Acadian forests of New Brunswick, Canada, are highly variable both in terms of species composition and quality. This is particularly accurate for hardwoods, for which value recovery is closely influenced by wood quality and a proper understanding of tree attributes. Therefore, based on several databases created between 2012 and 2021, the objectives of this study were to (1) characterize the stand-level distribution of species, size, form, and risk according to site factors and (2) determine the influence of different tree, stand, and site factors on the recovery of merchantable, sawlog, and veneer volumes. In total, 287,984 trees stemming from 9233 plots were analyzed for objective 1. For a subset of trees (743), tree, stand, and site attributes were also related to the product output of harvesting operations through a comprehensive inventory of standing trees and their associated products. Analyses were performed with linear and multinomial logistic regressions as well as factor analysis of mixed data (FAMD). Key results indicated that tree attributes and product recovery were significantly influenced by (1) environmental factors (soil, temperature, and precipitation), summarized by ecoregion in this study and (2) tree size and form. These findings suggest that the inclusion of site factors in supply planning could improve product recovery during forest operations.

Clear-cutting has been the dominant harvesting method used in boreal forest silviculture. Reducing the potential negative effects of intensive forestry activities on ecosystems, e.g., the simplification and homogenization of stand structure, requires diversifying silvicultural practices to promote forest resilience in the face of climate change. Priority therefore lies in developing, evaluating, and adapting partial cutting as a potential silvicultural option for ensuring the sustainable management of boreal forests. In this chapter, we summarize the findings of two large-scale experiments conducted in Canadian boreal forests that tested new silvicultural approaches and explore their implications for forest management. We discuss the effects of these treatments on tree growth, tree mortality, regeneration, and biodiversity, and we examine the challenges of existing silvicultural approaches in the context of climate change.

Bucking optimization was shown to generate high gains in volume and value recovery in harvesting operations. Several bucking optimizers have been developed between the 1960s and early 2000s but none of those programs were available in an open-source and easily modifiable format by users. Therefore, this paper presents BuckR, an open access bucking optimizer at tree-level, programmed in R. The objective function is the maximization of values for each study tree, but it can be modified depending on the needs of users. BuckR is based on a well-known dynamic programming algorithm and requires tree data and product specifications with prices as the inputs. One of the output files produced is the log sequence, generating the highest value for each study tree. Through the open access code, the developed bucking optimizer will facilitate future research and applications in the field of value maximization.

Fully mechanized hardwood operations usually rely on manual bucking, which may decrease potential volume and value recovery as compared to automatic bucking. This study aimed at evaluating bucking done in cut-to-length (CTL) operations, hypothesizing a possible increase of value recovery by using a bucking optimizer. Evaluation of bucking was done by a comparison of actual bucking with a mathematical solution – BuckR – a bucking optimizer based on dynamic programming. Results showed that the mathematical approach significantly outperformed manual bucking when quality was not considered, and only main stem products were included. Throughout 315 study trees (Acer saccharum, Acer rubrum, and Betula alleghaniensis) located in the Acadian forests of Eastern Canada, a mean increase of 112% in value and 84% in volume recovery per tree was reached through mathematical optimization. Contributions of mathematical bucking can be summarized by 1) a significantly higher number of sawlogs and a greater mean log length of sawlogs and pulp logs, 2) a two-fold increase in processed height, and 3) a considerable reduction in minimal diameters as compared to actual bucking. Those results illustrate the possibility to increase value and volume recovery in mechanized CTL operations and therefore to utilize the wooden resource more efficiently.