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Individual tree diameter at breast height (DBH) distribution is an important information for forest management planning. Forest managers obtain the DBH data either by field measurements or estimations using predictive models. However, probability distribution models are still lacking or need improvement. Therefore, we aimed to construct and fit diameter distribution models that reflect forest structure and composition change. We evaluated gamma, log-normal, and Weibull probability distribution functions (PDFs) for two commercially important tree species, black spruce (Picea mariana (Mill) B.S.P.) and jack pine (Pinus banksiana Lamb), grown in natural stands across Ontario, Canada. We modelled the parameters of the distributions as a function of stand-level variables for these species. We used DBH data from 735 permanent sample plots. Our results showed that all three evaluated PDFs reflected observed DBH distribution. We demonstrated that the moment-based recovered parameters could represent the maximum likelihood-estimated parameters precisely, and parameters of the PDFs can be modelled as a function of stand-level dynamic covariates. The models unbiasedly predicted the PDF parameters DBH means and DBH classes. The R2 of the model fit ranged between 0.35 and 0.98 for the predicted parameters and 0.90 and 0.97 for the predicted DBH. [ABSTRACT FROM AUTHOR]

Glyphosate-resistant giant ragweed (Ambrosia trifida L.) was first identified in Canada in 2008. Although early studies attributed resistance in this species solely to non-target site mechanisms, the presence of a proline (P) to serine (S) mutation at position 106 of EPSPS2 in common and giant ragweed has recently been reported. The objective of this research was (i) to determine whether a P106S mutation is present in historical samples of giant ragweed seed collected from the site of the first report of glyphosate resistance, and (ii) to determine the frequency and distribution of P106S in resistant and susceptible biotypes collected as part of historical surveys throughout southwestern Ontario. [ABSTRACT FROM AUTHOR]

Non-industrial wood ash may be an effective forest soil nutrient supplement but its use in Canada is largely restricted because of unknown concentrations of trace metal contaminants. Sugar maple (Acer saccharum Marshall) is particularly sensitive to low soil calcium (Ca) levels, and though maple syrup is of great economic importance in Canada, it is unknown how wood ash could affect sap chemistry. Non-industrial wood ash (NIWA; 6 Mg·ha−1) applied to experimental plots in Muskoka, Ontario was rich in Ca (27%), while metal concentrations were well below provincial regulatory limits. One-year post-application, significant increases were observed in the treated plots in the soil pH and base cations (Ca, K, and Mg) in the surface soil horizons, and metal concentrations in the litter. Sap yield in the control plots was significantly lower in the first-year post-application than in the second year, but no other differences were found. In both tapping years, sap sweetness remained similar and differences in nutrient and metal concentrations between treatments were generally small and inconsistent. Foliar chemistry remained largely unchanged 1 year following application, except for K that was twice as high in the treated plots. Ultimately, NIWA is unlikely to significantly alter sugar maple sap chemistry, indicating that it is a viable nutrient supplement that can enhance soil fertility in sugar bushes with no impact on sap sweetness. [ABSTRACT FROM AUTHOR]