Biomass Volume Research Articles

Predicting forest parameters through generalized linear mixed models using GEDI metrics in a temperate forest in Oaxaca, Mexico

ABSTRACT Lidar sensors are active remote sensing instruments that provide data on forest structure, which serve as inputs in the prediction of forest parameters. The objective of this study was to evaluate the performance of mixed-effects models to predict basal area (BA), aboveground biomass (AGB), and wood volume (VOL) from GEDI (Global Ecosystem Dynamics Investigation) predictor variables. Linear mixed and generalized linear mixed models (LMM and GLMM) were fitted with a clustering structure as a random effect between forest parameters and GEDI metrics. LMM and GLMM performed similarly regarding root mean square error (RMSE) and correlation coefficients (r) between observed and predicted data. Our results showed moderate correlations between RH50 and BA (r = 0.53), AGB (r = 0.54), and RH80 with VOL (r = 0.62). Another finding was the correlation between GEDI predictions of the AGB density and the biomass predicted in this study, with an agreement of 79% and 77% and a RMSE of 76.95 and 82.34 Mg ha−1 for LMM and GLMM, respectively. We conclude that the use of mixed models allowed for the inclusion of both fixed and random effects that capture the systematic and random variation in the data, and they provide a flexible framework for modelling forest parameters.

Effect of Stocking Density on the Growth of the Endangered Amazonian Fish Hypancistrus zebra (Siluriformes: Loricariidae)

ABSTRACTStocking density has a significant influence on animal homeostasis, and so is a crucial factor in the management of organisms in captivity and an important role in ex situ conservation of endangered species. Hypancistrus zebra is an endemic fish species from the Xingu River, Brazil—considered Critically Endangered since the early 2000s due to fishing pressure and, more recently, due to habitat changes resulting from the construction of the Belo Monte Hydroelectric Dam. The implementation of appropriate management in captivity is of utmost importance for its conservation, particularly in enhancing ex situ breeding techniques. This study aimed to evaluate the growth of juvenile H. zebra in aquaria with three different stocking density levels. The juveniles were distributed between three treatments, each with three replicates. We found no correlation between biomass and aquarium volume. The highest correlation coefficients were found between growth rates and densities related to the number of individuals per shelter area. Mortality rate was directly related to the initial number of fish in the aquariums, with larger populations showing higher mortality rates. The treatment with lower stocking density displayed the highest growth rate, while the treatment with higher density had the lowest growth rate, with a 23.38% difference between them.

Influence of Habitat and Effects of Salt Stress on Biochemical and Physiological Parameters of Glycyrrhiza uralensis.

The seeds of Glycyrrhiza uralensis Fisch. used for cultivating are primarily sourced from wild populations. However, the types of habitats where wild G. uralensis grow are diverse. We studied the effects of salinity on the growth, antioxidant capacity, and photosynthetic physiology of two-month-old licorice seedlings from different habitats to evaluate their salt tolerance. With the increasing NaCl concentration, compared with non-salinized habitats, seedlings originating from seeds collected from salinized habitats showed milder inhibition in root biomass and root volume. Also, the crown diameter increased more significantly. Activities of superoxide dismutase, catalase, and peroxidase are higher. Correspondingly, the electrolyte leakage rate of the leaves is low. Their leaves had a higher photoprotection capacity and potential maximum photochemical efficiency of PSII. Net photosynthetic rate, transpiration rate, and stomatal conductance showed less inhibition under 4 and 6 g/kg NaCl treatment. The content of glycyrrhizic acid and glycyrrhetinic acid in their roots was significantly increased under 2 g/kg NaCl treatment and was significantly higher than that of seedlings from non-salinized habitats under the same NaCl treatment. In conclusion, seeds from salinized habitats show improved tolerance to salt stress at the seedling stage, which is attributed to their superior phenotypic adaptability, strong antioxidant, and especially high light protection ability.

Developments in biochar incorporated geopolymers and alkali activated materials: A systematic literature review

Annually, industries related to agricultural products generate substantial volumes of waste biomass, presenting critical challenges for solid waste management due to its environmental and health implications. Pyrolysis emerges as a significant technique for converting such waste into biochar (BC), a material with notable internal microstructure, porosity, and chemical properties, contingent on the feedstock and processing conditions. BC is recognized for its exceptional water retention and alkalinity, primarily utilized for soil enhancement and fertilization. Its application across various fields, particularly in enhancement for sustainability, has gained momentum. This review meticulously explores BC's role in sustainable composites, focusing on geopolymers and alkali-activated binders through a comprehensive examination of existing literature, underscored by bibliometric analysis. This pioneering review, leveraging the PRISMA framework and VOSviewer for bibliometric insights, aims to bridge the research gap in this evolving domain, offering a critical assessment of BC's integration in sustainable construction materials, its challenges, and future research directions. Hence, this pioneering systematic review represents the first-ever exploration within the research domain of BC's applications in geopolymers and alkali-activated materials, marking a foundational step toward understanding its potential and challenges in sustainable engineering practices.

Variability of Water Use Efficiency of Gmelina arborea Plantations in the Tropical Dry Forest of Colombia

Effective forest management strategies to adapt to climate change are essential. Water use efficiency (WUE), which integrates biomass production and water consumption, is a key indicator of forest adaptation. This study evaluated the WUE of Gmelina arborea plantations in the tropical dry forest and identified the main influencing factors, with implications for silviculture and management. Data on total biomass (TB) and total volume (V) were obtained from permanent sample plots in the upper and lower Magdalena River basin in Colombia. WUE was calculated as m3 of V (WUEV) or kg of TB (WUETB) per m3 of evapotranspired water. Significant regional differences were found, with higher WUE in the Caribbean plains (WUETB = 1 kg m−3 and WUEV = 0.0018 m3 m−3) compared to the inter-Andean valleys (WUETB = 0.77 kg m−3 and WUEV = 0.013 m3 m−3). Stand variables had the greatest influence on WUE, showing positive associations with site productivity and stand density measures. Soil variables such as texture, available water, and calcium content, along with a drier climate, were crucial for achieving higher WUE. The study underscores the importance of comprehensive site selection and effective silvicultural practices to maximize WUE and productivity, especially in the context of climate change.

Growth of indigenous mountainous Indonesian Hibiscus macrophyllus in agroforestry system from various age, seed sources and slopes

In East Java, forest degradation on the slopes resulted landslides during rainy seasons, because of a farming change toward mountainous terrain. Government encouraged community to build agroforestry systems using Hibiscus macrophyllus, therefore this study examined the H. macrophyllus growth on slopes from 15° to 75° in two trials from 6 months to three years, using a variety of eight seed sources. The objectives of this study were to determine the growth responses of H. macrophyllus of various ages on various land slopes in two locations (Mount Kawi and Mount Willis). The trials in two locations were established by Incomplete Block Design (IBD) comprising of 4-6 replications with 50 open pollinated families from 8 seed sources. In both trials, this plant was grown alongside agricultural crops. The General Linear Model (GLM) was used to analyse the growth data from two trials to identify variations in plant age, location, slopes and seed sources. The results showed that growth was significantly different between locations, slopes, seed source and ages. It was found that there was an interaction between site and slope. Height varies, with three times more in Willis (72.6 cm) than in Kawi (26.05 cm). Dramatic changes in slopes, induce more than doubled the height between 75° and 30° slope, which influence considerable wood biomass volume at the end. Increasing growth occurred from 6 months to 3 years i.e.: >7.5 times for height and >6.5 times for diameter. This fast growth at 3 years immediately benefits in ameliorating the mountainside ecosystem. Seed sources perform differently, and considerable variances also occur between families. Comparison between the lowest and greatest seed sources were 40% greater in height and 9% in diameter, indicating that seed sources, as well as family selection, should be considered. The best growth response of H. macrophyllus was found at Willis after 3 years at 30° slope.

Application of remote sensing to understand the role of Galician feral horses in the biomass reduction of a shrub-grassland-dominated landscape

Galician forests in northwestern Spain are subject to frequent wildfires with high environmental and economic costs. In addition, due to the consequences of climate change, these fires are becoming more virulent, occurring throughout the year, and taking place in populated areas, in some cases involving the loss of human life. Therefore, forest fire prevention is even more relevant than mitigating its consequences. Given the costs involved in forestry work, alternative measures to reduce fuel load and create vegetation gaps are needed. One involves grazing by an endemic species of feral horses (Equus ferus atlanticus) that feed on thicket-forming gorse (Ulex europaeus). In a 100-ha forest fenced study area stocked with 11 horses, four 50 m2 enclosed plots prevented the access of these wild animals to the vegetation, with the aim of manipulating their impact on the reduction of forest biomass. The measurement of biomass volumes is an important method that can describe the assessment of wildfire risks, unfortunately, high-resolution data collection at the regional scale is very time-consuming. The best result can be using drones (unmanned aerial vehicles - UAVs) as a method of collecting remotely sensed data at low cost. From September 2018 to November 2020, we collected information about aboveground biomass from these four enclosed plots and their surrounding areas available for horses to forage, via UAV. These data, together with environmental variables from the study site, were used as input for a fire model to assess the differences in the surface rate of spread (SROS) among grazed and ungrazed areas. Our results indicated a consistent but small reduction in the SROS between 0.55 and 3.10 m/min in the ungrazed enclosured plots in comparison to their grazed surrounding areas (which have an SROS between 15 and 25 m/min). The research showed that radar remote sensing (UAV) can be used to map forest aboveground biomass, and emphasized the importance and role of feral horses in Galicia as a prevention tool against wildfires in gorse-dominated landscapes.

Accurate Calculation of Upper Biomass Volume of Single Trees Using Matrixial Representation of LiDAR Data

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection and Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, each of which is further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree’s upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. For a tree dimensions estimation, the study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees. The maximum absolute quantitative accuracy equals 0.49 m, and the maximum relative absolute error equals 0.29%.

Optimal Rotation Age in Fast Growing Plantations: A Dynamical Optimization Problem.

Forest plantations are economically and environmentally relevant, as they play a key role in timber production and carbon capture. It is expected that the future climate change scenario affects forest growth and modify the rotation age for timber production. However, mathematical models on the effect of climate change on the rotation age for timber production remain still limited. We aim to determine the optimal rotation age that maximizes the net economic benefit of timber volume in a negative scenario from the climatic point of view. For this purpose, a bioeconomic optimal control problem was formulated from a system of Ordinary Differential Equations (ODEs) governed by the state variables live biomass volume, intrinsic growth rate, and area affected by fire. Then, four control variables were associated to the system, representing forest management activities, which are felling, thinning, reforestation, and fire prevention. The existence of optimal control solutions was demonstrated, and the solutions of the optimal control problem were also characterized using Pontryagin's Maximum Principle. The solutions of the model were approximated numerically by the Forward-Backward Sweep method. To validate the model, two scenarios were considered: a realistic scenario that represents current forestry activities for the exotic species Pinus radiata D. Don, and a pessimistic scenario, which considers environmental conditions conducive to a higher occurrence of forest fires. The optimal solution that maximizes the net benefit of timber volume consists of a strategy that considers all four control variables simultaneously. For felling and thinning, regardless of the scenario considered, the optimal strategy is to spend on both activities depending on the amount of biomass in the field. Similarly, for reforestation, the optimal strategy is to spend as the forest is harvested. In the case of fire prevention, in the realistic scenario, the optimal strategy consists of reducing the expenses in fire prevention because the incidence of fires is lower, whereas in the pessimistic scenario, the opposite is true. It is concluded that the optimal rotation age that maximizes the net economic benefit of timber volume in P. radiata plantations is 24 and 19 years for the realistic and pessimistic scenarios, respectively. This corroborates that the presence of fires influences the determination of the optimal rotation age, and as a consequence, the net economic benefit.

Physico-Chemical and Microbiological Changes in Degradation of Agri-residue under Pit Compositing

Management of crop residues has remained a major challenge due to lack of easily adaptable and affordable interventions at farmer’s field. Cellulolytic bacteria and fungi have been recommended for recycling lignocellulosic-rich organic matter and to convert it into nutrient rich compost. However, these inoculants need to be generated on commercial scale for handling large volume of biomass. Also, the microbial formulation should also be capable of degrading diverse type of agri-residues. Seven fungal strains, namely Aspergillus awamori (F-18), Aspergillus nidulans, Trichoderma viride, Trichoderma longibrachitum, Drechslerahalodes, Eupenicilliumcrustaceumand Paecilomycesvariotiiwere characterized based on shelf life, functional activity to make consortium for degradation of various agro and horticultural residues using pit method of composting. An experiment was laid in cemented pits using four different substrates-maize cobs and stalks, paddy straw, kinnow fruit waste and flower waste for rapid degradation. The results revealed a maximum increase in spore count with Paecilomycesvariotii followed by Eupenicilliumcrustaceum and Drechslerahalodes. Out of four different additives, glycerol was found to be most suitable additive for incubation of selected fungi. The results on microbial population revealed highest bacterial population in flower waste and highest actinobacterial population in kinnow waste. It was also observed that inoculated organic waste degraded faster than un-inoculated wastes. As the degradation process progressed, total N also increased with time and varied from 1.1 to 1.5 percent. Flower and kinnow waste degradation was completed in 45 days while that of maize and paddy straw in 75 and 90 days, respectively. The pH range was 6.5-8.0 in all the substrates but in inoculated substrates, the range of pH was 7.2-7.6, while electrical conductivity (EC) was 1.4-3.6. The highest humus% was found with paddy straw followed by maize, flower and kinnow. The final product also showed variation in K% and S% which were found to be 0.6% -1.8% and 0.1% -0.20%, respectively.

Effect of Thermally Extracted Carrot Oil Using Biomass Solvent to Boost Consumer Goods: Box-Behnken Design Approach

Massive production of fast-moving consumer goods boosts the economy of any nation. Thus, the need to look into ways of accelerating and transforming carrot utilization into more commercialized usage in order to add value to the developmental strides of any nation where carrot is cultivated like Nigeria. This study concluded that the optimization of the carrot oil extracted from crushed carrot and coconut oil (biomass volume) via soxhlet equipment using Box-Behnken Design (BBD) of Response Surface Methodology (RSM) approach, generated an ideal optimal output of 18.58 wt% at SW of 60 g, BV of 200 ml and ET of 14mins. Although, three input elements which are sample weight (SW), biomass volume (BV), and extraction time (ET) were modelled to generate 17 setups by BBD, but standard order (Std) 8 from the 17 setups generated an ideal output of 18.58 wt%. Thus, the process optimization of the extraction process via BBD of RSM showed that both the coefficient of determination (R2) which is 0.9886, and the difference between adjusted R2 and predicted R2 which is less than 0.2 fall within an ideal range. Also, the elements considered for modeling are mutually significant with the quadratic model equation and the interactive effects of the independent parameters on the carrot oil output showed that an increase in the sample weight and time led to a corresponding increase in the carrot oil output, and this is corroborated by the perturbation plot. Additionally, the physiochemical valuables of the carrot oil generated showed that the free fatty acid and the acid value were very low signifying that the carrot oil is edible and can be used in the manufacturing process using the saponification method in making soap and moisturizing cream for the benefit of mankind.

Biomass characterization with semantic segmentation models and point cloud analysis for precision viticulture

The scientific progress in artificial intelligence and robotics has enabled precision viticulture to pursue sustainability and improve the final yield. For instance, monitoring the canopy volume of each plant can allow the correct ripening of the bunches. In this context, this paper proposes a novel approach for the characterization of biomass volume using images acquired in a vineyard with the low-cost Azure Kinect RGB-D camera. Semantic image segmentation is implemented using three encoder–decoder deep architectures (U-Net, DeepLabV3+, and MANet) to produce accurate masks of the vine leaf structure. In a transfer learning approach, a public dataset acquired with the Intel RealSense D435 depth camera is used to train the segmentation networks. Then, a complete pipeline to estimate possible changes in biomass volume is presented. Experiments are run to analyze the biomass removed during the trimming process of grapevine plants. The best segmentation result is obtained by the U-Net architecture with ResNet50 backbone, showing an accuracy of 92.10%, although the training and test sets consist of images acquired by different cameras. However, the DeepLabV3+ network with ResNeXt50 backbone, which scores an accuracy of 90.25% on the test set, gives the best estimate of the removed biomass, requiring the shortest time for training. These outcomes prove the potential capability of this automatic approach for controlling leaf growth and ensuring sustainable viticulture practices.

Development and implementation of a stand-level satellite-based forest inventory for Canada

Abstract Satellite data are increasingly used to provide information to support forest monitoring and reporting at varying levels of detail and for a range of attributes and spatial extents. Forests are dynamic environments and benefit from regular assessments to capture status and changes both locally and over large areas. Satellite data can provide products relevant to forest science and management on a regular basis (e.g. annually) for land cover, disturbance (i.e. date, extent, severity, and type), forest recovery (e.g. quantification of return of trees following disturbance), and forest structure (e.g. volume, biomass, canopy cover, stand height), with products generated over large areas in a systematic, transparent, and repeatable fashion. While pixel-based outcomes are typical based upon satellite data inputs, many end users continue to require polygon-based forest inventory information. To meet this information need and have a spatial context for forest inventory attributes such as tree species assemblages, we present a new work-flow to produce a novel spatially explicit, stand-level satellite-based forest inventory (SBFI) in Canada applying image segmentation approaches to generate spatially unique forest stands (polygons), which are the fundamental spatial unit of management-level inventories. Thus, SBFI offers spatial context to aggregate and generalize other pixel-based forest data sets. Canada has developed a National Terrestrial Ecosystem Monitoring System (NTEMS) that utilizes medium spatial resolution imagery, chiefly from Landsat, to annually characterize Canada’s forests at a pixel level from 1984 until present. These NTEMS datasets are used to populate SBFI polygons with information regarding status (e.g. current land cover type, dominant tree species, or total biomass) as well as information on dynamics (e.g. has this polygon been subject to change, when, by what, and if so, how is the forest recovering). Here, we outline the information drivers for forest monitoring, present a set of products aimed at meeting these information needs, and follow to demonstrate the SBFI concept over the 650-Mha extent of Canada’s forest-dominated ecosystems. In so doing, the entirety of Canada’s forest ecosystems (managed and unmanaged) were mapped using the same data, attributes, and temporal representation. Moreover, the use of polygons allows for the generation of attributes such as tree species composition, and total biomass and wood volume in a stand-scale format familiar to landscape managers and suitable for strategic planning. The data, methods, and outcomes presented here are portable to other regions and input data sources, and the national SBFI outcomes for Canada are available via open access.

Efeitos da densidade de plantio sobre características da madeira de sabiá

ABSTRACT This study aimed to evaluate the biomass yield, volume, and basic density of Mimosa caesalpiniifolia Benth. wood in response to planting densities in 13-year-old trees. The research was conducted in Mossoró-RN using a randomized block design with three replications. Plants obtained from seeds collected from the natural vegetation of the Caatinga in Mossoró-RN were subjected to densities of 800 (5.0 m x 2.5 m), 1600 (2.5 m x 2.5 m), 2000 (2.0 m x 2.5 m), and 4000 (1.0 m x 2.5 m) plants ha-1. The following characteristics were assessed: plant height, diameter at breast height, cross-sectional area, basal area, individual volume, stere volume, aboveground biomass, and basic wood density. The dendrometric variables showed a high correlation with planting density. For DBH and cross-sectional area, higher values were observed in the lowest planting densities. The highest values of basal area, volume (m3), stere volume, and dry biomass per hectare were found at the highest planting density. Biomass allocation showed the sequence stem>branches>leaves, regardless of the planting density evaluated. The higher densities resulted in a higher basic density of the wood. The higher planting densities proved advantageous 13 years after planting due to the higher production of dry biomass, volume (m3), and stere volume per hectare.

Produtividade da água em coqueiro irrigado nas condições de clima tropical úmido na Amazônia Oriental

ABSTRACT: The growing demand for coconut water has led to the expansion of irrigated green dwarf coconut cultivation; however, the inefficient use of water has contributed to the degradation and waste of water resources, making fundamental studies aiming to optimize the use of water. The objective of this study was to determine the physical productivity and water productivity of green dwarf coconut palms under the climatic conditions of Santa Izabel do Pará, eastern Amazonia, Brazil. The experiment was carried out from 2020 to 2021, in a green dwarf coconut plantation spaced 7.5 m x 7.5 m in a triangle, at Fazenda Reunidas Sococo, with an area of approximately 7 ha. Water productivity (WP) was determined both in terms of fruit production (WPf) and coconut water production (WPca), through the relationship of fruit productivity (fruit biomass and water volume) with accumulated evapotranspiration. The dwarf coconut tree presented a total production of 105 and 186 fruits plant-1 and 37 and 62 L plant-1 of coconut water in the years 2020 and 2021. The largest volumes of water and the highest weights occurred during the wettest season. WPf was of 1.87 fruits m-3 (2020) and 2.94 fruits m-3 (2021) and WPca 0.66 L m-3 (2020) and 0.98 L m-3 (2021).

STATE OF SOD-PODZOLIC SOIL FERTILITY LOAMY SOIL DURING LONG -TERM HAYMAKING WHEN USING IT

Morphological changes of sod-podzolic loamy soil during its haymaking use for 85 years are traced. The description of soilоfillets under different methods of using grass stands and their influence on plantcover, as well as morphological changes in the sod-humus horizon, is carried out. It was found that the presence of a sufficient amount of biomass or crop residues with the con-stant use of mineral fertilizers (N120P60K90) contributed to an increase in the sod-illuvial horizon and a decrease in the podzolic one, but the presence or lack of it did not significantly affect the acidic background of the soil of the experimental site. The content of humic substances in the soil, mobile forms of phosphorus and potassium in natural conditions (reserved) largely depended on the volume of biomass, but the highest value of these indicators in the experiment was obtained in the variant with the use of mineral fertilizers. Migration of nitrogen, calcium, and magnesium was observed. The maximum content of mobile forms of phosphorus and potassium was found in the humus horizon up to 30 cm. A common feature of mineral elements is the presence of two horizons with the maximum content: in the sodм and transitionalм to the soil-forming rock.

Functional Trait Responses of Sophora alopecuroides L. Seedlings to Diverse Environmental Stresses in the Desert Steppe of Ningxia, China.

The seedling stage of plants is a crucial and vulnerable period in population and community dynamics. Despite this, studies on how plant traits respond to different environmental stresses often tend to overlook this early stage. Our study focused on Sophora alopecuroides L. seedlings in Ningxia Yanchi desert steppe, analyzing the effects of sand burial, salinity, and drought on their key aboveground and belowground traits. The results showed that sand burial significantly negatively affected stem biomass (SB), leaf biomass (LB), stem diameter (SD), leaf length (LL), leaf width (LW), leaf area (LA), and total root volume (RV), but positively influenced total root length (RL). As sand burial depth increased, SB, LB, SD, LL, LW, LA, RV, root biomass (RB), RV, and lateral root numbers (LRN) significantly decreased. Salinity stress negatively affected SB, LB, SD, LL, LW, LA, RB, RL, and RV, with these traits declining as the stress concentration increased. Drought stress had a positive effect on SD and LL, with both traits showing an increase as the intensity of the drought stress intensified; however, it adversely affected RL. In Ningxia Yanchi desert steppe, salinity stress had the most significant effect on the traits of S. alopecuroides seedlings, followed by sand burial, with drought having the least significant effect. This study provides essential theoretical support for understanding how S. alopecuroides seedlings cope with environmental stresses in their early life stages.

Optimized strategies for nitrogen fertilizer application in Populus plantations in the context of climate change mitigation

Nitrogen (N) fertilizer application increases biomass volume and enhances the carbon sequestration of forest stands. However, overused N fertilizers induce nitrous oxide (N2O), a greenhouse gas with a higher global warming potential than CO2. This study estimates the growth function of Populus stands based on field data, based on which the revised Faustmann model is used to evaluate the optimal rotation and the N fertilizer application rate under different scenarios. Results show that the stand volume is an increasing logarithmic-reciprocal function of the age and N fertilizer rate, and the increment by age is more significant and lasting. When the cost of N2O emissions is considered, the fertilization rate is substantially reduced; a higher carbon price decreases the fertilization rate but prolongs the optimal rotation. Overall, participation in forest carbon projects is economically beneficial even when the costs of greenhouse gas emissions are considered. The research outcomes provide insights into the interplays between the benefits and costs of N fertilizer applications and forest owners' behavior. The conclusions support the accounting of N2O emissions in protocols of forest carbon projects and a more ambitious mitigation goal to push the carbon price on a national scale market.

Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning

The continuous assessment of grassland biomass during the growth season plays a vital role in making informed, location-specific management choices. The implementation of precision agriculture techniques can facilitate and enhance these decision-making processes. Nonetheless, precision agriculture depends on the availability of prompt and precise data pertaining to plant characteristics, necessitating both high spatial and temporal resolutions. Utilizing structural and spectral attributes extracted from low-cost sensors on unmanned aerial vehicles (UAVs) presents a promising non-invasive method to evaluate plant traits, including above-ground biomass and plant height. Therefore, the main objective was to develop an artificial neural network capable of estimating pasture biomass by using UAV RGB images and the canopy height models (CHM) during the growing season over three common types of paddocks: Rest, bale grazing, and sacrifice. Subsequently, this study first explored the variation of structural and color-related features derived from statistics of CHM and RGB image values under different levels of plant growth. Then, an ANN model was trained for accurate biomass volume estimation based on a rigorous assessment employing statistical criteria and ground observations. The model demonstrated a high level of precision, yielding a coefficient of determination (R2) of 0.94 and a root mean square error (RMSE) of 62 (g/m2). The evaluation underscores the critical role of ultra-high-resolution photogrammetric CHMs and red, green, and blue (RGB) values in capturing meaningful variations and enhancing the model’s accuracy across diverse paddock types, including bale grazing, rest, and sacrifice paddocks. Furthermore, the model’s sensitivity to areas with minimal or virtually absent biomass during the plant growth period is visually demonstrated in the generated maps. Notably, it effectively discerned low-biomass regions in bale grazing paddocks and areas with reduced biomass impact in sacrifice paddocks compared to other types. These findings highlight the model’s versatility in estimating biomass across a range of scenarios, making it well suited for deployment across various paddock types and environmental conditions.

EFFECT OF THINNING ON GROWTH AND WOOD PRODUCTION OF NATURALLY REGENERATED 8-YEAR-OLD ACACIA MANGIUM WILLD. PLANTATION ON ABANDONED MINING AREA, SOUTHERN THAILAND

Thinning is an important practice for promoting growth and maintaining forest plantation for wood production from the remaining trees. In this study, thinning was carried out in a naturally regenerated 8-year-old Acacia mangium plot in the Phangnga Forestry Research Station. Three thinning schemes, with 175 (T1), 300 (T2) and 600 (T3) remaining trees/ha, were compared with the control (no thinning) of 831 trees/ha. The diameter at breast height (DBH) and height (H) of the trees were measured. The differences in growth, current annual increment (CAI), aboveground biomass, and stem volume (V) were analyzed. We observed that the thinning of A. mangium increased the growth rate, with the DBH being clearly affected by thinning. CAIDBH increased significantly, with the DBH class of thinned A. mangium plots also improving after thinning. The stem volume and aboveground biomass of T3 plot was similar to the control plot after thinning. In addition, the number of large saw logs was the highest in T3 plot. The large saw logs can be used for multi-utilization and have a high value. These results suggest that thinning can promote stem growth, and increase the proportion of large saw logs in naturally regenerated A. mangium stands.