Comparison of sample rules for estimating jack pine density, basal area, and percentage with sweetfern rust cankers

Abstract

Sample rules that rate a cluster of trees at each sample point were investigated for performance in estimating the percentage of jack pine (Pinusbanksiana Lamb.) affected by cankers caused by sweetfern rust (Cronartiumcomptoniae Arth.). Performance for estimating the density and basal area of jack pine and cankered jack pine was also considered. Rule performance was rated with respect to efficiency in terms of the number of clusters or trees required for an adequate sample, bias, cluster size relative to optimal cluster size, and estimate precision.The types of rules included were fixed-area strip and circular plots, point samples, strips that include a constant number of trees, and rules based on point to tree distances. All rules appeared to provide unbiased estimates of the percentage of jack pine trees or basal area affected by sweetfern rust cankers. A cluster size of 18 was found to be optimal for such estimates with a confidence level of 80% and acceptable error size of E = ± 0.05. Optimal cluster size for other error factors and an efficient cluster size range were also identified. Only point sample and fixed-area rules appeared to be unbiased for density and basal area estimates. The best rule for all variables of interest was fixed-area strips with size adjusted to include an average of 18 jack pines per sample point.