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Although stakeholders' participation in forest management helps overcome problems and conflicts that prevent sustainable solutions, different approaches and nomenclature for similar contents in the literature hinder theoretical progress on the topic. This study organises existing information through a bibliometric analysis of scientific papers from the last 30 years (1991–2021) on sustainable forest management, focusing on the stakeholders' participation. Results demonstrate that stakeholders' participation in sustainable forest management gained relevance from 2017 onwards. Case studies are predominant (66%) and six major trends were identified. The first emphasises a systemic approach to participation. The second updates the community management discussion. The third studies historical problems related to the use of resources, rights, and services. The fourth focuses on regional assessments and studies. The fifth concerns assessment, decision-making, and planning, including issues related to certifications and policies. The sixth discusses innovation related to adaptation, climate change, equity, and resilience. The studies included in this last classification are problem-solving-oriented and seek new forest management. Although important, the role of innovation in stakeholders' participation in sustainable forest management is overlooked, which constitutes an avenue for future research. [ABSTRACT FROM AUTHOR]

Tree detection and canopy area measurement are important and difficult tasks in forest inventory, which are important for understanding forest stand structure. This study utilized remotely piloted aircraft (RPA) aerial photography technology to collect remote sensing images of forests in Xiong County, China, creating a dataset comprising 1200 images of six tree species. Based on this dataset, the paper proposes an optimized model, Att-Mask R-CNN, for canopy detection and segmentation. Att-Mask R-CNN outperforms the original models (Mask R-CNN and MS R-CNN) by achieving 65.29% mean average precision for detection, 80.44% mean intersection over union for segmentation, and 90.67% overall recognition rate for the six tree species. In addition, a pixel statistics method based on segmentation masks is introduced for estimating the vertical projected area of individual tree crowns, and comparisons between the measured and predicted vertical projected area of the crowns of six tree species (100 trees of each class) show an overall goodness-of-fit R2 of 85% and a relative root-mean-square error rRMSE of 12.81%. By using remote sensing images from RPAs and optimizing existing deep learning models, the detection and segmentation of individual tree canopies can be achieved, resulting in a more accurate understanding of forest structure, which provides scientific support for forest management and resource monitoring. [ABSTRACT FROM AUTHOR]

Spatially explicit global estimates of forest carbon storage are typically coarsely scaled. While useful, these estimates do not account for the variability and distribution of carbon at management scales. We asked how climate, topography, and disturbance regimes interact across and within geopolitical boundaries to influence tree biomass carbon, using the perhumid region of the Pacific Coastal Temperate Rainforest, an infrequently disturbed carbon dense landscape, as a test case. We leveraged permanent sample plots in southeast Alaska and coastal British Columbia and used multiple quantile regression forests and generalized linear models to estimate tree biomass carbon stocks and the effects of topography, climate, and disturbance regimes. We estimate tree biomass carbon stocks are either 211 (SD = 163) Mg C ha−1 or 218 (SD = 169) Mg C ha−1. Natural disturbance regimes had no correlation with tree biomass but logging decreased tree biomass carbon and the effect diminished with increasing time since logging. Despite accounting for 0.3% of global forest area, this forest stores between 0.63% and 1.07% of global aboveground forest carbon as aboveground live tree biomass. The disparate impact of logging and natural disturbance regimes on tree biomass carbon suggests a mismatch between current forest management and disturbance history. [ABSTRACT FROM AUTHOR]

We studied how management intensity and climate severity affect volume growth, timber yield, carbon stocks, and the amount of deadwood in Scots pine (Pinus sylvestris (L.)), Norway spruce (Picea abies (L.) Karst.), and silver birch (Betula pendula Roth.) dominated stands in the Republic of Karelia and Arkhangelsk region of northwest Russia. Using the forest ecosystem model (SIMA) under different climates (current and representative concentration pathway scenarios, RCP4.5 and RCP8.5), no-thinning, low, medium, and high intensity thinning rotational forestry regimes were simulated. Under RCPs, the volume growth and timber yield (5%–53%), carbon stocks (1%–22%), and deadwood amounts (11%–75%) increased for all Scots pine and silver birch stands. The use of low intensity management increased volume growth and carbon stocks (3%–16%) and deadwood amount (up to 60%) under RCPs, but not timber yield (±3%) in these stands. For Norway spruce stands, the volume growth (5%–26%), timber yield (23%–75%), and carbon stocks (5%–15%) decreased under RCP8.5, but deadwood amount increased (up to 142%). Intensive management increased volume growth (4%–19%), timber yield (4%–63%), carbon stocks (up to 14%), and deadwood amounts (up to 49%). Our results highlight that effects of climate severity and management intensity are site and species-specific for Eurasian's boreal forests. [ABSTRACT FROM AUTHOR]

Growth and yield systems are essential tools for enhancing forest management decision-making. This study systematically evaluated three stand-level models and two data types for predicting stand survival and basal area of Chinese fir (Cunning lanceolate (Lamb.) Hook.) plantations in southern China. The first model links survival and diameter through the self-thinning concept. The second model incorporates stand diameter, the previous year's diameter, and stand survival, while the third model treats stand survival and diameter as mutually independent functions of only stand age. Model 2 was the best performer for short-term prediction (2–4 years), whereas Model 3 excelled in longer projection periods (6–10 years). Despite the independent predictions of stand survival and diameter in Model 3, it closely tracked observed self-thinning trajectories in long-term predictions. Tree-level model growth derived from Models 2 and 3 performed optimally for short-term and long-term tree-level predictions, respectively. While limited to four experimental sites, this research contributes theoretical groundwork to growth and yield modeling for Chinese fir plantations. [ABSTRACT FROM AUTHOR]

As wildfires are increasingly causing negative impacts to communities and their livelihoods, many communities are demanding more proactive and locally driven approaches to address wildfire risk. This marks a shift away from centralized governance models where decision-making is concentrated in government agencies that prioritize reactive wildfire suppression. In British Columbia (BC), Canada, Community Forests—a long-term, area-based tenure granted to Indigenous and/or local communities—are emerging as local leaders facilitating proactive wildfire management. To explore the factors that are enabling local governance approaches to managing wildfire risk, we conducted semi-structured interviews with 26 Community Forest managers across BC. Managers highlighted financial and social capacity, especially trust and relationships with both community members and government agencies, as crucial factors influencing their ability to undertake proactive management. These factors enable Community Forests to address wildfire risk not only within their own tenure area, but also at household, community, and landscape scales, while balancing diverse community values, objectives for forest management, and legal and policy obligations. Despite ongoing challenges, Community Forests emphasized the importance of scaling up their efforts to address wildfire risk and are a critical form of local wildfire governance that can help advance proactive wildfire management across BC. [ABSTRACT FROM AUTHOR]

Climate change interacts with ecological processes leading to changes in tree and forest growth rate, biome shifts and species composition, all of which are influenced by disturbances. This study explores future overarching climate trends of eight of Canada's ecozones containing managed forests. For the 2071 to 2100 period, climate projections indicate a warming trend of up to an additional 5.5 °C and an overall increase in annual precipitation. Future trends suggest marked contrast between coastal and interior forests and polarization between western and eastern forests. Warmer temperatures, accumulating degree-days above 5 °C and frost-free days suggest longer and drier growing seasons and greater risk of drought particularly in moisture-limited areas such as montane cordillera, taiga shield and boreal shield ecozones. Warmer temperatures and rising precipitation combined with less snow suggest shorter and wetter future winters. This indicates greater risk of rain-on-snow and freeze-thaw events, flooding and landslides particularly in coastal ecozones. We discuss how these projections are likely to result in shifts in dominant species and abundance, which when coupled with the cumulative effects of future disturbances, is likely to alter future forest dynamics and impact harvestable wood volumes for Canada's forestry industry. [ABSTRACT FROM AUTHOR]

Fungi are primary agents of coarse woody debris (CWD) decay in boreal forests, playing an essential role in nutrient cycling and carbon storage. We compared fungal community assemblages using alpha and beta diversity metrics, and physical and chemical properties of CWD across three tree species (trembling aspen [Populus tremuloides], black spruce [Picea mariana], and jack pine [Pinus banksiana]), five decay classes, and two stand development stages, differing in time since stand replacing disturbance in Ontario's boreal forest region. We sampled 180 individual CWD logs from 6 independent stands, with 3 replicates per each species × decay class combination at each site. Using high-throughput sequencing of marker DNA, we found that fungal community structure significantly differed across tree species, decay stage, and stand age. Fungal diversity was highest in decay class 4 CWD. We found that Mn and K concentrations, total carbon, C/N ratio, N/P ratio, and moisture content were important predictors of fungal composition across CWD species and/or decay stage. This study suggests that forest management guidelines that consider both deadwood quantity and quality will support a broader range of fungal species and communities through post-disturbance stand development. [ABSTRACT FROM AUTHOR]