Estimation of forest litter fractions by regression analysis in different aged stands of Pinus nigra

TECİMEN H. B., SEVGİ O., YILMAZ O. Y., Carus S., Kavgaci A., AKBURAK S.

BOSQUE, vol.40, no.1, pp.41-48, 2019 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 40 Issue: 1
  • Publication Date: 2019
  • Doi Number: 10.4067/s0717-92002019000100041
  • Journal Name: BOSQUE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.41-48
  • Süleyman Demirel University Affiliated: Yes


Forest litter (FL) carbon accumulation patterns can be predicted by certain tree and stand parameters to assess how variably managed forests may accumulate carbon. The aim of our study was to use tree stand data to refine methods to predict the composition of FL fragments in temperate, semi-humid black pine forests (Pinus nigra) in western Anatolia, Turkey. Predictive models were established between FL fractions (fine fragments of < 2, 2-4, and > 4 mm and coarse woody debris of branches < 5 cm, > 5 cm, cones and bark) and tree parameters (stand age, tree height, diameter at breast height, tree basal area, tree density, lowest tree crown height and tree crown thickness). We sampled 105 stands of ages < 50, 50-100, and > 100 years, that were distributed at 5 altitudinal steps (500 to 1,750 m). A multi-regression analysis was used to estimate FL fraction for different-age stands. Total FL dry biomass varied from 18 to 213 Mg/ha (average: 94 Mg/ha). The fine fragment fraction (> 4 mm) represented the largest proportion of FL (36 %). Coarse woody debris amounted for 6.6-7.8 % of the FL and branches < 5 cm accounted for the highest proportion (12.4-26.4 %) of coarse woody debris. The most influential parameters predicting FL fragment proportions included thy branch thickness, thinning rate, height and age (R-2: 0.11 to 0.67). The combination of long-term observation and fine and coarse litter trapping methods should improve the estimation rates of sequestered carbon in forest ecosystems.