COMMUNITY, LAND DEGRADATION, DIVERSITY, NITROGEN, GRADIENT, PLATEAU, IMPACTS
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Afforestation is an essential strategy for erosion control. The objective of this study was to determine the soil quality index (SQI) in established afforested areas of different ages for erosion control in Erzurum, Turkey. Three afforested areas were selected as plots considering their establishment periods: + 40 years old (AA>40), 10-40 years old (AA10-40), and less than 10 years old (AA<10). Forty soil samples were taken in each plot area over the 0-15 and 15-30 cm depths. The soil samples were analysed for the texture, mean weight diameter, aggregate stability, pH, electrical con-ductivity, total nitrogen, total carbon, and total sulfur contents. These properties were used as the soil quality indicators, whereby the analytic hierarchy process (AHP) and principal component analysis (PCA) were used to establish their relative importance for describing the soil quality. The indicators were scored using the linear score functions of "more is better" and "optimum value". For determining the SQI, the additive method (SQIA), the weighted method with AHP (SQIAHP), and the weighted method with PCA (SQIPCA) were used. The SQI scores of the plots showed statistically significant differences. In all three methods, the highest SQI value was obtained from the AA>40 plots.