The Thai Forest Ecological Research Journal (TFERJ) is an open access bi-annual peer-reviewed journal of forest ecology in Thailand. The journal publishes original scientific papers that report and interpret the findings of pure and applied research into the plants and their interaction with biotic and abiotic environments. The goal of TFERJ is to promote the platform for scientists and academics who share and discuss various new issues and perspectives in diverse areas of forest ecology. TFERJ welcomes submissions from Thai and foreign researchers who study related ecological topics in Thailand including: Forest ecology: Studies of plant communities, populations, or individual ecology, plant ecophysiology, ecosystems, and landscape ecology are accepted. Forest management: Studies of forest management, silviculture, forest restoration, as well as plant utilization are accepted. Plant and wildlife management: Studies of the interactions between plants and animals (or fungi), and habitat management for biodiversity conservation are accepted. Forest dynamics and environmental changes: Studies of the impact of environmental changes, climate change, and natural or anthropogenic disturbance on forest dynamics are accepted. Other related plant science: Studies of experimental plant breeding, plant genetics, and other related plant ecological sciences are accepted.
Cooperation Centre of Thai Forest Ecological Research Network (CC-TFERN), Department of Forest Biology, Faculty of Forestry, Kasetsart University
Application of Random Forest Algorithm and Multi-Temporal Satellite Data for Forest Types Classification in Chiang Mai Province
Background and Objectives: Chiang Mai Province is strategically important as a major watershed area for the Ping River basin ecosystem and boasts one of the highest biodiversity levels in Thailand. However, this area is currently facing a severe and challenging environmental crisis, particularly the rapid decline in forest area and recurring wildfires during the dry season. These fires have ongoing consequences, leading to transboundary air pollution and PM 2.5 levels that are hazardous to public health and the regional economy. The severity and spread of wildfires are directly related to fuel type and forest types. Deciduous forests, such as dry dipterocarp forest and mixed deciduous forest, which ecologically shed leaves and accumulate large amounts of dry biomass fuel during the dry season, are more susceptible to fire and more severe fire spread than evergreen forests, which have higher humidity levels. Therefore, an accurate, high-resolution, and up-to-date forest classification map database is urgently needed for fuel management planning, wildfire risk zone identification, and natural resource restoration. However, classifying forest types in the complex mountainous terrain of Chiang Mai Province presents a significant challenge for remote sensing due to physical factors such as mountain shadows and the similarity of spectral reflectance values among different vegetation species at certain times. Traditional methods using single-temporal satellite imagery cannot effectively distinguish between deciduous and evergreen forests. To overcome this limitation, integrating multi-temporal satellite imagery capable of tracking vegetation phenology changes throughout the year, along with machine learning technology on a large-scale data processing platform like Google Earth Engine (GEE), is a powerful approach. This research therefore aims to: 1) create a forest classification map of Chiang Mai Province for the year 2024 using a random forest (RF) algorithm, and 2) analyze the feature importance of both spectral indices and topographic factors to identify the ecological factors that have the greatest influence on classification accuracy. Method: This study was conducted on the Google Earth Engine (GEE) platform to process large-scale geospatial data. The primary dataset comprised Sentinel-2 Level 2A (Surface Reflectance) imagery, which had been atmospherically corrected, covering the entire 22,436 square kilometers. The data preparation process was divided into two main parts. The first involved creating a median composite image during the dry season (December 1, 2023 – March 31, 2024), selecting only images with less than 60% cloud cover to serve as a cloud-free baseline for analyzing the relationships between variables. The second component involved constructing a time-series stack comprising representative monthly images from four dry-season periods and one wet-season period. This multi-temporal approach was specifically designed to capture the distinct phenological signatures of leaf shedding and greening. Furthermore, topographic data, including elevation, slope, and aspect, were derived from the Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) and resampled to a 20-meter spatial resolution. The researchers initially calculated a comprehensive set of 26 predictor variables, encompassing vegetation indices, water and soil indices, forest-specific indices, and original spectral bands. To optimize model performance, a two-step Feature Selection process was implemented. Initially, Pearson’s correlation coefficient analysis was used to eliminate highly redundant variables (excluding those with r > 0.90 or r < -0.90). Subsequently, the remaining variables were ranked based on the Mean Decrease in Gini Impurity metric using the Random Forest algorithm. The classification model targeted three distinct classes: deciduous forest, evergreen forest, and non-forest. Reference data consisted of 750 standard ground-truth points, collected via stratified random sampling to ensure spatial independence. These points were randomly partitioned into an 80% training set (600 points) and a 20% testing set (150 points). The RF classifier was parameterized with 500 decision trees (ntrees) to maximize stability. Results: The feature selection process successfully refined the dataset to an optimal subset of 12 non-redundant variables. The analysis revealed that topographic features were the most influential factors governing the model's predictive capability. Specifically, elevation was dominance the ranking with the highest importance score (629.27), followed by slope (492.16). Among the spectral predictors, the shadow index (SI) (215.45) and the Green Normalized Difference Vegetation Index (GNDVI) (184.90) proved to be the most critical variables, as they effectively captured the complexities of canopy structures and mitigated topographic shadow effects during the dry season. The developed RF model demonstrated exceptional performance, achieving a high Out-of-Bag (OOB) accuracy of 90.30%. When evaluated against the independent testing set, the model yielded an Overall Accuracy of 95.92% and a Kappa coefficient of 0.94. Class-specific performance analysis indicated that the non-forest class achieved the highest accuracy (Producer’s Accuracy 97.92%, User’s Accuracy 100%), followed by evergreen forest (Producer’s Accuracy 94.12%, User’s Accuracy 96.00%), and deciduous forest (Producer’s Accuracy 95.83%, User’s Accuracy 92.00%). The final spatial map revealed that deciduous forests cover approximately 48.70% (10,779.68 km2) of the province, predominantly distributed in foothills and mid-elevation zones, while evergreen forests account for 32.37% (7,164.34 km2), densely dominating the higher mountain ranges, which perfectly aligns with highland forest ecology principles. However, spatial verification identified specific limitations. Minor misclassifications were observed within ecological transition zones (ecotones) at elevations between 800 and 1,150 meters due to highly mixed forest structures. Additionally, spectral confusion occurred in agricultural areas containing perennial, long-living fruit orchards (e.g., longan and orange orchards), which maintain permanent green canopies that closely resemble the spectral signatures of natural evergreen forests. Conclusion: This study demonstrates that applying a RF algorithm with multi-temporal Sentinel-2 imagery on a cloud computing platform provides a highly robust, cutting-edge tool for mapping complex forest ecosystems in mountainous regions. Empirical findings confirm that elevation serves as the most important ecological boundary for forest classification in northern Thailand. The resulting high-precision classification map serves as a vital spatial database for accurately delineating wildfire risk zones and supporting targeted natural resource management. For further enhance model accuracy in future research, it is highly recommended to refine the non-forest class by explicitly separating perennial fruit orchards into distinct sub-categories. Furthermore, incorporating Synthetic Aperture Radar (Sentinel-1 SAR) data or employing advanced texture analysis should be strongly considered to improve the differentiation of physical vegetation structures across complex landscapes.
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Relationship between Measured Buttressed Stem Girth and Girth Derived from Actual Basal Area in Lagerstroemia floribunda Jack in Eastern Thailand
Background and Objectives: Accurate measurement of stem size is a fundamental component of forest mensuration, as it directly underpins the estimation of basal area, timber volume, aboveground biomass, and carbon stocks in forest ecosystems. In tropical forests, however, standard protocols for measuring stem girth or diameter at breast height (DBH) are frequently complicated by the presence of buttresses. These structural adaptations alter stem geometry, causing girth measurements taken at the conventional height of 1.30 m above ground to deviate from the idealized cylindrical form. Consequently, measurements that include buttresses tend to overestimate stem girth and propagate systematic bias into subsequent calculations of forest structure and ecosystem services. To avoid this issue, conventional practice recommends measuring stem size above the buttress. Nevertheless, this alternative approach introduces a different form of bias, as stem diameter typically decreases with height due to tapering. In many tropical species, such as Lagerstroemia floribunda, buttresses may extend continuously along much of the lower stem, making it difficult or impractical to define a consistent measurement position. These challenges are particularly critical in permanent plots, where monitored must be conducted at the same position. Despite the widespread recognition of this issue, practical and standardized methods for correcting buttressed stem measurements remain limited. Therefore, this study aimed to (1) develop a regression model relating measured buttressed girth to girth derived from the actual basal area of L. floribunda, (2) evaluate the accuracy of the developed model, and (3) assess its applicability to other tree species with similar buttress morphology. Methodology: The study was conducted in lowland tropical forest areas in eastern Thailand, where buttressed tree species are common. L. floribunda was selected as the focal species due to its well-developed ridge-type buttresses that often extend along the lower stem. A total of 50 trees were sampled using a size-class stratified sampling design to ensure representation across a wide range of girth classes. For each tree, stem girth including buttresses was measured at 1.30 m above ground. At the same height, the actual cross-sectional shape of the stem was captured by tracing the outer bark surface, including buttress contours, using a flexible aluminum strip to conform to irregular surfaces. The traced shapes were transferred onto reference sheets, scanned, and digitized in a geographic information system (GIS). The true cross-sectional area was then calculated from the digitized polygons. Based on the calculated area, an equivalent circular girth was derived mathematically to represent the girth corresponding to the actual basal area. The relationship between measured buttressed girth (denoted as GBH_mb, cm) and girth derived from actual basal area (denoted as GBH_pred, cm) was analyzed using simple linear regression based on the least squares method. Model performance was evaluated using the coefficient of determination (R²) and the statistical significance of regression parameters. To assess the robustness and applicability of the model, it was further validated using independent datasets of L. floribunda and additional buttressed species, including Markhamia stipulata var. stipulata and Irvingia malayana. Residual analysis was performed to evaluate systematic bias across girth classes and to examine model behavior at the lower and upper extremes of observed data. Main Results: A strong linear relationship was observed between measured buttressed girth and girth derived from the actual basal area for L. floribunda, with the regression model explaining a high proportion of variance (R² = 0.989, p < .001). The fitted equation was: GBH_pred = 3.266 + 0.874 × GBH_mb. The regression slope of less than unity indicates that measurements buttress systematically overestimate true girth, reflecting the lateral expansion of buttress structures rather than proportional increases in cross-sectional area. Validation using independent datasets showed no significant difference between predicted and observed values, with residuals symmetrically distributed around zero, indicating the absence of systematic bias within the calibrated range. When applied to other species with similar buttress morphology, the model maintained low mean prediction errors and showed consistent performance. However, when applied to species with distinctly different buttress morphologies, prediction errors increased substantially, highlighting the influence of stem architecture on model applicability. Residual analysis across girth classes revealed no consistent trend of bias, supporting the use of a single correction model across the observed size range. Nevertheless, for smaller trees with measured buttressed girth values below approximately 26 cm, the model tended to slightly overpredict girth derived from actual basal area. This pattern reflects the influence of positive intercept of the regression equation and the limited development in smaller trees. Conclusion: This study demonstrates that stem girth measured including buttresses at breast height can be effectively corrected to approximate true cross-sectional girth using an empirical regression approach. The proposed model provides a practical and field-applicable alternative to conventional measurement above buttresses, enabling consistent and repeatable measurements at a fixed height. This is particularly advantageous for long-term monitoring in permanent sample plots, where measurement consistency is essential. The model performs reliably within the calibrated girth range and for species with similar buttress morphology. However, caution is required when applying the model to small trees (GBH < 26 cm) or to species with different buttress forms. Overall, the approach reduces systematic measurement bias and enhances the accuracy and consistency of basal area, biomass, and carbon stock estimation in tropical forest inventories. Further research incorporating additional species and environmental conditions would help improve the general applicability of the model. This approach provides a standardized and practical solution for improving the accuracy of forest inventory and carbon stock estimation in tropical forests affected by buttressed tree forms.
Population Density and Habitat Suitability of Gaur (Bos gaurus H. Smith) in the Phu Fa Non-Hunting Area, Nan Province
Background and Objectives: Spatial ecology of wildlife provides a fundamental basis for conservation planning and sustainable natural resource management. This is particularly important for gaur (Bos gaurus H. Smith), the largest extant wild bovine, which requires extensive home ranges, exhibits low reproductive rates, and is highly sensitive to environmental changes. Currently, gaur populations are facing increasing pressure from habitat loss and fragmentation driven by human activities, as well as limitations in forest connectivity. These factors contribute to population decline and elevate the risk of habitat isolation in the long term. Although protected areas in Thailand have been progressively expanded, information on population density and spatial use patterns of gaur remains limited, particularly in mountainous forest ecosystems in northern Thailand, where terrain complexity and inaccessibility constrain field studies. Phu Fa Non-Hunting Area represents an ecologically significant forest landscape for wildlife, especially gaur, comprising relatively intact montane evergreen and dry evergreen forests. The area also has high potential as an ecological corridor facilitating movement of large mammals between Thailand and the Lao People’s Democratic Republic. However, current knowledge regarding population status and environmental determinants of habitat suitability in this area remains insufficient to support effective spatial management. Therefore, this study aims to estimate the population density of gaur and to analyze environmental factors influencing habitat selection. The findings are expected to provide baseline information for conservation planning, habitat restoration, and long-term population monitoring. Material and method: Field data collection was conducted from November 2024 to October 2025. A total of 10 camera trap stations were systematically deployed across the study area to record the occurrence of gaur. Camera locations were selected based on areas with a high likelihood of gaur presence, including wildlife trails, water sources, and natural salt licks. In addition, signs of wildlife were recorded during patrol surveys, including direct sightings, vocalizations, footprints, dung, and feeding evidence, along with their geographic coordinates. All collected data were processed for statistical and spatial analyses. Population abundance was assessed using the Relative Abundance Index (RAI), calculated as the detection rate per number of trap nights. Population density was estimated using the Random Encounter Model (REM), which does not require individual identification and is particularly suitable for large ungulates lacking distinctive individual markings. Habitat suitability was evaluated using the Maximum Entropy (MaxEnt) model, which has been widely recognized for its high performance in predicting species distribution from presence-only data. A total of seven environmental variables were included in the analysis, comprising both physical and biological factors: elevation above mean sea level, slope, land use, distance to water sources, distance to roads, distance to villages, and distance to ranger stations. Model performance was assessed using the Area Under the Receiver Operating Characteristic Curve (AUC) to evaluate the model’s ability to discriminate between suitable and unsuitable habitats. Results and discussion: A total sampling effort of 3,650 trap nights resulted in 27 independent detections of gaur, yielding a Relative Abundance Index (RAI) of 0.74%, indicating a relatively low detection rate. However, population density estimated using the REM was 19.6 individuals/km², suggesting that the study area still has the capacity to support a viable gaur population. The spatial distribution of gaur was uneven, with individuals tending to utilize specific areas associated with key resources, such as water sources, foraging grounds, and refuge sites. Habitat suitability analysis using the MaxEnt model demonstrated excellent model performance (AUC = 0.987). Approximately 35 km², representing 29.41% of the total study area (~119 km²), was classified as suitable habitat for gaur. Highly suitable areas were predominantly distributed within montane evergreen and dry evergreen forests, which provide favorable conditions for gaur survival. Permutation importance analysis indicated that distance to water sources, distance to ranger stations, and distance to villages were the most influential variables determining gaur occurrence. In contrast, percent contribution values highlighted the importance of both physical and biological factors, particularly elevation, land use (dry evergreen and montane evergreen forests), and distance to water sources, in shaping habitat suitability. Highly suitable habitats were primarily concentrated in high-elevation mountainous areas (1,200–1,600 m above mean sea level), characterized by a mosaic of ridge-top grasslands interspersed within montane and dry evergreen forests. These habitat features likely enhance resource availability, provide suitable shelter, and facilitate avoidance of potential threats. Although anthropogenic disturbance factors, such as roads and human settlements, had relatively lower contributions, they still played a role in constraining the spatial distribution of gaur within the study area. Conclusion: The results indicate that although the population density of gaur in the study area is relatively low, the presence of suitable habitat covering approximately one-third of the total area reflects the potential of the forest landscape to support population persistence and future expansion. These findings provide important implications for management interventions, including the improvement of water sources, enhancement of forage availability, and maintenance of habitat connectivity to reduce the risk of population isolation. Furthermore, the establishment of baseline data on population density and habitat suitability serves as a critical tool for long-term monitoring of population dynamics and for evaluating the effectiveness of conservation measures. With appropriate management, the study area has the potential to function as a core habitat and a source population, contributing to regional population stability. This, in turn, would strengthen forest ecosystem integrity and support the sustainable conservation of wildlife in northern Thailand over the long term.
Spatial Modeling and Environmental Factors Influencing Seasonal Habitat Use of Wild Elephants (Elephas maximus) in Thung Salaeng Luang National Park, Phitsanulok Province
Background and Objectives: The Asian elephant (Elephas maximus) is classified as an umbrella species that plays a critical role in forest ecosystem conservation. Thung Salaeng Luang National Park (1,262.40 km²), located within the Phu Miang–Phu Thong Forest Complex, represents a key habitat for wild elephants. However, habitat fragmentation resulting from the expansion of human settlements and agricultural areas has compelled elephants to increasingly utilize agricultural lands as pseudo-habitats, elevating the risk of human-elephant conflict. This study aimed to analyze environmental factors influencing seasonal habitat selection and estimate home range size of wild elephants in Thung Salaeng Luang National Park, with the goal of informing wildlife management and conflict mitigation strategies. Methodology: A total of 650 wild elephant occurrence records – comprising direct sightings, dung deposits, footprints, and rubbing marks – were collected from qualitative SMART patrol data between 2018 and 2024. Records were partitioned into dry season (November–April) and wet season (May–October) datasets. Maximum Entropy (MaxEnt) modeling was applied using 11 environmental variables across three categories: physical, biological, and threat factors, on a 100×100 m grid. Data were randomly split into 75% training and 25% testing sets, with five replications, and model performance was evaluated using the Area Under the Curve (AUC). Results: Both seasonal models demonstrated good predictive performance (dry season AUC = 0.764; wet season AUC = 0.858). During the dry season, the most influential factors were distance to evergreen forest (46.10%) and distance to grassland (12.70%), with elephants exhibiting a broad distribution across the park and a home range of 456.92 km². During the wet season, distance to dry evergreen forest (21.70%) and distance to salt licks (21.00%) were the primary determinants, with elephants showing a more clustered distribution in the central and southern areas and a reduced home range of 173.03 km². The difference of 283.89 km² between seasons reflects marked behavioral plasticity in response to seasonal resource availability. Elephants showed stronger avoidance of human settlements, agricultural areas, roads, and other threat indicators during the dry season. However, during the late wet season when crops reached maturity, some elephant groups moved toward agricultural lands in the northern and western zones where communities reside and cultivate within the park, increasing the likelihood of human-elephant encounters. Conclusion: Seasonal variation in wild elephant habitat selection was clearly evident, with biological factors as primary determinants and anthropogenic factors influencing avoidance or approach behavior depending on the season. These findings provide a scientific basis for targeted management interventions, including the establishment of buffer zones, systematic monitoring of high-risk conflict areas, and seasonal management of food and water resources within the park, to effectively mitigate human-elephant conflict and promote balanced conservation of wild elephants and their habitats.
Spatiotemporal Assessment of Plant Community in Mixed Deciduous Forest, Mahidol University (Kanchanaburi Campus)
Background and Objectives: Forests are vital natural resources that support living organisms and serve as key mechanisms for maintaining ecological stability and balance, particularly through their role in carbon sequestration and storage. Global climate change and the reduction of forest areas due to human activities have made monitoring and assessing forest resources critically important. Mahidol University, Kanchanaburi Campus, located in Sai Yok District, Kanchanaburi Province, encompasses approximately 6,500 rai of land, most of which consists of mixed deciduous forest on karst topography—a highly unique ecosystem suitable for sustainable conservation. The main objectives of this study are to: (1) assess the spatiotemporal changes in plant communities, (2) evaluate changes in plant community structure and growth of mixed deciduous forest species over a 10-year period, and (3) develop spatial data layers of the mixed deciduous forest within Mahidol University, Kanchanaburi Campus. Methodology: This study compared historical data on plant community structure (plant census) from 2014 (B.E. 2557) with current data from 2024 (B.E. 2567). Random sample plots measuring 40 m × 40 m were established within permanent study plots to collect information on species diversity and quantitative plant characteristics, such as species identity and diameter at breast height (DBH). These data were used to calculate key quantitative attributes of the plant community, including the Shannon–Wiener Diversity Index and the Importance Value Index (IVI), which was derived from relative density, relative dominance, and relative frequency to assess the status of the vegetation. Tree growth was evaluated by comparing the mean DBH of 34 previously recorded trees over the 10-year period, with statistical significance tested using a paired t-test. For assessing spatiotemporal changes, Landsat-8 satellite imagery from March 2014 and March 2024, representing the dry season, was used to classify land-use patterns. Geoinformatics technologies were employed to interpret and analyze the data to estimate land-use proportions. Differences in overall land-use change were analyzed using the Wilcoxon Signed-Rank Test. In addition, unmanned aerial vehicles (UAVs) were utilized to capture aerial photographs and generate three-dimensional (3D) forest structure models. These datasets serve as a foundation for evaluating forest structural attributes such as canopy height and density. Results: Spatiotemporal Changes: The assessment over a 10-year period revealed that the mixed deciduous forest area (F2) increased by 76,640 m2, representing 0.72% of the total area. However, statistical analysis using the Wilcoxon Signed-Rank Test indicated that overall land-use changes were not statistically significant (p-value = 0.674). The observed increase in forest area reflects the effectiveness of land management under the university’s supervision, where there has been no agricultural encroachment, unlike in other community forests on karst landscapes in Kanchanaburi Province, allowing for natural forest regeneration. Plant Community Structure and Diversity: The survey identified 37 tree species within the sample plots. The Shannon–Wiener Diversity Index was 2.94, indicating relatively low species diversity. The species with the highest Importance Value Index (IVI) was Grewia eriocarpa (52.67), which serves as a dominant species in this area. The top five species in terms of IVI were Grewia eriocarpa, Croton roxburghii, Millettia brandisiana, Sterculia pexa, and Dalbergia oliveri. Tree Growth: Comparison of 34 previously recorded trees showed an average increase in diameter at breast height (DBH) of 8.12 cm over the 10-year period, corresponding to an average annual growth rate of 0.812 cm/year. Paired t-test results confirmed a statistically significant difference in mean DBH between 2014 (B.E. 2557) and 2024 (B.E. 2567) (p-value<0.001) indicating continuous tree growth within the area. The species with the highest growth was Vitex quinata, followed by Grewia eriocarpa. Conclusions: This spatiotemporal study demonstrates that the mixed deciduous forest on karst topography at Mahidol University, Kanchanaburi Campus, is undergoing continuous recovery. A comparison of forest structure data over the 10-year period confirmed that the original trees exhibited statistically significant growth in diameter at breast height (DBH), reflecting positive outcomes from successful land management policies that effectively prevented encroachment. However, despite this encouraging structural recovery, species diversity within the plant community remains low. The data on spatiotemporal changes and forest structure thus provide a valuable baseline tool for the university to plan forest resource management and to assess the potential for sustainable carbon sequestration.
Enhancing Community Based Economic Value through Local Material Utilization within the Value Chain of Hed Cone Noi (Coprinopsis cinerea) Mushroom Cultivation in Chiang Mai Province
Background and Objectives: Hed-cone noi (Coprinopsis cinerea) is a saprophytic, edible mushroom widely distributed in Thailand’s tropical forest, particularly in the dry evergreen forests, mixed deciduous forest, and deciduous dipterocarp forest where leaf litter accumulates on the soil surface and termite mounds are present. The species also proliferates on moist piles of organic residues such as rice straw, legume residues, and sugarcane bagasse in high humidity, particularly after Thailand’s rainy season. Hed-cone-noi is well established in cultivation, with strong prominence in Chiang Mai Province. As a biological resource Hed-cone-noi links natural ecosystem functions with local based production systems. Its capacity to utilize locally available organic materials enables integration into smallholder farming and valorization of agricultural waste. By prioritizing locally sourced substrates, the research aims to minimize external inputs across the value chain, thereby enhancing household incomes and promoting sustainable resource management in local Thai communities. The objectives aimed to investigate the utilization of local raw materials in the cultivation process of Hed-cone noi and to strengthen the community-based enterprise development. Then, knowledge can promote grassroot economic development and enhance income generation throughout the value chain in the target areas of Chiang Mai Province. All data collection was done during March 2024 to February 2025. Methodology: This study employed a mixed-methods research design, integrating both qualitative and quantitative approaches, across three target areas in Chiang Mai Province, Thailand: the northern zone of Mae Taeng District, the eastern zone of Doi Saket District, and the southern zone of Saraphi District. The population samples involved two groups. The first group consisted of three local enterprise leaders (Local enterprises: LEs), each selected based on specific criteria: (i) leadership of a community enterprise, (ii) logistics suitable for Hed-cone-noi collection and distribution of, and (iii) possessing at least three years of experience in mushroom cultivation or related agribusiness experience. The second group included members of the three community enterprises (total n = 38). Using purposive sampling for sample population selecting, 12 members (four per site) participated in qualitative data collection in total, 15 participants (3 LEs and 12 members). Qualitative data were obtained through focus group discussions and analyzed through direct content analysis based on SWOT analysis. Then, the strengthens (S), weaknesses (W), opportunities (O), and threats (T) of community-based cultivation enterprises were received. Quantitative data were gathered over 12 months using structured recording forms to capture the value of raw materials used in fresh mushroom production. Data analysis employed descriptive statistics, including summation and ratio analysis, to compare the proportion of locally sourced materials with external input sourcing. A model learning and mentoring hub of the sustainable agriculture community enterprise in Ban Sop Faek, Mae Faek Mai Subdistrict, San Sai District facilitated knowledge transfer, appropriate technologies, and integrated production processes from inoculation and spawn production of substrate preparation and distribution to participating smallholders. The intervention aimed to transfer production techniques and technologies to emerging community-based entrepreneurs, thereby increasing local monetary circulation, reducing external inputs, and self-reliant agricultural development in Thailand. Main Results: The findings indicate that the establishment of three new community-based mushroom enterprises in Mae Ho Phra Subdistrict (Mae Taeng District), Samran Rat Subdistrict (Doi Saket District), and Nong Faek Subdistrict (Saraphi District), Chiang Mai Province, strengthened the Hed-cone-noi value chain by aligning supply with rising local demand and linking smallholder farmers to consumer markets and distribution networks. This enhanced value addition and monetary circulation at the grassroots level. Production capacity per enterprise was standardized: 38 inoculum bottles, 945 bottles of spawn, and 17,000 substrate blocks, which were subsequently distributed to a total of 750 cultivating households. The development of these enterprises resulted in a substantial increase in the utilization of locally sourced production inputs, with an annual value of 2,147,499.30 Thai Baht, compared to 1,042,091.95 Thai Baht for externally sourced inputs. This corresponds to a local to external input ratio of 67:33, highlighting the significant role of local resources in supporting fresh mushroom production systems. Spatial variation in local economies affected input sourcing regions with predominantly agricultural livelihoods relied more on local materials, while areas transitioning toward tourism-oriented economies depended more on external inputs. These patterns highlight the influence of socio-economic context on resource use strategies and the potential of localized production systems to bolster community resilience. Conclusion: Strengthening newly established community-based enterprises that serve as critical nodes within agricultural value chains by primarily utilizing locally sourced materials from the community for the production process of Hed Cone Noi mushrooms can stimulate grassroots economic development. While both local and external inputs are mobilized, increasing the share of locally sourced resources materially enhances local monetary circulation and economic resilience. Contextual factors, especially land-use patterns and shifts in economic structure, meaningfully influence material availability and production costs. In regions shifting toward tourism or non-agricultural sectors, greater reliance on external inputs may diminish local value retention. Fostering localized enterprise networks and robust local input supply systems to boost material retention and economic multipliers. Expanding technology transfer in production and post-harvest management, improving market access, and strengthening inventory management and logistics. Scaling the community-based enterprises model to the regions by adapting to local resource endowments and socio-economic contexts, with ongoing monitoring of input sourcing, yield, and household income impacts.
Vegetation Structure and Environmental Influences on Carbon Stocks in Lower Montane Evergreen Forest in Community Forests, Mae Hong Son Province
Background and Objectives: Lower montane forest (LMF) is indispensable in mountain ecosystems; it was important for carbon sequestration in forest ecosystems and mostly found that in northern Thailand. The areas where this forest type is located in the national forest reserve, are often found that inhabited by hill tribe communities, making the lower montane forest vulnerable to encroachment and destruction. Therefore, to prevent this problem, the community forests have been established to enable local communities to help protect these forest types. Despite several studies on the vegetation structure and carbon sequestration in lower montane forest but mostly focused on the conservation area. This leads to a lack of data in national forest reserves, especially community forests. As well as the study of the limitation’s factors of carbon storage in such a plant community is also limited. Therefore, this study aims to investigate the vegetation structure characteristics, carbon sequestration, and environmental factors that affect carbon sequestration in lower montane forest areas that are managed as community forests. Methodology: This study was conducted in the lower montane forest located in community forests of Ban La-Oob, Ban Dong Kao, Ban Dong Mai, and Ban Tun, at Huai Hom Subdistrict, Mae Lan Noi District, Mae Hong Son Province. Twelve - 0.16 ha (40 x 40 meters) of purposive sampling plots were established to cover the community forest area of four villages. The diameter at breast height (DBH) and total height of all trees within the DBH ≥ 4.5 cm in the sample plots were measured. Cluster analysis was performed to classified sub-communities. Plant community characteristics were analyzed for each sub-community, including diversity index (H′), density (D), basal area (BA), and importance value index (IVI). We also analyzed biomass, carbon sequestration, and carbon dioxide sequestration of each sub-community. Furthermore, the relationship between carbon sequestration of lower montane forest with the factors of topographical as elevation above mean sea level, aspect, and slope, moreover the plant community characteristics as BA, D, H′ and number of species were analyzed using a Generalized Linear Mixed Model (GLMM) with the “lme4 package” and “MuMin package”, respectively, in R version 4.2.2. Main Results: We found that a total of 138 tree species, 99 genera, and 54 families were founded including 2,548 trees. The tree density and basal area were 1,327 trees ha-1 and 29.93 m2 ha-1, respectively. The Shannon-Wiener index (H′) was high (H′=4.18). Plant communities can be divided into four sub-communities, three of which are secondary forest which dominated by Alstonia glaucescens (LMF-ALGL), Eurya nitida (LMF-EUNI) and Ostodes paniculate (LMF-OSPA), and one sub-community of primary forest of lower montane forest dominated by Castanopsis diversifolia (LMF-CADI). The forest structure and carbon sequestration varied among sub-community types. First, the sub-community of lower montane forest dominated by Alstonia glaucescens (LMF-ALGL) showed that 76 species 65 genera and 40 families were found. The Shannon-Wiener index (H′) was 3.64 with tree density and basal area were 2,014.58 trees ha-1 and 45 m2 ha-1, respectively. The biomass, carbon sequestration, and carbon dioxide sequestration values were 238.48±34.45. t ha-1, 112.08±16.19 tC eq ha-1 and 410.98±59.36 tCo2eq ha-1, respectively. Second, the sub-community of lower montane forest with Eurya nitida (LMF-EUNI) showed that 65 species 54 genera and 33 families were found. The Shannon-Wiener index (H′) was 3.46 with tree density and basal area were 1,472.91 trees ha-1 and 25.91 m2 ha-1, respectively. The biomass, carbon sequestration, and carbon dioxide sequestration values were 175.57±41.30 t ha-1, 82.52±19.41 tC eq ha-1 and 302.57±71.18 tCo2eq ha-1, respectively. Third, the sub-community of lower montane forest with Ostodes paniculata (LMF-OSPA) showed that 73 species 62 genera and 37 families were found. The Shannon-Wiener index (H′) was 3.81 with tree density and basal area were 887.50 trees ha-1 and 28.41 m2 ha-1, respectively. The biomass, carbon sequestration, and carbon dioxide sequestration values were 266.99±28.50 t ha-1, 125.48±13.39 tC eq ha-1 and 460.12±49.11 tCo2eq ha-1, respectively. Fourth, the sub-community of lower montane forest with Castanopsis diversifolia (LMF-CADI) showed that 59 species 46 genera and 30 families were found. The Shannon-Wiener index (H′) was 3.36 with tree density and basal area showed that 1,229.16 trees ha-1 and 29.85 m2 ha-1, respectively. The biomass, carbon sequestration, and carbon dioxide sequestration are shown 245.63±16.02 t ha-1, 115.44±7.53 tC eq ha-1 and 423.30±27.61 tCo2eq ha-1, respectively. Furthermore, the carbon sequestration of the lower montane forest in the study areas had negatively significantly with the elevation above mean sea level (p < 0.001), but positively significantly with the slope (p<0.05) and basal area (p<0.001). Indicating the carbon sequestration of LMF is positively associated with high elevations, steep slopes, and large basal areas. Conclusion: This study indicates that community forests of Huai Hom subdistrict, Mae Hong Son Province, consist of secondary lower montane forest. These forests maintain high biodiversity and possess significant carbon sequestration capacity. However, alongside tree growth, topographic factors such as elevation and slope remained crucial determinants of carbon sequestration. Therefore, topography must be taken into consideration when managing lower montane community forests to enhance their carbon sequestration efficiency.
Tree Diversity, Carbon Storage and Carbon Dioxide Sequestration Assessment in Dry Evergreen Forest and Mixed Deciduous Forest of Selected Botanical Gardens and Arboreta in Thailand
Background and Objectives: The increase in greenhouse gases concentrations is a major driver of climate change, which in turn affects to forest ecosystems. Forest plays a role in the release and storage of carbon, thereby influencing global warming. However, forest ecosystems also mitigate climate change by absorbing carbon dioxide through various processes and serve as reservoirs of biodiversity for both flora and fauna. In Thailand, the forests mostly are tropical dry forests and forests can be categorized into two types; 1) deciduous forests (such as deciduous dipterocarp forest and mixed deciduous forest) and 2) evergreen forests (such as dry evergreen forest, montane forest and moist evergreen forest). These two types of forest are distributed throughout the country, with most found in protected areas. Botanical gardens and arboreta are classified as urban forest that there are people using regularly and serve as important sites in protected areas. It comprised many rare or economically valuable plant species and also serves as a biodiversity conservation area and a research site but less documents were found in species diversity and the potential of carbon stock and carbon dioxide (CO2) sequestration. This study aimed to clarify species diversity in dry evergreen forest (DEF) and mixed deciduous forest (MDF) within selected botanical gardens and arboreta and study the potentials of botanical gardens and arboreta as carbon storage. Methodology: A total of 241 concentric sample plots were established in 2024 with inter-plot spacing of either 250 m or 2.5 km, depending on the size of the botanical gardens and arboreta and are divided into 115 sample plots within dry evergreen forest, covering an area of 11.5 ha, and 126 sample plots within mixed deciduous forest, covering an area of 12.6 ha. Concentric sample plots with radius about 17.84 m were established. All trees with diameter breast height (DBH) >4.5 cm and height greater than 1.3 m were tagged, identified and mapped azimuth. The data was used to calculate aboveground biomass using allometry equations, and the resulting aboveground biomass were used to quantify belowground biomass, carbon storage and carbon dioxide (CO2) sequestration. Main Results: The results revealed that 19, 514 individuals were found. In DEF contained 10,139 individuals across 481 species with 268 genera and 78 family and the dominant species based on importance value index (IVI) was Dipterocarpus alatus with 15.54 and followed with Streblus asper, Afzelia xylocarpa, Eucalyptus camaldulensis and Delonix regia, with species diversity and species richness index was 4.96 and 52.80 respectively. While, MDF contained 9,375 individual of trees across 406 species with 243 genera and 77 family and the dominant species based on IVI was Tectona grandis with 19.84 and followed with Pterocarpus macrocarpus, Xylia xylocarpa, Combretum quadrangulare and Streblus asper, with species diversity index and species richness index was 4.99 and 44.28 respectively. Carbon storage and carbon dioxide (CO2) sequestration assessment were estimated using allometry equation. Biomass in DEF and MDF were 190.18 t/ha and 142.26 t/ha, respectively, Carbon storage in DEF and MDF were 89.38 tC/ha and 66.86 tC/ha, respectively and Carbon dioxide (CO2) in DEF and MDF were 328.04 tCO2/ha and 245.38 tCO2/ha, respectively. Diameter class distribution in both communities exhibited a negative exponential pattern, indicating stable population structure. The high proportion of small-sized trees suggests strong regeneration potential, with many individuals likely to develop into mature trees in the future. Furthermore, in terms of carbon storage potential, larger trees (DBH > 30 cm) had the larger of carbon storage, even though there are less number of trees in the group. However, small to medium sized trees can still grow into mature trees in the future, thereby enhancing future carbon storage potential. A t-test was used to compare the mean of biomass, carbon storage and carbon dioxide (CO2) sequestration indicated that two forest types is non-significant (p-value = 0.22) in potentials of carbon storage and carbon dioxide (CO2) sequestration. Conclusion: This study highlights the potential of botanical gardens and arboreta to function as large carbon storage area. This study indicates that many tree species within natural forests had high potentials of carbon storage and carbon dioxide (CO2) sequestration. The results can serve as a valuable database for assessing carbon storage in botanical gardens and arboreta. Furthermore, this study can inform conservation planning within these areas. Effective management should prioritize not only the preservation of large trees but also keep smaller trees with the potential to develop into larger trees in the future, thereby enhancing overall carbon storage potential. In addition, future monitoring of the dynamics within the sample plots may provide greater clarity changes in tree populations and their impact of potential of carbon storage in botanical gardens and arboreta. Overall, our findings can support the sustainable management of botanical gardens and arboreta, contributing to their role towards a low-carbon society.
Natural Succession of Lower Montane Forest in Shifting Cultivation Systems at Namtok Mae Surin National Park, Northern Thailand
Background and Objectives: Forest recovery in shifting cultivation systems plays a crucial role in shaping forest structure and species composition in tropical mountainous regions. In northern Thailand, lower montane forests represent one of the most ecologically important ecosystems, characterized by high biodiversity and complex vegetation structure. However, land-use changes, particularly shifting cultivation practices, have significantly altered these ecosystems, leading to forest degradation and initiating natural succession processes. The recovery of plant communities following disturbance is a dynamic and complex process influenced not only by the time since abandonment but also by environmental conditions and site-specific factors. Understanding how these factors interact to influence forest recovery is essential for developing effective strategies for forest restoration and sustainable land management. Therefore, this study aimed to (1) investigate the natural succession of plant communities in lower montane forests across a chronosequence of shifting cultivation fallows, and (2) examine the relationships between environmental factors and plant species distribution. Methodology: The study was conducted in Namtok Mae Surin National Park, Mae Hong Son Province, northern Thailand, which is characterized by mountainous terrain and a tropical monsoon climate. A total of 15 temporary sample plots were established across five land-use stages: natural forest and shifting cultivation fallows of 1, 4, 7, and 10 years. Three plots were established for each stage. Within each plot, all trees with a diameter at breast height (DBH) ≥ 4.5 cm were measured and identified to species level. Saplings were also surveyed in subplots to assess regeneration patterns. In addition, soil samples were collected for the analysis of physical and chemical properties, including soil organic matter, soil moisture, and soil texture. Vegetation data were analyzed using the Importance Value Index (IVI) to determine dominant species and their ecological significance. Species diversity was assessed using the Shannon–Wiener diversity index (H′). Cluster analysis was performed to classify plant communities based on species composition, while Canonical Correspondence Analysis (CCA) was applied to examine the relationships between species distribution and environmental variables. These analytical approaches allowed for the identification of patterns in community composition along successional gradients and environmental conditions. Main Results: The natural forest exhibited high structural complexity and species diversity, with 70 tree species belonging to 35 families and 52 genera. The stand density was 1,074 stems ha-1, with a basal area of 9.26 m² ha-1 and a Shannon–Wiener diversity index of H′ = 3.69. In contrast, the 1-year fallow exhibited a very simple forest structure, with a low stand density of 23.33 stems ha-1 and a basal area of only 0.021 m² ha-1. This stage was dominated by pioneer species, reflecting the early stage of succession following disturbance. As the fallow age increased, forest structure showed a clear and continuous recovery trend. In the 4-year fallow, stand density increased to 1,030 stems ha-1, with a basal area of 1.12 m² ha-1. In the 7-year fallow, stand density further increased to 2,084 stems ha-1, with a basal area of 3.12 m² ha-1. In the 10-year fallow, basal area increased substantially to 7.48 m² ha-1, and species diversity (H′ = 3.64) approached that of the natural forest. These findings indicate a gradual transition from early successional stages dominated by pioneer species to more complex communities with increasing contributions from shade-tolerant species, particularly those in the family of Fagaceae and Lauraceae. The diameter class distribution of trees (DBH ≥ 4.5 cm) across all five land-use stages exhibited a negative exponential (L-shaped) pattern, characterized by a large number of small individuals and progressively fewer large trees. This pattern reflects a stable regeneration structure, suggesting that the forest has the potential to sustain itself through continuous recruitment and replacement of individuals over time. Cluster analysis classified the plant communities into three main groups corresponding to different stages of disturbance and recovery: (1) early disturbed sites dominated by pioneer species with low diversity and simple structure, (2) intermediate recovery sites characterized by the coexistence of pioneer and shade-tolerant species, and (3) natural forest sites with high species diversity and complex structure dominated by late-successional species. The results of CCA indicated that species distribution was strongly associated with environmental factors, including soil organic matter, soil moisture, soil texture, and canopy cover. These factors act as environmental filters, influencing species establishment, survival, and competitive interactions under different site conditions. Shade-tolerant species were primarily associated with areas of high canopy cover, high soil moisture, and high organic matter content, whereas pioneer species were more abundant in open areas with lower soil fertility and higher light availability. Soil texture also played an important role in determining water retention capacity and root establishment, thereby contributing to spatial variation in plant community composition. Conclusion: This study demonstrates that natural succession in shifting cultivation systems can lead to the recovery of plant communities with structural and compositional characteristics similar to those of natural lower montane forests. Time since abandonment is a key driver of forest recovery, controlling changes in species composition and forest structure from pioneer-dominated communities to more complex and stable systems. However, environmental factors such as soil organic matter, soil moisture, soil texture, and canopy cover also play critical roles in shaping successional trajectories through environmental filtering processes. These findings highlight that forest recovery is not solely dependent on time but is the result of interactions between successional processes and environmental conditions. While species diversity can recover relatively quickly, full structural recovery, particularly the development of large trees and biomass accumulation, requires longer time periods. Therefore, maintaining sufficient fallow periods and minimizing further disturbances are essential for promoting sustainable forest restoration and biodiversity conservation in the shifting cultivation landscapes of mountain forest ecosystem.
Seedling Recruitment and Mortality Rates under Gap and Crown Canopy in Lower Montane Forest at Doi Suthep – Pui National Park, Chiang Mai Province
Background and Objectives: Natural forests are dynamic ecosystems in which the structure and composition of plant communities continuously change through the process of natural regeneration. This regeneration process is an important ecological mechanism that maintains forest structure, species composition, and plant diversity over long periods of time. The seedling stage represents a critical phase in the life cycle of forest plants because seedlings must cope with intense competition and environmental filtering, which influence germination, growth, and survival. This process is particularly important in ecosystems with specific environmental characteristics, such as montane forests, which generally occur at elevations higher than 1,000 meters above mean sea level and are characterized by cool and humid conditions as well as dense forest canopies that limit light penetration to the forest floor. As a result, many plant species exhibit shade-tolerant characteristics. However, disturbances such as the fall or death of large trees can create forest gaps, which alter local environmental conditions, including light intensity, temperature, and humidity. These environmental differences influence seed germination and seedling establishment. Light-demanding species generally exhibit higher recruitment and growth rates in forest gap areas, whereas shade-tolerant species are better able to establish and survive under low-light conditions beneath the crown canopy. In addition, variations in light intensity and temperature also affect seedling mortality rates, reflecting the adaptive capacity of each species under different environmental conditions. However, quantitative information on the relationships between light intensity and temperature and the recruitment and mortality rates of seedlings in montane forest remain limited. Therefore, this study aims to: 1) compare light intensity and temperature between forest gap areas and crown canopy areas; 2) examine the recruitment and mortality rates of different seedling species in both habitat types; and 3) analyze the relationship between light intensity and seedling recruitment rates in both habitat types during 2013 - 2015. This study is expected to enhance the understanding of some role of environmental factors in natural regeneration processes of plant communities in a lower montane forest at Huai Kog Ma watershed, Doi Suthep–Pui National Park, Chiang Mai Province. Methodology: The study was conducted in a 16-hectare permanent plot measuring 400 × 400 meters located within Doi Suthep–Pui National Park, Chiang Mai Province. Two types of forest environments were investigated: forest gap areas and areas under crown canopy. Nine sampling locations were selected for each type of environment, resulting in a total of 18 study locations. At each location, five seedling subplots measuring 1 × 1 meter were established, giving a total of 90 seedling plots. All seedlings occurring within each subplot were tagged and identified to species level. Each seedling was assigned an identification number in order to monitor its survival and recruitment over time. Field observations were conducted monthly from August 2012 to December 2015. During each monitoring period, newly recruited seedlings and dead seedlings were recorded. The collected data were then analyzed to calculate seedling species diversity, seedling density, recruitment rates, and mortality rates in both forest gap areas and crown canopies. The relationships between environmental factors and seedling recruitment were examined in both gap and crown canopy using Spearman’s rank correlation in R. Main Results: A total of 105 seedling species belonging to 80 genera and 48 families were recorded during the study period, with an overall seedling density of 293,222 individuals.ha-1. Most seedlings belonged to the families Fagaceae and Lauraceae, which are dominant components of montane forests in northern Thailand. When the two habitat types were considered separately, 77 species representing 62 genera and 39 families were recorded in forest gap areas, whereas 70 species representing 53 genera and 36 families were found under the forest canopy. In both environments, Castanopsis acuminatissima were the most abundant species, with seedling densities of 210,000 and 136,444 individuals.ha-1 under forest gap and crown canopy conditions, respectively. Seedling recruitment and mortality in both forest gap and under crown canopies varied among years and also showed seasonal variation. The highest seedling recruitment was observed during the late rainy season to the early dry season, indicating that favorable moisture conditions during the rainy season may enhance seed germination and early seedling establishment. In contrast, seedling mortality occurred intermittently throughout the study period and remained lower than recruitment overall. When focusing on species with more than 10 individuals recorded between 2013 and 2015, a total of 11 species were analyzed. The results showed that recruitment and mortality rates differed among species. Seedlings in the family Fagaceae, including Castanopsis acuminatissima and Castanopsis tribuloides were found in both forest gaps and crown canopies, indicating that these species are able to establish under a wide range of light intensity. For species in the family Lauraceae, including Litsea martabanica and Persea gamblei, seedling recruitment occurred more frequently under the forest canopy than in forest gaps, reflecting the shade-tolerant characteristics of these species. In contrast, Cinnamomum iners seedlings were found only in forest gap areas, suggesting that this species requires higher light availability for successful establishment. The relationships between light intensity and seedling recruitment and mortality of all 11 species did not differ significantly between forest gap and under crown canopy conditions (p > 0.05). However, Castanopsis acuminatissima, Castanopsis tribuloides and Syzygium tetragonum showed a tendency to occur under lower light conditions, whereas Macaranga indica and Memecylon plebejum tended to be associated with higher light intensities. Conclusion: Seedling recruitment and mortality rates varied among species which related to the ecological niches, in particular species light demanding. Differences in light availability between under gap and crown canopy had influenced seedling establishments in montane evergreen forest. The formation of canopy gaps therefore play an important role in natural regeneration processes and contributes to the maintenance of plant diversity and forest dynamics in tropical forest ecosystems.