For root mass data at different depths a two-way Multivariate Ana

For root mass data at different depths a two-way Multivariate Analysis

of Variance (MANOVA) was performed using land-use or season, as appropriate, and genotype as fixed factors, and the different depths as repeated measurements. The multivariate approach to the analysis of repeated measurements was used as it does not assume any particular model covariance between the repeated measurements. The hypotheses tested in an analysis of repeated measurements with treatment factor by grouping observations were: (i) there is no interaction between depth ∗ treatment, (ii) there is no effect of depth, and (iii) there is no treatment buy Afatinib or group effect. In the case of a significant treatment effect, pairwise comparisons were performed using a Hotelling post-hoc test (P ⩽ 0.05). A second analysis was carried out partitioning the data in different

sampling depths. In this case a two-way analysis of variance (ANOVA) was performed using land-use type and genotype as fixed factors, with inclusion of their interactions, for each sampling depth. Two-way ANOVAs were performed also using land-use type, genotype and their interactions as treatment factors, and different dependent variables such as C%, and plant density. In the case of a significant treatment effect, pairwise comparisons were performed using check details a Tukey post-hoc test (P ⩽ 0.05). The software InfoStat ( Di Rienzo et al., 2011) was used for the analysis. Although an optimal experimental design should include a control treatment without coppicing, it was not possible in our plantation and we also recognize that the establishment phase of the plantation is a special situation. This is the most critical period after the land Cobimetinib concentration use change of agriculture into SRWC. The herbaceous competition is one of the principal factors affecting the establishment, the success and the early productivity of the SRWC culture (with ecological and economic consequences). This has, however, been very poorly quantified in the literature, especially

for belowground processes. The explicit quantification of the relative root productivity of the tree crop and the competing weeds is the principal contribution of the current study. It is, therefore, essential to characterize land use change effects early in the conversion from agriculture to SRC. Our presented data are useful for models that simulate long-term changes in relation to SRC. Biomass of Fr at a depth of 0–15 cm increased during the course of the second year of the first rotation (2011, pre-coppice, Fig. 3). There was no significant increase of Fr biomass, even a small reduction, in the first year of the second rotation (2012, post-coppice) just after the first harvest. Despite this small decrease in Fr biomass in 2012 (post-coppice), the Fr productivity was higher than the pre-coppice year (i.e. 2011). Necromass of Fr did not increase post-coppice as compared to pre-coppice (Fig. 3).

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