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This study aimed to determine optimal conditions for Watershed algorithm-based individual tree crown segmentation using UAV-derived Canopy Height Model (CHM) and grayscale imagery. Three sample plots were established in coniferous forests (Pinus koraiensis and Larix kaempferi) and a broadleaf forest (Quercus mongolica) in Pocheon-si, Gyeonggi-do, and Cheongju-si, Chungcheongbuk-do, South Korea. CHM and grayscale images were constructed at spatial resolutions of 5 cm, 25 cm, and 50 cm. Gap regions were classified using three thresholding methods (Otsu, Entropy, and Percentile 5%, 10%, 15%), followed by individual tree crown segmentation using the Watershed algorithm. Accuracy was assessed by comparing segmentation results with reference data generated through visual interpretation of the imagery. For gap region classification, the Percentile 10% method achieved the most balanced accuracy between crown and gap regions, with a mean crown IoU of 0.88, and showed consistent performance across tree species, data types, and spatial resolutions. For Watershed-based individual tree segmentation, the MAE of individual tree counts showed the most consistent segmentation accuracy at a spatial resolution of 25 cm in Pinus koraiensis and Larix kaempferi, with 50 trees/ha for CHM and 63 trees/ha for grayscale images. For Quercus mongolica, segmentation accuracy was highest at a spatial resolution of 50 cm, with 50 trees/ha for CHM and 100 trees/ha for grayscale images. Over-segmentation occurred at 5 cm, while under-segmentation was observed at 50 cm. CHM exhibited higher accuracy at finer resolutions, whereas grayscale imagery performed better at coarser resolutions. Regarding tree species, coniferous forests with conical crown structures showed higher segmentation accuracy than broadleaf forests. This study highlights the need to select appropriate data types and spatial resolutions according to forest stand characteristics and is expected to contribute to UAV-based individual tree-level forest structure analysis and precision forest inventory.

Cocoa poverty, low productivity and climate change have undermined sustainable production in several cocoa-producing countries. In response, Côte d’Ivoire and Ghana—accounting for about 60% of global cocoa exports—introduced a $400/ton Living Income Differential (LID) in 2019 to boost farmers’ earnings. This paper assessed farmers’ awareness of LID and their willingness to reinvest these earnings into cocoa production. Using a mixed-methods approach, 156 cocoa farmers were randomly selected from five communities and interviewed using a semi-structured questionnaire, complemented by in-depth interviews on LID policy to provide contextual understanding. The results showed 99% of respondents were aware of the then-new LID, and 96% perceived the disbursement process as transparent. While the LID broadly strengthened incentives for cocoa farming, only 30% of respondents were willing to reinvest in their farms and labor services, primarily citing poor returns on past reinvestments. Gender, household size, frequency of LID received, years in cocoa farming, communities with strong social networks and access to shared resources, perceived yield gains from previous reinvestment, and the interaction between yield increase and amount reinvested are statistically significant determinants. Notably, many cocoa farmers prioritize expenditure on education, housing, and healthcare, reflecting broader household livelihood strategies over farm-level investment. Farmers’ reluctance to reinvest points to structural challenges, including land tenure insecurity and persistent productivity constraints that limit the LID's intended environmental and sustainability aims. The findings call for rebalancing cocoa revenue allocation strategies, with strengthened value chain support and targeted policy intervention to address systemic barriers, ensuring the LID and related cocoa sector policies contribute meaningfully to sustainable cocoa production and farmers' livelihoods.

Gnetum africanum (Welw.) is a vital non-timber forest product that contributes to food security, income generation, and rural lives in Nigeria. Despite its importance, little empirical evidence exists on its processing and trade patterns. This study assessed processing practices, profitability, sustainability strategies, and the value chain of G. africanum among 120 processors and traders in Cross River State, Nigeria. Data were obtained through structured questionnaire, key informant interviews, and field observations, and analyzed using descriptive statistics, gross margin and rate of return on investment (RORI), and Chi-square tests with Cramér V. Results showed women dominated processing (88%) and retailing, with middle-aged respondents most active. Processing was largely manual and labor-intensive, while traders benefited from bulk aggregation. Profitability analysis confirmed viability, with RORI of 65% for processors and 78% for traders. However, sustainability practices were weak, as 72% relied solely on wild harvesting, though awareness of ecological concerns was high. Chi-square tests indicated that gender (χ2=14.27, p＜0.01), education (χ2=12.33, p＜0.01), and experience (χ2=15.62, p＜0.01) significantly influenced enterprise outcomes. Constraints included poor preservation technologies, tenure insecurity, and weak cooperative structures. The study underscores G. africanum’s dual role as a livelihood resource and conservation concern, calling for policies to strengthen domestication, improve processing technologies, and empower women in collective marketing and governance.

This study investigated the impacts of climate change on the distribution of the Near Threatened River Lapwing (Vanellus duvaucelii Lesson 1826) in Bhutan, where information about this species is not sufficient. The study aimed to understand River Lapwing’s current and future suitable habitat in Bhutan. An ensemble ecological modelling approach was used up to the year 2100, binding GLM, BRT, RF, and MaxEnt. Current and future climatic scenarios (SSP1-2.6 & SSP3-7.0) were analyzed, where the model demonstrated high predictive accuracy (average AUC=0.93, COR=0.72). Results suggested a significant threat from climate change and habitat shifts. Particularly towards central and eastern Bhutan with a considerable habitat loss in the southern region under the moderate greenhouse gas emission scenario (SSP3-7.0). The study showed that climate change is causing significant habitat shifts and losses, underscoring the need for conservation efforts to regulate human disturbance and promote climate-aligned conservation strategies for River Lapwings in Bhutan.

Milicia excelsa (iroko) is an economically important indigenous timber species in tropical Africa whose persistence may be affected by climate change. This study assessed current and future climatic suitability of M. excelsa across West and Central Africa using Random Forest species distribution modelling and explainable machine learning. A total of 307 spatially thinned occurrence records and 307 pseudo-absences were used. Following multicollinearity screening, four predictors: precipitation of the driest month (BIO14), precipitation seasonality (BIO15), precipitation of the coldest quarter (BIO19), and elevation, were retained. The final model achieved a test ROC-AUC of 0.8917, with an optimal classification threshold of 0.5824. Current suitable habitat covered 476,444.99 km2, declining to 431,335.14 km2 in 2050 and 434,938.59 km2 in 2070 under the SSP245 scenario. Despite these reductions, 80.85% and 80.64% of current suitable habitat were retained in 2050 and 2070, respectively. Persistent climatic refugia comprised 17,248 cells (368,088.30 km2) that remained suitable across all three periods. SHAP analysis identified BIO14 as the most influential predictor and revealed a nonlinear relationship between dry-season precipitation and predicted suitability. Environmental novelty increased from 0.79% under current conditions to 2.28% in 2050 and 2.86% in 2070, while approximately 99% of suitable cells remained environmentally supported. The findings indicate that climate change is likely to redistribute rather than uniformly eliminate climatically suitable habitat for M. excelsa, providing evidence to support climate-informed conservation and sustainable forest management.

Forest ecosystems play a critical role in harboring species diversity and the terrestrial carbon pool. However, it remains unclear how ecosystem parameters impact species diversity and carbon storage at the regional scale, specifically in the Indian scenario. In the present study, we investigated the divergent underlying factors controlling species diversity and ecosystem carbon storage in major forest types of North-East Himalaya, India. The vegetation data were collected by establishing 250 m×250 m major plots in each major forest type, and tree biomass was estimated using an allometric equation specifically developed for Northeast Indian forests. We observed that the species diversity was determined by the combined effects of environmental factors, soil nutrients, and plant structural attributes, whereas the forest carbon storage was significantly linked with plant density (r=0.853, p=0.01), basal area (r=0.933, p=0.01), and elevation (r=0.675, p=0.05). It is therefore recommended to include environmental factors, edaphic factors and plant structural attributes for predicting regional diversity; and both plant structural attributes and environmental parameters for predicting ecosystem carbon storage amidst current and future changing climatic scenarios, and also in formulating conservation strategies related to carbon sink management in the study area.

The objectives of this study were to assess and quantify afforestation and forest restoration in the village called Zighb for the year 2000 and 2018. Landsat TM (2000) and Landsat 8 OLI (2018) imagery data were gathered to evaluate the forestland cover change and the significance of afforestation program in Zighb. Supervised classification method using ENVI and GIS software was applied to extract, classify and analyze the imagery data into different land-use cover. In addition, field work, map of the study area from Ministry of Agriculture (MoA), unsupervised techniques, high resolution Google Earth image, and vegetation indexes such as Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI), were applied to develop signatures and enhance accuracy of classification. Relatively, the image classification accuracy is high where overall accuracy was circa 85.83% and 82.42% in 2000 and 2018, respectively. The results revealed that evidence of forest restoration was identified in the study area because of afforestation and forestry programs. The afforested land grew by about 3.7% between 2000 and 2018. However, irrigational land and natural vegetation are observed to decline by approximately 2.72% and 0.86%, respectively, as the farmland fell by circa 1.92% between 2000 and 2018. In addition, the bare lands are also decreased by circa 4.02%, possibly due to afforestation and forestry activities, expansion of building (2.41%). Therefore, this study provides useful information for decision making such as developing suitable policy for forest restoration using more appropriate afforestation and forestry programs. Moreover, it might be important for future studies.

In many parts of Nigeria, women and girls bear the cost of fetching firewood, a traditional cooking method. The expensive traditional cooking method burns upto 90% wood than necessary. Hence, this study focused on briquette production using residues generated from Non-Timber Forest Products (NTFPs) namely: Irvingia gabonenis husk Vitellaria paradoxa shell and Parkia biglobosa chaff, as suitable and sustainable source for clean cooking. The residue were sourced from Forestry Research Institute of Nigeria. Each material was oven dried (12% MC), grinded, sieved using 2 mm mesh and mixed thoroughly with cooked cassava starch at 10% and 15% binder level and the briquettes were replicated 5 times. The strength properties, energy value and cooking efficiency were carried out using American Standard Test Methods (ASTM). Data were analyzed using Analysis of Variance (ANOVA) at (p＜0.05). Results shows that briquette produced from V. paradoxa shell at 15% binder level had the highest density (655.37 g/cm3). Irvingia gabonensis husk briquette exibit highest shatter index at both binder level (96.72% and 96.99%). Likewise, I. gabonensis husk had the highest water resistance at 15% binder level (66.60%). Briquette with lowest ash content (3.40%) and highest calorific value (32.54 MJ/kg1) was found in V. paradoxa shell at 15% binder level. Highest Water Boiling Time of 32 mins was recorded for Parkia biglobosa chaff at 10% binder level. Fuel Burning Rate of I. gabonensis husk and V. paradoxa shell at 15% binder level were higher (0.004 kg/sec), Specific Fuel Consumption of V. paradoxa shell briquette (0.20 kg/L) was highest at 15% binder level. Among the three residues, briquettes produced from V. paradoxa shell at 15% binder level exhibited better performance and as environmentally friendly solution to waste management while offering a renewable energy source.

Afforestation in dry lands faces numerous challenges, particularly in regions like Darfur, Sudan, where droughts and desertification lead to forest degradation and social conflicts. This study evaluates the impact of rainwater harvesting techniques (RWHTs) on the survival and growth of Ziziphus spina-christi transplants in Nyala Agriculture Research Station Farm, South Darfur State. The experiment was conducted during March 2018 and January 2020; it tested four RWHTs: Control, Semicircular Bund, Trapezoidal Bund, and V-Shape Catchment, laid out in a 6 randomized block design with 3 replications of each technique within the block (6 blocks×4 RWHTs×3 replications=72 units, each containing one transplant). Key parameters measured included soil properties, soil moisture at various depths, transplants’ survival, and growth metrics. The soil type was clayey cambic, influenced by aridity and sand creep. Rainfall was erratic, totaling 183.2 mm, or 45.8% of the average. Mean temperature was 35.1°C; it affected transplants indirectly by lowering soil moisture storage through evaporation-transpiration. RWHTs significantly recharged soil moisture and improved transplants’ survival rates by 75%, 66.7%, 58.3%, and 25% for Trapezoidal Bund, Semicircular Bund, V-Shape Catchment, and the Control, respectively. RWHTs also increased growth metrics by following folds: 1.6 for shoot height, 1.5 for diameter, 1.9 for number of branches, 1.6 for root length, 2.3 for shoot biomass, and 1.9 for root biomass. Performance ranking of RWHTs was: Trapezoidal Bund＞Semicircular Bund=V-Shape Catchment＞Control. These findings suggest that RWHTs can support the establishment, survival, and growth of transplants in moisture-deficient dry lands, making them a reliable afforestation strategy for individuals and institutions.