Search

Forests are the locus of conflict in Canada, where the rights and interests of Indigenous peoples can collide with those of the province (Crown) and the forest industry. Efforts to achieve “forest justice” — or sufficient forest rights to meet the self-governance goals of Indigenous peoples, and in ways that ensure collective resilience — have typically been driven by the principle of reconciliation. In this paper, these “forest justice” efforts were examined through a tripartite justice theory, involving recognition, representation, and redistribution pathways. This paper documents that recognition involves Crown efforts to recognize Indigenous peoples’ forest rights, including ownership, and access and use rights; representation includes improved participation in forest governance; and redistribution covers the allocation of timber harvesting rights and forest lands to Indigenous peoples. This study documents that the bulk of “forest justice” activity is focused on the redistribution of timber harvesting licences, the volume of which has doubled over the last two decades. These three paths to justice must all be pursued together to deliver “forest justice”, and to move towards “reconciliation in the woods”. Recommendations are offered to support forest justice in practice.

Proponents of decentralized forest governance make a compelling case that community forest enterprises (CFEs) can aid in sustainable and equitable utilization of forest resources. The effectiveness of CFEs is thus dependent on their ability to balance social, environmental, and financial performance. In this paper, we examine the relationship between a commonly recommended differentiation strategy and CFE effectiveness. Using data obtained through a survey administered on 51 CFEs located in the Cascadia region (British Columbia province of Canada; and Oregon and Washington states of the United States), we find that CFEs pursuing a differentiation strategy are able to balance social, environmental, and financial objectives. Further, recognizing that all CFEs cannot pursue a differentiation strategy, and some may not even have a defined strategic orientation, the paper compares social, environmental, and financial performance of CFEs pursuing a differentiation strategy, a hybrid strategy (a combination of differentiation and cost leadership strategy), and no defined strategy. This analysis reveals that CFEs pursuing a hybrid strategy deliver better financial performance than those with no defined strategy but are similar to those pursuing a differentiation strategy.

High productivity in forest harvesting requires efficient forwarding. Planning is complicated by multiple choices of routes and their order, the number and types of assortments, the loading sequence, and pile organization at the landing. This paper develops and tests a decision support tool for forwarder routing with sequential co-loading of assortments. Input data are the harvester production file (including Global Navigation Satellite Systems tracking), placement of landing, and machine specifications. The trail network is generated from the harvester production data when devising routes to pick up all log piles, including specific assortments and volumes. Multiple assortments can be loaded along each route, and a certain loading sequence of assortments is preferred and (or) required. Sorting time during co-loading varies, depending on the assortment combinations and bunk loading pattern. Route planning is modeled using a set-partitioning problem, and the solution method is a metaheuristic based on repeated matching. In addition to routes and loading sequences, solutions include the organization of assortment piles at the landing, depending on the total volume of each assortment. The tool produces similar results to those attained by skilled forwarder operators on five clearcuts (3–11 ha) in northern Sweden, when the results are compared with data from actual forwarder production files.

Horvitz–Thompson-like stand density estimation is a method for estimating the stand density from tree crown objects extracted from airborne laser scanning data through individual tree detection. The estimator is based on stochastic geometry and mathematical morphology of the (planar) set formed by the detected tree crowns. This set is used to approximate the detection probabilities of trees. These probabilities are then used to calculate the estimate. The method includes a tuning parameter, which needs to be known to apply the method. We present a refinement of the method to allow more general detection conditions than those of previous papers. We also present and discuss the methods for estimating the tuning parameter of the estimator using a functional k-nearest neighbors method. We test the model fitting and prediction in two spatially separate data sets and examine the plot-level accuracy of estimation. The estimator produced a 13% lower RMSE (root-mean-square error) than the benchmark method in an external validation data set. We also analyze the effects of similarity and dissimilarity of training and validation data on the results.

In recent years, increasing attention has been drawn to improving productivity in logging passages while reducing negative impact on soil and water. The position of landings and extraction routes is crucial in these efforts, as it has a huge impact on efficient and sustainable forwarder passages. In this paper, we propose a two-phase approach to identify the best possible landing locations integrated with log extraction route design. The first phase identifies potential landing zones adjacent to forest roads. It considers practical restrictions such as slopes, stoniness, and closeness to infrastructure. The second phase uses an optimization model to evaluate the potential impact of each zone and aggregate zones, selecting one or two complete landings. This model is a relaxation of a formulation for an extraction route design; it is used to minimize a weighted objective of the total driving distance, avoid steep terrains and impact on soil and water. The proposed approach has been tested on a set of harvest areas in southern Sweden. The results not only show the potential to identify feasible landing zones but also identify a shorter driving distance and hence lower contractual cost with optimized positioning. The possibility to increase efficiency in forest operations by performing scenario analysis and thus forwarding distances with different landing sites is among the results.

Climate-smart forestry (CSF) is considered a promising approach for climate change adaptation and mitigation strategies, as highlighted in several European policy documents. This paper describes a prospective approach to introducing an incentive-based scheme to facilitate the implementation of CSF through a case study in Iceland. It is argued that the payments for ecosystem services (PES) scheme allows for effective CSF management and long-term sustainability if introduced in compliance with local, cultural, and social values. In a case study of an Icelandic afforestation programme, we conducted an institutional analysis of the PES scheme and assessed its effect on the sustainable provision of forest ecosystem services for the long term. We provide preliminary findings on the application of CSF in the 30-year-old Icelandic afforestation programme scheme. The perspectives of forest and policy experts, as well as local farmers participating in the scheme, were crucial for assessing the effectiveness of PES scheme performance in Iceland.

In this paper, we examine the implications of managing for sustained yield in a world characterized by growing risk and uncertainty. We review the history of sustained yield (SY) forestry in North America, with an emphasis on economic benefits and the persistence of the SY paradigm today, despite a publicized shift towards managing for a wider range of forest values called sustainable forest management (SFM). We show that current forest management goals around sustainability as well as SFM indicators are still predicated on maximizing harvest levels and timber flows. We build a simple model to explore the implications of SY under extreme (fat-tailed) risk assumptions to show that maximizing a level of harvest without adequately accounting for risk leads towards the depletion of the forest stock with a corresponding decline in the forest economy. We discuss these results in relation to real-world events such as the increase in catastrophic fires and pest outbreaks like the mountain pine beetle in Western Canada. We then examine the theoretical and practical implications that flow from this model and analysis.