Forest Management Research Articles

Newly established forests dominated global carbon sequestration change induced by land cover conversions.

Land cover conversions (LCC) have substantially reshaped terrestrial carbon dynamics, yet their net impact on carbon sequestration remains uncertain. Here, we use the remote sensing-driven BEPS model and high-resolution HILDA+ data to quantify LCC-induced changes in net ecosystem productivity (NEP) from 1981 to 2019. Despite global forest loss and cropland/urban expansion, LCC led to a net carbon gain of 229 Tg C. Afforestation and reforestation increased NEP by 1559 Tg C, largely offsetting deforestation-driven losses (-1544 Tg C), with newly established forests in the Northern Hemisphere driving gains that counterbalanced emissions from tropical deforestation. Regional carbon gains were concentrated in East Asia, North America, and Europe, while losses occurred mainly in the Amazon and Southeast Asia. Although smaller in area, newly established forests exhibited higher sequestration efficiency than degraded older forests, emphasizing the role of forest age in shaping global carbon sink dynamics. These findings highlight the critical importance of afforestation, forest management, and spatially informed land-use strategies in strengthening carbon sinks and supporting global carbon neutrality goals.

Nonlinear mixed effects height to crown base model for Larix kaempferi plantation in China by considering initial planting density and thinning intensity

Height to crown base is a main component of crown structure to understand the growth of the tree. It is essentially important to construct a comprehensive height to crown base model to facilitate the application in forest management practice decision making. Measurements from a total of 13,822 trees across 159 sample plots developed in the forest stands of Larix kaempferi plantations in Liaoning and Hubei provinces were used to fit the model. Variables of tree size, competition, climate, and thinning practice were considered in the model development. A dummy variable approach was used to analyze the effects of initial planting density and study area on height to crown base, and the interaction between initial planting density and competition was also considered in the height to crown base model. A nonlinear mixed effects model was developed to eliminate heteroscedasticity at the sample plot level. The results showed that the logistic model had the best performance and was therefore selected as the base model. Total tree height and height-diameter ratio from tree level variables, stand basal area of competition variables, spring degree-days below 0°C (DD_0_sp) of climate variables, and thinning variables showed significant contributions to height to crown base and were finally included in the final model. Height to crown base increased with the increase in total tree height, competition, height-diameter ratio, thinning intensity, and decreased with the increase in DD_0_sp and logarithmic transformation of altitude. Large initial planting density resulted in a rise in height to the crown base. The relative contributions of each group of variables to height to crown base were as follows: tree size (41.7%) > competition (27.3%) > thinning (24.5%) > interaction of competition and thinning (3.2%) > climate (2.4%) > site quality (0.9%). The model reveals that thinning mitigates the impact of competition on height to crown base, especially for trees from Hubei province.This comprehensive model provides a robust tool for optimizing Larix kaempferi plantation management strategies and will lay a foundation to conduct forest management strategies decision.

Influence of Thinning Regime on Woody Species Density and Abundance in Kimondi Forest, Nandi County, Kenya

A silvicultural regime refers to the planned sequence of treatments applied to a forest stand, which mainly includes pruning and thinning regimes. The latter is a silvicultural practice that is important for the management of forest growth, composition, structure, and health. Despite the ecological and silvicultural importance of thinning, its limited application in plantation forests has constrained the effective management of woody species density and abundance. Thus, the aim of this research was to assess the influence of the thinning regime on woody species density and abundance. This study focused on Eucalyptus saligna, Cupressus lusitanica and Pinus patula as the woody species that are harvested for timber in the Kimondi forest. The study applied a cross-sectional descriptive study design. Systematic sampling was used in collecting primary data. Data were analysed using box plots, Analysis of Variance and Duncan multiple range test. The box plots showed Eucalyptus saligna having the highest median density and the widest interquartile range, indicating both a greater abundance and variability across sampling sites. Cupressus lusitanica and Pinus patula had a moderate median density with a narrower distribution, indicating lower variability. Analysis of variance revealed a highly significant difference in tree abundance and density across the thinning regime (p = 0.000), with an effect size (Eta² = 0.7519), indicating that 75.19% of the variation of woody species density and abundance can be explained by the thinning regime. Duncan’s Multiple Range Test confirmed that mean abundance varied significantly across the thinning regime. The study concluded that a thinning regime can improve the density and abundance of woody species, Eucalyptus saligna, Cupressus lusitanica, and Pinus patula. We recommend that forest managers in plantation forests adopt thinning regimes to improve woody species density and abundance.

Effects of a Post-Harvest Management Practice on Structural Connectivity in Catchments with a Mediterranean Climate

Forest harvesting can alter sedimentary processes in catchments by reducing vegetation cover and exposing the soil surface. To mitigate these effects, post-harvest residue management is commonly used, though its effectiveness needs individual evaluation. This study assessed how windrowed harvest residues influence structural sediment connectivity in two forest catchments in south-central Chile with a Mediterranean climate. Using digital terrain models and the Index of Connectivity, scenarios with and without windrows were compared. Despite similar windrow characteristics, effectiveness varied between catchments. In catchment N01 (12.6 ha, average slope 0.28 m m−1), with 13.6% windrow coverage, connectivity remained unchanged, but in contrast, catchment N02 (14 ha, average slope 0.27 m m−1), with 21.9% coverage, showed a significant connectivity reduction. A key factor was windrows’ orientation: 83.9% aligned with contour lines in N02 versus 58.6% in N01. Distance to drainage channels also played a role, with the decreasing effect of connectivity at 50–60 m in N02. Bootstrap analysis confirmed significant differences between catchments. These results suggest that windrow configuration, particularly contour alignment, may be more critical than coverage percentage. For effective connectivity reduction, especially on moderate to steep slopes, forest managers should prioritize contour-aligned windrows. This study enhances our understanding of structural sediment connectivity and offers practical insights for sustainable post-harvest forest management.

Emulation or Degradation? Evaluating Forest Management Outcomes in Boreal Northeastern Ontario

Emulation or Degradation? Evaluating Forest Management Outcomes in Boreal Northeastern Ontario

The Role of Tree Size in Root Reinforcement: A Comparative Study of Trema orientalis and Mallotus paniculatus

Root reinforcement in soil plays a critical role in maintaining forest slope stability. However, accurately estimating the reinforcement provided by the entire root system of a mature tree remains a time-intensive task. Previous experimental studies on root reinforcement have predominantly focused on small trees, leaving a knowledge gap concerning larger specimens. This study integrates field pullout test data of individual roots, analyses of root geometry distribution within root systems, and theoretical frameworks, including root distribution and Root Bundle Models, to develop methods for estimating root reinforcement across varying tree sizes. The findings indicate that root system reinforcement in large trees is substantially greater than in smaller counterparts. The methodology proposed herein provides forest management professionals with a practical tool for evaluating root reinforcement in dominant forest trees, thereby facilitating improved assessment of landslide risks in forested slopes.

Rural Entrepreneurs and Forest Futures: Pathways to Emission Reduction and Sustainable Energy

Rural areas around the world are increasingly dealing with energy and environmental challenges. These challenges are particularly acute in developing countries, where persistent reliance on traditional energy sources—such as wood fuel—intersects with concerns about forest conservation and energy sustainability. While wood fuel use is often portrayed as unsustainable, it is important to acknowledge that much of it remains ecologically viable and socially embedded. This study explores the role of rural entrepreneurs in shaping low-carbon transitions at the intersection of household energy practices and environmental stewardship. Fieldwork was carried out in four rural Zambian communities in 2016 and complemented by 2024 follow-up reports. It examines the connections between household energy choices, greenhouse gas emissions, and forest resource dynamics. Findings reveal that over 60% of rural households rely on charcoal for cooking, with associated emissions estimated between 80 and 150 kg CO2 per household per month. Although this is significantly lower than the average per capita carbon footprint in industrialized countries, such emissions are primarily biogenic in nature. While rural communities contribute minimally to global climate change, their practices have significant local environmental consequences. This study draws attention to the structural constraints as well as emerging opportunities within Zambia’s rural energy economy. It positions rural entrepreneurs not merely as policy recipients but as active agents of innovation, environmental monitoring, and participatory resource governance. A model is proposed to support sustainable rural energy transitions by aligning forest management with context-sensitive emissions strategies.

Chromosome-level genome assembly of Elaeocarpus petiolatus (Elaeocarpaceae).

Elaeocarpus petiolatus is an ecologically and economically important species in tropical and subtropical forests. Despite its significance, the lack of genomic resources has hindered research on the genetic diversity and adaptive traits of E. petiolatus. To address this gap, we present a comprehensive chromosome-level genome assembly of E. petiolatus generated using advanced PacBio high-fidelity (HiFi) long-read sequencing and Hi-C technology. The assembly spans 322.45 Mb, with a scaffold N50 of 20.58 Mb, indicating that 37.11% of the genome is composed of repetitive elements. We identified 25,295 protein-coding genes, of which 96.74% were functionally annotated. This high-quality genome provides a critical resource for understanding the genetic mechanisms underlying environmental adaptability and biosynthesis of bioactive compounds in E. petiolatus, thereby supporting conservation efforts and sustainable forest management. The assembled genome and associated sequencing data are publicly available, facilitating further evolutionary and functional studies on the Elaeocarpaceae family.

Building trust and efficacy in forest carbon programs: lessons from stakeholder engagement in Central Appalachia

Abstract Despite significant investments in managing forest carbon as a natural climate solution, our research indicates that many stakeholders distrust climate change mitigation promises and potential environmental injustices associated with forest carbon offsets. The Central Appalachian region of the United States offers an insightful case study of challenges associated with carbon programs in a highly forested region with numerous small, family forest owners and high rates of socioeconomic distress. We synthesized the findings from stakeholder engagement processes, reviewed the challenges and opportunities associated with forest carbon management, and developed detailed case studies capturing the complexity and opportunities for forest carbon management. The stakeholders prioritized balancing forest management for carbon and other services, such as timber production, and the need for improved stakeholder education and collaboration. On the basis of our findings, we offer recommendations for fostering cooperation among different sectors of the forestry marketplace and equitably advancing climate change solutions in the Central Appalachian region.

Integrating Technical, Socio-Economic, and Sustainability Dimensions for Spatial Stratification of Ecosystem Services Using the AHP Method.

Forest management is inherently complex, requiring a multi-dimensional approach to set management goals that balance the competing demands of ecosystem services, public expectations, and scientific-political considerations. This study addresses the necessity for recognising, prioritizing, and spatially stratifying ecosystem services (ES) based on technical suitability, stakeholder involvement, and the categories of sustainability within Turkey's forest ecosystem management framework in Yalnızçam case study area. By leveraging Multi-Criteria Decision Analysis (MCDA) methods, particularly the Delphi technique with Analytical Hierarchy Process (AHP), this research captures both scientific ground and perspectives of various sectors with a stratification model to determine ES provisions. The iterative framework includes ES identification and prioritization steps, culminating in their spatial stratification of forest stands with geographic information system. The results indicate that ES stratification highlighted the primary focus on biodiversity conservation (78.5%) and water protection (13.3%), with minimal provision for timber production (7.9%) and soil protection (0.04%), and none for climate regulation, eco-tourism, and non-wood forest products. This approach enables a more efficient spatial zoning strategy, balancing technical and socio-cultural factors, and streamlining decision-making processes crucial for sustainable forest management paradigm.

Global wood fuel production estimates and implications

Abstract Global wood fuel production can indicate opportunities and also challenges in sustainable development, forest management, and energy access. Estimates of wood fuel removals and charcoal production are essential for tracking global goals yet reliable measurements are rare. We synthesize existing understanding through a mechanistic, conceptual model and build on it to develop statistical models from official statistics and over 2000 newly identified data points. For 2019, we estimate 2525.7 million m3 of wood fuel removals globally, approximately 30% higher than previously understood. Our estimates are 50% higher in Africa and 40% higher in Asia, 10% lower in the Americas and 20% lower in Europe. Global production of wood charcoal is estimated at 70.5 million tonnes, approximately 50% higher than previous values; our estimates are 20% higher in Africa and 200% higher in Asia. These estimates describe global shifts in wood fuel removals and charcoal production and improve our understanding of the forest sector; they will likely underlie global models used to forecast future trends.

Microbial determinants of soil quality in mixed larch and birch forests: network structure and keystone taxa abundances

Changes in forest soil microbial community characteristics affect soil function and quality. However, the mechanisms through which microbes drive soil quality across different stand types remain unclear. Three typical forest types, larch (Larix principis-rupprechtii) forest (LF), birch (Betula platyphylla) forest (BF), and mixed larch and birch forest (MF), were selected to assess soil properties, microbial community characteristics, and the complexity and stability of co-occurrence networks. The results showed that stand type significantly affected soil quality, microbial community composition, and network structure. Compared to LF stands, both MF and BF stands exhibited higher levels of soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), maximum water holding capacity (MWHC), and soil quality index (SQI), with the SQI increasing by 54.29% and 48.57%, respectively. The bacterial Shannon index was lower in MF and BF stands, whereas the fungal Shannon index was higher. Fungal community composition was more sensitive to variations among the three stand types than bacterial communities. The MF stands exhibited higher microbial complexity and stability, with a higher relative abundance of keystone bacterial and fungal taxa associated with nutrient cycling and transformation. These findings suggest that SQI can be enhanced by increasing soil fungal diversity, improving microbial network complexity and stability, and increasing the relative abundance of key microbial taxa. This study emphasized that the mixing of larch and birch significantly affected soil microbial community characteristics, which in turn impacted soil nutrient utilization. The insights gained provide a deeper understanding of soil nutrient cycling in plantation ecosystems, offering valuable references for sustainable forest management practices.

Imprecisions in imber yield estimation: challenges in Amazonian Forest management plans

In the Amazon, Forest Management Plans (FMPs) aim to balance economic activities with environmental objectives, yet relying solely on timber volume as a yield indicator may compromise the effectiveness of Annual Operating Plans (AOPs), leading to dis-crepancies between planned and actual harvesting. This study evaluated timber ex-ploitation by comparing planned variables with post-harvest data, focusing on timber volume, number of trees, and commercial height. The research was conducted in the Tapajós National Forest, Brazil, using data from a forest inventory, AOP planning documents and post-exploitation reports. Actual yield was calculated based on a 100% post-harvest census of felled trees and measured volumes, compared against AOP projections. Of the 6,267 trees scheduled for harvesting, 5,090 were felled (3.2 trees ha⁻¹), indicating an 85% yield. The most commonly harvested species were Manilkara huberi, Vochysia maxima, Lecythis lurida, Couratari guianensis and Hymenaea courbaril. Timber volume alone proved to be an insufficient yield predictor, as discrepancies also occurred in the number of trees and commercial height. Integrating these variables improves yield accuracy and allows for better adjustments in future AOPs. The adoption of species-specific volumetric equations is recommended to reduce discrepancies between planned and actual yield.

Impacts of Climate Change on Leaf Litter Chemistry and Decomposition in Forest Ecosystems

Chemistry and decomposition of leaf litter are integral to the carbon cycle in forest ecosystems. As leaves detach from trees, they accumulate on the forest floor, forming organic matter that serves as a source of energy and nutrients for soil microorganisms. Leaf litter decomposition releases carbon dioxide into the atmosphere and returns nutrients to the soil, which plants absorb. Climate change is expected to affect leaf litter chemistry and decomposition in forests significantly. Elevated temperatures may accelerate leaf litter decomposition, increasing carbon dioxide emissions. However, higher temperatures could worsen soil water stress, reducing water availability for plant growth and potentially slowing decomposition. Changes in precipitation patterns, such as increased drought frequency, can influence leaf litter chemistry and decomposition. Drought conditions may reduce soil moisture, slow decomposition and alter nutrient balance within leaf litter. Increased rainfall can enhance decomposition by providing moisture to support decomposer organisms. The chemical composition of leaf litter influences its decomposition rate. Leaves from different tree species contain varying levels of nitrogen, phosphorus, and other nutrients, affecting decomposition patterns. The chemistry and decomposition of leaf litter are key components of the carbon cycle within forest ecosystems, influenced by environmental and biotic factors. As climate change advances, these processes will be affected in complex ways, highlighting the importance of understanding their mechanisms. This understanding is essential for sustainable forest management in a changing world.

A Multimodal Deep Learning Framework for Accurate Biomass and Carbon Sequestration Estimation from UAV Imagery

Accurate quantification of above-ground biomass (AGB) and carbon sequestration is vital for monitoring terrestrial ecosystem dynamics, informing climate policy, and supporting carbon neutrality initiatives. However, conventional methods—ranging from manual field surveys to remote sensing techniques based solely on 2D vegetation indices—often fail to capture the intricate spectral and structural heterogeneity of forest canopies, particularly at fine spatial resolutions. To address these limitations, we introduce ForestIQNet, a novel end-to-end multimodal deep learning framework designed to estimate AGB and associated carbon stocks from UAV-acquired imagery with high spatial fidelity. ForestIQNet combines dual-stream encoders for processing multispectral UAV imagery and a voxelized Canopy Height Model (CHM), fused via a Cross-Attentional Feature Fusion (CAFF) module, enabling fine-grained interaction between spectral reflectance and 3D structure. A lightweight Transformer-based regression head then performs multitask prediction of AGB and CO2e, capturing long-range spatial dependencies and enhancing generalization. Proposed method achieves an R2 of 0.93 and RMSE of 6.1 kg for AGB prediction, compared to 0.78 R2 and 11.7 kg RMSE for XGBoost and 0.73 R2 and 13.2 kg RMSE for Random Forest. Despite its architectural complexity, ForestIQNet maintains a low inference cost (27 ms per patch) and generalizes well across species, terrain, and canopy structures. These results establish a new benchmark for UAV-enabled biomass estimation and provide scalable, interpretable tools for climate monitoring and forest management.

Estimating Biomass in Eucalyptus globulus and Pinus pinaster Forests Using UAV-Based LiDAR in Central and Northern Portugal

Accurate biomass estimation is important for forest management and climate change mitigation. This study evaluates the potential of using LiDAR (Light Detection and Ranging) data, acquired through Unmanned Aerial Vehicles (UAVs), for estimating above-ground and total biomass in Eucalyptus globulus and Pinus pinaster stands in central and northern Portugal. The acquired LiDAR point clouds were processed to extract structural metrics such as canopy height, crown area, canopy density, and volume. A multistep variable selection procedure was applied to reduce collinearity and select the most informative predictors. Multiple linear regression (MLR) models were developed and validated using field inventory data. Random Forest (RF) models were also tested for E. globulus, enabling a comparative evaluation between parametric and machine learning regression models. The results show that the 25th height percentile, canopy cover density at two meters, and height variance demonstrated an accurate biomass estimation for E. globulus, with coefficients of determination (R2) varying between 0.86 for MLR and 0.90 for RF. Although RF demonstrated a similar predictive performance, MLR presented advantages in terms of interpretability and computational efficiency. For P. pinaster, only MLR was applied due to the limited number of field data, yet R2 exceeded 0.80. Although absolute errors were higher for Pinus pinaster due to greater biomass variability, relative performance remained consistent across species. The results demonstrate the feasibility and efficiency of UAV LiDAR point cloud data for stand-level biomass estimation, providing simple and effective models for biomass estimation in these two species.

Endophytic Bacterial Consortia Isolated from Disease-Resistant Pinus pinea L. Increase Germination and Plant Quality in Susceptible Pine Species (Pinus radiata D. Don)

The nursery phase is vital for forest regeneration, yet studies on plant growth-promoting (PGP) bacteria to enhance sustainable nursery production in forest species are scarce. This study explores whether endophytic bacteria from disease-resistant Pinus pinea L. can improve germination and seedling quality in susceptible Pinus radiata D. Don. Root endophytes were isolated, screened for PGP traits, and identified via 16S rRNA gene sequencing. Bacterial formulations were applied to P. radiata seeds to determine their impact on germination and plant quality indicators (photosynthetic pigments and other metabolites). Paenibacillaceae (19%) and Bacillaceae (13%) were predominant among 68 isolates, with 94% producing indole-3-acetic acid, and Burkholderiaceae showing the broadest PGP trait diversity. Seedlings inoculated with formulation C3 (Caballeronia R.M3R3, Rhodococcus T.M4R4, and Mesorhizobium R.M1R2) displayed an improved germination rate (89% compared to 71% from the uninoculated control), while those inoculated with formulation P4 (Paenibacillus T.M5R4, Bacillus R.M2R7, Acinetobacter T.M2R22, and Paraburkholderia R.M1R3) showed an improved germination rate (81%), increased amount of starch (0.4-fold), and free amino acids (1.5-fold). This study presents a comprehensive approach, from endophyte isolation to in vivo tests, highlighting two bacterial formulations as candidates for further proof-of-concept nursery trials. Ultimately, these bioinoculants represent eco-friendly strategies to enhance forest seedling establishment and support sustainable forest management.

Preliminary Comparative Effects of Close‐to‐Nature and Structure‐Based Forest Management on Carbon Sequestration in Pinus tabuliformis Plantations of the Loess Plateau, China

ABSTRACTPinus tabuliformis plantations on the Loess Plateau face challenges such as poor quality and high mortality rates due to high initial value density and improper thinning practices. To prevent further deterioration of these forests, it is essential to identify suitable forest management methods as soon as possible. Within Pinus tabuliformis plantations under different management methods (structure‐based forest management [SBFM], close‐to‐nature forest management [CNFM], and unmanaged), after 5 years of investigation, we analyzed the changes in forest structural complexity and growth partitioning using size inequality (Gini), size–growth relationship (SGR), and growth dominance coefficient (GDC). A linear mixed‐effects model was applied to evaluate the impact of these practices on forest stands. We also compared the trends of the average annual breast height area increment (BAI) and projected the net‐zero timeline after thinning. The results showed that: (1) thinning management temporarily reduced the Gini due to the removal of a certain number of trees. However, the Gini rebounded significantly, and the forest structure became increasingly complex again, and the rebound of SBFM stands was greater than that of CNFM; (2) in the unmanaged stands, larger trees contribute more to stand growth. In the managed stands, the changes in GDC and SGR reflected an increasing contribution of smaller trees to overall growth; and (3) thinning management increased BAI, and this effect became more pronounced over time. Notably, carbon neutrality was projected to be achieved 7.8 years in CNFM stands, which was earlier than the 8.7 years in SBFM stands. These research results will provide a theoretical basis for managing and determining the trees to be harvested for high‐density, low‐quality Pinus tabuliformis plantations of the Loess Plateau.

Climate Change and Forest Governance: A Qualitative Review of Local Community Engagement in Rural East Africa

Community engagement plays a critical role in effective forest governance and climate change adaptation in East Africa. This qualitative review synthesizes evidence from 22 peer-reviewed studies published between 2010 and 2024, using participatory governance theory to examine how rural communities engage in forest management amid climate pressures. The analysis centers on three themes: forms and levels of participation, barriers to meaningful engagement, and implications for climate-resilient forest governance. Findings indicate that while frameworks such as Participatory Forest Management (PFM), Collaborative Forest Management (CFM), and Community Forest Associations (CFAs) have broadened community roles, genuine participation is limited. Across the reviewed literature, over 70% of studies reported that engagement remained superficial due to centralized decision-making, insecure land tenure, elite capture, and inequitable benefit-sharing. Conversely, customary institutions were highlighted in nearly half of the studies as offering adaptive, context-specific governance solutions—yet these systems are often sidelined in national policies. Additionally, climate finance mechanisms like REDD+ were noted in 8 studies to risk deepening exclusion if local voices are not meaningfully integrated. The review brings to light the need for transformative engagement rooted in secure rights, equitable power-sharing, recognition of indigenous knowledge, and strong accountability mechanisms. Moreover, these findings contribute to ongoing regional and global debates on climate justice, decolonizing conservation, and the future of community-based natural resource management in East Africa.

Featured Front Cover

The cover image is based on the article Integrating Restoration Practices With Productive Activities to Promote the Sustainable Management of Dry Forests Devoted to Livestock Raising by Laura Cavallero et al., https://doi.org/10.1002/ldr.5615. image