Addressing spatial variability in provenance experiments exemplified in two trials with black spruce

Abstract

Two exemplary black spruce (Picea mariana [Mill.] B.S.P.) provenance trials were analyzed using traditional and spatial techniques. The objective was to find out possible differences between these approaches in terms of both the resulting fit-statistics and the estimated mean heights of provenances. Further, the spatial model was consequently adjusted to treat global and extraneous sources of variation. As expected, models incorporating spatial variation provided a better fit to the data. Consequently, there was also a noticeable shift in ranking of individual provenances, which has an important implication for the interpretation of provenance experiments results. Problems associated with the analysis of traditional randomized block designs in forestry research are discussed.

Keywords

• picea mariana (mill.)
• provenance research
• reml
• spatial variation