Purpose of Review: Indigenous perspectives have often been overlooked in fire management in North America. With a focus on the boreal region of North America, this paper provides a review of the existing literature documenting Indigenous voices and the historical relationship of Indigenous peoples in northern North America to fire and landscapes that burn.Recent Findings: Early research on the topic explored how Indigenous people used fire in the boreal forest, with most research coming out of case studies in northern Alberta. Emerging research in the last two decades has broadened the geographic focus to include case studies in Alaska, Ontario, Labrador, and other regions in North America. This broadening of focus has shown that the diversity of Indigenous peoples in North America is reflected in a diversity of relationships to fire and landscapes that burn. Of note is an emerging interest in Indigenous fire knowledge in the wake of settler colonialism.Summary: Indigenous peoples in the boreal forest have applied fire on their landscapes to fulfill numerous objectives for thousands of years. More than a tool, Indigenous peoples in the boreal view fire as an agent, capable of movement, destruction and creation, acting on the landscape to create order, within a living, connected environment. Unfortunately, restrictions on the application of Indigenous fire knowledge and practice initiated during early colonial times remains a contemporary challenge as well.

We present historical monthly spatial models of temperature and precipitation generated from the North American dataset version “j” from the National Oceanic and Atmospheric Administration’s (NOAA’s) National Centres for Environmental Information (NCEI). Monthly values of minimum/maximum temperature and precipitation for 1901–2016 were modelled for continental United States and Canada. Compared to similar spatial models published in 2006 by Natural Resources Canada (NRCAN), the current models show less error. The Root Generalized Cross Validation (RTGCV), a measure of the predictive error of the surfaces akin to a spatially averaged standard predictive error estimate, averaged 0.94 °C for maximum temperature models, 1.3 °C for minimum temperature and 25.2% for total precipitation. Mean prediction errors for the temperature variables were less than 0.01 °C, using all stations. In comparison, precipitation models showed a dry bias (compared to recorded values) of 0.5 mm or 0.7% of the surface mean. Mean absolute predictive errors for all stations were 0.7 °C for maximum temperature, 1.02 °C for minimum temperature, and 13.3 mm (19.3% of the surface mean) for monthly precipitation.

Forest transition theory, as introduced by Alexander Mather, depicts forest recovery patterns often occurring in the wake of agricultural intensification and farmland abandonment. Since the forest transition theory was introduced, multiple pathways have been described in the scholarly literature to explain forest transition phases via varied socio-economic forces. This analysis of a set of 78 country-specific case studies published from 2019 to 2022 confirms social inequity in documented forest transitions; forest transition case studies from 2019 to 2022 were concentrated in highly developed countries. This review also substantiates the impact of agricultural land use changes in recent forest transitions. Four out of five case studies assessing pathways identified an economic development pathway for forest transitions. The effect of state interventions such as introducing incentives for reforestation in forest transitions reviewed was mixed; while almost one-third of forest transitions were attributed to state policies or laws, negative biodiversity impacts from forest plantations were documented. With respect to social justice, nearly a third of case studies included interviews with villagers or similar methodologies to capture social perceptions of forest transitions. Based on this review, governance and social equity forest transition benefits are critical issues for forest transition research.

This study presents spatial models (i.e., thin-plate spatially continuous spline surfaces) of adjusted precipitation for Canada at daily, pentad (5 day), and monthly time scales from 1900 to 2015. The input data include manual observations from 3346 stations that were adjusted previously to correct for snow water equivalent (SWE) conversion and various gauge-related issues. In addition to the 42 331 models for daily total precipitation and 1392 monthly total precipitation models, 8395 pentad models were developed for the first time, depicting mean precipitation for 73 pentads annually. For much of Canada, mapped precipitation values from this study were higher than those from the corresponding unadjusted models (i.e., models fitted to the unadjusted data), reflecting predominantly the effects of the adjustments to the input data. Error estimates compared favorably to the corresponding unadjusted models. For example, root generalized cross-validation (GCV) estimate (a measure of predictive error) at the daily time scale was 3.6 mm on average for the 1960–2003 period as compared with 3.7 mm for the unadjusted models over the same period. There was a dry bias in the predictions relative to recorded values of between 1% and 6.7% of the average precipitations amounts for all time scales. Mean absolute predictive errors of the daily, pentad, and monthly models were 2.5 mm (52.7%), 0.9 mm (37.4%), and 11.2 mm (19.3%), respectively. In general, the model skill was closely tied to the density of the station network. The current adjusted models are available in grid form at ~2–10-km resolutions.

This research investigates how biomass supply chains (BSChs) for bioenergy within the broader bioeconomy could contribute to the post-COVID-19 recovery in three dimensions: boosting economic growth, creating jobs, and building more resilient and cleaner energy systems in four future scenarios, in the short term (by 2023) and long term (by 2030). A SWOT analysis on BSChs was used for generating a questionnaire for foresight by a two-round Delphi study. To interpret the results properly, a short survey and literature review is executed to record BSChs behavior during the pandemic. In total, 23 (55% response rate) and 28 (46% response rate) biomass experts from three continents participated in the Delphi and the short survey, respectively. The strongest impact from investment in BSChs would be on economic growth, followed by a contribution to the resilient and cleaner energy systems and job creation. The effects would be more visible in the long- than in the short-term period. Investments with the most impact on recovery are those that improve biomass material efficiency and circularity. Refurbishment of current policies to enhance the supply of biomass as a renewable resource to the future economy is a must.

The ongoing COVID-19 pandemic has disrupted global economic activity in all sectors, including forest industries. Changes in demand for forest products in North America over the course of the pandemic have affected both primary processors and downstream industries reliant on residues, including wood pellet producers. Wood pellets have become an internationally traded good, mostly as a substitute for coal in electricity generation, with a significant proportion of the global supply coming from Canadian producers. To determine the effect of the COVID-19 pandemic on the Canadian wood pellet industry, economic and market data were evaluated, in parallel with a survey of Canadian manufacturers on their experiences during the first three waves of the pandemic (March 2020 to September 2021). Overall, the impact of the pandemic on the Canadian wood pellet industry was relatively small, as prices, exports, and production remained stable. Survey respondents noted some negative impacts, mostly in the first months of the pandemic, but the quick recovery of lumber production helped to reduce the impact on wood pellet producers and ensured a stable feedstock supply. The pandemic did exacerbate certain pre-existing issues, such as access to transportation services and labour availability, which were still a concern for the industry at the end of the third wave in Canada. These results suggest that the Canadian wood pellet industry was resilient to disruptions caused by the pandemic and was able to manage the negative effects it faced. This is likely because of the integrated nature of the forest sector, the industry’s reliance on long-term supply contracts, and feedstock flexibility, in addition to producers and end-users both being providers of essential services.