Effects of tree species, stand age and land-use change on soil carbon and nitrogen stock rates in northwestern Turkey

Effects of tree species, stand age and land-use change on soil carbon and nitrogen stock rates were investigated in the northwest of Turkey using 4 common tree species as black pine (Pinus nigra Arnold.), Scots pine (Pinus sylvestris L.), Oriental beech (Fagus orientalis Lipsky) and Uludag fir (Abies nordmanniana ssp. bornmuelleriana). Three tree species (black pine, Scots pine and Oriental beech) were used to investigate the differences in soil C and N among tree species. Old and young Uludag fir stands and adjacent grassland were used to study the differences in soil C and N with stand age and land-use change. Mineral soil samples were taken from 0-10 cm and 10-20 cm soil depths, and analyzed for pH, soil texture, bulk density, total soil carbon and total nitrogen. The total soil carbon and total nitrogen pools were then calculated by multiplying soil volume, soil bulk density, and the total soil carbon or total nitrogen content. Results showed significant differences in soil carbon and nitrogen contents, carbon/nitrogen ratios and stock rates among the three species, and between old and young fir stands and grassland. In general, when 0-20 cm soil depth was considered, mean soil carbon stock rate was the highest under black pine (79 Mg C ha(-1)) followed by Scots pine (73 Mg C ha(-1)) and beech (67 Mg C ha-1), whereas mean soil nitrogen stock rate was the highest under beech (9.57 Mg N ha(-1)) followed by Scots pine (5.77 Mg N ha(-1)) and black pine (4.20 Mg N ha(-1)). Young fir stands showed lower soil carbon stock, but higher soil nitrogen stock rates compared to old fir stands and grassland. Our results demonstrated that tree species, stand tree age and land-use change can have significant effects on soil carbon and nitrogen content and stocks rates. These findings can help to enhance forest management activities, such as selection of tree species for carbon sequestration in plantation systems, design of sustainable agroforestry systems, and improvement of biogeochemical models.