No abstract

Core Ideas Multivariate statistics and fuzzy logic analysis were used to assess aspen regeneration. Vegetation indices were the dominant factors in determining regeneration suitability. Vegetation indices were significantly higher in high suitability areas. Skidder traffic was significantly lower on high regeneration suitability land. The percentage of slash coverage was significantly lower on high suitability land. Vigorous aspen (Populus tremuloides Michx.) regeneration immediately following a harvesting event is important to ensuring the continued health and productivity of the future forest. This study aimed to examine the potential of using unoccupied aerial vehicle, multispectral remote sensing, and GIS mapping techniques to develop a comprehensive approach for predicting aspen regeneration success at the harvest block scale. Three winter harvested blocks were studied at Duck Mountain Provincial Park in east‐central Saskatchewan, Canada. Ten regeneration predictor variables (number of skidder passes, percentage slash coverage, topographic wetness index, slope, aspect, slope position, and four vegetation indices: green normalized vegetation index [GNDVI], normalized red‐edge index [NDRE], simple RED to NIR ratio [SR], and chlorophyll index green [CIG]) were determined for 168 measurement plots 1 yr after harvest. Principal component analysis, principal component regression, fuzzy logic analysis, and GIS mapping techniques, were combined for the first time in this study to determine cumulative effects on aspen regeneration. On average, low suitability areas had significantly more skidder traffic (34 passes) compared to below average (17), above average (10), and high (7) suitability areas. Low suitability areas also had significantly more slash coverage (13.1%) compared to below average (8.49%) or high suitability land (7.18%). High suitability areas had significantly higher GNDVI, NDRE, SR, and CIG indices, compared to low and below average suitability land. Not only does this method of analysis help to assess how a combination of factors may influence aspen regeneration, it can also act as a decision support system tool for industry, or government, to improve aspen regeneration assessments.

Proper redistribution of residual slash following harvesting is crucial for ensuring successful regeneration and continued health in trembling aspen (Populus tremuloides) forests. As traditional methods of measuring residual slash are a strenuous and tedious process, the objective of this study was to develop a new, faster, and more detailed method to assess residual slash distribution for entire harvested blocks. This study also aimed to assess the influence residual slash coverage had on the success of aspen regeneration 1 year after winter harvesting. Using high-resolution UAV imagery and maximum likelihood supervised image classification, residual slash was differentiated from the underlying forest floor. Overall, classification accuracy ranged between 85% and 96% with the highest accuracy occurring when aerial imagery was collected at the beginning of the second spring following winter harvesting. Slash distribution was quite consistent across harvested blocks, with 92% of harvested blocks experiencing <33% coverage. There was no relationship between the level of aspen regeneration following 1 year of growth and percentage slash coverage up to 60%. No vegetation plots occurred in areas with >60% slash coverage; therefore, it is unknown whether aspen regeneration will be affected in areas with higher slash coverage.