Objective 1: Test degree of spatial association or dissociation

The SADIE (Spatial Analysis by Distance Indices) software described in the previous methods section was used to measure the degree to which the spatial location of naturally occurring white spruce regeneration was positively or negatively associated with the location of mature white spruce seed sources. SADIE measures the correlation between two overlapping sets of cluster indices, rather than simply comparing the correlation of observed densities. This provides a much more rigorous measure of spatial correlation.

SADIE spatial association analysis was used to identify areas of significant association or dissociation (negative association) between seedlings and mature trees within each of the 25 transects. Clustering indices generated from the previous analysis steps were used. Overall association statistics were calculated for each transect. Individual association index values calculated by the SADIE software for each sample unit were exported into SURFER mapping software to visualize the spatial correlations.

Objective 2: Determine important factors affecting spatial relationships

Spatial association statistics calculated using the SADIE software for each transect were compiled and tested against the experimental treatment variables using the PROC MIXED method in SAS/STAT software. Variables tested included: area, age, season of harvest, and seed crop strength. A season of harvest-mast year interaction term was also included because different combinations of the two variables create unique conditions for regeneration (see the data collection section for details).