Forest Management Research Articles

A contemporary analysis of policy implementation for the coastal mangrove forest management in Bangladesh Sundarbans

Despite having more than 200 environmental laws and policies in Bangladesh, the overall ecological situation is almost beyond control. Relying on both primary and secondary sources of data, particularly the legal texts, this study delves into analysing the legal frameworks of Bangladesh pertaining to wildlife and biodiversity conservation in the Sundarbans mangrove forest (SMF). This study finds that the lack of implementation of stringent provisions is one of the key reasons for the failure to successfully conserve biological diversity in the SMF. The other reason that heavily accelerates environmental crimes in Bangladesh is the less severe punishment compared to other crimes. This study result reveals that the Animal Welfare Act 2019 imposes a mere BDT 10,000 (USD 116) for harming any animal. This study also finds that the Environment Court Act 2010 strives to expand environmental governance in every district, but the absolute authority of the Department of Environment (DoE) and its limited resources hinder such lavish expansion. Although the government has revised many outdated laws and policies and enacted new laws such as Bangladesh Environment Conservation Act 1995 (2023), Forest Act 2023, and Forest Conservation Act 2023, evidence indicates that most of the provisions were not successfully implemented due to overlaps with other laws and loopholes within the laws. In addition, complex bureaucratic systems significantly hamper the administration system in forest management. Furthermore, the Director General (DG) of the DoE’s sole authority often sparked concerns regarding the transparency and accountability of this department. Therefore, this paper examines the domestic legal system of Bangladesh for conserving biodiversity in the SMF.

The Influence of Participatory Forest Monitoring on Natural Forest Management and Community Welfare: A Case Study in Kibale National Park, Western Uganda

The paper presents findings from a Study on Participatory Forest Monitoring (PFM) and Natural Forest Restoration (NFR) in Uganda, a case of communities bordering Kibale National Park (KNP), western Uganda. The study involved 394 respondents who were interviewed from June to August 2024. The study adopted a cross-sectional research design to determine the perceived effect of Participatory Forest Monitoring Activities at the household level and examine the relationship between Participatory Forest Monitoring Activities and Natural Forest Restoration while involving communities bordering Kibale Forest. Almost half (54.4%) of the communities bordering Kibale National Park (KNP) work with UWA rangers during forest monitoring patrols in restored areas (M=2.25, SD = 1.95). Participation in PFM improved income at the household level directly addressing household needs especially income for school fees and other needs by 79.9% (r=0.799, P<0.05). PFM can restore natural forests, increase revenue and better community livelihoods.

I want to climb to the tops of trees! Factors facilitating the development of ivy vines in central European forests

Abstract Lianas, which are considered to form tree-related microhabitats, are known as important elements of tropical forests; however, their ecological function and relationships with host trees (phorophytes) in temperate forests are poorly known. This gap in knowledge stems from a low species diversity and abundance of lianas in temperate forests. An exception is common ivy (Hedera helix), which is widely distributed and is currently increasing its abundance in temperate forests. In this study, we examined the relationships between ivy vines with features of their phorophytes, using Central European upland mixed forests as an example. We assess the presence and density of ivy within 69 study plots, established in the forest interior and ecotone. We use generalized linear mixed-effects models to assess drivers of ivy’s presence and its density, while accounting for the tree diameter at breast height, bark roughness, and the canopy light transmittance. We show that ivy is able to grow on nearly all tree species, although it prefers phorophytes with rough bark and a large diameter. Large generative individuals (ivy vines that produce fruits) were found mostly on veteran trees (usually oaks, alders, or pines). For its growth, ivy requires tree phorophytes with only a moderate transparency of light through the tree crowns, which is likely related to evergreen leaves that enable ivy vines to also develop during leaf-off periods. The features of phorophytes preferred by ivy indicate that the vine finds optimal conditions for development in old patches of tree stand, often in areas inaccessible or unprofitable for forest management. We propose using large and fruiting ivy vines as indicators of old-growth forests that deserve protection, which would be in line with the current policy of sustaining and restoring close-to-natural forests in Europe.

Soil quality assessment and its response to water flow connectivity in different vegetation restoration types, eastern China

Vegetation restoration is the most widely used forest management practice for degraded soils, but the responses of soil quality in different vegetation restoration types may vary. In addition, the relationship between water flow paths connection and soil quality needs to be further explored. In this study, the soil quality index (SQI) and the index of water flow connectivity (IWFC) in the six water flow patterns (PFP, SSB, WSB, CPS, CPW, and CSW) were explored at three forest stands (oak, pine, and bamboo forests) with 50 years for enclosure. The results showed that the bamboo forest stand had the best soil quality as a whole (0.534 ± 0.135), followed by pine (0.530 ± 0.180) and oak forest stands (0.435 ± 0.205). The IWFC in PFP, CPS and CPW water flow patterns decreased gradually with increasing soil depth, while in SSB, WSB and CSB water flow patterns, the IWFC increased at first and then decreased. Finally, the IWFC in the CPW water flow pattern showed the largest positive correlation with the SQI (P < 0.05). The IWFC in the CPW water flow pattern driven by soil physical properties could mainly control the changes in the SQI indirectly (average IE = 0.825) by influencing soil nutrient (average IE = 0.447) and biological (average IE = 0.485) properties, while its direct effects could be ignored (average DE = −0.074), which demonstrated that the joint effects of preferential flow paths and weak stream buffer zones can dramatically reflect the changes in soil quality. The better soil improvement effect of bamboo and pine forest stands compared to the oak forest stand should be given more consideration. This study provided new insights for the assessment of the relationship between soil hydrology and soil quality.

Warming exacerbates global inequality in forest carbon and nitrogen cycles

Forests are invaluable natural resources that provide essential services to humanity. However, the effects of global warming on forest carbon and nitrogen cycling remain uncertain. Here we project a decrease in total nitrogen input and accumulation by 7 ± 2 and 28 ± 9 million tonnes (Tg), respectively, and an increase in reactive nitrogen losses to the environment by 9 ± 3 Tg for 2100 due to warming in a fossil-fueled society. This would compromise the global carbon sink capacity by 0.45 ± 0.14 billion tonnes annually. Furthermore, warming-induced inequality in forest carbon and nitrogen cycles could widen the economic gap between the Global South and Global North. High-income countries are estimated to gain US$179 billion in benefits from forest assets under warming, while other regions could face net damages of US$31 billion. Implementing climate-smart forest management, such as comprehensive restoration and optimizing tree species composition, is imperative in the face of future climate change.

Thermal Comfort Simulation-Based Forest Management Scenarios for Forest Healing

Background and objectives: Forest environments provide various healing benefits for humans and have been widely studied. Nevertheless, the field of forest management for forest healing remains relatively understudied. The purpose of this study is to utilize thermal environmental simulation to derive forest management scenarios that are optimized for forest healing. Methods: This study focused on the Seogwipo Experimental Forest on Jeju Island, Korea. Three-dimensional forest models were generated based on field surveys. Thermal environment simulations were conducted using Grasshopper with the Ladybug and Honeybee plug-ins, and the thermal comfort levels of six forest management scenarios were evaluated using the Universal Thermal Climate Index (UTCI). Results: The simulation results showed that, among all the scenarios, only scenario (c), “10% thinning in the buffer zone”, led to an improvement in thermal comfort. Additionally, the study identified discrepancies in thermal comfort between different forest management scenarios. Conclusions: In the management of forests for healing forestry purposes, the distinction of forest zones by use and the application of different forest management scenarios have thermal comfort implications. Thus, the methodology could be employed in forest management for forest healing purposes.

CPH-Fmnet: An Optimized Deep Learning Model for Multi-View Stereo and Parameter Extraction in Complex Forest Scenes

The three-dimensional reconstruction of forests is crucial in remote sensing technology, ecological monitoring, and forestry management, as it yields precise forest structure and tree parameters, providing essential data support for forest resource management, evaluation, and sustainable development. Nevertheless, forest 3D reconstruction now encounters obstacles including higher equipment costs, reduced data collection efficiency, and complex data processing. This work introduces a unique deep learning model, CPH-Fmnet, designed to enhance the accuracy and efficiency of 3D reconstruction in intricate forest environments. CPH-Fmnet enhances the FPN Encoder-Decoder Architecture by meticulously incorporating the Channel Attention Mechanism (CA), Path Aggregation Module (PA), and High-Level Feature Selection Module (HFS), alongside the integration of the pre-trained Vision Transformer (ViT), thereby significantly improving the model’s global feature extraction and local detail reconstruction abilities. We selected three representative sample plots in Haidian District, Beijing, China, as the study area and took forest stand sequence photos with an iPhone for the research. Comparative experiments with the conventional SfM + MVS and MVSFormer models, along with comprehensive parameter extraction and ablation studies, substantiated the enhanced efficacy of the proposed CPH-Fmnet model in addressing difficult circumstances such as intricate occlusions, poorly textured areas, and variations in lighting. The test results show that the model does better on a number of evaluation criteria. It has an RMSE of 1.353, an MAE of only 5.1%, an r value of 1.190, and a forest reconstruction rate of 100%, all of which are better than current methods. Furthermore, the model produced a more compact and precise 3D point cloud while accurately determining the properties of the forest trees. The findings indicate that CPH-Fmnet offers an innovative approach for forest resource management and ecological monitoring, characterized by cheap cost, high accuracy, and high efficiency.

Quantifying changes in forest structural complexity using bi-temporal airborne laser scanning

ABSTRACT Structural complexity is an important forest characteristic for habitat assessment, forest management and planning. However, monitoring how forest structural complexity evolves over time in various forest types has not been widely explored. In this study we investigate the feasibility of bi-temporal low-density airborne laser scanning (ALS) for the assessment of changes in light availability conditions within forest canopy, considered to imply changes in forest structural complexity. We used ALS data acquired in 2012 and 2019 to generate canopy vertical profiles by slicing the point clouds into 4 × 4 ×1 m voxels which were then rasterized and reclassified into four light availability categories. To understand structural development over time in different forest types we used field-measured tree heights and tree species information to stratify sample plots in different stand complexity categories. Stands with higher structural complexity represented increased proportions of space occupied by vegetation as well as decreased proportions of empty space below the canopy. The experiments showed the ability of low-density ALS to characterize the dynamics in canopy layering structure, implying changes in forest structural complexity. The presented methodology could potentially be upscaled and applied in the landscape-level monitoring of the development of boreal forest structural characteristics.

Differential responses of woodland caribou to fire and forestry across boreal and montane ecosystems—a literature review

Abstract Ecosystem-based management (EBM) is a landscape-level management and planning process that is common across North America. A primary tenet of EBM is that the area and intensity of anthropogenic disturbance should mimic the historical natural disturbance of the focal ecosystem. Biodiversity should persist, at least at a coarse scale, where anthropogenic disturbance, such as forest harvesting, matches natural disturbance. However, EBM is failing some species, particularly those that are dependent on old forest. Across many areas of Canada, woodland caribou (Rangifer tarandus caribou) are declining because of the direct and indirect effects of habitat loss and fragmentation. This is even though forest management often follows the principles of EBM. We conducted a qualitative comparison of the responses of woodland caribou to wildfire and forest harvesting, considering a broad range of responses, including habitat selection and distribution, forage, movement patterns, and population dynamics. We found that while wildfire and forest harvesting both influence caribou, the negative effects are generally greater following forest harvesting. For example, wildfire and forest harvesting result in the loss of habitat, but caribou are more likely to shift, abandon or contract their range in response to harvest. The literature also suggested a stronger negative population response of caribou to forest harvest when compared to wildfire. This difference could be the result of greater residual forest structure associated with wildfire as well as the extensive resource roads that are necessary for forestry operations. Although there is sound theoretical support for EBM, the practice, as implemented, may not be effective for maintaining the habitat and ultimately populations of woodland caribou.

Comparison Between Gans and Diffusion Models in the Generation of Synthetic Images for Enhancing Tree Species Recognition

Objective: This study investigates the application of Generative Adversarial Networks (GANs) and Diffusion Models in data augmentation to improve the classification of tree species images, which is essential for sustainable forest management. Theoretical Framework: Fundamental concepts of machine learning, generative and classifier networks, as well as data augmentation techniques through synthetic image generation, are presented, establishing a solid foundation for the research. Method: The research utilized 2,178 images of cross-sections of wood from 18 species, applying Deep Convolutional GAN (DCGAN) and U-Net with diffusion on a rare species, evaluated using FID and IS metrics. The generated images were used to train and validate classification models, assessed by F1-score. Results and Discussion: The results revealed that Diffusion Models generated more realistic images and performed better in the classification of the rare species. The discussion contextualizes these results in light of the theoretical framework, exploring their implications for environmental management. Limitations, such as the impact of indiscriminate addition of synthetic data, are also addressed. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of forest management and environmental management. These implications may cover areas such as sustainable innovation and biodiversity conservation. Originality/Value: This study contributes to the literature by demonstrating the potential of Diffusion Models to outperform GANs in generating synthetic images for sustainable forest management purposes. The relevance and value of this research are evidenced by its practical application in promoting innovative and sustainable practices in environmental management.

Where to start with climate-smart forest management? Climatic risk for forest-based mitigation

Abstract. Natural disturbances like windthrows or forest fires alter the provision of forest ecosystem services such as timber production, protection from natural hazards, and carbon sequestration. After a disturbance, forests release large amounts of carbon and therefore change their status from carbon sinks to carbon sources for some time. Climate-smart forest management may decrease forest vulnerability to disturbances and thus reduce carbon emissions as a consequence of future disturbances. But how can we prioritise the stands most in need of climate-smart management? In this study we adopted a risk mapping framework (hazard times vulnerability) to assess the risk to climate-related forest ecosystem services (carbon stock and sink) in forests prone to windthrow (in the Julian Alps, Italy) and forest fires (in the Apennines, Italy). We calculated hazard by using forest fire and windthrow simulation tools and examined the most important drivers of the respective hazards. We then assessed vulnerability by calculating current carbon stocks and sinks in each forest stand. We combined these values together with the calculated hazard to estimate “carbon risk” and prioritised high-risk stands for climate-smart management. Our findings demonstrate that combining disturbance simulation tools and forest carbon measurements may aid in risk-related decision-making in forests and in planning decisions for climate-smart forestry. This approach may be replicated in other mountain forests to enhance our understanding of their actual carbon vulnerability to forest disturbances.

Potential Global Distribution and Habitat Shift of Prunus subg. Amygdalus Under Current and Future Climate Change

The genus of Prunus subg. Amygdalus are endangered Tertiary-relict plants that are an essential source of woody plant oil. In order to provide a theoretical basis for better protection and utilization of species in the Prunus subg. Amygdalus. This study collected global distribution information for six species within the Prunus subg. Amygdalus, along with data on 29 environmental and climatic factors. The Maximum Entropy (MaxEnt) model was used to simulate the globally suitable distribution areas for these species within the subgenus. The suitable results showed that the area under the test curve (AUC) values of the simulation results were more than 0.8, indicating that the simulation results have high accuracy. Temperature, precipitation, UV-B, and altitude were critical environmental factors affecting the distribution of each species in Prunus subg. Amygdalus. Currently, the distribution area of six species in this genus, from largest to smallest, is Prunus triloba (Lindl.) Ricker, Prunus tenella Batsch, Prunus amygdalus Batsch, Prunus pedunculata Maxim, Prunus mongolica Maxim and Prunus tangutica (Batal.) Korsh. The simulation results of distribution areas showed that under the ssp2.45 and ssp5.85 scenarios, the potential distribution areas of P. amygdalus, P. tangutica, and P. pedunculata all show a decreasing trend, while the distribution areas of P. mongolica and P. tenella, and P. triloba exhibit an increasing trend. The general distribution of P. amygdalus, P. mongolica, and P. tenella will trend to transfer in a northwest direction. P. tangutica and P. pedunculata were affected by other environmental factors (such as slope, altitude, and soil pH), and the distribution area has a tendency to move northeastward. The P. triloba moved to the southwest. The spatiotemporal distribution patterns of Prunus subg. Amygdalus can be used as a reference for forest management and to formulate species conservation strategies.

Thirty Years of Research on Ecosystem Services: The Socio-Economic Role of Forest Visits and Foraging in Enhancing Human Well-Being

This paper examines the socio-economic significance of forest visits and the collection of forest berries and mushrooms (FBMs) in the Czech Republic, emphasising their role in enhancing human well-being and contributing to regional economies. Over a 30-year period, data were collected on the quantities and economic values of FBMs, alongside the intensity of forest visits by the Czech population. This study incorporates a detailed analysis of time series data on FBM collection, exploring trends and fluctuations in the harvested quantities and their economic value. A Lorenz curve analysis reveals significant disparities in the distribution of economic benefits, with a small segment of the population accounting for the majority of the FBM-derived value. Additionally, the research investigates the impact of forest visitation on well-being at the regional level, highlighting the relationship between forest access, visitation intensity, and public health benefits. This study also examines visitors’ expectations, motivations, and perceptions regarding an ideal forest for visitation, providing recommendations for effective marketing strategies. Furthermore, the study explores the contribution of FBMs to net income across different regions, demonstrating substantial regional variation in their economic importance. Notably, the analysis shows that the value of FBMs represents approximately 37% of the net income generated by traditional forestry activities, underscoring its significant economic potential. The findings emphasise the potential of territorial marketing strategies to enhance well-being, particularly in economically disadvantaged regions, and advocate for sustainable forest management practices to protect these valuable resources and ensure equitable access to the benefits provided by forest ecosystems.

Accessing the Trail, Interpreting the Forest

The Stephen F. Austin Experimental Forest is the site of the first ADA-compliant US Forest Service project in Texas. Offering information about the history of forest management alongside information on Pineywoods ecosystems, the interpretive trail raises questions about how access is framed across “natural” and “built” environments as well as how distinctions between nature and culture operate within US environmental imaginaries. This article draws on feminist, posthumanist, and disability studies to conduct a close reading of the interpretive trail as text. It tracks the trail’s approach to disability access as well as its presentation of forest ecology, analyzing how the ableist logic of capitalist commodification underwrites the management of multispecies actants in the woods. I read against the grain of the trail in search of feminist, crip, posthumanist configurations of interdependence and more fluid human–nature boundaries. I argue that cripping the Austin requires questioning the unevenness of disability access as well as the utilitarian ideas of nature presented on the trail while also imagining how we might access and relate to this postindustrial forest otherwise.

Evaluation of Ecological Service Functions of Urban Greening Tree Species in Northern China Based on the Species-Specific Air Purification Index

Urban forests, as an integral part of nature-based solutions (NBS), are significant contributors to improving urban air quality, delivering ecological service functions and environmental benefits to human health and well-being. Suitable urban forest management, including proper species selection, needs to be defined to efficiently reduce air pollutants in cities, with a focus on the removal ability of the main air pollutants (PM2.5, PM10, O3, and NO2), the ecological adaptability to O3 and NO2, and allergenic effects. This study ranked 73 urban greening tree species in northern Chinese cities based on their ability to maximize air quality and minimize disservices. This study proposed a novel Species-Specific Air Purification Index (S-API), which is suitable for air quality improvement for tree/shrub species. Urban managers are recommended to select species with an S-API &gt; 1.47—that is, species that have a high removal capacity of PM2.5, PM10, O3, and NO2, are O3- and NO2-tolerant, and are non-allergenic (e.g., Castanea mollissima Blume, Ginkgo biloba L., Hibiscus syriacus L., Ilex chinensis Sims, Juniperus procumbens (Endl.) Iwata et Kusaka, Liriodendron chinense (Hemsl.) Sarg., Morus alba L., Styphnolobium japonicum (L.) Schott, Syringa oblata Lindl., and Ulmus pumila L.). The S-API of urban greening species thus represents a potentially useful metric for air pollutant risk assessment and for selecting appropriate species for urban greening in cities facing serious air pollution challenges.

Carbon Stock Estimation of Poplar Plantations Based on Additive Biomass Models

Accurate estimation of biomass and carbon stocks in forest ecosystems is critical for understanding their roles in carbon sequestration and climate change mitigation. Currently, the development of stand biomass models and carbon stock estimation at the regional scale has emerged as a prominent research priority. In this study, 225 Populus spp. (poplar) trees in Shandong Province, China, were destructively sampled to obtain the biomass of their components. Two models (MS1 and MS2) were developed using allometric equations and the seemingly unrelated regression (SUR) method to ensure additive properties across tree components. The model evaluation employed the leave-one-out jackknife (LOO) method, considering statistics such as adjusted R-squared (Ra2), root mean square error (RMSE), mean absolute percent error (MAPE), and mean absolute error (MAE). The results from our models demonstrated high accuracy, with MS2 slightly outperforming MS1 after incorporating tree height as an independent variable. The models reliably estimated component-specific biomass and carbon stocks, with distinct variations observed in the carbon content among foliage (47.14 ± 2.07%), branches (47.26 ± 2.48%), stems (47.67 ± 2.21%), and roots (46.37 ± 2.78%). Carbon stocks in poplar plantations increased with the diameter class, ranging from 5 to 35 cm and correspondingly from 3.670 to 172.491 Mg C ha−1. As the diameter class increases, the carbon allocation strategy of poplars aligns with the CSR strategy, transitioning from prioritizing growth competition to emphasizing self-stabilization. Our research proposes a robust framework for assessing biomass and carbon stocks in poplar plantations, which is essential for evidence-based forest management strategies.

Depth-dependent effects of forest diversification on soil functionality and microbial community characteristics in subtropical forests

Soil microbes are critical to the maintenance of forest ecosystem function and stability. Forest diversification, such as monocultures versus mixed forests stands, can strongly influence microbial community patterns and processes, as well as their role in soil ecosystem multifunctionality, such as in subtropical forest ecosystems. However, less is known about these patterns and processes vary with soil depth. Here, we investigated the results of an eight-year forest diversification field experiment comparing the soil ecosystem multifunctionality, bacterial and fungal community assembly, and network patterns in mixed versus monoculture plantations along vertical profiles (0–80 cm depth) in a subtropical region. We found that the introduction of broadleaf trees in coniferous monocultures led to enhanced synergies between multiple functions, thus improving soil multifunctionality. The effects of mixed plantations on the functional potential in top soils were greater than in deep soils, especially for carbon degradation genes (apu, xylA, cex, and glx). Microbial community assembly in the top layer, particularly in mixed plantations, was dominated by stochastic processes, whereas deterministic were more important in the deep layer. Soil microbial network complexity and stability were higher in the top layer of mixed plantations, but in the deep layer was monoculture. Interestingly, the changes in microbial communities and multifunctionality in the top layer were mainly related to variation in nutrients, whereas those in the deep were more influenced by soil moisture. Overall, we reveal positive effects of mixed forest stands on soil microbial characteristics and functionality compared to that of monocultures. Our findings highlighted the importance of enhancing functional diversity through the promotion of tree species diversity, and managers can better develop forest management strategies to promote soil health under global change scenarios.

The Effect of Transition to Close-to-Nature Forestry on Growing Stock, Wood Increment and Harvest Possibilities of Forests in Slovakia

The aim of the study is to quantify the impacts of a possible transition to close-to-nature forestry in Slovakia and to compare the expected development of the total volume production, growing stock, merchantable wood increment and harvesting possibilities of forests in Slovakia with current conventional management using the FCarbon forest-growth model and available data from the Information System of Forest Management. The subject of the study was all forest stands available for wood supply (FAWS). The simulations were run in annual iterations using tree input data aggregated over 10-year-wide age classes. The calculation of wood increments was based on available growth models. In the business-as-usual (BAU) scenario, stock losses were based on the actual intensity of wood harvesting in the reference period 2013–2022. In the scenario of the transition to close-to-nature forest management, the losses were specifically modified from the usual harvesting regime at the beginning, to the target harvesting mode in selective forest at the end of the simulated period. With the modelling method used, a gradual increase in forest stocks occurred in both evaluated scenarios in the monitored period, namely by 10% in the case of BAU and by 23% in the case of close-to-nature forest management until 2050. In absolute mining volume, CTNF is by 5–10% lower than BAU management, with the difference gradually decreasing. The results show that the introduction of close-to-nature forest management will temporarily reduce the supply of wood to the market, but this reduction will not be significant and will be compensated by a higher total volume production, and thus also by increased carbon storage in forests.

The Historiography of Forests use Types and Implication for Forest Conservation in the Montane Forests of Ngongbaa, Kilum, Kovifem and Kovkinkar

This study explores the timeline history of forest use types and beneficial relationship of forest, forest communities and conservation in the montane forests of Ngongbaa, Kilum, Kovifem and Kovkinkar from the mid-1970s to 2015. Data and/or information collected for this study comprise literary, questionnaire, interview, focused group discussions and observations. Data for the study was secured from person directly resident adjacent forest in 29 villages. The study shows that apart from being asource of food and medicine, forest first served as settlement and refuge sites for the Nso, Mbiame and Oku people. Today, forest serves as cemetery for the fons (kings), and host shrines which have become conservation hot spots and nurseries for engendered plants and animal species, where the Nso, Mbiame and Oku also performed sacrifices. These conservation hot spots help to sustain the forest in montane ecosystems where pressure on land and forest is high and on the rise. Due to population pressure and limited grazing the grassland compartments in the above forests have been transformed into grazing ground. The long period of intercourse between the Nso, Mbiame, Oku people and their forest enabled them to accumulate rich and useful knowledge of the forest and established customary (non- statutory or quasi-statutory) regulatory frameworks for effective management of forest resources to improve their livelihood and culture. Due to the depletion of forest and the adoption of stricter conservation policies, some forest activities particularly carving and hunting have decreased in intensity while some like Ngwa’a (royal hunt) has simply phased out due to the extinction of animal species which were hunted. The paper recommends that traditional systems of managing forest be reinforced to enhance the conservation of resources in sacred groves that are nurseries for threatened and extinct species in degraded ecosystems. The state should recognise and integrate non-statutory forestry policy frameworks established in the Nso, Mbiame and Oku into the national forestry policy as village-based institutions for the management of land and forest in forest communities. The government should also empower traditional authorities (Fon,Nwerong and Lanlords (ataangven) and support reforestation and forest restoration programmes formulated by them. This is because laws put in place by these institutions are respected in the most part by their subjects without being forced to do so, unlike in the Ngongbaa and Kilum forests managed by the state, where forestry laws are permanently violated by local people who consider forestry authorities as state agents who are depriving them of their right of tenure and usufruct. This would likely help to maintain biodiversity and knowledge attached to it, which is gradually disappearing due to forest depletion.

DASR-Net: Land Cover Classification Methods for Hybrid Multiattention Multispectral High Spectral Resolution Remote Sensing Imagery

The prompt acquisition of precise land cover categorization data is indispensable for the strategic development of contemporary farming practices, especially within the realm of forestry oversight and preservation. Forests are complex ecosystems that require precise monitoring to assess their health, biodiversity, and response to environmental changes. The existing methods for classifying remotely sensed imagery often encounter challenges due to the intricate spacing of feature classes, intraclass diversity, and interclass similarity, which can lead to weak perceptual ability, insufficient feature expression, and a lack of distinction when classifying forested areas at various scales. In this study, we introduce the DASR-Net algorithm, which integrates a dual attention network (DAN) in parallel with the Residual Network (ResNet) to enhance land cover classification, specifically focusing on improving the classification of forested regions. The dual attention mechanism within DASR-Net is designed to address the complexities inherent in forested landscapes by effectively capturing multiscale semantic information. This is achieved through multiscale null attention, which allows for the detailed examination of forest structures across different scales, and channel attention, which assigns weights to each channel to enhance feature expression using an improved BSE-ResNet bilinear approach. The two-channel parallel architecture of DASR-Net is particularly adept at resolving structural differences within forested areas, thereby avoiding information loss and the excessive fusion of features that can occur with traditional methods. This results in a more discriminative classification of remote sensing imagery, which is essential for accurate forest monitoring and management. To assess the efficacy of DASR-Net, we carried out tests with 10m Sentinel-2 multispectral remote sensing images over the Heshan District, which is renowned for its varied forestry. The findings reveal that the DASR-Net algorithm attains an accuracy rate of 96.36%, outperforming classical neural network models and the transformer (ViT) model. This demonstrates the scientific robustness and promise of the DASR-Net model in assisting with automatic object recognition for precise forest classification. Furthermore, we emphasize the relevance of our proposed model to hyperspectral datasets, which are frequently utilized in agricultural and forest classification tasks. DASR-Net’s enhanced feature extraction and classification capabilities are particularly advantageous for hyperspectral data, where the rich spectral information can be effectively harnessed to differentiate between various forest types and conditions. By doing so, DASR-Net contributes to advancing remote sensing applications in forest monitoring, supporting sustainable forestry practices and environmental conservation efforts. The findings of this study have significant practical implications for urban forestry management. The DASR-Net algorithm can enhance the accuracy of forest cover classification, aiding urban planners in better understanding and monitoring the status of urban forests. This, in turn, facilitates the development of effective forest conservation and restoration strategies, promoting the sustainable development of the urban ecological environment.