Yield pattern of eucalypt clones across tropical Brazil: An approach to clonal grouping - Scolforo, Henrique Ferraco; McTague, John Paul; Burkhart, Harold; Roise, Joseph; Campoe, Otavio; Stape, Jose Luiz [UNESP] (Elsevier B.V., 2019)
The research objective of this paper was to group eleven widely planted eucalypt clones based on their volume yield pattern by assessing how climatic variation impacts their productivity in tropical Brazil. A total of 187 plots evenly distributed across eleven clones and 17 sites (from Parana to Para State) were used. Plot measurements were carried out every six months (from 2013 to 2017) to evaluate eucalyptus growth. Since the year of plot establishment differs across the sites, volumes of all the plots and sites were standardized at a common age of 5 years. Clonal grouping analysis was performed based on the common age for volume yields using a new approach, which consisted of three steps: (1) create general groups based on testing of the slope coefficient, which was applied to every clonal-specific regression with volume yield as a function of annual water deficit index (WDI); (2) split each general group using volume yield deviation computations into subgroups of high and low productivity; (3) apply linear mixed effects models for every subgroup in order to confirm the non-existence of statistical difference among the volume yield of the clones. Statistical tests showed satisfactory yield estimates at the common age of 5 years. Clonal grouping revealed the identification of four groups (A: high productivity and non-sensitive to climate variation, B: high productivity and sensitive to climate variation, C: low productivity and sensitive to climate variation, D: low productivity and non-sensitive to climate variation). The volume yield of the Clonal group B was detected to be the most impacted by annual water deficit index variation, followed by clonal groups C, A and D. The findings of the study highlighted the utility of the proposed approach for grouping clones. Group identification and detection of the climatic impact on yield patterns was evaluated as a measure to increase site-specific productivity.
Keywords: Mixed effect modeling; Annual water deficit index; Productivity