Search Results (30)

This investigation examines diffusion processes for predicting whole-stand volume, incorporating the variability and uncertainty inherent in regional, operational, and environmental factors. The distribution and spatial organization of trees within a specified forest region, alongside dynamic fluctuations and intricate uncertainties, are modeled by a set of nonsymmetric stochastic differential equations of a sigmoidal nature. The study introduces a three-dimensional system of stochastic differential equations (SDEs) with mixed-effect parameters, designed to quantify the dynamics of the three-dimensional distribution of tree-size components—namely diameter (diameter at breast height), potentially occupied area, and height—with respect to the age of a tree. This research significantly contributes by translating the analysis of tree size variables, specifically height, occupied area, and diameter, into stochastic processes. This transformation facilitates the representation of stand volume changes over time. Crucially, the estimation of model parameters is based exclusively on measurements of tree diameter, occupied area, and height, avoiding the need for direct tree volume assessments. The newly developed model has proven capable of accurately predicting, tracking, and elucidating the dynamics of stand volume yield and growth as trees mature. An empirical dataset composed of mixed-species, uneven-aged permanent experimental plots in Lithuania serves to substantiate the theoretical findings. According to the dataset under examination, the model-based estimates of stand volume per hectare in this region exhibited satisfactory goodness-of-fit statistics. Specifically, the root mean square error (and corresponding relative root mean square error) for the living trees of mixed, pine, spruce, and birch tree species were 68.814 m³ (20.4%), 20.778 m³ (7.8%), 32.776 m³ (37.3%), and 4.825 m³ (26.3%), respectively. The model is executed within Maple, a symbolic algebra system. Full article

Thinning is a key silvicultural practice for managing forests; however, its effects on stand growth and yield remain debated. This study evaluated the growth and yield responses to thinning in even-aged Quercus robur stands in Galicia (NW Spain) using data from three long-term thinning trials established between 1998 and 1999. A randomised complete block design was applied with four thinning intensities from below: control (C, 0% basal area removal), light (L, 15%), moderate (M, 35%), and heavy (H, 55%). Two complementary analytical approaches were implemented using linear mixed-effects models: a state-space approach examining post-thinning stand dynamics and a thinning-effect approach assessing the cumulative stand growth and yield, accounting for both standing and harvested components. The state-space analysis confirmed that thinning produced distinct stand structures in moderate and heavy treatments (M and H), with the largest differences observed in the stand basal area and trees per hectare, while the dominant height remained unaffected. In the thinning-effect approach, the cumulative basal area and volume—excluding and including mortality—followed the pattern L > C > M > H. Overall, the results indicate that light or moderate thinning intensities maintain stand yield and enable intermediate harvests. At the same time, although the mean diameter increased under more intensive thinning, differences in the dominant diameter—approximating potential future crop trees—were not significant, indicating that stronger thinning from below did not necessarily enhance the development of the dominant trees. Full article

This study utilizes data from the eighth and ninth Chinese National Forest Inventories of Qinghai Province to establish a climate-sensitive transfer matrix growth model for natural forests in Qinghai Province. The model considers tree species diversity (S_d), size diversity (D_c), mean annual temperature (MAT), and mean annual precipitation (MAP) and their impacts on tree growth, mortality, and recruitment. Additionally, the forest stand growth and development were predicted under different climate scenarios (RCP2.6, RCP4.5, RCP8.5) for the next 50 years. The results show that the number of Qinghai spruce (Picea crassifolia Kom.) and White birch (Betula platyphylla Sukaczev) trees per hectare gradually decreases, but the stock volume continues to increase. The number of trees per hectare remains relatively stable (from 2235 to 855), with stock volume increasing annually for the first 30 years of the simulation and then stabilizing (from 76.96 to 798.02). Other tree species groups exhibit a continuous annual increase. Comparing the changes in stock volume and tree numbers under three different climate scenarios, there was no significant difference, and the overall trend remained similar. The finding fills a gap in the research on climate-sensitive transfer matrix growth models for natural forests in Qinghai Province. Compared to single-tree and whole-stand models, this model can predict forest stand growth more quickly and effectively, providing a reliable reference for future forest management. It helps formulate policies to address climate change and promote the sustainable development of forest health. This achievement will contribute to a better understanding of future forest stand growth trends, offering valuable insights for sustainable forest management. Full article

Improving the precision of forest vegetation carbon stock estimation is essential for scientifically evaluating its economic value and ecological benefits. This study aims to investigate the impact of different estimation methods on carbon stock and its economic value. Taking the forest vegetation of the Zixi Mountain Nature Reserve as the research object, the carbon stock of the arbor layer was estimated using four approaches: the variable biomass expansion factor method, the biomass expansion factor method, the volume conversion method, and the continuous function method of the biomass conversion factor. The carbon stocks of economic forests and shrublands were estimated using the average biomass method. The economic value of forest carbon storage was then evaluated through the market value method and the optimal pricing approach for forest carbon sinks. The results revealed no significant differences among the four estimation methods. The estimated arbor forest carbon stocks were 692,548.39 tC, 672,599.83 tC, 673,161.07 tC, and 400,369.17 tC, respectively, with an overall average of 609,669.62 tC. The biomass expansion factor method and the volume conversion method produce the most consistent results. The corresponding relative errors were 13.59%, 10.32%, 10.41%, and −34.33%, respectively. The continuous function method of the biomass conversion factor exhibited the greatest variability, mainly due to the influence of Pinus yunnanensis parameters. Among all methods, the biomass expansion factor method yielded the smallest relative error, making it the most suitable for estimating arbor carbon stocks in the study area. The total average economic value of forest carbon storage in the region was estimated at CNY 58.09 million. Among all forest types, Pinus yunnanensis contributed the highest carbon value, totaling CNY 50.48 million. In terms of economic value per unit area, Pinus armandii ranked first, with CNY 11,418.92 per hectare. Among different age groups of arbor forests, middle-aged stands had the highest carbon sequestration value, reaching CNY 36.87 million. Across all functional zones, the core zone showed the greatest economic value at CNY 29.34 million. Enhancing forest resource protection to maximize both carbon sink capacity and economic returns, as well as promoting forest carbon trading, can bring additional economic benefits to Southwest China while contributing to the achievement of the national “dual carbon” goals. Full article

Light Detection and Ranging (LiDAR) provides three-dimensional information that can be used to extract tree parameter measurements such as height (H), canopy volume (CV), canopy diameter (CD), canopy area (CA), and tree stand density. LiDAR data does not directly give diameter at breast height (DBH), an important input into allometric equations to estimate biomass. The main objective of this study is to estimate tree DBH using existing allometric models. Specifically, it compares three global DBH pantropical models to calculate DBH and to estimate the aboveground biomass (AGB) of the Lake Broadwater Forest located in Southeast (SE) Queensland, Australia. LiDAR data collected in mid-2022 was used to test these models, with field validation data collected at the beginning of 2024. The three DBH estimation models—the Jucker model, Gonzalez-Benecke model 1, and Gonzalez-Benecke model 2—all used tree H, and the Jucker and Gonzalez-Benecke model 2 additionally used CD and CA, respectively. Model performance was assessed using five statistical metrics: root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), percentage bias (MBias), and the coefficient of determination (R²). The Jucker model was the best-performing model, followed by Gonzalez-Benecke model 2 and Gonzalez-Benecke model 1. The Jucker model had an RMSE of 8.7 cm, an MAE of −13.54 cm, an MAPE of 7%, an MBias of 13.73 cm, and an R² of 0.9005. The Chave AGB model was used to estimate the AGB at the tree, plot, and per hectare levels using the Jucker model-calculated DBH and the field-measured DBH. AGB was used to estimate total biomass, dry weight, carbon (C), and carbon dioxide (CO₂) sequestered per hectare. The Lake Broadwater Forest was estimated to have an AGB of 161.5 Mg/ha in 2022, a Total C of 65.6 Mg/ha, and a CO₂ sequestered of 240.7 Mg/ha in 2022. These findings highlight the substantial carbon storage potential of the Lake Broadwater Forest, reinforcing the opportunity for landholders to participate in the carbon credit systems, which offer financial benefits and enable contributions to carbon mitigation programs, thereby helping to meet national and global carbon reduction targets. Full article

This study presents a model for estimating forest productivity based on a sample of 2048 permanent field plots covering a wide range of growing sites in Mexico. Our state-space approach assumes that the growth behavior of any stand over time can be estimated on the basis of its current state, defined by the dominant height (H), number of trees per hectare (N), and stand basal area (BA). We used transition functions to estimate the change in states as a function of the current state. We also present transition functions for the change in stand volume (V) and total above-ground biomass (AGB). The first transition function relates dominant height to dominant diameter by using the guide-curve method to estimate site form. The transition function for N consists of two models, one for estimating natural mortality and the other for estimating recruitment. These models were developed in two steps: in the first step, the logistic regression and maximum likelihood approach were used to estimate the probability of the occurrence of mortality or recruitment, and in the second step, the rate of change associated with each event was modeled when mortality or recruitment was assumed to have occurred as a result of the first step. The remaining three transition functions (BA, V, and AGB) were fitted simultaneously to account for possible correlations between errors. The model estimating total above-ground biomass (AGB), which can be considered a state variable that summarizes the performance of the whole model, explained more than 97% of the observed variability, with a root mean square error value of 10.57 Mg/ha. Full article

As forest managers increasingly seek to develop and maintain mixedwood forests, more information is required on the potential facilitative and competitive interactions between tree species. We present data from a broadleaf thinning study established in a mixedwood stand in Central British Columbia, Canada, to examine how residual trembling aspen and paper birch competitively affect spruce growth after thinning but may also concurrently protect spruce from attack by the white pine weevil. Tree-level data collected at a stand age of 36 years, 19 years after broadleaf trees were thinned, show that spruce height and diameter growth declined with broadleaf competition, particularly from taller trees, resulting in a competition-related reduction in stand-level spruce volume yields. The fastest spruce growth occurred in treatments where all broadleaf trees were removed, but complete broadleaf removal also resulted in higher rates of weevil attack on spruce, which also caused height and diameter growth reductions. Our results suggest that maintaining a density of approximately 500 broadleaf trees per hectare may achieve a stand condition that balances spruce growth reductions from competitive interactions with broadleaf trees while providing some protection from white pine weevil attacks. Full article

Understanding how thinning strategies impact wood quality and quantity for different purposes is of interest, given that plantation management is often based on parameters that require validation under varying growth conditions. Planted forests for solid purposes in the northern region of Urugay, western Argentina and South of Brazil are usually managed in initial stockings ranging from 800 to 1200 trees·ha⁻¹ depending on the use of clones or seeds. Subsequent thinnings are applied (at plantation ages varying from 3 to 11 years) up to final stockings of around 200 trees·ha⁻¹. This study evaluated contrasting thinning regimes applied early in the crop cycle, with an initial tree density of 840 trees·ha⁻¹. Two thinning treatments were applied at 1.5 and 7.3 years, reducing tree densities to 700–400 and 400–100 trees·ha⁻¹, respectively. Growth analyses were conducted from 1.5 to 20.8 years, considering total height, diameter at breast height, individual volume, total and commercial volume per hectare, mean annual increase, and current annual increase. At the final harvest, contrasting tree densities of 100, 250, and 400 trees·ha⁻¹ were sampled to assess wood density and mechanical properties (bending and compression on small-scale clear samples). Individual growth and wood properties were related to a Stand Density Index to understand the effect of competition on these values. The results identified thinning regimes that resulted in the most significant individual and per-hectare growth (both in thinning and clear felling) and the optimal harvest time under specific growth conditions. We assessed the proportions of commercial logs for sawmill and pulp uses, providing valuable inputs for subsequent economic analyses of thinning regimes aiming for the most convenient combination of wood products. Wood’s physical and mechanical properties were relatively little affected by contrasting levels of competition between trees; therefore, the choice of silvicultural system will depend on production and economic criteria. Full article

This study aimed to develop simultaneous models with universal applicability for the estimation of the main factors of forest stands based on airborne LiDAR data and to provide a reference for standardizing the approach and evaluation indices of main forest factor modeling. Using airborne LiDAR and field survey data from 190 sample plots in spruce (Picea spp.), fir (Abies spp.), and spruce–fir mixed forests in Northeast China, the simultaneous models for estimating the main factors of forest stands were developed. To develop the models, the relationships between mean tree height, stand basal area, stand volume, and the main metrics of the LiDAR data and the correlations between eight quantitative factors of forest stands were considered, and the error-in-variable simultaneous equations approach was employed to fit the models. The results showed that the mean prediction errors (MPEs) of eight forest stand factors estimated by the simultaneous models were mostly within 5%, and only the MPE of the number of trees per hectare exceeded 5%. The mean percentage standard errors (MPSEs) of the estimates, including the mean diameter at the breast height (DBH), mean tree height, and mean dominant tree height, were within 15%; the MPSEs of the estimates of the stand basal area, volume, biomass, and carbon stock per hectare were within 25%; and only the MPSE of the estimated number of trees per hectare exceeded 30%. The coefficients of determination (R²) of the core prediction models for the volume, biomass, and carbon storage were all greater than 0.7. It can be concluded that estimating the main factors of forest stands based on the combination of LiDAR and field survey data is technically feasible, and the simultaneous models developed in this study for the estimation of the eight main stand factors of spruce–fir forests can meet the precision requirements of forest resource inventory, except for the number of trees, indicating that the models can be applied in practice. Full article

The aim of this study is to relate initial stand density and thinning intensity to tree diameter, height, and volume increment based on continuous 30-year observations in thinning experimental stands of Scots pine (Pinus sylvestris L.). The thinning experiments on Scots pine were established in 1990 and 1992, and the experimental model in each trial comprised five density variants: control and four plots with tree densities up to 3.0–4.4, 2.0–2.4, 1.0–1.2, and 0.5–0.6 thousand trees per hectare after the initial thinning. Since the establishment, only the dead trees were removed in control plots, and other initial density plots were thinned according to predefined thinning treatment plans. Our study shows that the lowest increment in diameter was found in control plots and the highest in the most intensive thinning plots, in which the diameter increment was 1.5 times higher. However, the intensification of thinning and the signs of growth stabilization in the control stands cannot guarantee them the position of highest productivity and cumulative volume in the future. Full article

The forest inventory plays a crucial role in forest management planning, and it is the first step in planning actions for forest production. However, conducting an inventory can be expensive and complex. Forest inventory applications on smartphones have emerged as an alternative to traditional methods and they aim to make field data collection more accessible to non-professionals while ensuring accuracy in determining the volume of wood in a given area. This study evaluates the effectiveness of the Katam, Arboreal, and Trestima applications compared to traditional data collection methods. The study focuses on assessing the stand density and diameter of sampled trees—two key variables that are assessed in forest inventories. Two species, maritime pine (Pinus pinaster Aiton) and Eucalyptus spp. (mainly Eucalyptus globulus and Eucalyptus nitens), were used to evaluate the performance of the methods, with assessments performed in the stands of diverse dendrometric characteristics, specifically those regarding the tree age, stand density, and topographic conditions (flat or sloping terrain). For the purpose of comparison, goodness-of-fit statistics (R², RMSE, and BIAS) were calculated, and an analysis of the diameter distribution and comparison of the mean diameter, number of trees per hectare, and basal area were performed. In general, the applications were accurate, and the average basal area did not differ significantly from the traditional method. The diameter measurements showed good accuracy. The accuracy of the applications varied depending on the terrain and forest characteristics, with the applications performing better in areas with flat terrain, as well as with older forests that were regular and had low under-cover density. In contrast, the applications performed worse in younger, irregular forests with sloping terrain, high tree density, and those with a great deal of understory vegetation. The applications still need to evolve in evaluating other important variables (such as tree height or volume) as they are currently estimated from auxiliary variables through mathematical equations. Full article

The structural diversity of old-growth forests is a fundamental element as regards ecosystem stability and functionality. The current study aims at exploring the texture diversity in the unique virgin Frakto forest of Greece through the determination of the forest development phases and their related stages. Eight sample plots of 0.25 hectares each were randomly distributed to serve the field research needs. During the single phases, a significant number of variables at the stand level, such as the total dead and living timber volume and the density expressed as the number of stems per hectare and basal area, were calculated, and their values were merged into three main stages. The Frakto virgin forest was found to be dominated by the optimal stage (61.7%), followed by the decay stage (22.7%), and the initial stage (15.6%), in alignment with relevant distributions reported for other European virgin forests. Statistically significant differences in terms of stem density and woody volume between the stages demonstrated increased structural diversity and heterogeneity, a typical characteristic of primeval forests. The results offer an insight into forest growth dynamics under natural processes, thus providing a knowledge base for the promotion of sustainable forest management. Full article

Subalpine fir mortality and stand decline are increasingly evident in British Columbia (B.C.). This long-term study confirmed Dryocoetes confusus to be the major disturbance agent in high-elevation subalpine forests, killing over two-thirds of subalpine fir in eleven one-hectare study plots. D. confusus infestations in mature stands can be described as early-, mid-, or late-phase. The transition from the early- through late-phase is characterized by a lowered stem density as high levels of D. confusus attack and remove the largest trees, while other mortality factors kill smaller trees. Initially, live subalpine fir density and D. confusus activity varied among plots. By a final assessment, very little difference was observed in live stems per hectare. Mortality from all factors ranged from 0.5% to 5% annually, reaching as high as 80% in-stand mortality with >6 times more dead than live volume. When subalpine fir density was reduced to <400 sph, the D. confusus attack rate declined. Cumulative mortality increased the average gap size in plots from 11 m² to 18 m². Our study also showed that D. confusus might be able to switch to a univoltine life cycle, taking advantage of warmer and longer growing seasons that, in part, could explain the rapid increase in mortality in stands. Full article

For the monitoring and management of forest resources, the main index is the stand volume, which is determined on the basis of the tree diameter, height, and number of trees per hectare of three-dimensional distribution. The development of trees in the forest stand is dynamic and is driven by random phenomena. In this study, the tree diameter, the potentially available area, and the height are described by the mixed-effect parameters of the Gompertz-type diffusion process. A normal copula function is used to connect a three-dimensional distribution to its one-dimensional margins. The newly developed model was illustrated using empirical data from 53 permanent experimental plots (measured for seven cycles), which were characterized as follows: pine forests (Pinus sylvestris), 63.8%; spruce (Picea abies), 30.2%; silver birch (Betula pendula Roth and Betula pubescens Ehrh.), 5.8%; and others, 0.2%. An analysis of the tree diameter and height of growth, including current and mean increments and inflection points, is presented. The models for the change in the number of trees per hectare with age are presented on the basis of the probabilistic density functions of the solutions of stochastic differential equations and the copula function. The dynamics of the number of trees per hectare are visualized graphically, and the goodness of fit of the newly developed models is evaluated using standard statistical measures. Full article

The objectives of this study were to develop site index and variable-density yield models for Korean red pine (Pinus densiflora Siebold & Zucc.), Korean white pine (P. koraiensis S. & Z.), and Japanese larch (Larix kaempferi (Lamb.) Carrière) in Korea. The data were collected between 2012 and 2021 from repeatedly measured empirical plots in each target stand in the North Central region of Korea: Gangwon and North Gyeongsang provinces. To develop the site index for each species, a dominant height growth model by species was developed using the Chapman–Richards function. The site index was computed with a base age of 40 years and used as an independent variable to predict the stand volume. To develop the variable-density yield models, three stand density variables, the stand age, and the site index were applied. The stand density variables used were the stand basal area, the number of trees per hectare, and the relative density. All the models were successfully developed with significant parameters and reasonable fit statistics, and the residuals analyzed presented unbiased scatter plots. Yield models with the stand basal area, or the number of trees, can be used to predict the stand volume. The yield model with relative density was flexible to apply across the stand age because the input of the absolute stand density was not required. Model simulation and comparisons with other studies also supported the applicability of the models developed in this study. The models were found to be highly applicable for predicting and simulating these targeted stands, particularly in Korea. Full article