(2011) based on organic carbon content (Corg) (Eq. (3)): equation(3) BD=β0+β1·CorgBD=β0+β1·Corg A detailed stem analysis was performed using software that was written specifically for our study in the R programming language (R Development Core Team, 2013). The software enabled the past growth history of a tree stem to be reconstructed. We used the correction proposed by

Carmean (1972) to estimate the height growth of each analysed tree. This method assumes that the annual height growth within a given stem section is constant and that crosscuts occurred in the middle of a given annual height growth. The height increments were calculated for the last 100 years. This time period was selected because of the long period of suppressed growth during

which Selisistat ic50 the trees had not reached a dominant canopy position. The specific basal area increment (SBAI) of a subject tree was chosen as a measure of tree growth rather than the relative growth rate (RGR). Originally, “specific increment” was defined for volume growth ( Bevilacqua, 2002), but we applied this concept to basal area growth. SBAI seems to be a more suitable measure for tree growth because growth is expressed per unit cambial length and does not Angiogenesis inhibitor consider the non-productive inner circle part ( Bevilacqua, 2002 and MacKinnon and MacLean, 2004). The SBAI for the last 5 years was calculated as: equation(4) SBAI5=BA0-BA-5CIRC-5where SBAI5 is the specific basal area increment of the last 5 years, BA0 is the current basal area of a tree, BA−5 is the basal area of a tree before the 5 years and CIRC−5 is the circumference of a section at breast height before the 5 years and represents the length of the cambium (Eq. (4)). As a measure of the competitive influence of neighbouring trees on a subject tree, we calculated the distance-dependent Hegyi competition index (Hegyi, 1974): equation(5) CIi=∑j=1nDj/DiDISTijwhere CIi is the competition index for subject tree i, Dj is the DBH of the jth competitor, Di is the DBH of the subject tree i, DISTij is the distance between the subject tree i and the jth competitor and n is the total number of competitors (Eq. (5)). All species were pooled before calculating the Hegyi competition

index. To determine an optimum search radius (maximum DISTij) and an optimum search DBH (minimum DBHj) above which a tree was considered as a competitor, an optimisation procedure described by Astemizole Miina and Pukkala, 2000 and Vanclay, 2006 was used. We iteratively revised the relative search radius (DISTij) and relative optimum search DBH (DBHj) until we reached a stable optimum (maximum) coefficient of determination adj. R2 between the Hegyi competition index and the SBAI. Multiple linear regressions were used to relate silver fir growth to corresponding soil attributes at single tree level, e.g. soil depth (minimum, mean and maximum value), mean thickness of soil horizons (A, Bw, Bt and E), share of the soil with different profile development (Fig.