Protection Of Forest Resources Research Articles

RAF-Unet: A Remote Sensing Identification Method for Forest Land Information with Modified Unet

Abstract Carrying out remote sensing refinement identification of forest land in complex environment is of great significance for timely mapping of forest distribution. Aiming at the problem that remote sensing images have bias in the extraction of forest land information data, based on the semantic segmentation algorithm Unet, combining the ResNet50 deep learning network, the attention mechanism module and the feature pyramid structure, we construct RAF-Unet (ResNet+Attention+FPN+Unet) to improve the extraction of forest land information data. The ResNet50 classification network is used as the encoder of the Unet network to extract the feature maps at five different scales; then, the attention mechanism module is introduced in the decoder stage of the Unet network to extract the key task goal information by learning the weight values of the features; finally, the feature pyramid structure is used in the output stage of the encoder to fuse the information from the shallow network and the deep network to extract the remote sensing forest land information in the image. The results show that the RAF-Unet algorithm outperforms the Unet algorithm in all the indexes, with a precision of 95.24%, a recall of 91.80%, an F1-score value of 93.49%, an intersection over union of 87.63%, and an accuracy of 93.68%; the validity of the modules is verified by the ablation experiments, and the ResNet network, the attention mechanism, and the feature pyramid structure are all effective in improve the classification effect. It helps the forestry department to better manage and dynamically monitor forestry information, which is of great significance to the scientific development, utilization and protection of forest land resources.

Harnessing Potentials of Indigenous Environmental Myths for Forest Conservation in Rivers State

Indigenous environmental mythology has long been an essential component of many communities' ecological and cultural systems in the Rivers State, Nigerian These myths, which usually stem from the notion that nature is untouchable, offer crucial insights into the practices of traditional forest protection. This study looks into how these indigenous myths could help with current conservation efforts, particularly those that are meant to protect forest resources. By examining a number of myths and the associated behaviours, the study demonstrated how these cultural narratives have historically controlled human interaction with the environment, ensuring the sustainable use of forest resources. It also suggested how community members can remain involved in the conservation of forest resources. The study pointed out the forest's critical role in the welfare of rural Nigerian households. Therefore, the more community people participate in sustainable forest management, the more the forests contribute to meeting the needs of rural Nigerian household welfare. Thus, it was concluded that community involvement not only protects people of the community's means of sustenance but also enhances the social, economic, and environmental aspects of forestry efforts.

SmokeFireNet: A Lightweight Network for Joint Detection of Forest Fire and Smoke

In recent years, forest fires have been occurring frequently around the globe, affected by extreme weather and dry climate, causing serious economic losses and environmental pollution. In this context, timely detection of forest fire smoke is crucial for realizing real-time early warning of fires. However, fire and smoke from forest fires can spread to cover large areas and may affect distant areas. In this paper, a lightweight joint forest fire and smoke detection network, SmokeFireNet, is proposed, which employs ShuffleNetV2 as the backbone for efficient feature extraction, effectively addressing the computational efficiency challenges of traditional methods. To integrate multi-scale information and enhance the semantic feature extraction capability, a feature pyramid network (FPN) and path aggregation network (PAN) are introduced in this paper. In addition, the FPN network is optimized by a lightweight DySample upsampling operator. The model also incorporates efficient channel attention (ECA), which can pay more attention to the detection of forest fires and smoke regions while suppressing irrelevant features. Finally, by embedding the receptive field block (RFB), the model further improves its ability to understand contextual information and capture detailed features of fire and smoke, thus improving the overall detection accuracy. The experimental results show that SmokeFireNet is better than other mainstream target detection algorithms in terms of average APall of 86.2%, FPS of 114, and GFLOPs of 8.4, and provides effective technical support for forest fire prevention work in terms of average precision, frame rate, and computational complexity. In the future, the SmokeFireNet model is expected to play a greater role in the field of forest fire prevention and make a greater contribution to the protection of forest resources and the ecological environment.

Effect of Microbial Degradation Treatments on Lignocellulose, Cellulose, and Water-Holding Capacity of Four Typical Forest Fuels from Northeast China

Since forest fuel decomposes slowly and increases the risk of forest fires by accumulating over the years, forest fuel management to accelerate the decomposition process is essential to prevent forest fires and protect forest resources. In this study, we conducted experiments on forest fuels (Pinus sylvestris var. mongholica, Larix gmelinii, Quercus mongolica and Fraxinus mandshurica) in four typical plantation forests in northeast China by adding Trichoderma spp. to investigate the decomposition process and the changes in cellulose, hemicellulose and the water-holding capacity of the fuels. The addition of Trichoderma spp. accelerated the decomposition of cellulose, hemicellulose and lignin in the fuel. Trichoderma spp. promoted the ratio of water absorption and loss, as well as the water-holding capacity of the fuels. The ratio of water absorption and loss reached equilibrium when the decomposition time was up to 35 days, and the addition of Trichoderma spp. increased the maximal water-holding capacity of the fuel. The residual ratio of the four types of fuel degraded by the different treatments was inversely proportional to their maximal water-holding capacities and to the residual ratios of cellulose, hemicellulose and lignin. The residual ratios of degradation of the four fuels under different treatments were linearly related to their maximum water-holding capacity, cellulose, hemicellulose and lignin residual ratios. Trichoderma spp. had a positive effect on the degradation effect and water-holding capacity of fuel on the ground surface of four typical plantation forests. The study is of positive significance for the decomposition of fuel in forests, it promotes the development of biological fire prevention technology and provides a basis for the reinforcement of the management of fuel in forests and the protection of forest resources.

State and ameliorative properties of old original oak stands

The ameliorative properties of forest stands are essential for developing effective measures for environmental protection and sustainable use of forest resources. The purpose of the study was to assess the current condition and performance of erosion control properties of old oak stands of natural origin. The method of assessing the condition of old oak plantations using an integral indicator that takes into account biometric, ameliorative and health characteristics of stands, as well as agrochemical indicators of the soil has been tested. Field work was carried out on four experimental plots, where 794 age-old trees were enumerated. Comprehensive studies included determination of biometric indicators, analysis of root systems, detection of the content of available forms of nitrogen, mobile phosphorus, mobile potassium in soil. Soil hardness was measured with a durometer and soil water permeability using steel cylinders. High values of integral indicators were obtained in the experimental areas, which range from 11.9 to 19.7%. They guarantee the effective performance of erosion control properties by native old-growth forests. It has been researched that the proposed integral indicator of forest stand condition not only allows for assessing their current state but also demonstrates the effective control of erosion and ecological functions of the stand. It was established that essential requirement is to convert the absolute values of various indicators into relative values, with mandatory consideration of their positive or negative impacts on the forest stands themselves. It was found that an integral condition indicator can be used for erosion control plantations of any age range. The results can be used to develop biodiversity conservation programs and establish effective strategies for managing forest resources

Assessment of Community Participation in Forest Conservation in Ondo State, Nigeria

This study examines community participation in forest conservation in Ondo State, Nigeria, exploring the socio-economic dynamics and the effectiveness of decentralized forest management. Amidst escalating environmental degradation and forest depletion, this research highlights the critical role local communities’ play in the stewardship of forest reserves. Data were collected through surveys, interviews, and field observations involving 200 households across multiple communities adjacent to forest reserves. The findings reveal a strong community willingness to engage in forest conservation, with a substantial proportion of respondents prepared to accept financial incentives to aid in conservation efforts. The study also uncovers a significant correlation between socioeconomic factors—such as income levels, educational attainment, and proximity to forests—and the willingness to participate in conservation initiatives. Despite the readiness to support forest preservation, the research identifies a glaring lack of awareness and involvement in existing forest conservation programs. It is recommended that enhanced community education on the benefits of forest conservation, the introduction of more robust economic incentives, increased community involvement in conservation decision-making, and the strengthening of legal frameworks to protect forest resources. These steps are essential for sustainable forest management and biodiversity conservation in the area, which could serve as a model for similar regions globally.

Forest Fire Prediction Based on Time Series Networks and Remote Sensing Images

Protecting forest resources and preventing forest fires are vital for social development and public well-being. However, current research studies on forest fire warning systems often focus on extensive geographic areas like states, counties, and provinces. This approach lacks the precision and detail needed for predicting fires in smaller regions. To address this gap, we propose a Transformer-based time series forecasting model aimed at improving the accuracy of forest fire predictions in smaller areas. Our study focuses on Quanzhou County, Guilin City, Guangxi Province, China. We utilized time series data from 2021 to 2022, along with remote sensing images and ArcGIS technology, to identify various factors influencing forest fires in this region. We established a time series dataset containing twelve influencing factors, each labeled with forest fire occurrences. By integrating these data with the Transformer model, we generated forest fire danger level prediction maps for Quanzhou County. Our model’s performance is compared with other deep learning methods using metrics such as RMSE, and the results reveal that the proposed Transformer model achieves higher accuracy (ACC = 0.903, MAPE = 0.259, MAE = 0.053, RMSE = 0.389). This study demonstrates that the Transformer model effectively takes advantage of spatial background information and the periodicity of forest fire factors, significantly enhancing predictive accuracy.

Assessing social capital in community forest management in Kalibawang Sub-district, Wonosobo District, Central Java, Indonesia

Abstract. Herdananta BY, Ibriza NM, Wardha’adlina WA, Sulton MN, Sugiyarto, Budiharta S, Setyawan AD. 2024. Assessing social capital in community forest management in Kalibawang Sub-district, Wonosobo District, Central Java, Indonesia. Asian J Ethnobiol 7: 50-60. Community-based Forest Management (CFM) offers more effective protection of forest resources with a decentralized approach to ownership and management, as well as the establishment of autonomous local institutions that provide adequate incentives for the parties involved. The community manages natural resources through mutual use agreements, which lead to the concept of social capital as a solution to overcome collective problems. The study aims to evaluate the state of social capital in community forest management in Kalibawang Sub-district, Wonosobo, Central Java, Indonesia and identify the determinants that influence it as recommendations for improvement to policymakers. Data collection was conducted in March 2024 with research methods included interviews, surveys with questionnaires based on The Social Capital Assessment Tool (SCAT) and the Social Capital Integrated Questionnaire (SC-IQ) and Focus Group Discussion (FGD) discussions with local communities. The results showed that social capital in the studied area was significantly influenced by various variables, such as the role of forest farmer groups, access to information, community knowledge, non-formal education, and forestry extension activities. Consequently, the average level of social capital is obtained at 36.91 with a moderate category. Additionally, the analysis of concern community reveals a high classification, with an average score of 8.39. Increased social capital can be reflected in a higher density and diversity of social ties, as well as greater access to resources and stronger trust among group members. The recommendations of this study emphasize the importance of government in encouraging community participation in CFM management, reducing mistrust and conflict with government agencies, and strengthening social capital essential for sustainable forest management.

Formaldehyde-free bio-composites based on Pleurotus ostreatus substrate and corn straw waste

Corn straw-based board has great potential for the protection of forest resources, waste recycling, and sustainable economic development. However, corn stalk-based board has poor mechanical properties due to its short fiber length and poor water resistance because of the presence of numerous hydrophilic hydroxyl functional groups in its structure. Natural mycelium originating from waste Pleurotus ostreatus substrate is a hydrophobic bio-adhesive. In the present study, formaldehyde-free corn stalk/P. ostreatus substrate bio-composites were prepared using the hot-pressing technique without the addition of any chemical adhesive. The mechanical properties and water resistance of the prepared bio-composites were excellent. The highest internal bonding strength (IBS) of 2.16 MPa and the minimum thickness swelling (TS) of 18.3% were observed, which are beyond the national standards for particleboard in China. These bio-composites were prepared using a simple, green, and convenient manufacturing method to promote their popularization and application. The method may, therefore, be used as a novel technical measure to resolve the problem of overuse of forestry resources and waste disposal.

The Role of Local Governments in Supporting Social Forestry Implementation in Indonesia: A Social Network Analysis and Evidence from Eastern Indonesia

Social forestry has become an integral part of Indonesia's efforts to balance economic development, conservation of natural resources, and the well-being of local communities. The Jokowi administration has made significant efforts to promote this initiative, including allocating 12.7 million hectares of state forest areas and recognizing it as an instrument to address tenure issues in forest areas through the Omnibus Law on Job Creation with getting support from various regulations by relevant ministries. However, social forestry support is needed down to the local government/regional levels (provincial, regency, and village levels). This study aims to analyze the local government’s support for implementing social forestry. We employ Social Network Analysis to identify local government entities and their relationships in implementation processes. Additionally, document analysis is used to assess the extent of local government support through their working documents. The study shows that local government support for the implementation is still limited, with its execution primarily concentrated within a few agencies. Social forestry has not yet fully become a strategy for achieving community well-being around forests, enhancing local economies, or protecting forest resources. Furthermore, stakeholders' understanding of social forestry, resource availability, and local government policies to support it remains limited. Improvements in these three aspects are necessary to ensure successful implementation at the regional levels.

Legal terminology in environmental and land law: theoretical-legal analysis

The article examines the peculiarities of the formation of legal terminology in the field of environmental and land law and proves the feasibility of its improvement in connection with the adaptation of the norms of national law to the law of the European Union. The article states that today in Ukraine there is significant environmental pollution, climate change, land deterioration, which significantly worsened in connection with the military aggression of the Russian Federation and caused a particularly dangerous ecological situation in the country. The article proves that the implementation of the principles of the right of citizens to a safe environment, ensuring human safety, protection and rational use of land, forest, water and subsoil resources is not possible without a clear definition of legal prescriptions enshrined in the law. The article states that one of the important aspects of the language of law is legal terminology, which makes it possible to formulate the content of a legal document. The article defines the concepts of “terminology”, “terminology”, “legal terminology”. It is noted that it is not appropriate to equate the concepts of “terminology” and “terminological system”. It has been investigated that despite the presence of established terminology in environmental law, the presence of terms in need of improvement is observed in this field, namely: “ecological law” and “environmental law”. It has been proved that for the purpose of further codification of environmental law, it seems appropriate to use the term “environmental law” as an established term of EU legislation. It has been analyzed that today the language of the law in the field of land relations is gaining importance, which is due to the formation of the land market in Ukraine and the need to adapt the norms of land law to EU law. It is noted that in land law there is a problem of identifying the terms: “land”, “land plot”. It was noted that the legal terms related to the formation of the land market in Ukraine need improvement and detailing. It was concluded that legal terminology in the field of environmental and land law is one of the important aspects of the development of the language of law. The issue of improving legal terminology in the field of environmental and land law is one of the necessary steps that will contribute to the unification and harmonization of the legal norms of the specified fields in the context of adapting the norms of national law to EU law.

ASSESSMENT OF FOREST DISTURBANCES USING REMOTE SENSING: CASE OF KALIWA RIVER FOREST RESERVE (KRFR), PHILIPPINES

Abstract. The Kaliwa River Forest Reserve (KRFR) is located in the southwestern part of the Sierra Madre Mountain Range, Philippines. KRFR is one of the most important forest reserves in the country that is adjacent to urban areas and is very much affected by various forest disturbances. Forest disturbances can be caused by either anthropogenic or natural phenomena (e.g., typhoons, drought, and pathogen outbreaks) and may have negative effects on the forest structure and function. The study used the Normalized Difference Moisture Index (NDMI) in detecting forest disturbances for the period of 2010, 2015, and 2020. Results showed that the deforestation rate has significantly decreased from 6.22% in 2010 to 3.40% in 2020. The National Greening Program (NGP) and intensified forest protection activities of the Department of Environment and Natural Resources (DENR) may have contributed to the observed decreasing trend in deforestation rate. However, forest disturbance in the closed and open forest areas of KRFR gradually increased from 0.11% to 0.40%. Based on the accuracy assessment, the NDMI performed well in determining forest disturbances with mean values of 0.91 and 0.93 for completeness and correctness, respectively. The main contributor to forest disturbances in KRFR was mainly anthropogenic factors such as kaingin, illegal logging, urban sprawl, and upland farming. Outputs of this study can aid in the formulation of policies for better forest resource management, rehabilitation, and protection in the protected area.

Assessing forest cover changes in Dak Lak province (Central Highlands of Vietnam) from multi-temporal Landsat data and machine learning techniques

Dak Lak is a province in the Central Highlands region of Vietnam, with a large area of forests and forestry land. However, the forest cover has changed dramatically in recent times due to the influence of human activities and climate change. This article presents the results of assessing forest cover changes in Dak Lak province from Landsat satellite image data for the period 2000 – 2020. Three Landsat satellite image scenes, including Landsat 5 TM images taken in March 2000 and February 2010 and Landsat 8 OLI image taken in February 2020 are used to classify forest cover. Three common machine learning techniques, including Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Tree (CART) and the traditional maximum likelihood classification algorithm are used to classify forest cover in the study area, thereby choosing the method with the highest accuracy. The results show that the RF algorithm has the highest accuracy in classifying forest cover from multi-temporal Landsat images by comparing the overall accuracy value and the Kappa coefficient. The obtained results are used to build forest cover change maps in the period 2000 - 2010, 2010 - 2020 and 2000 - 2020. The results received in the study provide information to help managers in monitoring and protecting forest resources.

Beyond Ostrom: Randomized experiment of the impact of individualized tree rights on forest management in Ethiopia

We argue that while community forest management is effective in protecting forest resources, as argued by Ostrom, such management may fail to provide the proper incentives to nurture such resources because the benefits of forest management are collectively shared. This study proposes a mixed private and community management system characterized by communal protection of community-owned forest areas and individual management of individually owned trees as a desirable arrangement for timber forest management in developing countries. By conducting a randomized experiment in Ethiopia, we found that the mixed management system significantly stimulated intensive forest management activities, including pruning, guarding, and watering. Furthermore, more timber trees and forest products were extracted from the treated areas, which are byproducts of tree management (e.g., thinned trees and pruned branches). In contrast, the extracted volumes of non-timber forest products unrelated to tree management (fodder and honey) did not change with the intervention.

Mechanical soil disturbance in a pine savanna has multiyear effects on plant species composition

AbstractSoil disturbance threatens native perennial grasslands and savannas worldwide, including pine savannas of the North American Coastal Plain. Disk harrows are used in the region to plow linear features for firebreaks to contain prescribed fires, to manage game and other wildlife, and to reduce wildfire hazard to protect forest resources. However, the long‐term response of vegetation to these disturbances has not been well investigated. Our aim was to compare vegetation changes over time (0–9 years) following repeated disturbance by disking and a single disturbance by disking for firebreaks with undisturbed vegetation within a native pine savanna. We hypothesized that (1) a single disking event has multiyear effects on plant species composition and abundance because of the loss of perennial, dispersal‐limited species, but that partial survival of propagules allows the recovery to be more complete than following repeated disturbance, and (2) post‐disturbance changes are determined by species' life‐history characteristics resulting in a successional trajectory toward the undisturbed community. We established 10 plots within a repeated‐disturbance firebreak and a single‐disturbance firebreak, and in undisturbed vegetation (n = 30). We identified plant species within the plots six times over nine years, categorized plant species by life span, seed bank persistence, and dispersal mechanism, and assessed changes in the plant community using ordination. Changes in species composition in both repeated and single disturbance treatments showed a pattern consistent with succession toward the undisturbed plant community, but vegetation in neither disturbance treatment matched undisturbed treatment conditions within the nine years of study. Repeated‐disturbance plots progressed from a high occurrence of annuals to species with persistent seed banks and wind‐dispersed species. Single‐disturbance plots were more strongly associated with perennials, species lacking a persistent seed bank, and species dispersed by vertebrate consumption, but not to the same degree as undisturbed plots, although differences decreased slightly over time. Our results relating to narrow mechanical soil disturbances in pine savanna vegetation are consistent with studies concluding that similar but larger scale disturbances have long‐term degradational effects on the plant community. Therefore, conservation management plans should consider the possible negative long‐term effects of soil disturbance on native perennial herbaceous plant communities.

Fire-PPYOLOE: An Efficient Forest Fire Detector for Real-Time Wild Forest Fire Monitoring

Forest fire has the characteristics of sudden and destructive, which threatens safety of people’s life and property. Automatic detection and early warning of forest fire in the early stage is very important for protecting forest resources and reducing disaster losses. Unmanned forest fire monitoring is one popular way of forest fire automatic detection. However, the actual forest environment is complex and diverse, and the vision image is affected by various factors easily such as geographical location, seasons, cloudy weather, day and night, etc. In this paper, we propose a novel fire detection method called Fire-PPYOLOE. We design a new backbone and neck structure leveraging large kernel convolution to capture a large arrange area of reception field based on the existing fast and accurate object detection model PP-YOLOE. In addition, our model maintains the high-speed performance of the single-stage detection model and reduces model parameters by using CSPNet significantly. Extensive experiments are conducted to show the effectiveness of Fire-PPYOLOE from the views of detection accuracy and speed. The results show that our Fire-PPYOLOE is able to detect the smoke- and flame-like objects because it can learn features around the object to be detected. It can provide real-time forest fire prevention and early detection.

Early-Stage Pine Wilt Disease Detection via Multi-Feature Fusion in UAV Imagery

Pine wilt disease (PWD) is a highly contagious and devastating forest disease. The timely detection of pine trees infected with PWD in the early stage is of great significance to effectively control the spread of PWD and protect forest resources. However, in the spatial domain, the features of early-stage PWD are not distinctly evident, leading to numerous missed detections and false positives when directly using spatial-domain images. However, we found that frequency domain information can more clearly express the characteristics of early-stage PWD. In this paper, we propose a detection method based on deep learning for early-stage PWD by comprehensively utilizing the features in the frequency domain and the spatial domain. An attention mechanism is introduced to further enhance the frequency domain features. Employing two deformable convolutions to fuse the features in both domains, we aim to fully capture semantic and spatial information. To substantiate the proposed method, this study employs UAVs to capture images of early-stage pine trees infected with PWD at Dahuofang Experimental Forest in Fushun, Liaoning Province. A dataset of early infected pine trees affected by PWD is curated to facilitate future research on the detection of early-stage infestations in pine trees. The results on the early-stage PWD dataset indicate that, compared to Faster R-CNN, DETR and YOLOv5, the best-performing method improves the average precision (AP) by 17.7%, 6.2% and 6.0%, and the F1 scores by 14.6%, 3.9% and 5.0%, respectively. The study provides technical support for early-stage PWD tree counting and localization in the field in forest areas and lays the foundation for the early control of pine wood nematode disease.

Stability Analysis of Fixed Points in Forest Biomass Depletion Model

The main focus of this article is to present a model that explains the depletion in forest biomass due to population size , population pressure , and industrialization . This research explores the complex relationship between forest biomass, population growth, and industrialization. The model generates four fixed points that are all non-negative, and they are known as and . The article proceeds to analyze the stability of these fixed points in the context of forest biomass depletion. It is discovered that the fixed points and are saddle points and not stable, while the fixed point is stable if it meets certain conditions. The article concludes by carrying out numerical simulations to determine the equilibrium point of the model, which shows that forest resource biomass stability declines as population size, population pressure, and industrialization increase. The simulations reveal that population growth results in a depletion in forest resource biomass, while the opposite is true for the positive impact that forest resource biomass on population levels. Consequently, it is essential to regulate population density and industrialization to manage population growth and protect forest resources.

СПЕЦИФИЧЕСКИЕ ОСОБЕННОСТИ, ОПРЕДЕЛЯЮЩИЕ УСТОЙЧИВОЕ И РАЦИОНАЛЬНОЕ ЛЕСОПОЛЬЗОВАНИЕ В РОССИЙСКОЙ ФЕДЕРАЦИИ

Sustainable development of enterprises and rational forest management in the Russian Federation are distinguished by a number of specific features that are determined by the national, geographical and economic conditions of the country. Rich forest resources, which represent an important natural wealth of Russia, provide the potential for the development of the timber industry sector and create opportunities for rational forest management. Russia also has a unique natural environment, including diverse ecosystems and rare species of animals and plants. The rational and sustainable use of forests is becoming a priority for maintaining the biological diversity and environmental sustainability of the country. In general, the sustainable development of enterprises and rational forest management in the Russian Federation is a complex and multifaceted process that requires a harmonious interaction of economic, environmental, social and technological aspects. It is necessary to take into account the specifics of the country's natural, geographical and cultural characteristics, as well as comply with international standards and norms in the field of protection and sustainable use of forest resources. 
 The need to incorporate the entire set of existing specific features defining sustainable and rational forest management arose quite a long time ago, which led to the author's approach to this topic.
 The article considers the systematized list of specific features proposed by the author that determine the sustainable development of the subjects of the forest complex and rational forest management in the Russian Federation.

Forest Management in Ukraine Under War Conditions

Attention is drawn to scientifically based theoretical and practical approaches to the implementation of the concept of sustainable forest management and, accordingly, to ensuring the principles of sustainable forestry aimed at the adequate protection, use, and regeneration of forest resources in Ukraine during Russia's war against Ukraine. The main socio-economic and ecological aspects that influence the implementation of the concept of sustainable forest management at the national and regional level in the current conditions of Russia's military aggression against Ukraine are considered. The changes in the forest sector in the conditions of war are reflected, which must be considered from the point of view of understanding the principles of sustainable development, sustainable forestry, and the concept of sustainable forest management. It is proposed to develop and implement a theoretical, methodological, and practical approach to the implementation of the concept of sustainable forest management in Ukraine which would take into account the regional differences regarding the organisation and development of forestry in Ukraine.