Adaptive forest management requires planning and implementation of activities designed to maintain or improve forest conditions, and in support of these endeavors knowledge of silviculture, economics, operations research, and other allied fields are necessary. With regard to forest planning, traditional (exact) mathematical techniques along with heuristics have been demonstrated as useful in developing alternative courses of action for forest managers to consider. In this discussion paper, we present six areas of future work with regard to investigations into the development of heuristics, along with several recommendations that are based on our experiences. These areas include process improvements, reversion strategies, destruction and reconstruction strategies, intelligent or dynamic parameterization approaches, intelligent termination or transitioning approaches, and seeding strategies. We chose the six areas based on our experiences in developing forest planning heuristics. These areas reflect our opinion of where future research might concentrate. All of these areas of work have the potential to enhance the capabilities and effectiveness of heuristic approaches when applied to adaptive forest management problems.

This review presents a synthesis of global research on precision forestry, a field that integrates advanced technologies to enhance—rather than replace—established tools and methods used in the operational forest management and the wood products industry. By evaluating 210 peer-reviewed publications indexed in Web of Science (up to 2025), the study identifies six main categories and eight components of precision forestry. The findings indicate that “forest management and planning” is the most common category, with nearly half of the studies focusing on this topic. “Remote sensing platforms and sensors” emerged as the most frequently used component, with unmanned aerial vehicle (UAV) and light detection and ranging (LiDAR) systems being the most widely adopted tools. The analysis also reveals a notable increase in precision forestry research since the early 2010s, coinciding with rapid developments in small UAVs and mobile sensor technologies. Despite growing interest, robotics and real-time process control systems remain underutilized, mainly due to challenging forest conditions and high implementation costs. The research highlights geographical disparities, with Europe, Asia, and North America hosting the majority of studies. Italy, China, Finland, and the United States stand out as the most active countries in terms of research output. Notably, the review emphasizes the need to integrate precision forestry into academic curricula and support industry adoption through dedicated information and technology specialists. As the forestry workforce ages and technology advances rapidly, a growing skills gap exists between industry needs and traditional forestry education. Equipping the next generation with hands-on experience in big data analysis, geospatial technologies, automation, and Artificial Intelligence (AI) is critical for ensuring the effective adoption and application of precision forestry.

In the Pacific Northwest, forest roads have the potential to cause significant environmental degradation, especially to water resources due to increased sediment production. The goal of this research is to improve the understanding of road degradation during hauling by improving our understanding of the aggregate degradation process. We correlate the wear rates to standard material property tests that may allow for improved prediction of the impacts from forest roads based on the selection of aggregate surfacing. Finally, we determine the changes in stress distribution between the subgrade and aggregate interface. High-, medium-, and low-quality aggregates were used from three quarries in western Oregon for this project. These aggregates are indicative of the range of materials used on forest roads in the region. Two material property tests, namely the Los Angeles (LA) abrasion and micro-Deval tests, were used to determine their ability to predict aggregate performance during hauling by relating values for aggregate wear to these aggregate properties. Eighteen nonwoven geotextile bags were created, measuring 60 cm (two-feet long) and 20 cm (eight inches) in diameter, with a pore size equivalent to a 0.149 mm (# 100) sieve. They were filled with a known quantity and particle size distribution of aggregate and embedded into a newly constructed forest road. Stress gages were installed in the road surface between the aggregate and subgrade levels to record the changes in stress at the subgrade level. Samples were subjected to three levels of traffic (500, 950, and 1500 passes) using a loaded dump-truck that had a steering axle and one tandem drive axle, weighing 25,038 kg or 55,200 lb. The results showed that less breakage occurred with the medium- and high-quality aggregates than the low-quality aggregate. There was a correlation between the material property test (either the micro-Deval or the LA abrasion test) and the fine index, indicating the predictability of these tests in terms of aggregate performance. Finally, the higher quality aggregate was able to better distribute the stresses from the wheel better than the lower quality aggregate and was able to reduce the stress reaching the subgrade. Although the results are limited to the three types of rock used in this study, they indicate the ability of the high-quality aggregate to lessen the environmental impacts from forest roads.

The construction sector contributes significantly to global greenhouse gases, accounting for 39% of worldwide emissions. Multi-story wood buildings (MSWBs) present a sustainable alternative to traditional emissions-intensive construction materials like concrete and steel. However, only a few studies have investigated how potential customers perceive MSWBs, which influences their acceptance and demand. This study uses a concept-driven scoping review to explore perceptions and concerns about living in MSWBs and to understand barriers to their adoption. Through a narrative synthesis of 20 peer-reviewed articles, this study uncovered five key themes: environmental sustainability, fire safety, human well-being, structural durability, and costs. These findings highlight opportunities and challenges for MSWBs’ market growth and inform future communication strategies to enhance public acceptance and promote sustainable construction and the built environment.

Indigenous communities have experienced a loss of access and ability to contribute to the management of natural resources due to removal from lands, marginalization, and conflicting knowledge systems. Currently, there is increasing momentum toward re-engaging tribes as stewards of their ancestral lands. This article outlines tribal views on co-management and identifies the forest management objectives of a tribal partner to help better inform a forest co-management partnership between a Native American Tribe (Wiyot Tribe) and a California Polytechnic State University (Humboldt). Qualitative research methods were used to analyze 13 semi-structured interviews utilizing an adaptive co-management framework with enrolled tribal members and representatives to understand the expectations and perceived barriers to a successful co-management relationship. Interviewees repeatedly mentioned interest in the management of wildlife, forest health and resilience, and fuels reduction. Participants also expressed interest in incorporating education and training of tribal youth in the management of forest resources and traditional ecological knowledge. The semi-structured interviews provided participants a platform to share their thoughts and express their feelings regarding the future stewardship of ancestral forest lands.

Arkansas has experienced a decline in the number of primary wood processing mills (PWPMs) despite maintaining relatively stable roundwood production, raising concerns about efficient utilization of surplus forest resources and long-term forest management. This study identified suitable and optimal locations for establishing new PWPMs in Arkansas using a GIS-based fuzzy multi-criteria analysis integrated with location-allocation modeling. Site suitability was evaluated using constraint and preference layers representing land use restrictions, flood hazards, transportation infrastructure, electric transmission lines, labor availability, market access, and terrain characteristics. Candidate locations were subsequently evaluated using a p-median location-allocation model that incorporated existing mills, surplus forest resources, hauling distance, and mill capacity. Potential employment opportunities and hauling costs were also estimated for medium- and large-sized softwood- and hardwood-processing mills. Approximately 11% of Arkansas was identified as highly suitable for PWPM establishment, with highly suitable locations concentrated primarily in the Ozark Highlands and Mississippi Alluvial Plain regions. The location-allocation analysis selected 12 medium-sized and 9 large-sized softwood-processing mill locations and 32 medium-sized and 20 large-sized hardwood-processing mill locations. Medium-sized mills utilized a greater proportion of surplus forest resources than large-sized mills. Estimated employment potential was substantially greater for softwood-processing mills than hardwood-processing mills, while hauling costs varied among candidate locations and increased proportionally under higher transportation cost scenarios. The framework developed in this study provides a spatially explicit approach for evaluating future PWPM locations and may support investment planning, forest industry development, and resource utilization in Arkansas.